title: Joint Text Embedding for Personalized Content-based Recommendation

abstract: Learning a good representation of text is key to many recommendation applications. Examples include news recommendation where texts to be recommended are constantly published everyday. However, most existing recommendation techniques, such as matrix factorization based methods, mainly rely on interaction histories to learn representations of items. While latent factors of items can be learned effectively from user interaction data, in many cases, such data is not available, especially for newly emerged items. ::: In this work, we aim to address the problem of personalized recommendation for completely new items with text information available. We cast the problem as a personalized text ranking problem and propose a general framework that combines text embedding with personalized recommendation. Users and textual content are embedded into latent feature space. The text embedding function can be learned end-to-end by predicting user interactions with items. To alleviate sparsity in interaction data, and leverage large amount of text data with little or no user interactions, we further propose a joint text embedding model that incorporates unsupervised text embedding with a combination module. Experimental results show that our model can significantly improve the effectiveness of recommendation systems on real-world datasets.


title: Diversified Top-k Partial MaxSAT Solving

abstract: We introduce a diversified top-k partial MaxSAT problem, a combination of partial MaxSAT problem and enumeration problem. Given a partial MaxSAT formula F and a positive integer k, the diversified top-k partial MaxSAT is to find k maximal solutions for F such that the k maximal solutions satisfy the maximum number of soft clauses of F. This problem can be widely used in many applications including community detection, sensor place, motif discovery, and combinatorial testing. We prove the problem is NP-hard and propose an approach for solving the problem. The concrete idea of the approach is to design an encoding EE which reduces diversified top-k partial MaxSAT problem into partial MaxSAT problem, and then solve the resulting problem with state-of-art solvers. In addition, we present an algorithm MEMKC exactly solving the diversified top-k partial MaxSAT. Through several experiments we show that our approach can be successfully applied to the interesting problem.


title: Shape Deformation with a Stretching and Bending Energy

abstract: In this report we describe a mesh editing system that we implemented that uses a natural stretching and bending energy defined over smooth surfaces. As such, this energy behaves uniformly under various mesh resolutions. All of the elements of our approach already exist in the literature. We hope that our discussions of these energies helps to shed light on the behaviors of these methods and provides a unified discussion of these methods.


title: Trust in Typical and High-Reliability Contexts: Building and Reacting to Trust among Firefighters

abstract: We develop theory that distinguishes trust among employees in typical task contexts (marked by low levels of situational unpredictability and danger) from trust in “high-reliability” task contexts (those marked by high levels of situational unpredictability and danger). A study of firefighters showed that trust in high-reliability task contexts was based on coworkers' integrity, whereas trust in typical task contexts was also based on benevolence and identification. Trust in high-reliability contexts predicted physical symptoms, whereas trust in typical contexts predicted withdrawal. Job demands moderated linkages with performance: trust in high-reliability task contexts was a more positive predictor of performance when unpredictable and dangerous calls were more frequent.


title: Aharonov-Bohm oscillations in a quasi-ballistic three-dimensional topological insulator nanowire.

abstract: Aharonov-Bohm oscillations effectively demonstrate coherent, ballistic transport in mesoscopic rings and tubes. In three-dimensional topological insulator nanowires, they can be used to not only characterize surface states but also to test predictions of unique topological behaviour. Here we report measurements of Aharonov-Bohm oscillations in (Bi1.33Sb0.67)Se3 that demonstrate salient features of topological nanowires. By fabricating quasi-ballistic three-dimensional topological insulator nanowire devices that are gate-tunable through the Dirac point, we are able to observe alternations of conductance maxima and minima with gate voltage. Near the Dirac point, we observe conductance minima for zero magnetic flux through the nanowire and corresponding maxima (having magnitudes of almost a conductance quantum) at magnetic flux equal to half a flux quantum; this is consistent with the presence of a low-energy topological mode. The observation of this mode is a necessary step towards utilizing topological properties at the nanoscale in post-CMOS applications.


