title: Democracy as an Essentially Contested Concept

abstract: ABSTRACTMore than sixty years ago, T. D. Weldon (1953) published an influential book entitled The Vocabulary of Politics. In it he affirmed a common belief among philosophers of language that words which could not be connected to objective, measurable objects and rendered the legitimate study of scientific investigation deserved to be dismissed as merely emotive utterances unworthy of serious consideration. They, he said, were either "boo" words that registered displeasure or "hurrah" words that expressed pleasure. Whichever they were, however, they were meaningless, since there was no externally observable referent to which an unbiased observer could appeal. They might, of course, fulfill some emotional need or communicate a personal preference; but, they were philosophically useless beyond that. So, for example, my statement that I like chocolate ice cream and your statement that you like Tutti Frutti ice cream may describe our different tastes, but they are useless insofar as determining which flavour is somehow "better." What goes for ice cream goes equally well for justice, beauty and so on. Weldon argued that normative or evaluative concepts, in the absence of some basis for empirical falsification, were not worth a single philosopher's breath. This discussion paper invites readers to consider whether there is more to "just semantics" than that. Readers are invited to consider some of the philosophical underpinnings of what our words mean and, indeed, to ponder what meaning might be. In fact, it comes close to asking what "meaning" might be. It also implies that it is incumbent upon anyone from patricians, plutocrats, prime ministers and presidents, plebeians, peasants, proletarians and even lumpenproletarians to use care when discussing politics.Keywords: democracy, essentially contested concept, meaning, semantic differential, GallieIntroductionPolitical scientists and others whose job it is to study democracy have a number of questions that they must ask and answer before their hypothesizing, theorizing and philosophizing can begin in earnest. Among other things, they must get comfortable with their basic approach. For the empirically inclined, that means that they must decide what specific aspect of democracy they want to study, from which theoretical perspective and with what methodological techniques. There are ample options. Among the potentially fruitful domains of inquiry are the relationships between democratic governance and economic, geographic, psychological and sociological variables. Social scientists of all sorts are eager to determine how democratic governance is initiated and maintained. What are the prerequisites of a democratic order? How do democracies function? What can bring them down?Democracy as a Subject of "Scientific Inquiry"Researchers who like to putter about with the origins and evolution of democracy want to know how democratic innovations undermined and ultimately replaced authoritarian feudal regimes. This subject must be approached historically. It involves posing questions such as:* What gave rise to the English Civil War (1640-1649) and the subsequent Glorious Revolution (1688) that set the wheels of modern British constitutional government in motion?* What were the precursors of dramatic events including the American and the French revolutions?* What were the precursors of dramatic events including the American and the French revolutions?* What prompted the European revolts of 1848, and what caused them to fail?Others are more interested in the workings of contemporary democracies. Some of the many forms that their inquiries can take involve questions about how democratic governments can be institutionalized, especially in countries with no significant exposure to the far-famed "Westminster Model" and little indigenous experience with democratic controls on the state. Of special interest here are the socio-economic preconditions needed for formal democracies to develop. …


title: Learning to Cooperate in Decentralized Multi-robot Exploration of Dynamic Environments

abstract: This paper presents an approach to train a decentralized multi-robot system to learn cooperation strategy in the exploration of dynamic environments. The traditional approaches to multi-robot exploration problem are all based on the “pre-designed” cooperation strategy. However, many real-world settings are too complex for humans to “design” effective strategies. Besides, “pre-designed” strategy does not possess the ability to adapt to different task environment features, which also limits its application in real-world practices. Inspired by the superiority of deep reinforcement learning technique on complex individual behavior design, we apply the same technology to the cooperative learning process on the robot collective level. Our approach has been evaluated in a simulated multi-robot Disaster Exploration scenario and the results show that it could be applied in more complicated scenarios in contrast with two traditional “human-designed” methods.


title: Binary Document Image Super Resolution for Improved Readability and OCR Performance

abstract: There is a need for information retrieval from large collections of low-resolution (LR) binary document images, which can be found in digital libraries across the world, where the high-resolution (HR) counterpart is not available. This gives rise to the problem of binary document image super-resolution (BDISR). The objective of this paper is to address the interesting and challenging problem of super resolution of binary Tamil document images for improved readability and better optical character recognition (OCR). We propose multiple deep neural network architectures to address this problem and analyze their performance. The proposed models are all single image super-resolution techniques, which learn a generalized spatial correspondence between the LR and HR binary document images. We employ convolutional layers for feature extraction followed by transposed convolution and sub-pixel convolution layers for upscaling the features. Since the outputs of the neural networks are gray scale, we utilize the advantage of power law transformation as a post-processing technique to improve the character level pixel connectivity. The performance of our models is evaluated by comparing the OCR accuracies and the mean opinion scores given by human evaluators on LR images and the corresponding model-generated HR images.


title: , You ’ re It !

abstract: Mass deployment of RF identification (RFID) is hindered by its cost per tag. The main cost comes from the application-specific integrated circuit (ASIC) chip set in a tag. A chipless tag costs less than a cent, and these have the potential for mass deployment for low-cost, item-level tagging as the replacement technology for optical barcodes. Chipless RFID tags can be directly printed on paper or plastic packets just like barcodes. They are highly useful for automatic identification and authentication, supply-chain automation, and medical applications. Among their potential industrial applications are authenticating of polymer bank notes; scanning of credit cards, library cards, and the like; tracking of inventory in retail settings; and identification of pathology and other medical test samples.


title: Automated identification of cryptographic primitives in binary programs

abstract: Identifying that a given binary program implements a specific cryptographic algorithm and finding out more information about the cryptographic code is an important problem. Proprietary programs and especially malicious software (so called malware) often use cryptography and we want to learn more about the context, e.g., which algorithms and keys are used by the program. This helps an analyst to quickly understand what a given binary program does and eases analysis. ::: ::: In this paper, we present several methods to identify cryptographic primitives (e.g., entire algorithms or only keys) within a given binary program in an automated way. We perform fine-grained dynamic binary analysis and use the collected information as input for several heuristics that characterize specific, unique aspects of cryptographic code. Our evaluation shows that these methods improve the state-of-the-art approaches in this area and that we can successfully extract cryptographic keys from a given malware binary.


title: Conditional reasoning by mental models: chronometric and developmental evidence

abstract: Abstract The aim of this article is to verify two predictions resulting from the mental models theory of conditional reasoning. First, the denial of antecedent (DA) and modus tollens (MT) inferences should take longer to verify than modus ponens (MP) and affirmation of consequent (AC) because the former require subjects to flesh out the initial model whereas the latter do not. This prediction was confirmed in two reaction time experiments in adults. In line with Evans' proposal (Evans, J. St. B. T. (1993). The mental model theory of conditional reasoning: critical appraisal and revision. Cognition , 48 , 1–20), there was a strong directionality effect: inferences from antecedent to consequent (MP and DA) took less time to verify than the inferences in the opposite direction (AC and MT). Second, the development of conditional reasoning should result from the increasing capacity to construct and coordinate more and more models. As a consequence, the pattern of conditional inference production should evolve with age from a one-model conjunctive pattern (production of MP and AC more frequent than DA and MT) to a three-model conditional production pattern (higher production rate for MP and MT than for DA and AC). This prediction was confirmed using an inference production task in children, adolescents, and adults.


title: On Patterns for Decentralized Control in Self-Adaptive Systems

abstract: Self-adaptation is typically realized using a control loop. One prominent approach for organizing a control loop in self-adaptive systems is by means of four components that are responsible for the primary functions of self-adaptation: Monitor, Analyze, Plan, and Execute, together forming a MAPE loop. When systems are large, complex, and heterogeneous, a single MAPE loop may not be sufficient for managing all adaptation in a system, so multiple MAPE loops may be introduced. In self-adaptive systems with multiple MAPE loops, decisions about how to decentralize each of the MAPE functions must be made. These decisions involve how and whether the corresponding functions from multiple loops are to be coordinated (e.g., planning components coordinating to prepare a plan for an adaptation). To foster comprehension of self-adaptive systems with multiple MAPE loops and support reuse of known solutions, it is crucial that we document common design approaches for engineers. As such systematic knowledge is currently lacking, it is timely to reflect on these systems to: (a) consolidate the knowledge in this area, and (b) to develop a systematic approach for describing different types of control in self-adaptive systems. We contribute with a simple notation for describing interacting MAPE loops, which we believe helps in achieving (b), and we use this notation to describe a number of existing patterns of interacting MAPE loops, to begin to fulfill (a). From our study, we outline numerous remaining research challenges in this area.


