title: Mechanomyography signals in spastic muscle and the correlation with the modified Ashworth scale

abstract: The modified Ashworth scale (MAS) is the most widely used measurement technique to assess levels of spasticity. In MAS, the evaluator graduates spasticity considering his/her subjective analysis of the muscular endurance during passive stretching. Therefore, it is a subjective scale. Mechanomyography (MMG) allows registering the vibrations generated by muscle contraction and stretching events that propagate through the tissue until the surface of the skin. With this in mind, this study aimed to investigate possible correlations between MMG signal and muscle spasticity levels determined by MAS. We evaluated 34 limbs considered spastic by MAS, including upper and lower limbs of 22 individuals of both sexes. Simultaneously, the MMG signals of the spastic muscle group (agonists) were acquired. The features investigated involved, in the time domain, the median energy (MMGME) of the MMG Z-axis (perpendicular to the muscle fibers) and, in the frequency domain, the median frequency (MMG mf ). The Kruskal-Wallis test (p me . There was a high linear correlation between the MMG me and MAS (R2=0.9557) and also a high correlation as indicated by Spearman test (ρ=0.9856; p mf did not present significant differences between MAS spasticity levels. There was moderate linear correlation between MAS and MMG mf (R2=0.4883 and Spearman test [ρ = 0.4590; p < 0.001]). Between the two investigated features, we conclude that the median energy is the most viable feature to evaluate spasticity due to strong correlations with the MAS.


title: Ranking Paragraphs for Improving Answer Recall in Open-Domain Question Answering

abstract: Recently, open-domain question answering (QA) has been combined with machine comprehension models to find answers in a large knowledge source. As open-domain QA requires retrieving relevant documents from text corpora to answer questions, its performance largely depends on the performance of document retrievers. However, since traditional information retrieval systems are not effective in obtaining documents with a high probability of containing answers, they lower the performance of QA systems. Simply extracting more documents increases the number of irrelevant documents, which also degrades the performance of QA systems. In this paper, we introduce Paragraph Ranker which ranks paragraphs of retrieved documents for a higher answer recall with less noise. We show that ranking paragraphs and aggregating answers using Paragraph Ranker improves performance of open-domain QA pipeline on the four open-domain QA datasets by 7.8% on average.


title: Concept Map Mining: A Definition and a Framework for Its Evaluation

abstract: Concept maps are visual representations of knowledge, widely used in educational contexts. We use the term "concept map mining" (CMM) to refer to the automatic extraction of concept maps from documents such as essays. The principles behind CMM have been proposed for applications such as: information extraction in specific knowledge domains, the measurement of student understanding and misconceptions based on written essays, and as a preliminary step to creating domain ontologies.Previous work on the automatic extraction of concept maps present two problems: 1) overly simplistic and varying definitions of concept maps, and 2) the lack of an evaluation framework that can be used to measure the quality of the generated maps. In this paper, we propose a formal definition of the term CMM, with a focus on educational applications.We also propose an evaluation framework that will allow other researchers to share a common ground to evaluate the performance of CMM methods.


title: Modeling the statistical time and angle of arrival characteristics of an indoor multipath channel

abstract: Most previously proposed statistical models for the indoor multipath channel include only time of arrival characteristics. However, in order to use statistical models in simulating or analyzing the performance of systems employing spatial diversity combining, information about angle of arrival statistics is also required. Ideally, it would be desirable to characterize the full spare-time nature of the channel. In this paper, a system is described that was used to collect simultaneous time and angle of arrival data at 7 GHz. Data processing methods are outlined, and results obtained from data taken in two different buildings are presented. Based on the results, a model is proposed that employs the clustered "double Poisson" time-of-arrival model proposed by Saleh and Valenzuela (1987). The observed angular distribution is also clustered with uniformly distributed clusters and arrivals within clusters that have a Laplacian distribution.


Study group SURF : Feature detection & description


title: Air pointing: Design and evaluation of spatial target acquisition with and without visual feedback

abstract: Sensing technologies such as inertia tracking and computer vision enable spatial interactions where users make selections by 'air pointing': moving a limb, finger, or device to a specific spatial region. In addition of expanding the vocabulary of possible interactions available, air pointing brings the potential benefit of enabling 'eyes-free' interactions, where users rely on proprioception and kinaesthesia rather than vision. This paper explores the design space for air pointing interactions, and presents tangible results in the form of a framework that helps designers understand input dimensions and resulting interaction qualities. The framework provides a set of fundamental concepts that aid in thinking about the air pointing domain, in characterizing and comparing existing solutions, and in evaluating novel techniques. We carry out an initial investigation to demonstrate the concepts of the framework by designing and comparing three air pointing techniques: one based on small angular 'raycasting' movements, one on large movements across a 2D plane, and one on movements in a 3D volume. Results show that large movements on the 2D plane are both rapid (selection times under 1s) and accurate, even without visual feedback. Raycasting is rapid but inaccurate, and the 3D volume is expressive but slow, inaccurate, and effortful. Many other findings emerge, such as selection point 'drift' in the absence of feedback. These results and the organising framework provide a foundation for innovation and understanding of air pointing interaction.


title: An effiecient human tracking system using Haar-like and hog feature extraction

abstract: The traditional human tracking systems are often prone to problems which can be deduced either from the subject, camera or background movements which includes major changes in posture, appearance, clothing and lighting of the background. The work introduced here proposes a system for extracting and tracking objects from a video sequence by initializing the process of feature extraction of the selected area of the human. The need for cascade extraction by using Haar-like features, is to basically decrease the use of crude or raw pixel values and then make classification easier. The major issue here is the problem in extracting the required finite set of input for identifying the characteristics necessary for domain encoding rule In the proposed work the major aim is to address the tracking procedure by facilitating the exclusive histogram of oriented gradient (HOG) methodology, using which only the human’s unit element is embraced in the usual tracking system, making it problematic for robust monitoring. The features of Haar-like and HOG methods are combined to propose a tracking system which uses the Haar characteristics for the object’s structure and the HOG features for the edge. A set of mixed features is developed with these two features. Boosting Online’s selection feature is used to select important features and update these online features to understand the optimal choice using cascading SVM classifier.


title: Long-term measurements of 36Cl to investigate potential solar influence on the decay rate

abstract: Abstract Recently, Jenkins et al. [6] reported on fluctuations in the detected decay events of 36 Cl which were measured with a Geiger–Muller counter. Experimental data of 32 Si measured by means of an end-window gas-flow proportional counter at the Brookhaven National Laboratory show similar periodicity, albeit a different amplitude. Jenkins et al. interpret the fluctuations as evidence of solar influence on the decay rates of beta-decaying radionuclides. In this work, liquid scintillation counting was used to check for potential variations in the 36 Cl decay rates. A custom-built counter with three photomultiplier tubes was used. In contrast to commercial counters, the relevant parameters of our system are well controlled and the discrimination threshold and HV setting can be adjusted and checked. The experimental data were analyzed by means of the triple-to-double coincidence ratio (TDCR) method which is a primary method for activity determination. Thus, our results do not depend on any other standard or reference source. Our data show fluctuations which are by more than one order of magnitude lower than those seen in the experiment using a Geiger–Muller counter. More importantly, no oscillation could be identified. Interestingly, our data overlap in time with those from Jenkins et al. [6]. We do not observe the phase and amplitude as seen by Jenkins and conclude that the fluctuations are not due to solar influence. This also implies that the interpretation by Jenkins et al. is false.


title: AMES-Cloud: A Framework of Adaptive Mobile Video Streaming and Efficient Social Video Sharing in the Clouds

abstract: While demands on video traffic over mobile networks have been souring, the wireless link capacity cannot keep up with the traffic demand. The gap between the traffic demand and the link capacity, along with time-varying link conditions, results in poor service quality of video streaming over mobile networks such as long buffering time and intermittent disruptions. Leveraging the cloud computing technology, we propose a new mobile video streaming framework, dubbed AMES-Cloud, which has two main parts: adaptive mobile video streaming (AMoV) and efficient social video sharing (ESoV). AMoV and ESoV construct a private agent to provide video streaming services efficiently for each mobile user. For a given user, AMoV lets her private agent adaptively adjust her streaming flow with a scalable video coding technique based on the feedback of link quality. Likewise, ESoV monitors the social network interactions among mobile users, and their private agents try to prefetch video content in advance. We implement a prototype of the AMES-Cloud framework to demonstrate its performance. It is shown that the private agents in the clouds can effectively provide the adaptive streaming, and perform video sharing (i.e., prefetching) based on the social network analysis.