title: Ideal categories of rings and ring of cones

abstract: In this paper we describe the ideal category of a ring R as preadditive proper category. Further it is also shown that the cones in this category is a ring with appropriate addition and multiplication.


title: μ Shield Configurable Code-Reuse Attacks Mitigation For Embedded Systems

abstract: Embedded devices are playing a major role in our way of life. Similar to other computer systems embedded devices are vulnerable to code-reuse attacks. Compromising these devices in a critical environment constitute a significant security and safety risk. In this paper, we present backslashmu Shield, a memory corruption exploitation mitigation system for embedded COTS binaries with configurable protection policies that do not rely on any hardware-specific feature. Our evaluation shows that backslashmu Shield provides its protection with a limited performance overhead.


title: Synchrophasor Standards Development - IEEE C37.118 & IEC 61850

abstract: The concept of a phasor synchronized with the power system was introduced in the 1980s and standardized for the first time with the standard IEEE 1344. That measurement concept was further developed in the current synchrophasor standard, IEEE C37.118 that was completed in 2005. It is currently undergoing revision to fully define the measurement in all conditions including dynamic changes in the power system. The standard has been split into measurement and data exchange to harmonize it with the IEC 61850 standard. This paper summarizes the synchrophasor concept, reviews the governing standards, and surveys the ongoing standards development.


title: Manipulating Virtual Objects with Your Hands: A Case Study on Applying Desktop Augmented Reality at the Primary School

abstract: Augmented Reality (AR) offers many opportunities as an interactive tool to improve learning and teaching processes. This paper presents a pilot study conducted on third graders where a series of AR contents about Natural and Social Sciences have been used as a teaching tool. The main objective of the application is to help the students to learn complex concepts that present a difficult understanding. A user centered approach was followed to create the AR contents, where several teachers collaborated on its definition. The AR application combines 3D models and animations, mini games and quizzes. An evaluation of the educational contents was made from the point of view efficiency (academic achievement), usability and motivation. Results confirm that the use of desktop AR has had a positive impact on the learning and teaching process and reinforce the vision of AR as an affordable and feasible technological tool to support the students' learning activities.


title: Using Message Logs and Resource Use Data for Cluster Failure Diagnosis

abstract: Failure diagnosis for large compute clusters using only message logs is known to be incomplete. Recent availability of resource use data provides another potentially useful source of data for failure detection and diagnosis. Early work combining message logs and resource use data for failure diagnosis has shown promising results. This paper describes the CRUMEL framework which implements a new approach to combining rationalized message logs and resource use data for failure diagnosis. CRUMEL identifies patterns of errors and resource use and correlates these patterns by time with system failures. Application of CRUMEL to data from the Ranger supercomputer has yielded improved diagnoses over previous research. CRUMEL has: (i) showed that more events correlated with system failures can only be identified by applying different correlation algorithms, (ii) confirmed six groups of errors, (iii) identified Lustre I/O resource use counters which are correlated with occurrence of Lustre faults which are potential flags for online detection of failures, (iv) matched the dates of correlated error events and correlated resource use with the dates of compute node hang-ups and (v) identified two more error groups associated with compute node hang-ups. The pre-processed data will be put on the public domain in September, 2016.