title: "Un fil visible": Poetry and Reportage in Stephane Mallarme's "Un Spectacle interrompu"

abstract: Stephane Mallarme lamented the vulgarity of the press, but the newspaper, with its increasing audience, awakened his desire to appropriate journalism's commercial power. In describing journalism's "theft" of literature, its invention of the feuilleton, in the poeme critique "Etalages" (1892), he implies an uncharacteristic conclusion: popular culture must be reclaimed for poetry. (1) The question of journalism's value, prominent in the poemes critiques of the 1890s, such as "Le Livre, instrument spirituel" (1895), enters Mallarme's work in the 1870s. The prose poem "Un Spectacle interrompu" (1875), first published when Mallarme was in the midst of journalistic projects and recognized as a harbinger of his later prose style, exemplifies Mallarme's experimentation with reportage. Anticipating both his 1880s explorations of performance and the 1890s poemes critiques, Mallarme's anecdote interrogates the poetic vision, the "recherche assoupie d'imaginations ou de symboles." (2) Presenting itself as a report, and the poet as reporter, the poem announces the poet's spiritual authority and the hierarchy of poetry and journalism. Yet this poetic report linguistically and dramatically overturns the poem's hierarchies. In "Un Spectacle," encounters between the poet-reporter and reporters in general, poetry and reportage, reality and artifice, the poet's and the audience's interpretations of the spectacle, the poet and the clown, and the clown and the bear, implicitly question the distinction between the poetic and the popular, as well as the poetic and the real. (3) Rather than establishing poetry's superiority over reportage, the prose poem seems an odd attempt at reconciliation. In showing how the accident that interrupts the spectacle produces meaning, this poetic report interrogates the theatrical illusion to illustrate the interdependence of the figurative and the real. The poet's vision of the audience and their response to this spectacle hints at the desire for a ritual that reveals the poetic within the public. "Un Spectacle interrompu" foreshadows the possibility, entertained later in the poemes critiques, of a rapprochement of poetry and the popular. In its exploration of the oppositions of poetry and journalism, reality and artifice, and the mythic and the public, "Un Spectacle interrompu" dramatizes one of Mallarme's early attempts to capture the power of popular genres and discourse for poetry. The poem's opening is an avatar of Mallarme's stance toward journalism. The speaker states that he seeks to write about the spectacle as a poet, not a reporter: (4) "Je veux, en vue de moi seul, ecrire comme elle frappa mon regard de poete, telle Anecdote, avant que la divulguent des reporters par la foule dresses a assigner a chaque chose son caractere commun" (OC 276). The poet's account results in an understanding different from the vulgarized version reporters are required to provide, "divulguent," to the crowd. This remark, anticipating observations about reportage in "Crise de vers," starts to formulate the problem of defining poetic prose (OC 386). In "Crise de vers," Mallarme redivides the poetry/prose split, implicitly replacing it with a split between language that is musical, and thus poetic, and language that is not. (5) This notion generalizes "poetry" into what Roman Jakobson called "the poetic function" of language. Jakobson acknowledged his debt to Mallarme when he observed that "poeticalness is not a supplementation of discourse with rhetorical adornment but a total reevaluation of the discourse and of all of its components whatsoever" (377). The tension of distinguishing and incorporating poetry and prose persists in Divagations (1897), where the section collecting this and other prose poems is entitled "Anecdotes ou poemes." The anecdote relates how a person describing himself as a poet attends a popular spectacle in a theater. The performance consists of an actor--a clown--and a bear. …


Analytical précis of Chime by Orbital: towards an analysis of electronic dance music


title: Human Wakefulness and Biological Rhythms After Birth

abstract: Both a sleep-wakefulness cycle and a basic rest-activity cycle were observed in 20 normal infants left undisturbed for ten hours following birth. Behavioral wakefulness occurred immediately following delivery and in between sleep periods despite the lack of feeding and other intervention. Medication given to mothers during labor resulted in decreased amounts of infant wakefulness and increased amounts of quiet (non rapid eye movement) sleep.


title: A modelling and reasoning framework for social networks policies

abstract: Policy languages (such as privacy and rights) have had little impact on the wider community. Now that social networks have taken off, the need to revisit policy languages and realign them towards social networks requirements has become more apparent. One such language is explored as to its applicability to the social networks masses. We also argue that policy languages alone are not sufficient and thus they should be paired with reasoning mechanisms to provide precise and unambiguous execution models of the policies. To this end, we propose a computationally oriented model to represent, reason with and execute policies for social networks.


title: Transmission properties of full-mode and half-mode folded corrugated SIW

abstract: The transmission properties of a folded corrugated substrate integrated waveguide (FCSIW) and a proposed half-mode FCSIW is investigated. For the same cut-off frequency, these structures have similar performance to CSIW and HMCSIW respectively, but with significantly reduced width. The top wall is isolated from the bottom wall at DC thereby permitting active devices to be connected directly to, and biased through them. Arrays of quarter-wave stubs above the top wall allow TE1,0 mode conduction currents to flow between the top and side walls. Measurements and simulations of waveguides designed to have a nominal cut-off frequency of 3 GHz demonstrate the feasibility of these compact waveguides.


title: SOLAR: Scalable Online Learning Algorithms for Ranking

abstract: Traditional learning to rank methods learn ranking models from training data in a batch and offline learning mode, which suffers from some critical limitations, e.g., poor scalability as the model has to be retrained from scratch whenever new training data arrives. This is clearly nonscalable for many real applications in practice where training data often arrives sequentially and frequently. To overcome the limitations, this paper presents SOLAR — a new framework of Scalable Online Learning Algorithms for Ranking, to tackle the challenge of scalable learning to rank. Specifically, we propose two novel SOLAR algorithms and analyze their IR measure bounds theoretically. We conduct extensive empirical studies by comparing our SOLAR algorithms with conventional learning to rank algorithms on benchmark testbeds, in which promising results validate the efficacy and scalability of the proposed novel SOLAR algorithms.


title: A nonparallel hexrotor UAV with faster response to disturbances for precision position keeping

abstract: This paper presents a fully actuated UAV platform with a nonparallel design. Standard multirotor UAVs equipped with a number of parallel thrusters would result in underactuation. Fighting horizontal wind would require the robot to tilt its whole body toward the direction of the wind. We propose a hexrotor UAV with nonparallel thrusters which results in faster response to disturbances for precision position keeping. A case study is presented to show that hexrotor with a nonparallel design takes less time to resist wind gust than a standard design. We also give the results of a staged peg-in-hole task that measures the rising time of exerting forces using different actuation mechanisms.


THE AMAZING DIGITAL GLOVES THAT GIVE VOICE TO THE VOICELESS


title: Histogram modification based image watermarking resistant to geometric distortions

abstract: A geometrically invariant digital image watermarking scheme based on histogram modification is proposed in this paper. The feature extraction method called Adaptive Harris Detector with Simulated Attacks is proposed and employed, which adjusts and ranks the response threshold value of the traditional Harris Corner Detector, and trains the input image with several simulated attacks, to extract the most reliable feature points for watermark data bits embedding and extraction. The watermark embedding regions are then found as square patches centering at the selected geometric invariant feature points. In each region, the intensity-level histogram is modified by moving some pixels to form a specific pattern according to the corresponding watermark bit. For watermark extraction, the proposed Adaptive Harris Detector with Simulated Attacks is proposed to restore the watermarked image to its original position if any geometric attack exists, and to retrieve the watermarked regions. According to the pattern of intensity-level histogram distribution in these regions, a sequence of watermark bits is then extracted. Experimental results show that the proposed scheme is robust against both the geometric attacks and common signal processing, such as rotation, scaling, cropping, JPEG compression, median filtering, low-pass Gaussian filtering and also noise pollution.


title: Highly-resilient, energy-efficient multipath routing in wireless sensor networks

abstract: Previously proposed sensor network data dissemination schemes require periodic low-rate flooding of data in order to allow recovery from failure. We consider constructing two kinds of multipaths to enable energy efficient recovery from failure of the shortest path between source and sink. Disjoint multipath has been studied in the literature. We propose a novel braided multipath scheme, which results in several partially disjoint multipath schemes. We find that braided multipaths are a viable alternative for energy-efficient recovery from isolated and patterned failures.


title: Security and Privacy Challenges in the Internet of Things [Security and Privacy Matters]

abstract: This is the first installment of the new "Security and Privacy Matters" column in IEEE Consumer Electronics Magazine. Security and privacy are always at the heart of everything that happens in the Consumer Electronics (CE) industry. This column aims to provide insight on various aspects of security and privacy in the CE industry.


title: LDA-based context dependent recurrent neural network language model using document-based topic distribution of words

abstract: Adding context information into recurrent neural network language models (RNNLMs) have been investigated recently to improve the effectiveness of learning RNNLM. Conventionally, a fast approximate topic representation for a block of words was proposed by using corpus-based topic distribution of word incorporating latent Dirichlet allocation (LDA) model. It is then updated for each subsequent word using an exponential decay. However, words could represent different topics in different documents. In this paper, we form document-based distribution over topics for each word using LDA model and apply it in the computation of fast approximate exponentially decaying features. We have shown experimental results on a well known Penn Treebank corpus and found that our approach outperforms the conventional LDA-based context RNNLM approach. Moreover, we carried out speech recognition experiments on Wall Street Journal corpus and achieved word error rate (WER) improvements over the other approach.


title: Visibility of wavelet quantization noise

abstract: The discrete wavelet transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2-lambda, where r is display visual resolution in pixels/degree, and lambda is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.


title: Applying ecological and evolutionary theory to cancer: a long and winding road

abstract: Since the mid 1970s, cancer has been described as a process of Darwinian evolution, with somatic cellular selection and evolution being the fundamental processes leading to malignancy and its many manifestations (neoangiogenesis, evasion of the immune system, metastasis, and resistance to therapies). Historically, little attention has been placed on applications of evolutionary biology to understanding and controlling neoplastic progression and to prevent therapeutic failures. This is now beginning to change, and there is a growing international interest in the interface between cancer and evolutionary biology. The objective of this introduction is first to describe the basic ideas and concepts linking evolutionary biology to cancer. We then present four major fronts where the evolutionary perspective is most developed, namely laboratory and clinical models, mathematical models, databases, and techniques and assays. Finally, we discuss several of the most promising challenges and future prospects in this interdisciplinary research direction in the war against cancer.