How Mothers of Hearing-Impaired Infants Interact With Their Babies Through Speech and Touch


title: Maximal causality reduction for TSO and PSO

abstract: Verifying concurrent programs is challenging due to the exponentially large thread interleaving space. The problem is exacerbated by relaxed memory models such as Total Store Order (TSO) and Partial Store Order (PSO) which further explode the interleaving space by reordering instructions. A recent advance, Maximal Causality Reduction (MCR), has shown great promise to improve verification effectiveness by maximally reducing redundant explorations. However, the original MCR only works for the Sequential Consistency (SC) memory model, but not for TSO and PSO. In this paper, we develop novel extensions to MCR by solving two key problems under TSO and PSO: 1) generating interleavings that can reach new states by encoding the operational semantics of TSO and PSO with first-order logical constraints and solving them with SMT solvers, and 2) enforcing TSO and PSO interleavings by developing novel replay algorithms that allow executions out of the program order. We show that our approach successfully enables MCR to effectively explore TSO and PSO interleavings. We have compared our approach with a recent Dynamic Partial Order Reduction (DPOR) algorithm for TSO and PSO and a SAT-based stateless model checking approach. Our results show that our approach is much more effective than the other approaches for both state-space exploration and bug finding – on average it explores 5-10X fewer executions and finds many bugs that the other tools cannot find.


title: 50-Gb/s Direct Modulation of a 1.3-μm InGaAlAs-Based DFB Laser With a Ridge Waveguide Structure

abstract: We demonstrate 50-Gb/s direct modulation by using 1.3-μm distributed-feedback lasers with a ridge waveguide structure. We employed InGaAlAs material for a multiple-quantum well to obtain a low damping factor K, and fabricated a ridge waveguide structure buried in benzocyclobutene to realize a structure with a low parasitic capacitance. In addition, to obtain high maximum frequency relaxation oscillations fr, we designed the cavity length L), and achieved a 3-dB-down frequency bandwidth of 34 GHz. We realized 50-Gb/s clear eye openings with a back-to-back configuration, and achieved a mean output power of over 5.0 dBm, and a dynamic extinction ratio of 4.5 dB. We measured the 50-Gb/s transmission characteristics, and obtained clear eye openings for transmissions over 20-, 40-, and 60-km single-mode fibers (SMF). We also measured the bit-error-rate performance, and obtained an error-free operation and a power penalty of less than 0.5 dB after a 10-km SMF transmission.


title: Modelling information flow and sharing matrix for fresh food supply chains

abstract: Purpose ::: ::: ::: ::: ::: Despite much research on supply chain (SC) integration and the growing emphasis on recent information technology advancements as an enabler of improved performance, there has been limited research focussed specifically on information integration in supply chains (SCs). The purpose of this paper is to systematically review the literature on information integration in the fresh food supply chain (FFSC) from a holistic perspective. ::: ::: ::: ::: ::: Design/methodology/approach ::: ::: ::: ::: ::: Literature review is done by systematically collecting and analysing the recent literature to identify various participant entities of the FFSC information network and their specific information needs. ::: ::: ::: ::: ::: Findings ::: ::: ::: ::: ::: The information needs of FFSC entities are diverse but the needs are common across multiple entities. ::: ::: ::: ::: ::: Research limitations/implications ::: ::: ::: ::: ::: This study only reviewed the FFSC-related literature; an extended study of the food industry may reveal a more comprehensive view. ::: ::: ::: ::: ::: Practical implications ::: ::: ::: ::: ::: These findings are useful for practitioners in understanding the participant entities in the information network and their information needs and for policymakers in formulating FFSC development initiatives. ::: ::: ::: ::: ::: Originality/value ::: ::: ::: ::: ::: The authors are not aware of another study that investigates the FFSC in a holistic approach, one that identifies the actors, their interactions and information needs.


title: Solving large-scale planning problems by decomposition and macro generation

abstract: Large-scale classical planning problems such as factory assembly problems pose a significant challenge for domain-independent planners. We propose a macro-based planner which automatically identifies subproblems, generate macros from subplans and integrate the subplans by solving the whole augmented problem. We show experimentally that our approach can be used to solve large problem instances that are beyond the reach of current state-of-the-art satisficing planners.


title: A Gap Waveguide-Fed Wideband Patch Antenna Array for 60-GHz Applications

abstract: This communication presents a wideband aperture-coupled patch antenna array based on ridge gap waveguide feed layer for 60-GHz applications. The novelty of this antenna lies in the combination of relatively new gap waveguide technology along with conventional patch antenna arrays allowing to achieve a wideband patch antenna array with high gain and high radiation efficiency. An $8 \times 8$ -element array antenna is designed, fabricated, and tested. Experimental results show that the bandwidth of VSWR < 2 is up to 15.5% (57.5–67.2 GHz). More than 75% efficiency and higher than 21.5-dBi gain are achieved over the operational bandwidth. The results are valuable for the design and evaluation of wideband planar antenna arrays at millimeter-wave frequencies.


title: Simulink based performance analysis of lead acid batteries with the variation of load current and temperature

abstract: Storage device in renewable energy applications plays an important role for efficient operation. For solar PV applications, storage device is an integral part during post sun shine hours to supply power to the load. For Solar Home System (SHS), approximately 60% of the total cost is due to storage battery and the battery needs replacement in every five years or so. If the performance of the battery can be enhanced, not only the cost of energy will come down appreciably but the reliability of the system will improve. Battery is needed in PV system to store the excess energy from the sun and release the power to the system again when it is needed. In other words, to enhance a system performance we have to increase the battery performance. In this paper, the parameters which play important role for optimum performance has been studied. The major two parameters that affect the battery performance are load current and temperature. It has been found that, when the discharge current is high, battery capacity reduces and the vice-versa. Again in case of temperature, when temperature increases more than the rated standard value of 25°C, capacity increases but the life time of the battery decreases. On the other hand, when the ambient temperature goes down, capacity of battery decreases but lifetime of the battery is increased. To analyse the effect of temperature and load current on battery performance, the standard equivalent circuit of battery is considered first and then the equivalent circuit is simulated using Simulink under MATLAB environment.


title: Nonnegativity constraints in numerical analysis

abstract: A survey of the development of algorithms for enforcing nonnegativity constraints in scientific computation is given. Special emphasis is placed on such constraints in least squares computations in numerical linear algebra and in nonlinear optimization. Techniques involving nonnegative low-rank matrix and tensor factorizations are also emphasized. Details are provided for some important classical and modern applications in science and engineering. For completeness, this report also includes an effort toward a literature survey of the various algorithms and applications of nonnegativity constraints in numerical analysis.


title: Advances in antenna designs for UHF RFID tags mountable on conductive items

abstract: The design of antennas for metal-mountable radio-frequency identification tags is driven by a unique set of challenges: cheap, small, low-profile, and conformal structures need to provide reliable operation when tags are mounted on conductive platforms of various shapes and sizes. During the past decade, a tremendous amount of research has been dedicated to meeting these stringent requirements. Currently, the tag-reading ranges of several meters are achieved with flexible-label types of tags. Moreover, a whole spectrum of tag-size performance ratios has been demonstrated through a variety of innovative antenna-design approaches. This article reviews and summarizes the progress made in antennas for metal-mountable tags, and presents future prospects.


title: TAIGA: A new RISC-V soft-processor framework enabling high performance CPU architectural features

abstract: Recently, there has been an increased focus on integration of reconfigurable fabric with modern processors. However, existing soft-processors are optimized to leverage older FPGA fabrics, focus primarily on resource minimization and have fixed-pipeline designs that limit the scope for tightly integrated hardware accelerators. In this work, we present Taiga: a RISC-V, 32-bit, soft-processor architecture supporting the RISC-V Multiply/Divide and Atomic operations extensions (RV32IMA) designed to support Linux-based shared-memory systems. The processor design is highly configurable and features a standardized interface for functional units allowing for ease of integration of new functional units. Despite a more complex pipeline, our design uses approximately 33% fewer slices while clocking 39% faster than a LEON3 based system built on a Xilinx Zynq X7CZ020.


title: Performing perception—staging aesthetics of interaction

abstract: In interaction design for experience-oriented uses of technology, a central facet of aesthetics of interaction is rooted in the user's experience of herself “performing her perception.” By drawing on performance (theater) theory, phenomenology and sociology and with references to recent HCI-work on the relation between the system and the performer/user and the spectator's relation to this dynamic, we show how the user is simultaneously operator, performer and spectator when interacting. By engaging with the system, she continuously acts out these three roles and her awareness of them is crucial in her experience. We argue that this 3-in-1 is always already shaping the user's understanding and perception of her interaction as it is staged through her experience of the object's form and expression. Through examples ranging from everyday technologies utilizing performances of interaction to spatial contemporary artworks, digital as well as analogue, we address the notion of the performative spectator and the spectating performer. We demonstrate how perception is also performative and how focus on this aspect seems to be crucial when designing experience-oriented products, systems and services.


title: Lessons learned from child sexual abuse research: prevalence, outcomes, and preventive strategies

abstract: Although child sexual abuse (CSA) is recognized as a serious violation of human well-being and of the law, no community has yet developed mechanisms that ensure that none of their youth will be sexually abused. CSA is, sadly, an international problem of great magnitude that can affect children of all ages, sexes, races, ethnicities, and socioeconomic classes. Upon invitation, this current publication aims at providing a brief overview of a few lessons we have learned from CSA scholarly research as to heighten awareness of mental health professionals on this utmost important and widespread social problem. This overview will focus on the prevalence of CSA, the associated mental health outcomes, and the preventive strategies to prevent CSA from happening in the first place.


title: Self-discipline outdoes IQ in predicting academic performance of adolescents

abstract: In a longitudinal study of 140 eighth-grade students, self-discipline measured by self-report, parent report, teacher report, and monetary choice questionnaires in the fall predicted final grades, school attendance, standardized achievement-test scores, and selection into a competitive high school program the following spring. In a replication with 164 eighth graders, a behavioral delay-of-gratification task, a questionnaire on study habits, and a group-administered IQ test were added. Self-discipline measured in the fall accounted for more than twice as much variance as IQ in final grades, high school selection, school attendance, hours spent doing homework, hours spent watching television (inversely), and the time of day students began their homework. The effect of self-discipline on final grades held even when controlling for first-marking-period grades, achievement-test scores, and measured IQ. These findings suggest a major reason for students falling short of their intellectual potential: their fail...