title: Biofeedback Treatment for Asthma

abstract: Study objectives: We evaluated the effectiveness of heart rate variability (HRV) biofeedback as a complementary treatment for asthma. Patients: Ninety-four adult outpatient paid volunteers with asthma. Setting: The psychophysiology laboratory at The University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, and the private outpatient offices of participating asthma physicians. Interventions: The interventions were as follows: (1) a full protocol ( ie , HRV biofeedback and abdominal breathing through pursed lips and prolonged exhalation); (2) HRV biofeedback alone; (3) placebo EEG biofeedback; and (4) a waiting list control. Design: Subjects were first prestabilized using controller medication and then were randomly assigned to experimental groups. Medication was titrated biweekly by blinded asthma specialists according to a protocol based on National Heart, Lung, and Blood Institute guidelines, according to symptoms, spirometry, and home peak flows. Measurements: Subjects recorded daily asthma symptoms and twice-daily peak expiratory flows. Spirometry was performed before and after each weekly treatment session under the HRV and placebo biofeedback conditions, and at triweekly assessment sessions under the waiting list condition. Oscillation resistance was measured approximately triweekly. Results: Compared with the two control groups, subjects in both of the two HRV biofeedback groups were prescribed less medication, with minimal differences between the two active treatments. Improvements averaged one full level of asthma severity. Measures from forced oscillation pneumography similarly showed improvement in pulmonary function. A placebo effect influenced an improvement in asthma symptoms, but not in pulmonary function. Groups did not differ in the occurrence of severe asthma flares. Conclusions: The results suggest that HRV biofeedback may prove to be a useful adjunct to asthma treatment and may help to reduce dependence on steroid medications. Further evaluation of this method is warranted.


title: The parallel distributed processing approach to semantic cognition

abstract: How do we know what properties something has, and which of its properties should be generalized to other objects? How is the knowledge underlying these abilities acquired, and how is it affected by brain disorders? Our approach to these issues is based on the idea that cognitive processes arise from the interactions of neurons through synaptic connections. The knowledge in such interactive and distributed processing systems is stored in the strengths of the connections and is acquired gradually through experience. Degradation of semantic knowledge occurs through degradation of the patterns of neural activity that probe the knowledge stored in the connections. Simulation models based on these ideas capture semantic cognitive processes and their development and disintegration, encompassing domain-specific patterns of generalization in young children, and the restructuring of conceptual knowledge as a function of experience.


title: Face occlusion detection using skin color ratio and LBP features for intelligent video surveillance systems

abstract: A face occlusion detection scheme which is based on both skin color ratio (SCR) and Local Binary Pattern (LBP) feature, is proposed. The proposed method mainly consists of four steps: foreground extraction, head detection, feature extraction, and occlusion detection. First, foreground is extracted by codebook background subtraction algorithm. Then, the head region is located using HOG head detector. After that, the skin-color ratio and LBP feature are extracted. Finally, SVM is trained based on LBP feature. The recognition result of SVM and the result of skin-color ratio feature are merged by weighted voting strategy, and then occluded faces are classified as three categories: concealed, partially concealed, and visible. Experimental results show that the proposed detection system can achieve desirable results in intelligent video surveillance systems.


title: Evaluation of learning curves for ovariohysterectomy of dogs and cats and castration of dogs

abstract: OBJECTIVE To define learning curves for fourth-year veterinary students performing ovariohysterectomy procedures in dogs and cats and castration in dogs. DESIGN Retrospective study. SAMPLE 3,196 ovariohysterectomies or castrations performed in dogs and cats by 88 veterinary students during a spay-neuter surgery and animal shelter rotation (n = 3,056) or by 1 experienced general practitioner (n = 140). PROCEDURES Data collected from medical records included patient signalment, type and duration of procedure, and sequence (by date and time) of the procedure within a list of procedures of the same type generated for each student. For each procedure type, geometric mean surgery time and 95% confidence intervals were determined for each number of surgeries completed by ≥ 10 students. Median surgery times for the same procedure types were determined for the experienced practitioner. The learning curve for each procedure was modeled with nonlinear (3-factor exponential equation with a nonzero asymptote) and line...


title: RENO: A high-efficient reconfigurable neuromorphic computing accelerator design

abstract: Neuromorphic computing is recently gaining significant attention as a promising candidate to conquer the well-known von Neumann bottleneck. In this work, we propose RENO -- a efficient reconfigurable neuromorphic computing accelerator. RENO leverages the extremely efficient mixed-signal computation capability of memristor-based crossbar (MBC) arrays to speedup the executions of artificial neural networks (ANNs). The hierarchically arranged MBC arrays can be configured to a variety of ANN topologies through a mixed-signal interconnection network (M-Net). Simulation results on seven ANN applications show that compared to the baseline general-purpose processor, RENO can achieve on average 178.4x (27.06x) performance speedup and 184.2x (25.23x) energy savings in high-efficient multilayer perception (high-accurate auto-associative memory) implementation. Moreover, in the comparison to a pure digital neural processing unit (D-NPU) and a design with MBC arrays co-operating through a digital interconnection network, RENO still achieves the fastest execution time and the lowest energy consumption with similar computation accuracy.