title: A stopping rule for threshold learning

abstract: A stopping rule is derived for time-varying training procedures operating on trainable signal detectors and single-feature pattern classifiers. It is assumed that the statistical description of the environment is partially unknown. The stopping rule is baaed on a recently-developed technique for obtaining a bounded-length confidence interval for the expected value of a non-stationary random variable. Training is stopped when this interval falls inside specified limits, thereby assuring a specified minimum performance at a desired confidence level. The rule is illustrated by a numerical example in which the two classes of obser vations overlap. An expression is obtained for the limit to which the probability of acquiring the stopping criterion converges in probability.


title: To See and Be Seen: Celebrity Practice on Twitter

abstract: Social media technologies let people connect by creating and sharing content. We examine the use of Twitter by famous people to conceptualize celebrity as a practice. On Twitter, celebrity is practiced through the appearance and performance of ‘backstage’ access. Celebrity practitioners reveal what appears to be personal information to create a sense of intimacy between participant and follower, publicly acknowledge fans, and use language and cultural references to create affiliations with followers. Interactions with other celebrity practitioners and personalities give the impression of candid, uncensored looks at the people behind the personas. But the indeterminate ‘authenticity’ of these performances appeals to some audiences, who enjoy the game playing intrinsic to gossip consumption. While celebrity practice is theoretically open to all, it is not an equalizer or democratizing discourse. Indeed, in order to successfully practice celebrity, fans must recognize the power differentials intrinsic to the...


title: Mixed Low-precision Deep Learning Inference using Dynamic Fixed Point

abstract: We propose a cluster-based quantization method to convert pre-trained full precision weights into ternary weights with minimal impact on the accuracy. In addition, we also constrain the activations to 8-bits thus enabling sub 8-bit full integer inference pipeline. Our method uses smaller clusters of N filters with a common scaling factor to minimize the quantization loss, while also maximizing the number of ternary operations. We show that with a cluster size of N=4 on Resnet-101, can achieve 71.8% TOP-1 accuracy, within 6% of the best full precision results while replacing ~85% of all multiplications with 8-bit accumulations. Using the same method with 4-bit weights achieves 76.3% TOP-1 accuracy which within 2% of the full precision result. We also study the impact of the size of the cluster on both performance and accuracy, larger cluster sizes N=64 can replace ~98% of the multiplications with ternary operations but introduces significant drop in accuracy which necessitates fine tuning the parameters with retraining the network at lower precision. To address this we have also trained low-precision Resnet-50 with 8-bit activations and ternary weights by pre-initializing the network with full precision weights and achieve 68.9% TOP-1 accuracy within 4 additional epochs. Our final quantized model can run on a full 8-bit compute pipeline, with a potential 16x improvement in performance compared to baseline full-precision models.


title: An empirical analysis of the optimization of deep network loss surfaces

abstract: The success of deep neural networks hinges on our ability to accurately and efficiently optimize high-dimensional, non-convex loss functions. In this paper, we empirically investigate the geometry of the loss functions of state-of-the-art networks, and how commonly-used stochastic gradient descent variants optimize these loss functions. To do this, we visualize the loss function by projecting it down to low-dimensional spaces chosen based on the convergence points of different optimization algorithms. Our observations suggest that optimization algorithms encounter and choose different descent directions at many saddle points to find different final weights. Based on consistency we observe across re-runs of the same stochastic optimization algorithm, we hypothesize that each optimization algorithm makes characteristic choices at these saddle points.


title: Business Process Analysis in Healthcare Environments: a Methodology based on Process Mining

abstract: Performing business process analysis in healthcare organizations is particularly difficult due to the highly dynamic, complex, ad hoc, and multi-disciplinary nature of healthcare processes. Process mining is a promising approach to obtain a better understanding about those processes by analyzing event data recorded in healthcare information systems. However, not all process mining techniques perform well in capturing the complex and ad hoc nature of clinical workflows. In this work we introduce a methodology for the application of process mining techniques that leads to the identification of regular behavior, process variants, and exceptional medical cases. The approach is demonstrated in a case study conducted at a hospital emergency service. For this purpose, we implemented the methodology in a tool that integrates the main stages of process analysis. The tool is specific to the case study, but the same methodology can be used in other healthcare environments.


title: Latency and Reliability-Aware Task Offloading and Resource Allocation for Mobile Edge Computing

abstract: While mobile edge computing (MEC) alleviates the computation and power limitations of mobile devices, additional latency is incurred when offloading tasks to remote MEC servers. In this work, the power-delay tradeoff in the context of task offloading is studied in a multi-user MEC scenario. In contrast with current system designs relying on average metrics (e.g., the average queue length and average latency), a novel network design is proposed in which latency and reliability constraints are taken into account. This is done by imposing a probabilistic constraint on users' task queue lengths and invoking results from extreme value theory to characterize the occurrence of low-probability events in terms of queue length (or queuing delay) violation. The problem is formulated as a computation and transmit power minimization subject to latency and reliability constraints, and solved using tools from Lyapunov stochastic optimization. Simulation results demonstrate the effectiveness of the proposed approach, while examining the power-delay tradeoff and required computational resources for various computation intensities.


title: Malware phylogeny generation using permutations of code

abstract: Malicious programs, such as viruses and worms, are frequently related to previous programs through evolutionary relationships. Discovering those relationships and constructing a phylogeny model is expected to be helpful for analyzing new malware and for establishing a principled naming scheme. Matching permutations of code may help build better models in cases where malware evolution does not keep things in the same order. We describe methods for constructing phylogeny models that uses features called n-perms to match possibly permuted codes. An experiment was performed to compare the relative effectiveness of vector similarity measures using n-perms and n-grams when comparing permuted variants of programs. The similarity measures using n-perms maintained a greater separation between the similarity scores of permuted families of specimens versus unrelated specimens. A subsequent study using a tree generated through n-perms suggests that phylogeny models based on n-perms may help forensic analysts investigate new specimens, and assist in reconciling malware naming inconsistencies


title: Children ’ s development of analogical reasoning : Insights from scene analogy problems

abstract: We explored how relational complexity and featural distraction, as varied in scene analogy problems, affect children’s analogical reasoning performance. Results with 3- and 4-year-olds, 6- and 7-year-olds, 9- to 11-year-olds, and 13- and 14-year-olds indicate that when children can identify the critical structural relations in a scene analogy problem, development of their ability to reason analogically interacts with both relational complexity and featural distraction. Error patterns suggest that children are more likely to select a distracting object than to make a relational error for problems that present both possibilities. This tendency decreases with age, and older children make fewer errors overall. The results suggest that changes in analogical reasoning with age depend on the interplay among increases in relational knowledge, the capacity to integrate multiple relations, and inhibitory control over featural distraction. � 2006 Elsevier Inc. All rights reserved.


title: Can we prevent aspiration pneumonia in the nursing home?

abstract: Aspiration pneumonia is a significant cause of morbidity, hospitalization, and mortality in the nursing home population. Patients who aspirate have three times higher mortality than patients who do not aspirate. We discuss the factors known to increase the risk of aspiration and its consequences, and recognize some of the preventive measures for aspiration pneumonia. We suggest approaches to decrease the risk of this very prevalent syndrome.


title: The YouTube video recommendation system

abstract: We discuss the video recommendation system in use at YouTube, the world's most popular online video community. The system recommends personalized sets of videos to users based on their activity on the site. We discuss some of the unique challenges that the system faces and how we address them. In addition, we provide details on the experimentation and evaluation framework used to test and tune new algorithms. We also present some of the findings from these experiments.


title: FORMATIVE EVALUATION OF BUSINESS MODEL REPRESENTATIONS - THE SERVICE BUSINESS MODEL CANVAS

abstract: Drivers like global competition, advances in technology, and new attractive market opportunities foster a process of servitization and thus the search for innovative service business models. To facilitate this process, different methods and tools for the development of new business models have emerged. Nevertheless, business model approaches are missing that enable the representation of cocreation as one of the most important service-characteristics. Rooted in a cumulative research design that seeks to advance extant business model representations, this goal is to be closed by the Service Business Model Canvas (SBMC). This contribution comprises the application of thinking-aloud protocols for the formative evaluation of the SBMC. With help of industry experts and academics with experience in the service sector and business models, the usability is tested and implications for its further development derived. Furthermore, this study provides empirically based insights for the design of service business model representation that can facilitate the development of future business models.


title: Kademlia: A Peer-to-Peer Information System Based on the XOR Metric

abstract: We describe a peer-to-peer distributed hash table with provable consistency and performance in a fault-prone environment. Our system routes queries and locates nodes using a novel XOR-based metric topology that simplifies the algorithm and facilitates our proof. The topology has the property that every message exchanged conveys or reinforces useful contact information. The system exploits this information to send parallel, asynchronous query messages that tolerate node failures without imposing timeout delays on users.