title: Distributed Reinforcement Learning via Gossip

abstract: We consider the classical TD(0) algorithm implemented on a network of agents wherein the agents also incorporate the updates received from neighboring agents using a gossip-like mechanism. The combined scheme is shown to converge for both discounted and average cost problems.


title: Applications of Solid-Phase Microextraction and Gas Chromatography/Mass Spectrometry (SPME-GC/MS) in the Study of Grape and Wine Volatile Compounds

abstract: Volatile compounds are responsible for the wine "bouquet", which is perceived by sniffing the headspace of a glass, and of the aroma component (palate-aroma) of the overall flavor, which is perceived on drinking. Grape aroma compounds are transferred to the wine and undergo minimal alteration during fermentation (e.g., monoterpenes and methoxypyrazines); others are precursors of aroma compounds which form in winemaking and during wine aging (e.g., glycosidically-bound volatile compounds and C13-norisoprenoids). Headspace solid phase microextraction (HS-SPME) is a fast and simple technique which was developed for analysis of volatile compounds. This review describes some SPME methods coupled with gas chromatography/mass spectrometry (GC/MS) used to study the grape and wine volatiles.


title: Recent trends in decentralized cryptocurrencies (invited talk)

abstract: Following Bitcoin's introduction, decentralized cryptocurrencies began to emerge as a new application domain for computer science. Bitcoin's protocol has been researched and improved upon along many fronts: from its underlying incentives, through to its cryptographic primitives and its security. Many research questions and challenges still remain as cryptocurrencies and other financial systems that rely on similar principles gain wider adoption.


title: Color image decomposition and restoration

abstract: Meyer has recently introduced an image decomposition model to split an image into two components: a geometrical component and a texture (oscillatory) component. Inspired by his work, numerical models have been developed to carry out the decomposition of gray scale images. In this paper, we propose a decomposition algorithm for color images. We introduce a generalization of Meyer’s G norm to RGB vectorial color images, and use Chromaticity and Brightness color model with total variation minimization. We illustrate our approach with numerical examples.


title: Neural reuse: A fundamental organizational principle of the brain

abstract: An emerging class of theories concerning the functional structure of the brain takes the reuse of neural circuitry for various cognitive purposes to be a central organizational principle. According to these theories, it is quite common for neural circuits established for one purpose to be exapted (exploited, recycled, redeployed) during evolution or normal development, and be put to different uses, often without losing their original functions. Neural reuse theories thus differ from the usual understanding of the role of neural plasticity (which is, after all, a kind of reuse) in brain organization along the following lines: According to neural reuse, circuits can continue to acquire new uses after an initial or original function is established; the acquisition of new uses need not involve unusual circumstances such as injury or loss of established function; and the acquisition of a new use need not involve (much) local change to circuit structure (e.g., it might involve only the establishment of functional connections to new neural partners). Thus, neural reuse theories offer a distinct perspective on several topics of general interest, such as: the evolution and development of the brain, including (for instance) the evolutionary-developmental pathway supporting primate tool use and human language; the degree of modularity in brain organization; the degree of localization of cognitive function; and the cortical parcellation problem and the prospects (and proper methods to employ) for function to structure mapping. The idea also has some practical implications in the areas of rehabilitative medicine and machine interface design.


title: Modeling solar photovoltaic cell and simulated performance analysis of a 250W PV module

abstract: The main purpose of this study is to develop the mathematical model of solar photovoltaic (PV) cell and to simulate its behavior. The study includes the performance analysis of a 250W PV module and its behavior on different temperature conditions, irradiance levels. It also focuses on the effects of varying shunt and series resistances. The model has been developed considering possible environmental effects on solar PV generation. The results of the characteristics curves in this paper are compared to the curves provided by the CS6P-250M PV module datasheet. Using this model it is possible to simulate the behavior of any large scale PV array or solar Photovoltaic Energy Conversion Systems (PVECS). The model was developed by using Matlab®/Simulink” software. This model can be used for further simulation based research and analysis on PVECS.


title: Classification of electroencephalography (EEG) signals for different mental activities using Kullback Leibler (KL) divergence

abstract: Automatic classification of electroencephalography (EEG) signals, for different type of mental activities, is an active area of research and has many applications such as brain computer interface (BCI) and medical diagnoses. We introduce a simple yet effective way to use Kullback-Leibler (KL) divergence in the classification of raw EEG signals. We show that k-nearest neighbor (k-NN) algorithm with KL divergence as the distance measure, when used using our feature vectors, gives competitive classification accuracy and consistently outperforms the more commonly used Euclidean k-NN. We also develop and demonstrate the use of a KL-based kernel to classify EEG data using support vector machines (SVMs). Our KL-distance based kernel compares favorably to other well established kernels such as linear and radial basis function (RBF) kernel. The EEG data, used in our experiments for classification, was recorded while the subject performed 5 different mental activities such as math problem solving, letter composing, 3-D block rotation, counting and resting (baseline). We present classification results for this data set that are obtained by using raw EEG data with no explicit artifact removal in the pre-processing steps.


title: CAPTCHA Design: Color, Usability, and Security

abstract: Most user interfaces use color, which can greatly enhance their design. Because the use of color is typically a usability issue, it rarely causes security failures. However, using color when designing CAPTCHAs, a standard security technology that many commercial websites apply widely, can have an impact on usability and interesting but critical implications for security. Here, the authors examine some CAPTCHAs to determine whether their use of color negatively affects their usability, security, or both.


title: End-to-End Optimization of Task-Oriented Dialogue Model with Deep Reinforcement Learning

abstract: In this paper, we present a neural network based task-oriented dialogue system that can be optimized end-to-end with deep reinforcement learning (RL). The system is able to track dialogue state, interface with knowledge bases, and incorporate query results into agent's responses to successfully complete task-oriented dialogues. Dialogue policy learning is conducted with a hybrid supervised and deep RL methods. We first train the dialogue agent in a supervised manner by learning directly from task-oriented dialogue corpora, and further optimize it with deep RL during its interaction with users. In the experiments on two different dialogue task domains, our model demonstrates robust performance in tracking dialogue state and producing reasonable system responses. We show that deep RL based optimization leads to significant improvement on task success rate and reduction in dialogue length comparing to supervised training model. We further show benefits of training task-oriented dialogue model end-to-end comparing to component-wise optimization with experiment results on dialogue simulations and human evaluations.


title: Photo2Trip: Exploiting Visual Contents in Geo-tagged Photos for Personalized Tour Recommendation

abstract: Recently accumulated massive amounts of geo-tagged photos provide an excellent opportunity to understand human behaviors and can be used for personalized tour recommendation. However, no existing work has considered the visual content information in these photos for tour recommendation. We believe the visual features of photos provide valuable information on measuring user / Point-of-Interest (POI) similarities, which is challenging due to data sparsity. To this end, in this paper, we propose a visual feature enhanced tour recommender system, named 'Photo2Trip', to utilize the visual contents and collaborative filtering models for recommendation. Specifically, we first extract various visual features from photos taken by tourists. Then, we propose a Visual-enhanced Probabilistic Matrix Factorization model (VPMF), which integrates visual features into the collaborative filtering model, to learn user interests by leveraging the historical travel records. Moreover, user interests together with trip constraints are formalized to an optimization problem for trip planning. Finally, the experimental results on real-world data show that our proposed visual-enhanced personalized tour recommendation method outperforms other benchmark methods in terms of recommendation accuracy. The results also show that visual features are effective on alleviating the data sparsity and cold start problems on personalized tour recommendation.


title: Effects of continuous Trichloroethylene inhalation on different strains of mice

abstract: Seven different strains of mice (wild, C57BL, DBA, B6CBA, A/sn, NZB and NMRI) were continuously exposed to 150 ppm trichloroethylene (TCE) during 30 days. After exposure all strains showed large increases in liver weight, while changes in kidney and spleen weights were small. Plasma butyrylcholinesterase (BuChE) activity increased in males of all strains and in females of strains A/sn and NZB. The increase in the females was less than that of the corresponding males. We concluded that there are moderate, but in some cases, significant differences in TCE sensitivity between different mouse strains. The differences observed between sexes emphasizes the importance of specifying sex as well as strain when reporting on toxic effects.


Proofs of Catalytic Space.


title: Factors associated with mothers’ knowledge on infant and young child feeding recommendation in slum areas of Bahir Dar City, Ethiopia: cross sectional study

abstract: BACKGROUND ::: Malnutrition is a public health concern in Ethiopia. This might be correlated with inappropriate infant and young child feeding practice. This in turn is affected by Mothers' knowledge on feeding practice. However, information on mothers' knowledge on infant and young child feeding recommendation was scarce in Ethiopia. Therefore, this study was designed to assess mothers' knowledge on infant and young child feeding recommendation and associated factors in slum areas of Bahir Dar City, Ethiopia. ::: ::: ::: METHODS ::: A community based cross-sectional study was conducted from May 1-26/2015. Systematic sampling technique was used to select respondents. Data were collected by pretested, structured, interviewer administered questionnaire. Data were entered and analyzed by SPSS version 20 software. Knowledge score was computed. Binary and multivariable logistic regression analysis were used to identify factors associated with maternal knowledge. ::: ::: ::: RESULTS ::: Only 28.7% of mothers had sufficient knowledge on infant and young child feeding recommendation. Factors associated with mothers, knowledge were above primary education [AOR 2.5, 95% CI (1.5, 3.9)], possession of radio [AOR 1.7, 95% CI (1.1, 2.7)], attending antenatal care [AOR 2.4, 95% CI (1.5, 4.0)], and having employed husband [AOR 2.3, 95% CI (1.2, 4.4)]. ::: ::: ::: CONCLUSION ::: Mothers' knowledge on infant and young child feeding recommendation was very low. Hence, education on infant and young child feeding recommendation should be strengthened during antenatal care visit and using mass media especially for mothers with lower educational status to fill up of this gap.