title: I feel good, therefore I am real: Testing the causal influence of mood on state authenticity

abstract: Although the literature has focused on individual differences in authenticity, recent findings suggest that authenticity is sensitive to context; that is, it is also a state. We extended this perspective by examining whether incidental affect influences authenticity. In three experiments, participants felt more authentic when in a relatively positive than negative mood. The causal role of affect in authenticity was consistent across a diverse set of mood inductions, including explicit (Experiments 1 and 3) and implicit (Experiment 2) methods. The link between incidental affect and state authenticity was not moderated by ability to down-regulate negative affect (Experiments 1 and 3) nor was it explained by negative mood increasing private self-consciousness or decreasing access to the self system (Experiment 3). The results indicate that mood is used as information to assess one's sense of authenticity.


title: AI Grand Challenges for Education

abstract: This article focuses on contributions that AI can make to address long-term educational goals. It describes five challenges that would support: (1) mentors for every learner; (2) learning twenty-first century skills; (3) interaction data to support learning; (4) universal access to global classrooms; and (5) lifelong and life-wide learning. A vision and brief research agenda are described for each challenge along with goals that lead to access to global educational resources and the reuse and sharing of digital educational resources. Instructional systems with AI technology are described that currently support richer experiences for learners and supply researchers with new opportunities to analyze vast data sets of instructional behavior from big databases, containing elements of learning, affect, motivation, and social interaction. Personalized learning is described using computational tools that enhance student and group experience, reflection, and analysis, and supply data for development of novel theory development.


title: Automatic Measurement and Control System for Vehicle ECU Based on CAN Bus

abstract: This paper illustrates the development of the automatic measurement and control system (AMCS) based on control area network (CAN) bus for the engine electronic control unit (ECU). The system composes of the ECU, test ECU (TECU), simulation ECU (SIMU), usb-CAN communication module (CRU ) and AMCS software platform, which is applied for engine control, data collection, transmission, engine signals simulation and the data conversion from CAN to USB and master control simulation and measurement. The AMCS platform software is designed with VC++ 6.0.This system has been applied in the development of engine ECU widely.


title: A Modified Gysel Power Divider of Arbitrary Power Ratio and Real Terminated Impedances

abstract: The Gysel power divider (PD) is modified to achieve unequal or equal power division and suitability for three arbitrary real terminated impedances without any transmission losses in this letter. The calculation of electrical parameters in this asymmetrical structure is flexible. Meanwhile, this modified Gysel PD maintains high power-handling advantage over Wilkinson PD. By using the transmission line theory, the simple closed-form design equations are available for evaluation of these circuit parameters. For verification, two microstrip examples, which include an equal Gysel PD with three different output-port impedances and an unequal one for three standard 50-Ω ports without additional output-port transformers, are given. It can be observed that there is excellent agreement between the simulated and measured results.


title: FaceWarehouse: A 3D Facial Expression Database for Visual Computing

abstract: We present FaceWarehouse, a database of 3D facial expressions for visual computing applications. We use Kinect, an off-the-shelf RGBD camera, to capture 150 individuals aged 7-80 from various ethnic backgrounds. For each person, we captured the RGBD data of her different expressions, including the neutral expression and 19 other expressions such as mouth-opening, smile, kiss, etc. For every RGBD raw data record, a set of facial feature points on the color image such as eye corners, mouth contour, and the nose tip are automatically localized, and manually adjusted if better accuracy is required. We then deform a template facial mesh to fit the depth data as closely as possible while matching the feature points on the color image to their corresponding points on the mesh. Starting from these fitted face meshes, we construct a set of individual-specific expression blendshapes for each person. These meshes with consistent topology are assembled as a rank-3 tensor to build a bilinear face model with two attributes: identity and expression. Compared with previous 3D facial databases, for every person in our database, there is a much richer matching collection of expressions, enabling depiction of most human facial actions. We demonstrate the potential of FaceWarehouse for visual computing with four applications: facial image manipulation, face component transfer, real-time performance-based facial image animation, and facial animation retargeting from video to image.