title: Characteristics of Fatal Child Maltreatment Associated with Multiple Births in Japan

abstract: The purpose of the present study was to clarify the characteristics of fatal child maltreatment in families with multiple births in Japan. An exhaustive information search was performed to find multiple-birth cases between July 2003 and March 2011. There were 437 cases of fatal maltreatment of children aged 0-17 years during this period, including 14 involving multiple-birth children. A keyword search was performed to create a full profile for each multiple-birth case. The 14 multiple-birth victims were twins from 13 families. No significant difference between twins and singletons with fatal maltreatment was observed for most characteristics. However, in the case of twins, 0-month victims were rare, and the number of children per family was larger. One twin died from shaken baby syndrome. The victim's siblings were also maltreated in six out of 12 relevant cases, including all six co-twins. Premature birth, having a disabled co-twin, delay of growth or development, and parental disfavor tended to be factors of maltreatment when only one twin was maltreated. Four families were given suspended sentences in total, including three mothers who acted as solitary murderers (43% = 3/7). In conclusion, recent Japanese nationwide data suggests that the non-specific overburden of child rearing might be one possible reason for higher frequency of child maltreatment for multiples compared with singletons, and parental comparisons between two twins might be another. The penal sentences for fatal child maltreatment might be more lenient for perpetrators of this crime against twins than against singletons.


title: Trends in online social networking: adolescent use of MySpace over time

abstract: MySpace has received a significant amount of negative attention from the media and many concerned adults, who point to several isolated incidents where predators have contacted, become involved with and even assaulted adolescents whom they met through the popular social networking web site. Furthermore, concerned parents have expressed discontent with the amount and type of personal and private information youth seem to reveal on their profile pages. In 2006, the authors performed an extensive content analysis of approximately 2423 randomly sampled adolescent MySpace profiles, and found that the vast majority of youth were making responsible choices with the information they shared online. In this follow-up study, the authors revisited the profiles one year later to examine the extent to which the content had changed. Though exceptions occur, youth are increasingly exercising discretion in posting personal information on MySpace and more youth are limiting access to their profile. Moreover, a significant ...


title: A review on bicycle dynamics and rider control

abstract: This paper is a review study in dynamics and rider control of bicycles. The first part gives a brief overview of the modelling of the dynamics of bicycles and the experimental validation. The second part focuses on a review of modelling and measuring human rider control, together with the concepts of handling and manoeuvrability and their experimental validation. The paper concludes with the open ends and promising directions for future work in the field of handling and control of bicycles.


title: Bootstrapped Learning of Semantic Classes from Positive and Negative Examples

abstract: We present an algorithm for unsupervised learning and semantic classiflcation of names and terms. Given a small number of seed examples and an unlabeled training corpus, the algorithm learns patterns that identify more examples, in a bootstrapping cycle. Multiple classes are learned simultaneously, including negative classes that serve to provide negative examples for the target classes. We apply the algorithm to texts from several domains, in English and Chinese.


title: Implementing linearizability at large scale and low latency

abstract: Linearizability is the strongest form of consistency for concurrent systems, but most large-scale storage systems settle for weaker forms of consistency. RIFL provides a general-purpose mechanism for converting at-least-once RPC semantics to exactly-once semantics, thereby making it easy to turn non-linearizable operations into linearizable ones. RIFL is designed for large-scale systems and is lightweight enough to be used in low-latency environments. RIFL handles data migration by associating linearizability metadata with objects in the underlying store and migrating metadata with the corresponding objects. It uses a lease mechanism to implement garbage collection for metadata. We have implemented RIFL in the RAMCloud storage system and used it to make basic operations such as writes and atomic increments linearizable; RIFL adds only 530 ns to the 13.5 μs base latency for durable writes. We also used RIFL to construct a new multi-object transaction mechanism in RAMCloud; RIFL's facilities significantly simplified the transaction implementation. The transaction mechanism can commit simple distributed transactions in about 20 μs and it outperforms the H-Store main-memory database system for the TPC-C benchmark.


title: The structure of information: from probability to homology

abstract: D. Bennequin and P. Baudot introduced a cohomological construction adapted to information theory, called"information cohomology"(see"The homological nature of Entropy", 2015). Our text serves as a detailed introduction to information cohomology, containing the necessary background in probability theory and homological algebra. It makes explicit the link with topos theory, as introduced by Grothendieck, Verdier and their collaborators in the SGA IV. It also contains several new constructions and results. (1) We define generalized information structures, as categories of finite random variables related by a notion of extension or refinement; probability spaces are models (or representations) for these general structures. Generalized information structures form a category with finite products and coproducts. We prove that information cohomology is invariant under isomorphisms of generalized structures. (2) We prove that the relatively-free bar construction gives a projective object for the computation of cohomology. (3) We provide detailed computations of $H^1$ and describe the"degenerate"cases. (4) We establish the homological nature of Tsallis entropy. (5) We re-interpret Shannon's axioms for a 'measure of choice' in the light of this theory and provide a combinatorial justification for his recurrence formula.


title: Mediterranean diet and public health: personal reflections

abstract: My concern about diet as a public health problem began in the early 1950s in Naples, where we observed very low incidences of coronary heart disease associated with what we later came to call the good Mediterranean diet. The heart of this diet is mainly vegetarian, and differs from American and northern European diets in that it is much lower in meat and dairy products and uses fruit for dessert. These observations led to our subsequent research in the Seven Countries Study, in which we demonstrated that saturated fat is the major dietary villain. Today, the healthy Mediterranean diet is changing and coronary heart disease is no longer confined to medical textbooks. Our challenge is to persuade children to tell their parents to eat as Mediterraneans do. Am J Clin Nutr 1995 ;61(suppl) :1321S-3S.


Advanced Separation Techniques for Polyolefins


title: Hybrid feature selection for text classification

abstract: Feature selection is vital in the field of pattern classification due to accuracy and processing time considerations. The selection of proper features is of greater importance when the initial feature set is considerably large. Text classification is a typical example of this situation, where the size of the initial feature set may reach to hundreds or even thousands. There are numerous research studies in the literature offering different feature selection strategies for text classification, mostly focused on filters. In spite of the extensive number of these studies, there is no significant work investigating the efficacy of a combination of features, which are selected by different selection methods, under different conditions. In this study, a hybrid feature selection strategy, which consists of both filter and wrapper feature selection steps, is proposed to comprehensively analyze the redundancy or relevancy of the text features selected by different methods in the case of different feature set sizes, dataset characteristics, classifiers, and success measures. The results of the experimental study reveal that a combination of the features selected by various methods is more effective than the features selected by the single selection method. The profile of the combination is, however, influenced by characteristics of the dataset, choice of the classification algorithm, and the success measure.


Reproducing the Stay-At-Home Wife : Japanese Women ' s Magazines and the Image of Marriage


Recovering OpenSSL ECDSA Nonces Using the FLUSH+RELOAD Cache Side-channel Attack.


title: To Discount or Not to Discount in Reinforcement Learning: A Case Study Comparing R Learning and Q Learning

abstract: Abstract Most work in reinforcement learning (RL) is based on discounted techniques, such as Q learning, where long-term rewards are geometrically attenuated based on the delay in their occurence. Schwartz recently proposed an undiscounted RL technique called R learning that optimizes average reward , and argued that it was a better metric than the discounted one optimized by Q learning. In this paper we compare R learning with Q learning on a simulated robot box-pushing task. We compare these two techniques across three different exploration strategies: two of them undirected, Boltzmann and semi-uniform, and one recency-based directed strategy. Our results show that Q learning performs better than R learning, even when both are evaluated using the same undiscounted performance measure. Furthermore, R learning appears to be very sensitive to choice of exploration strategy. In particular, a surprising result is that R learning's performance noticeably deteriorates under Boltzmann exploration. We identify precisely a limit cycle situation that causes R learning's performance to deteriorate when combined with Boltzmann exploration, and show where such limit cycles arise in our robot task. However, R learning performs much better (although not as well as Q learning) when combined with semi-uniform and recency-based exploration. In this paper, we also argue for using medians over means as a better distribution-free estimator of average performance, and describe a simple non-parametric significance test for comparing learning data from two RL techniques.


title: Evaluation of MPP Voltage and Power of mc-Si PV Modules in Partial Shading Conditions

abstract: Photovoltaic (PV) system performance is influenced by several factors, including irradiance, temperature, shading, degradation, mismatch losses, soiling, etc. Shading of a PV array, in particular, either complete or partial, can have a significant impact on its power output and energy yield, depending on array configuration, shading pattern, and the bypass diodes incorporated in the PV modules. In this paper, the effect of partial shading on multicrystalline silicon (mc-Si) PV modules is investigated. A PV module simulation model implemented in P-Spice is first employed to quantify the effect of partial shading on the I-V curve and the maximum power point (MPP) voltage and power. Then, generalized formulae are derived, which permit accurate enough evaluation of MPP voltage and power of mc-Si PV modules, without the need to resort to detailed modeling and simulation. The equations derived are validated via experimental results.


title: Survey and Challenges of Mining Customer Data Sets to Enhance Customer Relationship Management

abstract: Data mining is a useful and powerful tool for any organization especially for marketing people. Data mining is used in managing relationships with customers. New trends in customer relationship management –CRMhave growth. One of them is social customer relationship management –sCRM-. The major problem here is data accessibility. If the research process is not started from inside the organization, the researchers cannot have access to customer’s data. In this research paper, the research creates a survey to find out available customer’s data sets that can be used in academic research. In addition, the research reviews basic concepts of CRM and Data Mining Techniques. Finally, the research focuses on current challenges of mining customer’s data from business perspective and analytical customer relationship management -aCRM-.


Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid


title: AC Resistance Factor of Litz-Wire Windings Used in Low-Voltage High-Power Generators

abstract: New types of heavy litz wires with noninsulated or insulated strands are offered for high-power low-voltage electrical machines, where skin and proximity effects can cause serious problems if traditional windings are used. This paper evaluates the ac resistance of a litz wire and its usability in megawatt-range low-voltage electrical machines. The evaluation is made by finite-element analysis and by resistance measurements with an experimental test setup. A simple amplifier configuration was used to minimize current and voltage phase shift errors, which are critical in this kind of low-impedance and low-frequency measurement. A simple measurement device based on the aforementioned configuration was prepared to ensure a precise measurement result. Tests were done in a frequency range of 50-200 Hz, to cover a wide range of practical high-power low-voltage electrical machines. It is found that the measured litz wire with originally noninsulated strands can be used in large electrical machines up to about 120 Hz if about 50% increase in ac resistance compared to the dc resistance is allowed. Impregnation of the originally noninsulated litz wire with vacuum pressure impregnation improved the ac resistance in one test case, and in the other case, it seemed to have no effect on the ac resistance.


title: Enhancing students' ICT problem solving skills using flipped classroom model

abstract: The role of Information and Communication Technology (ICT) is so great and growing significantly in teaching and learning of this 21st Century. The flipped classroom model has grown in popularity as it is the only blended learning model that utilized both in class time and out of class time. There is a need to evaluate the quality of the best flipped learning approach that could enhance students' ICT skills as mastering ICT skill is becoming the key of learning in this 21st century. The ability to educate students for higher order learning using technology does enhance the learning processes as compared to the traditional settings. There are only a few studies conducted on the students taking ICT subject and none have in depth studies in their ICT skills. Therefore, this paper proposed a new flipped classroom model that increases students' ICT skills. The model incorporates the Social Constructivism theory and Flipped Classroom Model that are derived from blended learning. There are also two learning strategies used in this model which is Competency-based Learning and Inquiry-based Learning which helps to enhance students' ICT Problem Solving Skill.


title: Software-Reconfigurable e-Learning Platform for Power Electronics Courses

abstract: An effective course in power electronics should ideally contain hands-on design and experimental work as well as theory explanation and simulations. In this paper, a software- reconfigurable e-learning platform for power electronics courses is proposed. The aim of the proposed system is to realize a platform capable of constructing a wide range of circuit topologies and control techniques, thus enabling students to gain a better understanding of power electronics converters through practical experiments. The proposed platform consists of a reconfigurable power electronics testbed, a Web-based distance laboratory, and a user interactive e-learning platform. The reconfigurable power electronics testbed can be configured by the students via a Web- based interface to construct a wide variety of converters and inverters. The Internet accessible distance laboratory system permits the instructors and students to remotely conduct experiments over the Internet. The integrated interactive multimedia material can support the educational environment of power electronics courses and can be executed on any modern personal computer (PC) without additional hardware. The advantages of the proposed platform include flexibility, friendly user interface, allow for distance waveform measurements, and removal of laboratory time and space constraints. The positive response from students indicates that the proposed platform is extremely useful for power electronics courses.


title: A Context-Theoretic Framework for Compositionality in Distributional Semantics

abstract: Formalizing “meaning as context” mathematically leads to a new, algebraic theory of meaning, in which composition is bilinear and associative. These properties are shared by other methods that have been proposed in the literature, including the tensor product, vector addition, point-wise multiplication, and matrix multiplication.Entailment can be represented by a vector lattice ordering, inspired by a strengthened form of the distributional hypothesis, and a degree of entailment is defined in the form of a conditional probability. Approaches to the task of recognizing textual entailment, including the use of subsequence matching, lexical entailment probability, and latent Dirichlet allocation, can be described within our framework.


title: Distributed Kalman filtering for sensor networks

abstract: In this paper, we introduce three novel distributed Kalman filtering (DKF) algorithms for sensor networks. The first algorithm is a modification of a previous DKF algorithm presented by the author in CDC-ECC '05. The previous algorithm was only applicable to sensors with identical observation matrices which meant the process had to be observable by every sensor. The modified DKF algorithm uses two identical consensus filters for fusion of the sensor data and covariance information and is applicable to sensor networks with different observation matrices. This enables the sensor network to act as a collective observer for the processes occurring in an environment. Then, we introduce a continuous-time distributed Kalman filter that uses local aggregation of the sensor data but attempts to reach a consensus on estimates with other nodes in the network. This peer-to-peer distributed estimation method gives rise to two iterative distributed Kalman filtering algorithms with different consensus strategies on estimates. Communication complexity and packet-loss issues are discussed. The performance and effectiveness of these distributed Kalman filtering algorithms are compared and demonstrated on a target tracking task.


title: Azimuthal Scattering from Elliptical Hair Fibers

abstract: The appearance of hair follows from the small-scale geometry of hair fibers, with the cross-sectional shape determining the azimuthal distribution of scattered light. Although previous research has described some of the effects of non-circular cross sections, no accurate scattering models for non-circular fibers exist. This article presents a scattering model for elliptical fibers, which predicts that even small deviations from circularity produce important changes in the scattering distribution and which disagrees with previous approximations for the effects of eccentricity. To confirm the model’s predictions, new scattering measurements of fibers from a wide range of hair types were made, using a new measurement device that provides a more complete and detailed picture of the light scattered by fibers than was previously possible. The measurements show features that conclusively match the model’s predictions, but they also contain an ideal-specular forward-scattering behavior that is not predicted and has not been fully described before. The results of this article indicate that an accurate and efficient method for computing scattering in elliptical cylinders—something not provided in this article—is the correct model to use for realistic hair in the future and that the new specular behavior should be included as well.


title: Unmatched projector/backprojector pairs in an iterative reconstruction algorithm

abstract: Computational burden is a major concern when an iterative algorithm is used to reconstruct a three-dimensional (3-D) image with attenuation, detector response, and scatter corrections. Most of the computation time is spent executing the projector and backprojector of an iterative algorithm. Usually, the projector and the backprojector are transposed operators of each other. The projector should model the imaging geometry and physics as accurately as possible. Some researchers have used backprojectors that are computationally less expensive than the projectors to reduce computation time. This paper points out that valid backprojectors should satisfy a condition that the projector/backprojector matrix must not contain negative eigen-values. This paper also investigates the effects when unmatched projector/backprojector pairs are used.


title: Sequence Stratigraphy and Depositional Facies of the Silurian-Devonian Interval of the Northern Permian Basin

abstract: The Silurian and Devonian intervals of the northern Central Basin platform area of west Texas and southeastern New Mexico include the Fusselman, Wristen, and Thirtyone formations and the Woodford Shale. The carbonate-rich Fusselman, Wristen, and Thirtyone formations record a transition from ramp to platform deposition. Oolite grainstones of the lower Fusselman Formation were deposited in a ramp setting during an Upper Ordovician/Lower Silurian transgression. The overlying crinoid packstones and grainstones represent shoals that developed along a break in slope separating the evolving platform from a southward-dipping starved basin. By the close of Fusselman deposition, the platform was well developed, with shallow peridtidal mudstones and wackestones, and high-energy grainstones deposited as near-parallel facies tracts over the platform area. The platform system became fully developed during the deposition of the Wristen Formation. Porous dolomitic peridtidal and platform margin facies grade downdip into nonporous, limy and argillaceous open-shelf facies. Platform facies are typified by numerous shallowing-upward parasequences that terminated at subaerial exposure surfaces. The rocks of the Lower Devonian Thirtyone Formation were deposited as a wedge that onlaps the exposed Silurian platform margin. This formation contains a porous, chert-rich, lowstand deposit; a transgressive disconformity; and variably porous, grain-rich highstand deposits representing an overallmore » sea level rise. A major unconformity marks the contact between the karsted upper surface of the Thirtyone Formation and the overlying organic-rich, anoxic Woodford Shale.« less


Gigapixel Whole-Slide Image Classification Using Unsupervised Image Compression And Contrastive Training


title: Automatic speech classification to five emotional states based on gender information

abstract: Emotional speech recognition aims to automatically classify speech units (e.g., utterances) into emotional states, such as anger, happiness, neutral, sadness and surprise. The major contribution of this paper is to rate the discriminating capability of a set of features for emotional speech recognition when gender information is taken into consideration. A total of 87 features has been calculated over 500 utterances of the Danish Emotional Speech database. The Sequential Forward Selection method (SFS) has been used in order to discover the 5–10 features which are able to classify the samples in the best way for each gender. The criterion used in SFS is the crossvalidated correct classification rate of a Bayes classifier where the class probability distribution functions (pdfs) are approximated via Parzen windows or modeled as Gaussians. When a Bayes classifier with Gaussian pdfs is employed, a correct classification rate of 61.1% is obtained for male subjects and a corresponding rate of 57.1% for female ones. In the same experiment, a random classification would result in a correct classification rate of 20%. When gender information is not considered a correct classification score of 50.6% is obtained.


title: Staging for Rhinosinusitis

abstract: Interest in the surgical treatment of chronic rhinosinusitis has increased, primarily because rigid endoscopy and, more particularly, computed tomographic scanning have facilitated the visualization of disease. At the same time it has become both scientifically and financially imperative to audit therapeutic outcome. Consequently, a staging system for nonneoplastic sinus disease is needed. It is clear that any assessment of medical or surgical therapeutic response requires a method of quantifying disease severity that will be widely accepted by practitioners in the field. This acceptance will largely depend on how easy the method is to apply. With computed tomographic scanning it is possible to more accurately determine the extent of the pathologic condition in rhinosinusitis, a disease in which the severity of symptoms and the appearances on nasal endoscopy have a significantly more unpredictable correlation with the extent of disease. One goal of the Task Force on Rhinosinusitis of the American Academy of Otolaryngology–Head and Neck Surgery was to recommend a system for outcomes research that combines quantification with ease of application. (Otolaryngol Head Neck Surg 1997;117:S35-S40.)