Utilizing Learners' Negative Ratings in Semantic Content-based Recommender System for e-Learning Forum


title: Inhibition of anaerobic digestion process: a review.

abstract: Anaerobic digestion is an attractive waste treatment practice in which both pollution control and energy recovery can be achieved. Many agricultural and industrial wastes are ideal candidates for anaerobic digestion because they contain high levels of easily biodegradable materials. Problems such as low methane yield and process instability are often encountered in anaerobic digestion, preventing this technique from being widely applied. A wide variety of inhibitory substances are the primary cause of anaerobic digester upset or failure since they are present in substantial concentrations in wastes. Considerable research efforts have been made to identify the mechanism and the controlling factors of inhibition. This review provides a detailed summary of the research conducted on the inhibition of anaerobic processes. The inhibitors commonly present in anaerobic digesters include ammonia, sulfide, light metal ions, heavy metals, and organics. Due to the difference in anaerobic inocula, waste composition, and experimental methods and conditions, literature results on inhibition caused by specific toxicants vary widely. Co-digestion with other waste, adaptation of microorganisms to inhibitory substances, and incorporation of methods to remove or counteract toxicants before anaerobic digestion can significantly improve the waste treatment efficiency.


title: Assessment of land surface temperature in relation to landscape metrics and fractional vegetation cover in an urban/peri-urban region using Landsat data

abstract: Land surface temperature LST is essentially considered to be one of the most important indicators used for assessment of the urban thermal environment. It is quite evident that land-use/land-cover LULC and landscape patterns have ecological implications at varying spatial scales, which in turn influence the distribution of habitat and material/energy fluxes in the landscape. This article attempts to quantitatively analyse the complex interrelationships between urban LST and LULC landscape patterns with the purpose of elucidating their relation to landscape processes. The study employed an integrated approach involving remote-sensing, geographic information system GIS, and landscape ecology techniques on bi-temporal Landsat Thematic Mapper images of Southwestern Sydney metropolitan region and the surrounding fringe, taken at approximately the same time of the year in July 1993 and July 2006. First, the LULC categories and LST were extracted from the bi-temporal images. The LST distribution and changes and LST of the LULC categories were then quantitatively analysed using landscape metrics and LST zones. The results show that large differences in temperature existed in even a single LULC category, except for variations between different LULC categories. In each LST zone, the regressive function of LST with fractional vegetation cover FVC indicated a significant relationship between LST and FVC. Landscape metrics of LULC categories in each zone in relation to the other zones showed changing patterns between 1993 and 2006. This study also illustrates that a method integrating retrieval of LST and FVC from remote-sensing images combined with landscape metrics provides a novel and feasible way to describe the spatial distribution and temporal variation in urban thermal patterns and associated LULC conditions in a quantitative manner.


title: High-Performance Hypervisor Architectures: Virtualization in HPC Systems

abstract: Virtualization presents both challenges and opportunities for HPC systems and applications. This paper reviews them and also offers technical insights into two key challenges faced by future highend machines: (1) the I/O challenges they face and (2) the multicore nature of future HPC platforms. Concerning the latter, we argue the need to better structure virtualization solutions, to improve the compute experience of future HPC applications, and to provide scalability for virtualization solutions on future many-core platforms. Concerning (1), we present new methods for device virtualization, along with evidence that such methods can improve the I/O performance experienced by guest operating systems and applications running on HPC machines. Experimental results validate the claims made in (1) and (2), attained with the Xen hypervisor running on modern multi-core machines. Finally, the paper offers new directions for research in virtualization for HPC machines. It describes ways for further improving the effective I/O performance as seen by HPC applications by extending virtualization to associate application-relevant functions with I/O data streams and through QoS support for these streams. Other issues discussed are reliability enhancements for I/O, and online system and resource management.


title: Global Encoding for Abstractive Summarization

abstract: In neural abstractive summarization, the conventional sequence-to-sequence (seq2seq) model often suffers from repetition and semantic irrelevance. To tackle the problem, we propose a global encoding framework, which controls the information flow from the encoder to the decoder based on the global information of the source context. It consists of a convolutional gated unit to perform global encoding to improve the representations of the source-side information. Evaluations on the LCSTS and the English Gigaword both demonstrate that our model outperforms the baseline models, and the analysis shows that our model is capable of reducing repetition.


title: Above 500V class Superjunction MOSFETs fabricated by deep trench etching and epitaxial growth

abstract: Above 500V class superjunction (SJ) MOSFETs fabricated by deep-trench etching and epitaxial growth are investigated. These SJ-MOSFETs show the lowest specific on-resistance (RonA) of 21.3mOmegacm2 at a breakdown voltage (VB) of 540V, among reported trench-filling type of devices in the same voltage class. These RonA-VB trade-off characteristics are accomplished by optimizing doping concentrations of n- and p- column regions. In addition, low reverse biased leakage current has been achieved by filling deep trenches with defect-free single crystal silicon


title: The embryology of behavior: The beginnings of the human mind

abstract: Preface 1. The search for beginnings 2. Birth and age 3. Zygote and embryo 4. The genesis of behaviour 5. The archaic motor system 6. The growth of fetal behaviour 7. Breathing behaviour 8. Muscle tonus 9. Electrotonic integration 10. The fetal-infant 11. The circumnatal infant 12. The diurnal cycle of sleep and wakeness 13. Species and individual 14. The dynamic morphology of behaviour 15. The hierarchical continuum A photographic delineation of behaviour patterns and growth sequences Appendices Selected references Index.


title: Citation analysis and peer ranking of Australian social science journals

abstract: Citation analyses were performed for Australian social science journals to determine the differences between data drawn from Web of Science and Scopus. These data were compared with the tier rankings assigned by disciplinary groups to the journals for the purposes of a new research assessment model, Excellence in Research for Australia (ERA), due to be implemented in 2010. In addition, citation-based indicators including an extended journal impact factor, the h-index, and a modified journal diffusion factor, were calculated to assess whether subsequent analyses influence the ranking of journals. The findings suggest that the Scopus database provides higher number of citations for more of the journals. However, there appears to be very little association between the assigned tier ranking of journals and their rank derived from citations data. The implications for Australian social science researchers are discussed in relation to the use of citation analysis in the ERA.


title: Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons

abstract: An activation boundary for a neuron refers to a separating hyperplane that determines whether the neuron is activated or deactivated. It has been long considered in neural networks that the activations of neurons, rather than their exact output values, play the most important role in forming classificationfriendly partitions of the hidden feature space. However, as far as we know, this aspect of neural networks has not been considered in the literature of knowledge transfer. In this paper, we propose a knowledge transfer method via distillation of activation boundaries formed by hidden neurons. For the distillation, we propose an activation transfer loss that has the minimum value when the boundaries generated by the student coincide with those by the teacher. Since the activation transfer loss is not differentiable, we design a piecewise differentiable loss approximating the activation transfer loss. By the proposed method, the student learns a separating boundary between activation region and deactivation region formed by each neuron in the teacher. Through the experiments in various aspects of knowledge transfer, it is verified that the proposed method outperforms the current state-of-the-art.


title: Do RNNs learn human-like abstract word order preferences?

abstract: RNN language models have achieved state-of-the-art results on various tasks, but what exactly they are representing about syntax is as yet unclear. Here we investigate whether RNN language models learn humanlike word order preferences in syntactic alternations. We collect language model surprisal scores for controlled sentence stimuli exhibiting major syntactic alternations in English: heavy NP shift, particle shift, the dative alternation, and the genitive alternation. We show that RNN language models reproduce human preferences in these alternations based on NP length, animacy, and definiteness. We collect human acceptability ratings for our stimuli, in the first acceptability judgment experiment directly manipulating the predictors of syntactic alternations. We show that the RNNs' performance is similar to the human acceptability ratings and is not matched by an n-gram baseline model. Our results show that RNNs learn the abstract features of weight, animacy, and definiteness which underlie soft constraints on syntactic alternations.


Controlling Expressiveness ofQuestion Interpretation with a Constrained Tree Transducer Induction


title: Games, motivation and learning: A research and practice model. Simulation & Gaming 33(4

abstract: Although most agree that games can be engaging and that games can be instructive, there is little consensus regarding the essential characteristics of instructional games. Implicit in the research literature is the notion that if we pair instructional content with certain game features, we can harness the power of games to engage users and achieve desired instructional goals. In this article, the authors present an input-process- output model of instructional games and learning that elaborates (a) the key features of games that are of interest from an instructional perspective; (b) the game cycle of user judgments, behavior, and feedback that is a hallmark of engagement in game play; and (c) the types of learning outcomes that can be achieved. The authors discuss the implications of this approach for the design and implementation of effective instruc- tional games.


title: On exploiting cognitive radio to mitigate interference in macro/femto heterogeneous networks

abstract: To successfully deploy femtocells underlaying the macrocell as a heterogeneous network, which has been proven to greatly improve indoor coverage and system capacity, the cross-tier interference among the macrocell and femtocells as well as the intratier interference among femtocells must be mitigated. However, some unique features present a challenge in interference mitigation in a two-tier heterogeneous network such as random deployment for femtocells, nonexistence of macro-femto backhaul coordination, and mandates allowing no modifications of existing macrocells. Carefully examining the existing distributed information acquisition mechanisms, cognitive radio is the most promising solution for two-tier heterogeneous networks. We therefore study possible interference mitigation approaches, including orthogonal radio resource assignment in the time-frequency and antenna spatial domains, as well as interference cancellation via novel decoding techniques. According to the information acquired by cognitive radio technology, recent innovations such as game theory and the Gibbs sampler have been explored to mitigate both cross-tier and intratier interferences. Performance evaluations show that considerable performance improvement can be generally achieved, and thus demonstrate the potential of applying cognitive radio in mitigating interference.