On Contrastive Divergence Learning


title: Validating viral marketing strategies in Twitter via agent-based social simulation

abstract: We present a method to validate viral marketing strategies in Twitter.The method is based on an Agent-based Social Simulation research methodology.A rumor spread model and control strategies are also presented as a case study.The model and the strategies are evaluated against others in the literature.An open-source simulator and the Twitter data employed are also given. A number of marketing phenomena are too complex for conventional analytical or empirical approaches. This makes marketing a costly process of trial and error: proposing, imagining, trying in the real world, and seeing results. Alternatively, Agent-based Social Simulation (ABSS) is becoming the most popular approach to model and study these phenomena. This research paradigm allows modeling a virtual market to: design, understand, and evaluate marketing hypotheses before taking them to the real world. However, there are shortcomings in the specialized literature such as the lack of methods, data, and implemented tools to deploy a realistic virtual market with ABSS. To advance the state of the art in this complex and interesting problem, this paper is a seven-fold contribution based on a (1) method to design and validate viral marketing strategies in Twitter by ABSS. The method is illustrated with the widely studied problem of rumor diffusion in social networks. After (2) an extensive review of the related works for this problem, (3) an innovative spread model is proposed which rests on the exploratory data analysis of two different rumor datasets in Twitter. Besides, (4) new strategies are proposed to control malicious gossips. (5) The experimental results validate the realism of this new propagation model with the datasets and (6) the strategies performance is evaluated over this model. (7) Finally, the article is complemented by a free and open-source simulator.


title: Trust, but verify: predicting contribution quality for knowledge base construction and curation

abstract: The largest publicly available knowledge repositories, such as Wikipedia and Freebase, owe their existence and growth to volunteer contributors around the globe. While the majority of contributions are correct, errors can still creep in, due to editors' carelessness, misunderstanding of the schema, malice, or even lack of accepted ground truth. If left undetected, inaccuracies often degrade the experience of users and the performance of applications that rely on these knowledge repositories. We present a new method, CQUAL, for automatically predicting the quality of contributions submitted to a knowledge base. Significantly expanding upon previous work, our method holistically exploits a variety of signals, including the user's domains of expertise as reflected in her prior contribution history, and the historical accuracy rates of different types of facts. In a large-scale human evaluation, our method exhibits precision of 91% at 80% recall. Our model verifies whether a contribution is correct immediately after it is submitted, significantly alleviating the need for post-submission human reviewing.


title: Interpretation and trust: designing model-driven visualizations for text analysis

abstract: Statistical topic models can help analysts discover patterns in large text corpora by identifying recurring sets of words and enabling exploration by topical concepts. However, understanding and validating the output of these models can itself be a challenging analysis task. In this paper, we offer two design considerations - interpretation and trust - for designing visualizations based on data-driven models. Interpretation refers to the facility with which an analyst makes inferences about the data through the lens of a model abstraction. Trust refers to the actual and perceived accuracy of an analyst's inferences. These considerations derive from our experiences developing the Stanford Dissertation Browser, a tool for exploring over 9,000 Ph.D. theses by topical similarity, and a subsequent review of existing literature. We contribute a novel similarity measure for text collections based on a notion of "word-borrowing" that arose from an iterative design process. Based on our experiences and a literature review, we distill a set of design recommendations and describe how they promote interpretable and trustworthy visual analysis tools.