Capability and Digital Transformation : A Firm Performance Perspective Completed Research Paper


abstract: Understanding how learners acquire knowledge is always an important issue in science education (Wu & Tsai, 2005). There are a lot of studies and theories on how students perform learning. Of these, constructivist theory has received a great attention recently. Researchers and theorists maintain that the key element of constructivist theory is that people learn by actively constructing their own knowledge, comparing new information with their previous understanding and using all of these to work through discrepancies to grasp the new understanding (Brooks & Brooks, 2000; Hodson & Hodson, 1998; Bettencourt,1993; Bodner,1986). Three decades, science educators and researcher have strongly advocated the perspectives of constructivism on learning and teaching (Wu & Tsai, 2005). There are a lot of studies based upon the assertions of constructivism to promote students’ learning science (Wu & Tsai, 2005; Venville, 2004; Marss, Blake & Garvin, 2003; Alparslan, Tekkaya, & Geban, 2003; Palmer, 2003; Tsai, 2000; Zietsman & Hewson, 1986; Arnaundin, Mintzes, Dunn, & Sbafer, 1984). Most of these studies utilized conceptual change model based on constructivist view and this model is one of the important model in learning. The model of conceptual change developed by Posner, Strike, Hewson, and Gertzog (1982) suggest that there are three conditions which a new conception has to satisfy before it can be integrated with existing knowledge. THE EFFECT OF DUAL SITUATED LEARNING MODEL ON STUDENTS’ UNDERSTANDING OF PHOTOSYNTHESIS AND RESPIRATION CONCEPTS


title: Mineralocorticoid activity of 18-OH-DOC and DOCA in dogs with an aortic-caval fistula

abstract: The mineralocorticoid activity of 18-hydroxydeoxycorticosterone (18-OH-DOC) was measured during chronic electrolyte balance studies or during the postprandial increase in electrolyte excretion in conscious dogs with an aortic-caval fistula. In the chronic balance study, daily doses of DOCA and 18-OH-DOC ranging from 1 to 25 mg were administered intramuscularly for 3 consecutive days each, 6 h prior to feeding. For the postprandial study, 2-10 mg of DOCA and 18-OH-DOC were administered at feeding and postprandial electrolyte excretion was measured hourly for 6 h. Sodium and fluid retention in the dogs with an aortic-caval fistula was related to the dose of mineralocorticoid administered and equivalent sodium-retaining responses were achieved with 6-10 times more 18-OH-DOC than DOCA. Rapid absorption of both steroids was suggested from the postprandial measurements of urinary sodium excretion. Slight potassium retention occurred during the chronic administration of large doses of DOCA but the postprandial potassium responses produced by the steroids were variable and suggested a slight kaliuresis. The data also emphasize the importance of mineralocorticoids in sodium retention and ascites formation in this experimental model of high-output heart failure.


title: Dysuria: Evaluation and Differential Diagnosis in Adults.

abstract: The most common cause of acute dysuria is infection, especially cystitis. Other infectious causes include urethritis, sexually transmitted infections, and vaginitis. Noninfectious inflammatory causes include a foreign body in the urinary tract and dermatologic conditions. Noninflammatory causes of dysuria include medication use, urethral anatomic abnormalities, local trauma, and interstitial cystitis/bladder pain syndrome. An initial targeted history includes features of a local cause (e.g., vaginal or urethral irritation), risk factors for a complicated urinary tract infection (e.g., male sex, pregnancy, presence of urologic obstruction, recent procedure), and symptoms of pyelonephritis. Women with dysuria who have no complicating features can be treated for cystitis without further diagnostic evaluation. Women with vulvovaginal symptoms should be evaluated for vaginitis. Any complicating features or recurrent symptoms warrant a history, physical examination, urinalysis, and urine culture. Findings from the secondary evaluation, selected laboratory tests, and directed imaging studies enable physicians to progress through a logical evaluation and determine the cause of dysuria or make an appropriate referral.


title: Some applications of reversal theory to the explanation of gambling and gambling addictions

abstract: Reversal theory (Apter, 1982) provides a conceptual framework for the study of homeostatic psychological systems with multiple points of stability. This theory is applied to the explanation of normal and pathological gambling with special attention given to Apter's distinction between Telic (goal oriented) and Paratelic (playful) States. The entry of an individual to an episode of gambling is interpreted as a means of achieving a reversal or switch from one metamotivational state to another and so affecting the hedonic tone of the experience of arousal. The action during an episode of gambling is interpreted as a series of rapid switches from Telic to Paratelic States. Exit from the gambling situation is interpreted as resulting from a reversal from Paratelic to Telic metamotivational states. Scores of regular gamblers on the Telic Dominance Scale are related to their scores on the Sensation Seeking Scale, The interrelationship of arousal and reversals is used to advance an explanation both of some of the rewards of normal gambling and of the continued persistence of pathological gamblers in the face of punishing losses.


title: The Long-Term Effects of Small Classes in Early Grades: Lasting Benefits in Mathematics Achievement at Grade 9

abstract: Abstract Reducing class size to increase academic achievement is a policy option currently of great interest. Although the results of small-scale randomized experiments and some interpretations of large-scale econometric studies point to positive short-term effects of small classes, some scholars view the evidence as ambiguous. Project STAR in Tennessee-a 4-year, large-scale randomized experiment on the effects of class size—provided persuasive evidence that small classes have immediate positive effects on academic achievement. Unlike most other early education interventions, these effects persisted for several years after the children returned to regular-sized classes. The authors of the present article report analyses of a 6-year follow-up of the students in that experiment. Class-size effects persisted for at least 6 years and remained large enough to be important for educational policy. The results suggest that small classes in early grades have lasting benefits and that those benefits are greater for...


title: High-quality single-shot capture of facial geometry

abstract: This paper describes a passive stereo system for capturing the 3D geometry of a face in a single-shot under standard light sources. The system is low-cost and easy to deploy. Results are submillimeter accurate and commensurate with those from state-of-the-art systems based on active lighting, and the models meet the quality requirements of a demanding domain like the movie industry. Recovered models are shown for captures from both high-end cameras in a studio setting and from a consumer binocular-stereo camera, demonstrating scalability across a spectrum of camera deployments, and showing the potential for 3D face modeling to move beyond the professional arena and into the emerging consumer market in stereoscopic photography. ::: Our primary technical contribution is a modification of standard stereo refinement methods to capture pore-scale geometry, using a qualitative approach that produces visually realistic results. The second technical contribution is a calibration method suited to face capture systems. The systemic contribution includes multiple demonstrations of system robustness and quality. These include capture in a studio setup, capture off a consumer binocular-stereo camera, scanning of faces of varying gender and ethnicity and age, capture of highly-transient facial expression, and scanning a physical mask to provide ground-truth validation.


title: Determinants of adolescent pregnancy in sub-Saharan Africa: a systematic review

abstract: Adolescent pregnancy has been persistently high in sub-Saharan Africa. The objective of this review is to identify factors influencing adolescent pregnancies in sub-Saharan Africa in order to design appropriate intervention program. A search in MEDLINE, Scopus, Web of science, and Google Scholar databases with the following keywords: determinants, factors, reasons, sociocultural factors, adolescent pregnancy, unintended pregnancies, and sub- Saharan Africa. Qualitative and cross-sectional studies intended to assess factors influencing adolescent pregnancies as the primary outcome variable in sub- Saharan Africa were included. Our search was limited to, articles published from the year 2000 to 2017 in English. Twenty-four (24) original articles met the inclusion criteria. The study identified Sociocultural, environmental and Economic factors (Peer influence, unwanted sexual advances from adult males, coercive sexual relations, unequal gender power relations, poverty, religion, early marriage, lack of parental counseling and guidance, parental neglect, absence of affordable or free education, lack of comprehensive sexuality education, non-use of contraceptives, male’s responsibility to buy condoms, early sexual debut and inappropriate forms of recreation). Individual factors (excessive use of alcohol, substance abuse, educational status, low self-esteem, and inability to resist sexual temptation, curiosity, and cell phone usage). Health service-related factors (cost of contraceptives, Inadequate and unskilled health workers, long waiting time and lack of privacy at clinics, lack of comprehensive sexuality education, misconceptions about contraceptives, and non-friendly adolescent reproductive services,) as influencing adolescent pregnancies in Sub-Saharan Africa High levels of adolescent pregnancies in Sub-Saharan Africa is attributable to multiple factors. Our study, however, categorized these factors into three major themes; sociocultural and economic, individual, and health service related factors as influencing adolescent pregnancies. Community sensitization, comprehensive sexuality education and ensuring girls enroll and stay in schools could reduce adolescent pregnancy rates. Also, provision of adolescent-friendly health services in schools and healthcare centers and initiating adolescent empowerment programs could have a positive impact.