Signposting for design process improvement - A dynamic approach to design process planning


title: Regulation of the fungal secretome

abstract: The ability of countless representatives of the Kingdom Fungi to adapt to and proliferate in diverse environments is facilitated by regulation of their secretomes to respond to changes in environmental conditions and to mediate interactions with other organisms. Secretome changes often fulfill common functions of nutrient acquisition, facilitation of host/symbiont interactions, cell wall modification, and optimization of the enzyme suite to adapt to new environmental resources. In this review, we expand on our recent work on signaling and the secretome in the pathogenic fungus Cryptococcus neoformans to consider a range of selected examples of regulation of fungal secretomes. These examples include the impact of carbon source and aspects of the response to plant and animal hosts. Additionally, the influence of key protein kinases (e.g., Pka1, Snf1) and transcription factors (e.g., Rim101/PacC) is highlighted to illustrate some underlying regulatory factors influencing the secretome. Although there is a wealth of information about fungal secretomes from both experimentation and genome sequence mining, there are also major gaps in our knowledge about the complete composition of fungal secretomes and mechanisms of dynamic change. For example, a more comprehensive understanding of the composition and regulation of the secretome will require consideration of the emerging roles of unconventional secretion and extracellular vesicles in delivering proteins outside the cell. Overall, changes in the secretome are well documented in diverse fungi and the underlying mechanisms are currently under investigation; however, there remain unknown steps in the regulation of secretory pathways and gaps in understanding the regulation of unconventional secretion, which warrant further research.


title: Cryolipolysis: a historical perspective and current clinical practice.

abstract: Dermatologists have long used cold-based therapeutic approaches for a variety of applications. Based on the differences in chemical composition, it is possible to selectively target certain tissues rich with lipid, while sparing the surrounding tissue predominantly containing water. With historical observations of cold-induced panniculitis suggesting the feasibility of this strategy, cryolipolysis has emerged as a new methodology using controlled cooling to selectively target fat. Both preclinical and clinical studies have established the safety and efficacy of cryolipolysis for noninvasive body contouring. This review will focus on the evolution of cryolipolysis from initial case reports of cold-induced panniculitis, to preclinical and clinical studies, and the current clinical practice.


title: Novel IPCA-Based Classifiers and Their Application to Spam Filtering

abstract: This paper proposes a novel two-class classifier, called IPCAC, based on the Isotropic Principal Component Analysis technique; it allows to deal with training data drawn from Mixture of Gaussian distributions, by projecting the data on the Fisher subspace that separates the two classes. The obtained results demonstrate that IPCAC is a promising technique; furthermore, to cope with training datasets being dynamically supplied, and to work with non-linearly separable classes, two improvements of this classifier are defined: a model merging algorithm, and a kernel version of IPCAC. The effectiveness of the proposed methods is shown by their application to the spam classification problem, and by the comparison of the achieved results with those obtained by Support Vector Machines SVM, and K-Nearest Neighbors KNN.


title: Security risk assessment framework for cloud computing environments

abstract: Cloud computing has become today's most common technology buzzword. Despite the promises of cloud computing to decrease computing implementation costs and deliver computing as a service, which allows clients to pay only for what they need and use, cloud computing also raises many security concerns. Most popular risk assessment standards, such as ISO27005, NIST SP800-30, and AS/NZS 4360, assume that an organization's assets are fully managed by the organization itself and that all security management processes are imposed by the organization. These assumptions, however, do not apply to cloud computing environments. Hence, this paper proposes a security risk assessment framework that can enable cloud service providers to assess security risks in the cloud computing environment and allow cloud clients to contribute in risk assessment. The proposed framework provides a more realistic and accurate risk assessment outcome by considering the cloud clients' evaluation of security risk factors and avoiding the complexity that can result from the involvement of clients in whole risk assessment process. Copyright © 2014 John Wiley & Sons, Ltd.


title: A cell-phone-based brain–computer interface for communication in daily life

abstract: Moving a brain–computer interface (BCI) system from a laboratory demonstration to real-life applications still poses severe challenges to the BCI community. This study aims to integrate a mobile and wireless electroencephalogram (EEG) system and a signal-processing platform based on a cell phone into a truly wearable and wireless online BCI. Its practicality and implications in a routine BCI are demonstrated through the realization and testing of a steady-state visual evoked potential (SSVEP)-based BCI. This study implemented and tested online signal processing methods in both time and frequency domains for detecting SSVEPs. The results of this study showed that the performance of the proposed cell-phone-based platform was comparable, in terms of the information transfer rate, with other BCI systems using bulky commercial EEG systems and personal computers. To the best of our knowledge, this study is the first to demonstrate a truly portable, cost-effective and miniature cell-phone-based platform for online BCIs.


Routing Issues in Internet of Things : A Survey


title: Power dissipation in nanoscale conductors: classical, semi-classical and quantum dynamics

abstract: Modelling Joule heating is a difficult problem because of the need to introduce correct correlations between the motions of the ions and the electrons. In this paper we analyse three different models of current induced heating (a purely classical model, a fully quantum model and a hybrid model in which the electrons are treated quantum mechanically and the atoms are treated classically). We find that all three models allow for both heating and cooling processes in the presence of a current, and furthermore the purely classical and purely quantum models show remarkable agreement in the limit of high biases. However, the hybrid model in the Ehrenfest approximation tends to suppress heating. Analysis of the equations of motion reveals that this is a consequence of two things: the electrons are being treated as a continuous fluid and the atoms cannot undergo quantum fluctuations. A means for correcting this is suggested.


title: The IX Operating System: Combining Low Latency, High Throughput, and Efficiency in a Protected Dataplane

abstract: The conventional wisdom is that aggressive networking requirements, such as high packet rates for small messages and μs-scale tail latency, are best addressed outside the kernel, in a user-level networking stack. We present ix , a dataplane operating system that provides high I/O performance and high resource efficiency while maintaining the protection and isolation benefits of existing kernels. ix uses hardware virtualization to separate management and scheduling functions of the kernel (control plane) from network processing (dataplane). The dataplane architecture builds upon a native, zero-copy API and optimizes for both bandwidth and latency by dedicating hardware threads and networking queues to dataplane instances, processing bounded batches of packets to completion, and eliminating coherence traffic and multicore synchronization. The control plane dynamically adjusts core allocations and voltage/frequency settings to meet service-level objectives. We demonstrate that ix outperforms Linux and a user-space network stack significantly in both throughput and end-to-end latency. Moreover, ix improves the throughput of a widely deployed, key-value store by up to 6.4× and reduces tail latency by more than 2× . With three varying load patterns, the control plane saves 46%--54% of processor energy, and it allows background jobs to run at 35%--47% of their standalone throughput.


title: Learning Extraction Patterns For Subjective Expressions

abstract: This paper presents a bootstrapping process that learns linguistically rich extraction patterns for subjective (opinionated) expressions. High-precision classifiers label unannotated data to automatically create a large training set, which is then given to an extraction pattern learning algorithm. The learned patterns are then used to identify more subjective sentences. The bootstrapping process learns many subjective patterns and increases recall while maintaining high precision.


title: Defending Against XML-Based Attacks Using State-Based XML Firewall

abstract: With the proliferation of service-oriented systems and cloud computing, web services security has gained much attention in recent years. Web service attacks, called XML-based attacks, typically occur at the SOAP message level, thus they are not readily handled by existing security mechanisms such as a conventional firewall. In order to provide effective security mechanisms for service-oriented systems, XML firewalls have recently been introduced as one of the major means for web services security. In this paper, we present a framework for state-based XML firewall, called S-Wall, which supports dynamic role-based access control (D-RBAC) and detection of XML-based attacks in real-time. We provide a detailed design of the S-Wall security model by defining state-based information, user information, access control policies, and detection and verification (D&V) rules. The D&V rules are modularized into separate units, which support real-time detection and verification of various types of attacks using state-based information. To illustrate the effectiveness of our approach, we develop a prototype S-Wall, and utilize a case study to demonstrate how S-Wall can be used to efficiently detect and defend against XML-based attacks.


title: Fundamental motives: How evolutionary needs influence consumer behavior

abstract: Can we better understand modern consumer behavior by examining its links to our ancestral past? We consider the underlying motives for consumption and choice from an evolutionary perspective. We review evidence that deep-seated evolutionary motives continue to influence much modern behavior, albeit not always in obvious or conscious ways. These fundamental motives include: (1) evading physical harm, (2) avoiding disease, (3) making friends, (4) attaining status, (5) acquiring a mate, (6) keeping a mate, and (7) caring for family. We discuss how, why, and when these motives influence behavior, highlighting that many consumer choices ultimately function to help fulfill one or more of these evolutionary needs. An important implication of this framework is that a person's preferences, behaviors, and decision processes change in predictable ways depending on which fundamental motive is currently active. We discuss how consideration of evolutionary motives provides fertile ground for future consumer research, while also helping build bridges between consumer behavior, evolutionary biology, and other social sciences.


title: Linear and quadratic time-frequency signal representations

abstract: A tutorial review of both linear and quadratic representations is given. The linear representations discussed are the short-time Fourier transform and the wavelet transform. The discussion of quadratic representations concentrates on the Wigner distribution, the ambiguity function, smoothed versions of the Wigner distribution, and various classes of quadratic time-frequency representations. Examples of the application of these representations to typical problems encountered in time-varying signal processing are provided. >


title: Neural Multigrid

abstract: We propose a multigrid extension of convolutional neural networks (CNNs). Rather than manipulating representations living on a single spatial grid, our network layers operate across scale space, on a pyramid of tensors. They consume multigrid inputs and produce multigrid outputs; convolutional filters themselves have both within-scale and cross-scale extent. This aspect is distinct from simple multiscale designs, which only process the input at different scales. Viewed in terms of information flow, a multigrid network passes messages across a spatial pyramid. As a consequence, receptive field size grows exponentially with depth, facilitating rapid integration of context. Most critically, multigrid structure enables networks to learn internal attention and dynamic routing mechanisms, and use them to accomplish tasks on which modern CNNs fail. Experiments demonstrate wide-ranging performance advantages of multigrid. On CIFAR image classification, flipping from single to multigrid within standard CNN architectures improves accuracy at modest compute and parameter increase. Multigrid is independent of other architectural choices; we show synergistic results in combination with residual connections. On tasks demanding per-pixel output, gains can be substantial. We show dramatic improvement on a synthetic semantic segmentation dataset. Strikingly, we show that relatively shallow multigrid networks can learn to directly perform spatial transformation tasks, where, in contrast, current CNNs fail. Together, our results suggest that continuous evolution of features on a multigrid pyramid could replace virtually all existing CNN designs.


title: ACI (automated Continuous Integration) using Jenkins: Key for successful embedded Software development

abstract: Continuous Integration (CI) is the most common practice among software developers where they integrate their work into a baseline frequently. The industry is facing huge challenges while developing Software (S/W)s at multiple sites and tested on multiple platforms. The best way to make CI faster and more efficient is to automate the build and testing process. Jenkins is a CI tool that helps in automating the complete process, reducing the work of a developer and check the development at each and every step of S/W evolution. In this paper, we discuss the implementation of Jenkins for software patch integration and release to client. We consider a real-life scenario, how the software development is carried out in corporate ventures and how Jenkins can save developers / integrators crucial work hours by automating the complete process. In this paper, Jenkins is implemented in a master / slave architecture where master node is the Jenkins server and slaves are the Jenkins clients. We discuss the usage of various plug-ins available that allow Jenkins to be used with any environment of software development.


title: EDGAR-analyzer: automating the analysis of corporate data contained in the SEC's EDGAR database

abstract: Publicly owned companies, their officers and major investors are required to file regular disclosures with the Securities and Exchange Commission (SEC). To improve accessibility to these public documents, the SEC began developed the EDGAR (Electronic Data Gathering, Analysis and Retrieval) electronic disclosure system. This system provides ready, free access to all electronic filings made since 1994. The paper describes a tool that automates the analysis of SEC filings, emphasizing the unstructured text sections of these documents. To illustrate the capabilities of the EDGAR-Analyzer program, results of a large-scale case study of corporate Y2K disclosures in 18,595 10K filings made from 1997 to 1999 is presented.


title: Two-Stage License Plate Detection Using Gentle Adaboost and SIFT-SVM

abstract: This paper presents a two-stage method to detect license plates in real world images. To do license plate detection (LPD), an initial set of possible license plate character regions are first obtained by the first stage classifier and then passed to the second stage classifier to reject non-character regions. 36 Adaboost classifiers (each trained with one alpha-numerical character, i.e. A..Z, 0..9) serve as the first stage classifier. In the second stage, a support vector machine (SVM) trained on scale-invariant feature transform (SIFT) descriptors obtained from training sub-windows were employed. A recall rate of 0.920792 and precision rate of 0.90185 was obtained.


title: Caffeine consumption.

abstract: Scientific literature cites a wide range of values for caffeine content in food products. The authors suggest the following standard values for the United States: coffee (5 oz) 85 mg for ground roasted coffee, 60 mg for instant and 3 mg for decaffeinated; tea (5 oz): 30 mg for leaf/bag and 20 mg for instant; colas: 18 mg/6 oz serving; cocoa/hot chocolate: 4 mg/5 oz; chocolate milk: 4 mg/6 oz; chocolate candy: 1.5-6.0 mg/oz. Some products from the United Kingdom and Denmark have higher caffeine content. Caffeine consumption survey data are limited. Based on product usage and available consumption data, the authors suggest a mean daily caffeine intake for US consumers of 4 mg/kg. Among children younger than 18 years of age who are consumers of caffeine-containing foods, the mean daily caffeine intake is about 1 mg/kg. Both adults and children in Denmark and UK have higher levels of caffeine intake.


New Alignment Methods for Discriminative Book Summarization Work in Progress


title: Zero-Shot Learning Through Cross-Modal Transfer

abstract: This work introduces a model that can recognize objects in images even if no training data is available for the object class. The only necessary knowledge about unseen visual categories comes from unsupervised text corpora. Unlike previous zero-shot learning models, which can only differentiate between unseen classes, our model can operate on a mixture of seen and unseen classes, simultaneously obtaining state of the art performance on classes with thousands of training images and reasonable performance on unseen classes. This is achieved by seeing the distributions of words in texts as a semantic space for understanding what objects look like. Our deep learning model does not require any manually defined semantic or visual features for either words or images. Images are mapped to be close to semantic word vectors corresponding to their classes, and the resulting image embeddings can be used to distinguish whether an image is of a seen or unseen class. We then use novelty detection methods to differentiate unseen classes from seen classes. We demonstrate two novelty detection strategies; the first gives high accuracy on unseen classes, while the second is conservative in its prediction of novelty and keeps the seen classes' accuracy high.


title: In vitro flowering of Dendrobium

abstract: Dendrobium plants are the most frequently used orchids to study the process of in vitro flowering. Among the various environmental cues and plant growth regulators employed thus far, cytokinins have shown the most prominent effects on the transition from vegetative to reproductive stage. A clear correlation between flowering establishment and enhancement of endogenous cytokinins has been observed. However, the experimental utilization of a large amount of different Dendrobium species and hybrids, combined with a large diversity of variable media types and media compositions make interpretation of flowering control in the in vitro environment difficult. The combination of a specific model Dendrobium in vitro regeneration system or protocol with a simple, but well defined culture medium, could contributed, to some degree, to reaching a clearer consensus about the physiological and molecular mechanisms controlling the Dendrobium flowering phase change.


title: Parallel surface reconstruction on GPU

abstract: Marching Cubes is the most frequently used method to reconstruct isosurface from a point cloud. However, the point clouds are getting denser and denser, thus the efficiency of Marching cubes method has become an obstacle. This paper presents a novel GPU-based parallel surface reconstruction algorithm. The algorithm firstly creates a GPU-based uniform grid structure to manage point cloud. Then directed distances from vertices of cubes to the point cloud are computed in a newly put forwarded parallel way. Finally, after the generation of triangles, a space indexing scheme is adopted to reconstruct the connectivity of the resulted surface. The results show that our algorithm can run more than 10 times faster compared to the CPU-based implementations.


title: The Loopix Anonymity System

abstract: We present Loopix, a low-latency anonymous communication system that provides bi-directional 'third-party' sender and receiver anonymity and unobservability. Loopix leverages cover traffic and Poisson mixing--brief independent message delays--to provide anonymity and to achieve traffic analysis resistance against, including but not limited to, a global network adversary. Mixes and clients self-monitor and protect against active attacks via self-injected loops of traffic. The traffic loops also serve as cover traffic to provide stronger anonymity and a measure of sender and receiver unobservability. Loopix is instantiated as a network of Poisson mix nodes in a stratified topology with a low number of links, which serve to further concentrate cover traffic. Service providers mediate access in and out of the network to facilitate accounting and off-line message reception. ::: ::: We provide a theoretical analysis of the Poisson mixing strategy as well as an empirical evaluation of the anonymity provided by the protocol and a functional implementation that we analyze in terms of scalability by running it on AWS EC2. We show that mix nodes in Loopix can handle upwards of 300 messages per second, at a small delay overhead of less than 1.5ms on top of the delays introduced into messages to provide security. Overall message latency is on the order of seconds - which is relatively low for a mix-system. Furthermore, many mix nodes can be securely added to the stratified topology to scale throughput without sacrificing anonymity.


title: Speed control of buck converter fed DC motor drives

abstract: This research paper presents a new speed control method for DC motor through differential flatness control. The desired angular velocity trajectory is well tracked and the performance of the controller is healthy in all dynamic operating circumstances. The actual value follows the trajectory with time delay and reduced magnitude in simulation. So controller gains are introduced to overcome these issues. Along with that, hardware is to be implemented for the simulation model of overall system. It is significant that these kinds of sudden deviations do not occur in repetition at the similar time, or through such huge deviations about their nominal values.


title: Validation of Calibrated Energy Models: Common Errors

abstract: Nowadays, there is growing interest in all the smart technologies that provide us with information and knowledge about the human environment. In the energy field, thanks to the amount of data received from smart meters and devices and the progress made in both energy software and computers, the quality of energy models is gradually improving and, hence, also the suitability of Energy Conservation Measures (ECMs). For this reason, the measurement of the accuracy of building energy models is an important task, because once the model is validated through a calibration procedure, it can be used, for example, to apply and study different strategies to reduce its energy consumption in maintaining human comfort. There are several agencies that have developed guidelines and methodologies to establish a measure of the accuracy of these models, and the most widely recognized are: ASHRAE Guideline 14-2014, the International Performance Measurement and Verification Protocol (IPMVP) and the Federal Energy Management Program (FEMP). This article intends to shed light on these validation measurements (uncertainty indices) by focusing on the typical mistakes made, as these errors could produce a false belief that the models used are calibrated.