Frame Semantic Parsing using Framester Knowledge Graphs


title: Single-Chip CMOS-MEMS Dual Mode Scanning Microwave Microscope

abstract: We present the design, fabrication and experimental validation of an integrated Scanning Microwave Microscopy (SMM)/Atomic Force Microscopy (AFM) system that does not require the use of a conventional laser-based AFM. Microfabricated SMM probes are collocated with piezoresistive strain-based sensing AFM probes in a CMOS-MEMS process, and are actuated by integrated electrothermal scanners. Integration of AFM enables dual mode imaging (topography and electrical properties) and more importantly, it enables control over tip-sample distance, which is crucial for accurate SMM imaging. This design is unique in the sense that the tip can be scanned over the sample in 3 degrees of freedom, over a 20 μm×10 μm×30 μm scan range in the x, y, and z directions respectively. We fabricate our device by using a standard foundry CMOS process followed by in-house maskless MEMS post processing to release the devices. Single-chip SMM/AFM devices with integrated 1-D and 3-D actuation are thus obtained. These devices can be used to modulate the tip-sample separation to underlying samples with a periodic signal, improving immunity to long-term system drifts. We also investigate the effect of tip-sample separation on the resolution of the instrument. To increase measurement sensitivity, a single-stub matching network has been used to match the high tip-to-sample impedance to the 50 ohm characteristic impedance of a performance network analyzer. Measurement results of the CMOS-MEMS SMM are presented to verify the proposed concept.


title: Recovering microplastics from marine samples: A review of current practices.

abstract: An important component of microplastic research is development of reproducible methods for microplastic recovery and characterization. Presented is a review of the literature comparing microplastic separation and identification methodologies from seawater, sediment and marine organisms. The efficiency of methods was examined, including processing time, recovery rates, and potential destruction of microplastics. Visual examination and acid digestion were the most common separation methods for seawater samples and organisms, while density flotation was the primary method for sediment. Few studies reported recovery rates, or investigated the physical or chemical impact on plastics. This knowledge gap may lead to misidentification of plastic or unreliable pollution estimates. Further investigation of the impact chemical treatments have on plastic is warranted. Factors, i.e. biomass loading, recovery rates, and chemical compatibility, must be considered to allow for appropriate methodology. Standardizing this will contribute to efficient sample processing, and allow for direct comparison of microplastic contamination across environments.


title: Exploring the Usability of Video Game Heuristics for Pervasive Game Development in Smart Home Environments

abstract: Over the last years, a variety of pervasive games was developed. Al- though some of these applications were quite successful in bringing digital games back to the real world, very little is known about their successful integration into smart environments. When developing video games, developers can make use of a broad variety of heuristics. Using these heuristics to guide the development process of applications for intelligent environments could significantly increase their func- tional quality. This paper addresses the question, whether existing heuristics can be used by pervasive game developers, or if specific design guidelines for smart home environments are required. In order to give an answer, the transferability of video game heuristics was evaluated in a two-step process. In a first step, a set of validated heuristics was analyzed to identify platform-dependent elements. In a second step, the transferability of those elements was assessed in a focus group study.


Automatic Scene Text Recognition using a Convolutional Neural Network


title: A Non-invasive Wearable Neck-Cuff System for Real-Time Sleep Monitoring

abstract: Sleep is an important part of our lives which affects many life factors such as memory, learning, metabolism and the immune system. Researchers have found correlations between sleep and several diseases such as Chronic Obstructive Pulmonary disease, Chronic Heart Failure, Alzheimer's disease, etc. However, sleep data is mainly recorded and diagnosed in sleep labs or in hospitals for some critical cases with high costs. In this work we develop a non-invasive, wearable neck-cuff system capable of real-time monitoring and visualization of physiological signals. These signals are generated from various sensors housed in a soft neck-worn collar and sent via Bluetooth to a cell phone which stores the data. This data is processed and reported to the user or uploaded to the cloud and/or to a local PC. With this system we are able to monitor people's sleep continuously in a non-invasive and low cost method while at the same time collect a large database for sleep data which may benefit future advances in new findings and possibly enable a diagnosis of other diseases. We show as one of the applications of our system the possible detection of obstructive sleep apnea which is a common sleep disorder.


Unsupervised Profiling Methods for Fraud Detection


title: Verilog HDL model based thermometer-to-binary encoder with bubble error correction

abstract: This paper compares several approaches to come up with the Verilog HDL model of the thermometer-to-binary encoder with bubble error correction. It has been demonstrated that implementations of different ideas to correct bubble errors yield circuits whose parameters tremendously vary in delay, area and power consumption. The shortest delay is achieved for the design synthesized from the model which mimics a human reading temperature on classic liquid-in-glass thermometer.


title: CoQA: A Conversational Question Answering Challenge

abstract: Humans gather information through conversations involving a series of interconnected questions and answers. For machines to assist in information gathering, it is therefore essential to enable them to answer conversational questions. We introduce CoQA, a novel dataset for building Conversational Question Answering systems. Our dataset contains 127k questions with answers, obtained from 8k conversations about text passages from seven diverse domains. The questions are conversational, and the answers are free-form text with their corresponding evidence highlighted in the passage. We analyze CoQA in depth and show that conversational questions have challenging phenomena not present in existing reading comprehension datasets, e.g., coreference and pragmatic reasoning. We evaluate strong dialogue and reading comprehension models on CoQA. The best system obtains an F1 score of 65.4%, which is 23.4 points behind human performance (88.8%), indicating there is ample room for improvement. We present CoQA as a challenge to the community at https://stanfordnlp.github.io/coqa


title: Classical negation in logic programs and disjunctive databases

abstract: An important limitation of traditional logic programming as a knowledge representation tool, in comparison with classical logic, is that logic programming does not allow us to deal directly with incomplete information. In order to overcome this limitation, we extend the class of general logic programs by including classical negation, in addition to negation-as-failure. The semantics of such extended programs is based on the method of stable models. The concept of a disjunctive database can be extended in a similar way. We show that some facts of commonsense knowledge can be represented by logic programs and disjunctive databases more easily when classical negation is available. Computationally, classical negation can be eliminated from extended programs by a simple preprocessor. Extended programs are identical to a special case of default theories in the sense of Reiter.


title: SVD-Based Precoding for Single Carrier MIMO Transmission With Frequency Domain MMSE Turbo Equalization

abstract: This letter proposes an SVD-based precoding technique for single carrier transmission over frequency selective MIMO channels with frequency domain (FD) minimum-mean-squared-error (MMSE) turbo equalization. We consider the problem of optimizing the transmit power allocation over the FD channel eigenmodes subject to maintaining a target bit error rate of the turbo equalizer, and show that this problem can be efficiently solved by convex programming techniques. Results of the simulations conducted to demonstrate the superiority of the turbo equalizer with the proposed precoding technique, and to verify the accuracy of the analysis are presented in this letter.


title: Positive psychological capital: beyond human and social capital

abstract: or years, business academics and practitioners haveoperated in the belief that sustained competitiveadvantage could accrue from a variety of industry-level entry barriers, such as technological supremacy,patent protections, and government regulations. However,technological change and diffusion, rapid innovation, andderegulation have eroded these widely recognized barriers.In today’s environment, which requires flexibility, innova-tion, and speed-to-market, effectively developing andmanaging employees’ knowledge, experiences, skills, andexpertise—collectively defined as “human capital”—hasbecome a key success factor for sustained organizationalperformance. Traditionally, economic capital (both financial and tangi-ble assets such as plant and equipment) has received allthe attention. But enlightened managers today recognizethe importance not only of tangible assets, data, andphysical resources, but also of this intangible human capi-tal (sometimes called intellectual capital)—“human”referring to the people working at all levels of the organi-zation, and the economic term “capital” referring to theresources withdrawn from consumption that are investedfor future anticipated returns. Bill Gates has been knownto comment that the most important assets in his com-pany walk out the door every night. In other words, herecognizes that the collective knowledge, skills, and abili-ties of his employees represent a distinctive competencythat has created value and set Microsoft apart from itscompetitors.The value created when human capital is aligned withcorporate strategy and fully engaged in making the enter-prise effective has been researched extensively by Harter,Schmidt, and Hayes (2002) and others and found to havea significant positive impact on performance outcomes.Regardless of the recent downturn in the equity market,the past two decades have seen the market-to-book-valueratio of the S&P 500 go from about 1:1 to around 5:1.Oxman (2002) and others have attributed this increase tothe development of new models of company value that


title: Accounting for the effects of accountability

abstract: This article reviews the now extensive research literature addressing the impact of accountabilit y on a wide range of social judgments and choices. It focuses on 4 issues: (a) What impact do various accountability ground rules have on thoughts, feelings, and action? (b) Under what conditions will accountability attenuate, have no effect on, or amplify cognitive biases? (c) Does accountability alter how people think or merely what people say they think? and (d) What goals do accountable decision makers seek to achieve? In addition, this review explores the broader implications of accountability research. It highlights the utility of treating thought as a process of internalized dialogue; the importance of documenting social and institutional boundary conditions on putative cognitive biases; and the potential to craft empirical answers to such applied problems as how to structure accountability relationships in organizations.


title: Multi-view stereo reconstruction with high dynamic range texture

abstract: In traditional 3D model reconstruction, the texture information is captured in a certain dynamic range, which is usually insufficient for rendering under new environmental light. This paper proposes a novel approach for multi-view stereo (MVS) reconstruction of models with high dynamic range (HDR) texture. In the proposed approach, multiview images are firstly taken with different exposure times simultaneously. Corresponding pixels in adjacent viewpoints are then extracted using a multi-projection method, to robustly recover the response function of the camera. With the response function, pixel values in the differently exposed images can be converted to the desired relative radiance values. Subsequently, geometry reconstruction and HDR texture recovering can be achieved using these values. Experimental results demonstrate that our method can recover the HDR texture for the 3D model efficiently while keep high geometry precision. With our reconstructed HDR texture model, high-quality scene re-lighting is exemplarily exhibited.