title: Semantic Web Service Search: A Brief Survey

abstract: Scalable means for the search of relevant web services are essential for the development of intelligent service-based applications in the future Internet. Key idea of semantic web services is to enable such applications to perform a high-precision search and automated composition of services based on formal ontology-based representations of service semantics. In this paper, we briefly survey the state of the art of semantic web service search.


title: Transcriptomic and metabolomic analyses reveal mechanisms of adaptation to salinity in which carbon and nitrogen metabolism is altered in sugar beet roots

abstract: BACKGROUND ::: Beta vulgaris L. is one of the main sugar-producing crop species and is highly adaptable to saline soil. This study explored the alterations to the carbon and nitrogen metabolism mechanisms enabling the roots of sugar beet seedlings to adapt to salinity. ::: ::: ::: RESULTS ::: The ionome, metabolome, and transcriptome of the roots of sugar beet seedlings were evaluated after 1 day (short term) and 7 days (long term) of 300 mM Na+ treatment. Salt stress caused reactive oxygen species (ROS) damage and ion toxicity in the roots. Interestingly, under salt stress, the increase in the Na+/K+ ratio compared to the control ratio on day 7 was lower than that on day 1 in the roots. The transcriptomic results showed that a large number of differentially expressed genes (DEGs) were enriched in various metabolic pathways. A total of 1279 and 903 DEGs were identified on days 1 and 7, respectively, and were mapped mainly to 10 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Most of the genes were involved in carbon metabolism and amino acid (AA) biosynthesis. Furthermore, metabolomic analysis revealed that sucrose metabolism and the activity of the tricarboxylic acid (TCA) cycle increased in response to salt stress. After 1 day of stress, the content of sucrose decreased, whereas the content of organic acids (OAs) such as L-malic acid and 2-oxoglutaric acid increased. After 7 days of salt stress, nitrogen-containing metabolites such as AAs, betaine, melatonin, and (S)-2-aminobutyric acid increased significantly. In addition, multiomic analysis revealed that the expression of the gene encoding xanthine dehydrogenase (XDH) was upregulated and that the expression of the gene encoding allantoinase (ALN) was significantly downregulated, resulting in a large accumulation of allantoin. Correlation analysis revealed that most genes were significantly related to only allantoin and xanthosine. ::: ::: ::: CONCLUSIONS ::: Our study demonstrated that carbon and nitrogen metabolism was altered in the roots of sugar beet plants under salt stress. Nitrogen metabolism plays a major role in the late stages of salt stress. Allantoin, which is involved in the purine metabolic pathway, may be a key regulator of sugar beet salt tolerance.


title: Parkinsons disease patients perspective on context aware wearable technology for auditive assistance

abstract: In this paper we present a wearable assistive technology for the freezing of gait (FOG) symptom in patients with Parkinsons disease (PD), with emphasis on subjective user appreciation. Patients with advanced PD often suffer from FOG, which is a sudden and transient inability to move. It often causes falls, interferes with daily activities and significantly impairs quality of life. Because gait deficits in PD patients are often resistant to pharmacologic treatment, effective non+pharmacologic treatments are of special interest.


title: A Taxonomy for Designing Walking-based Locomotion Techniques for Virtual Reality

abstract: Designers have yet to find a fully general and effective solution to solve the problem of walking in large or unlimited virtual environments. A detailed taxonomy of walking-based locomotion techniques would be beneficial to better understand, analyze, and design walking techniques for virtual reality (VR). We present a taxonomy that can help designers and researchers investigate the fundamental components of locomotion techniques. Researchers can create novel locomotion techniques by making choices from the components of this taxonomy, analyze and improve existing techniques, or perform experiments to evaluate locomotion techniques in detail using the organization we present.


title: Beyond Cyberbullying: Self-Disclosure, Harm and Social Support on ASKfm

abstract: ASKfm is a social media platform popular among teens and young adults where users can interact anonymously or semi-anonymously. In this paper, we identify the modes of disclosure and interaction that occur on the site, and evaluate why users are motivated to post and interact on the site, despite its reputation for facilitating cyberbullying. Through topic modeling - supplemented with manual annotation - of a large dataset of ASKfm posts, we identify and classify the rich variety of discourse posted on ASKfm, including both positive and negative forms, providing insights into the why individuals continue to engage with the site. These findings are complemented by a survey of young adults (aged 18-20) ASKfm users, which provides additional insights into users' motivations and interaction patterns. We discuss how the affordances specific to platforms like ASKfm, including anonymity and visibility, might enable users to respond to cyberbullying in novel ways, engage in positive forms of self-disclosure, and gain social support on sensitive topics. We conclude with design recommendations that would highlight the positive interactions on the website and help diminish the repurcussions of the negative interactions.


title: BrainBrush , a Multimodal Application for Creative Expressivity

abstract: We combined the new developments of multimodal Brain-Computer Interfaces (BCI) and wireless EEG headsets with art by creating BrainBrush. Users can paint on a virtual canvas by moving their heads, blinking their eyes and performing selections using a P300 BCI. A qualitative evaluation (n=13) was done. A questionnaire was administered and structured interviews were conducted to assess the usability and user experience of the system. Most participants were able to achieve good control over the modalities and able to express themselves creatively. The user experience of the modalities varied. The use of head movement was considered most positive with the use of eye blinks coming in second. Users were less positive about the use of the BCI because of the low reliability and higher relative cost of an error. Even though the reliability of the BCI was low, the BCI was considered to have an added value: the use of BCI was considered to be fun and interesting.


title: QLib: Quantum module library

abstract: Quantum algorithms are known for their ability to solve some problems much faster than classical algorithms. They are executed on quantum circuits, which consist of a cascade of quantum gates. However, synthesis of quantum circuits is not straightforward because of the complexity of quantum algorithms. Generally, quantum algorithms contain two parts: classical and quantum. Thus, synthesizing circuits for the two parts separately reduces overall synthesis complexity. In addition, many quantum algorithms use similar subroutines that can be implemented with similar circuit modules. Because of their frequent use, it is important to use automated scripts to generate such modules efficiently. These modules can then be subjected to further synthesis optimizations. This article proposes QLib, a quantum module library, which contains scripts to generate quantum modules of different sizes and specifications for well-known quantum algorithms. Thus, QLib can also serve as a suite of benchmarks for quantum logic and physical synthesis.


title: Implicitly parallel programming models for thousand-core microprocessors

abstract: This paper argues for an implicitly parallel programming model for many-core microprocessors, and provides initial technical approaches towards this goal. In an implicitly parallel programming model, programmers maximize algorithm- level parallelism, express their parallel algorithms by asserting high-level properties on top of a traditional sequential programming language, and rely on parallelizing compilers and hardware support to perform parallel execution under the hood. In such a model, compilers and related tools require much more advanced program analysis capabilities and programmer assertions than what are currently available so that a comprehensive understanding of the input program's concurrency can be derived. Such an understanding is then used to drive automatic or interactive parallel code generation tools for a diverse set of parallel hardware organizations. The chip-level architecture and hardware should maintain parallel execution state in such a way that a strictly sequential execution state can always be derived for the purpose of verifying and debugging the program. We argue that implicitly parallel programming models are critical for addressing the software development crises and software scalability challenges for many-core microprocessors.


title: The Event Tunnel: Interactive Visualization of Complex Event Streams for Business Process Pattern Analysis

abstract: Event-based systems are gaining increasing popularity for building loosely coupled and distributed systems. Since business processes are becoming more interconnected and event-driven, event-based systems fit well for supporting and monitoring business processes. In this paper, we present an event-based business intelligence tool, the Event Tunnel framework. It provides an interactive visualization of event streams to support business analysts in exploring business incidents. The visualization is based on the metaphor of considering the event stream as a cylindrical tunnel, which is presented to the user from multiple perspectives. The information of single events laid out in the Event Tunnel is encoded in event glyphs that allow for a selective mapping of event attributes to colors, size and position. Different policies for the placement of the events in the tunnel as well as a clustering mechanism generate various views on historical event data. The Event Tunnel is able to display the relationships between events. This facilitates users to discover root causes and causal dependencies of event patterns. Our framework couples the event-tunnel visualization with query tools that allow users to search for relevant events within a data repository. Using query, filler and highlighting operations the analyst can navigate through the Event Tunnel until the required information or event patterns become visible. We demonstrate our approach with use cases from the fraud management and logistics domain.


title: Learning Image and User Features for Recommendation in Social Networks

abstract: Good representations of data do help in many machine learning tasks such as recommendation. It is often a great challenge for traditional recommender systems to learn representative features of both users and images in large social networks, in particular, social curation networks, which are characterized as the extremely sparse links between users and images, and the extremely diverse visual contents of images. To address the challenges, we propose a novel deep model which learns the unified feature representations for both users and images. This is done by transforming the heterogeneous user-image networks into homogeneous low-dimensional representations, which facilitate a recommender to trivially recommend images to users by feature similarity. We also develop a fast online algorithm that can be easily scaled up to large networks in an asynchronously parallel way. We conduct extensive experiments on a representative subset of Pinterest, containing 1,456,540 images and 1,000,000 users. Results of image recommendation experiments demonstrate that our feature learning approach significantly outperforms other state-of-the-art recommendation methods.


Exploiting Argument Information to Improve Event Detection via Supervised Attention Mechanisms


title: Narcissistic Subtypes and Contingent Self‐Esteem: Do All Narcissists Base Their Self‐Esteem on the Same Domains?

abstract: ABSTRACT It has been suggested that there are two forms of narcissism: a grandiose subtype and a vulnerable subtype. Although these forms of narcissism share certain similarities, it is believed that these subtypes may differ in the domains upon which their self-esteem is based. To explore this possibility, the present study examined the associations between these narcissistic subtypes and domain-specific contingencies of self-worth. The results show that vulnerable narcissism was positively associated with contingencies of self-worth across a variety of domains. In contrast, the associations between grandiose narcissism and domain-specific contingencies of self-worth were more complex and included both positive and negative relationships. These results provide additional support for the distinction between grandiose and vulnerable narcissism by showing that the domains of contingent self-esteem associated with grandiose narcissism may be more limited in scope than those associated with vulnerable narcissism.


title: Emotion recognition from speech: a review

abstract: Emotion recognition from speech has emerged as an important research area in the recent past. In this regard, review of existing work on emotional speech processing is useful for carrying out further research. In this paper, the recent literature on speech emotion recognition has been presented considering the issues related to emotional speech corpora, different types of speech features and models used for recognition of emotions from speech. Thirty two representative speech databases are reviewed in this work from point of view of their language, number of speakers, number of emotions, and purpose of collection. The issues related to emotional speech databases used in emotional speech recognition are also briefly discussed. Literature on different features used in the task of emotion recognition from speech is presented. The importance of choosing different classification models has been discussed along with the review. The important issues to be considered for further emotion recognition research in general and in specific to the Indian context have been highlighted where ever necessary.


title: Synthetic-aperture radar autofocus by maximizing sharpness

abstract: To focus a synthetic-aperture radar image that is suffering from phase errors, a phase-error estimate is found that, when it is applied, maximizes the sharpness of the image. Closed-form expressions are derived for the gradients of a sharpness metric with respect to phase-error parameters, including both a point-by-point (nonparametric) phase function and coefficients of a polynomial expansion. Use of these expressions allows for a highly efficient gradient-search algorithm for high-order phase errors. The effectiveness of the algorithm is demonstrated with an example.


title: Options for Middle Vault and Dorsum Restoration after Hump Removal in Primary Rhinoplasty.

abstract: Prevention of unfavorable sequelae following humpectomy in reduction rhinoplasty by restoration of the middle nasal vault complex today has become imperative in the majority of patients with perhaps the exception of small humps. In general, the techniques used for preservation and reconstruction of these important anatomical structures can be divided into two main categories: spreader graft and spreader flap techniques. Oversimplified spreader graft techniques require donor cartilage, whereas spreader flap techniques use the excess height of the medial portion of the upper lateral cartilages in patients with a cartilaginous hump. In principle, both donor cartilage and preserved upper lateral cartilages usually are positioned along both sides of the dorsal septum to provide natural and harmonious contours as well as to avoid functional impairment (valve collapse). However, the considerable number of publications on this topic attests to existing downsides of both surgical principles. To overcome these shortcomings, we illustrate additional modifications in the application of spreader grafts as well as spreader flaps. However, the main goal of this article is to provide an algorithm helping to decide which technique is best suited to meet the requirements of each individual patient.


title: Opportunities for the Cardiovascular Community in the Precision Medicine Initiative.

abstract: The Precision Medicine Initiative recently announced by President Barack Obama seeks to move the field of precision medicine more rapidly into clinical care. Precision medicine revolves around the concept of integrating individual-level data including genomics, biomarkers, lifestyle and other environmental factors, wearable device physiological data, and information from electronic health records to ultimately provide better clinical care to individual patients. The Precision Medicine Initiative as currently structured will primarily fund efforts in cancer genomics with longer-term goals of advancing precision medicine to all areas of health, and will be supported through creation of a 1 million person cohort study across the United States. This focused effort on precision medicine provides scientists, clinicians, and patients within the cardiovascular community an opportunity to work together boldly to advance clinical care; the community needs to be aware and engaged in the process as it progresses. This article provides a framework for potential involvement of the cardiovascular community in the Precision Medicine Initiative, while highlighting significant challenges for its successful implementation.


title: A SYSTEMATIC, TOOL-SUPPORTED METHOD FOR CONDUCTING LITERATURE REVIEWS IN INFORMATION SYSTEMS

abstract: While the importance of literature studies in the IS discipline is well recognized, little attention has been paid to the underlying structure and method of conducting effective literature reviews. Despite the fact that literature is often used to refine the research context and direct the pathways for successful research outcomes, there is very little evidence of the use of resource management tools to support the literature review process. In this paper we want to contribute to advancing the way in which literature studies in Information Systems are conducted, by proposing a systematic, pre-defined and tool-supported method to extract, analyse and report literature. This paper presents how to best identify relevant IS papers to review within a feasible and justifiable scope, how to extract relevant content from identified papers, how to synthesise and analyse the findings of a literature review and what are ways to effectively write and present the results of a literature review. The paper is specifically targeted towards novice IS researchers, who would seek to conduct a systematic detailed literature review in a focused domain. Specific contributions of our method are extensive tool support, the identification of appropriate papers including primary and secondary paper sets and a pre-codification scheme. We use a literature study on shared services as an illustrative example to present the proposed approach.


title: CUTE: a concolic unit testing engine for C

abstract: In unit testing, a program is decomposed into units which are collections of functions. A part of unit can be tested by generating inputs for a single entry function. The entry function may contain pointer arguments, in which case the inputs to the unit are memory graphs. The paper addresses the problem of automating unit testing with memory graphs as inputs. The approach used builds on previous work combining symbolic and concrete execution, and more specifically, using such a combination to generate test inputs to explore all feasible execution paths. The current work develops a method to represent and track constraints that capture the behavior of a symbolic execution of a unit with memory graphs as inputs. Moreover, an efficient constraint solver is proposed to facilitate incremental generation of such test inputs. Finally, CUTE, a tool implementing the method is described together with the results of applying CUTE to real-world examples of C code.


title: Experience from the operation of the Pepper humanoid robots

abstract: This paper summarizes authors' experience with the operation of both versions of autonomous humanoid robot Pepper. The robot's construction, as well as its capabilities and limitations are discussed and compared to the NAO robot. Practical background of working with Pepper robots and several years of experience with NAO, result in specific know-how, which the authors would like to share in this article. It reviews not only the robots' technical aspects, but also practical use-cases that the robot has proven to be perfect for (or not).


title: Transient Positioning of a Silicone T Tube in Frontal Sinus Surgery

abstract: We applied transient positioning of a silicone T tube in 18 patients with frontal sinus cysts. Inflammation in the nasal cavity usually subsided within 6 months of surgery, whereas the frontal sinus showed pathologic changes in more than half of the patients even 6 months after surgery. After removal of the tube, the nasofrontal passage remained open in 16 patients who obtained good aeration with an intact mucosal lining in the frontal sinus, but it eventually closed in the remaining 2 patients who failed to obtain good aeration. This finding suggests that persistent inflammation in the frontal sinus encourages the closure of the nasofrontal passage and that transient positioning of a silicone T tube is successful if it is removed after subsidence of inflammation in the sinonasal tract.


title: Development, risk, and resilience of transgender youth

abstract: Transgender youth face unique and complex issues as they confront cultural expectations of gender expression and how these fit with what is natural for them. Striving for balance, learning to cope, questioning, and eventually becoming comfortable with one's gender identity and sexual orientation are of paramount importance for healthy growth and development. Ineffective management of intense challenges over time without adequate social support places youth at risk for a number of unhealthy behaviors, including risk behaviors associated with acquiring HIV. This article explores early foundations of gender identity development, challenges in the development of transgender youth, and the limited data that exist on transgender youth and HIV risks. The concept of resilience is introduced as a counterbalancing area for assessment and intervention in practice and future research with transgender youth.


title: LATTICE BOLTZMANN METHOD FOR FLUID FLOWS

abstract: We present an overview of the lattice Boltzmann method (LBM), a parallel and efficient algorithm for simulating single-phase and multiphase fluid flows and for incorporating additional physical complexities. The LBM is especially useful for modeling complicated boundary conditions and multiphase interfaces. Recent extensions of this method are described, including simulations of fluid turbulence, suspension flows, and reaction diffusion systems.


title: Discovery Radiomics via StochasticNet Sequencers for Cancer Detection

abstract: Radiomics has proven to be a powerful prognostic tool for cancer detection, and has previously been applied in lung, breast, prostate, and head-and-neck cancer studies with great success. However, these radiomics-driven methods rely on pre-defined, hand-crafted radiomic feature sets that can limit their ability to characterize unique cancer traits. In this study, we introduce a novel discovery radiomics framework where we directly discover custom radiomic features from the wealth of available medical imaging data. In particular, we leverage novel StochasticNet radiomic sequencers for extracting custom radiomic features tailored for characterizing unique cancer tissue phenotype. Using StochasticNet radiomic sequencers discovered using a wealth of lung CT data, we perform binary classification on 42,340 lung lesions obtained from the CT scans of 93 patients in the LIDC-IDRI dataset. Preliminary results show significant improvement over previous state-of-the-art methods, indicating the potential of the proposed discovery radiomics framework for improving cancer screening and diagnosis.