Analysis of Windows 8 Registry Artifacts


title: Effects of nanoscale thickness and elastic nonlinearity on measured mechanical properties of polymeric films

abstract: Scanning probe microscope-enabled nanoindentation is increasingly reported as a means to assess the mechanical properties of nanoscale, compliant material volumes such as polymeric films and bio-membranes. It has been demonstrated experimentally that the Hertzian contact model developed for linear elastic materials of semi-infinite thickness fails to accurately predict the nominal elastic modulus E for polymeric thin films, consistent with limitations identified for comparably rigid metal and ceramic thin films. Here we employ computational simulations based on experimental parameters for compliant polyelectrolyte films, in order to separate limitations of such analysis due to the finite material thickness from those due to nonlinear constitutive relations approximating polymer deformation. We thus identify the range of strains, strain rates, and material thickness for which a modified Hertzian solution can accurately predict the elastic stiffness of polymeric films of nanoscale (b100nm) thickness from scanning probe microscope-enabled nanoindentation experiments.


title: Replay attack detection in a multi agent system using stability analysis and loss effective watermarking

abstract: In this paper the problem of detecting replay attack in a homogeneous multi agent system is addressed. Information exchange among the agents is under network topology and each agent is controlled to satisfy both local and global objectives. A local estimator and an anomaly detector are designed for each agent. Under replay attack to a part of network, we provide conditions on the stability of the under attack system in which, the attack cannot be detected by none of the agents. Next, a detection method is proposed which is based on using a watermarked control strategy, in which watermarking signal is shared among the agents through the network. Nevertheless, since this exogenous watermarking signal affects the performance of the controlled system, an optimization problem is introduced to find a watermarking signal with minimum loss effect.


Variety-Aware OLAP of Document-Oriented Databases


title: Improving the Extraction of Text in PDFs by Simulating the Human Reading Order

abstract: Text preprocessing and segmentation are critical tasks in search and text mining applications. Due to the huge amount of documents that are exclusively pre- sented in PDF format, most of the Data Mining (DM) and Information Retrieval (IR) systems must extract content from the PDF files. In some occasions this is a difficult task: the result of the extraction process from a PDF file is plain text, and it should be returned in the same order as a human would read the original PDF file. However, current tools for PDF text extraction fail in this objective when working with complex documents with multiple columns. For instance, this is the case of official government bulletins with legal information. In this task, it is mandatory to get correct and or- dered text as a result of the application of the PDF extractor. It is very usual that a legal article in a document refers to a previous article and they should be offered in the right sequential order. To overcome these difficulties we have designed a new method for extraction of text in PDFs that simulates the human reading order. We evaluated our method and compared it against other PDF extraction tools and algo- rithms. Evaluation of our approach shows that it significantly outperforms the results of the existing tools and algorithms.


title: Comparing deep neural network and other machine learning algorithms for stroke prediction in a large-scale population-based electronic medical claims database

abstract: Electronic medical claims (EMCs) can be used to accurately predict the occurrence of a variety of diseases, which can contribute to precise medical interventions. While there is a growing interest in the application of machine learning (ML) techniques to address clinical problems, the use of deep-learning in healthcare have just gained attention recently. Deep learning, such as deep neural network (DNN), has achieved impressive results in the areas of speech recognition, computer vision, and natural language processing in recent years. However, deep learning is often difficult to comprehend due to the complexities in its framework. Furthermore, this method has not yet been demonstrated to achieve a better performance comparing to other conventional ML algorithms in disease prediction tasks using EMCs. In this study, we utilize a large population-based EMC database of around 800,000 patients to compare DNN with three other ML approaches for predicting 5-year stroke occurrence. The result shows that DNN and gradient boosting decision tree (GBDT) can result in similarly high prediction accuracies that are better compared to logistic regression (LR) and support vector machine (SVM) approaches. Meanwhile, DNN achieves optimal results by using lesser amounts of patient data when comparing to GBDT method.


title: Safe robotic grasping: Minimum impact-force grasp selection

abstract: This paper addresses the problem of selecting from a choice of possible grasps, so that impact forces will be minimised if a collision occurs while the robot is moving the grasped object along a post-grasp trajectory. Such considerations are important for safety in human-robot interaction, where even a certified"human-safe"(e.g. compliant) arm may become hazardous once it grasps and begins moving an object, which may have significant mass, sharp edges or other dangers. Additionally, minimising collision forces is critical to preserving the longevity of robots which operate in uncertain and hazardous environments, e.g. robots deployed for nuclear decommissioning, where removing a damaged robot from a contaminated zone for repairs may be extremely difficult and costly. Also, unwanted collisions between a robot and critical infrastructure (e.g. pipework) in such high-consequence environments can be disastrous. In this paper, we investigate how the safety of the post-grasp motion can be considered during the pre-grasp approach phase, so that the selected grasp is optimal in terms applying minimum impact forces if a collision occurs during a desired post-grasp manipulation. We build on the methods of augmented robot-object dynamics models and"effective mass"and propose a method for combining these concepts with modern grasp and trajectory planners, to enable the robot to achieve a grasp which maximises the safety of the post-grasp trajectory, by minimising potential collision forces. We demonstrate the effectiveness of our approach through several experiments with both simulated and real robots.


title: Acquired resistance to Kudoa thyrsites in Atlantic salmon Salmo salar following recovery from a primary infection with the parasite

abstract: Abstract The influence of prior infection with Kudoa thyrsites or host size on the susceptibility of Atlantic salmon post-smolts to infection with the parasite was investigated. Exposure to infective K. thyrsites in raw seawater (RSW) was regulated by the use of ultraviolet irradiation (UVSW). Naive smolts were exposed to RSW for either 38 days (440 degree-days, DD) or 82 days (950 DD) after which they were maintained in UVSW. Control fish were maintained on UVSW only. Microscopic examination at day 176 (1985 DD) revealed K. thyrsites infection in nearly 90% of exposed fish but not in controls. Prevalence and severity of the infection decreased in later samples. Following a second exposure of all fish at day 415 (4275 DD), prevalence and severity were elevated in the UVSW controls compared to previously exposed fish groups, suggesting the acquisition of protective immunity. In a second experiment, naive smolts were exposed to RSW at weights of 101 g, 180 g, 210 g or 332 g and the prevalence and severity of K. thyrsites in the smallest fish group were higher than in any other group. However, infection parameters in the 101 g fish were not different from those in control fish (495 g) exposed in the first experiment. Concurrently, RSW was screened for K. thyrsites ribosomal DNA (rDNA) and the number of rDNA copies L − 1 seawater did not agree well with prevalence or severity of infections. Possible reasons for this poor agreement are discussed. Increased resistance to K. thyrsites was evident in Atlantic salmon post-smolts that have recovered from the infection, suggesting strategies for the mitigation of soft-flesh in market-size salmon. Statement of Relevance We showed that Atlantic salmon which had recovered from infection with Kudoa thyrsites were resistant to reinfection with the parasite, suggesting an acquired immunity and the possibility of vaccination as a management strategy. Quantitative detection of parasite DNA in seawater provides a tool for predicting the risk of infection with this economically important parasite.


title: How to manage children who have come into contact with patients affected by tuberculosis

abstract: Childhood tuberculosis (TB) indicates a recent infection, particularly in children aged < 5 years, and therefore is considered a sentinel event insofar as it highlights the presence of an undiagnosed or untreated source case. The risk of acquiring TB is directly proportional to the number of bacilli to which a subject is exposed and the environment in which the contact occurred. This document contains the recommendations of a group of Italian scientific societies for managing a child exposed to a case of TB based on an analysis of the risk factors for acquiring latent tuberculous infection (LTBI) and developing the disease, and the particular aspects TB transmission during the first years of life. The guidance includes a detailed description of the methods used to identify the index case, the tests that the exposed child should receive and the possibilities of preventive chemoprophylaxis depending on the patient's age and immune status, the chemotherapy and monitoring methods indicated in the case of LTBI, the management of a child who has come into contact with a case of multidrug-resistant or extensively drug-resistant TB, and the use of molecular typing in the analysis of epidemics. The group of experts identified risk factors for tuberculous infection and disease in pediatric age as well as gave recommendation on management of contacts of cases of TB according to their age, risk factors and exposure to multidrug-resistant or extensively drug-resistant TB.


title: A hybrid methodology for effort estimation in Agile development: an industrial evaluation

abstract: In agile software development, functionality is added to the system in an incremental and iterative manner. Practitioners often rely on expert-judgment to estimate effort in this context. The impact of a change on the existing system can provide objective information to practitioners to arrive at an informed estimate. In this regard, we have developed an innovative hybrid method that utilizes change impact analysis information for improving effort estimation. Additionally, an estimation model based on boosted trees is also developed. In this study, we evaluate the performance and usefulness of our innovative method and model in the context of agile software development from the perspective of agile development teams. A case study has been conducted with Insiders Technologies, a German software company, where we have applied our proposed method with tool-support in a live iteration and have evaluated it. The results show that the proposed method is useful and effective. It produces more accurate estimates than purely expert-based or purely model-based estimates.