title: View management for virtual and augmented reality

abstract: We describe a view-management component for interactive 3D user interfaces. By view management, we mean maintaining visual constraints on the projections of objects on the view plane, such as locating related objects near each other, or preventing objects from occluding each other. Our view-management component accomplishes this by modifying selected object properties, including position, size, and transparency, which are tagged to indicate their constraints. For example, some objects may have geometric properties that are determined entirely by a physical simulation and which cannot be modified, while other objects may be annotations whose position and size are flexible.We introduce algorithms that use upright rectangular extents to represent on the view plane a dynamic and efficient approximation of the occupied space containing the projections of visible portions of 3D objects, as well as the unoccupied space in which objects can be placed to avoid occlusion. Layout decisions from previous frames are taken into account to reduce visual discontinuities. We present augmented reality and virtual reality examples to which we have applied our approach, including a dynamically labeled and annotated environment.


title: An R&D knowledge management method for patent document summarization

abstract: Purpose – In an era of rapidly expanding digital content, the number of e‐documents and the amount of knowledge frequently overwhelm the R&D teams and often impede intellectual property management. The purpose of this paper is to develop an automatic patent summarization method for accurate knowledge abstraction and effective R&D knowledge management.Design/methodology/approach – This paper develops an integrated approach for automatic patent summary generation combining the concepts of key phrase recognition and significant information density. Significant information density is defined based on the domain‐specific key concepts/phrases, relevant phrases, title phrases, indicator phrases and topic sentences of a given patent document.Findings – The document compression ratio and the knowledge retention ratio are used to measure both quantitative and qualitative outcomes of the new summarization methodology. Both measurements indicate the significant benefits and superior results of the method.Research lim...


title: Relationship between lumbar spinal stenosis and psychosocial factors: a multicenter cross-sectional study (DISTO project)

abstract: Introduction ::: Lumbar spinal stenosis (LSS) is a lumbar spinal disorder that causes leg symptoms and intermittent claudication. It is reported that the risk factors for low back pain include age, family history, smoking, obesity, work-related physical load, exercise, and depression. This was a multicenter, cross-sectional survey, and the aim of this study was to investigate the prevalence of LSS by age and the relationships between LSS and psychosocial factors and job satisfaction.


title: Choosing Useful Word Alternates for Automatic Speech Recognition Correction Interfaces

abstract: Speech recognition is an increasingly important input modality, especially for mobile computing. Because errors are unavoidable in real applications, efficient correction methods can greatly enhance the user experience. In this paper we study a reranking and classification strategy for choosing word alternates to display to the user in the framework of a tap-to-correct interface. By employing a logistic regression model to estimate the probability that an alternate will offer a useful correction to the user, we can significantly reduce the average length of the alternates lists generated with no reduction in the number of words they are able to correct.


title: A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research

abstract: OBJECTIVE ::: Intraclass correlation coefficient (ICC) is a widely used reliability index in test-retest, intrarater, and interrater reliability analyses. This article introduces the basic concept of ICC in the content of reliability analysis. ::: ::: ::: DISCUSSION FOR RESEARCHERS ::: There are 10 forms of ICCs. Because each form involves distinct assumptions in their calculation and will lead to different interpretations, researchers should explicitly specify the ICC form they used in their calculation. A thorough review of the research design is needed in selecting the appropriate form of ICC to evaluate reliability. The best practice of reporting ICC should include software information, "model," "type," and "definition" selections. ::: ::: ::: DISCUSSION FOR READERS ::: When coming across an article that includes ICC, readers should first check whether information about the ICC form has been reported and if an appropriate ICC form was used. Based on the 95% confident interval of the ICC estimate, values less than 0.5, between 0.5 and 0.75, between 0.75 and 0.9, and greater than 0.90 are indicative of poor, moderate, good, and excellent reliability, respectively. ::: ::: ::: CONCLUSION ::: This article provides a practical guideline for clinical researchers to choose the correct form of ICC and suggests the best practice of reporting ICC parameters in scientific publications. This article also gives readers an appreciation for what to look for when coming across ICC while reading an article.


title: Mining Business Contracts for Service Exceptions

abstract: A contract is a legally binding agreement between real-world business entities whom we treat as providing services to one another. We focus on business rather than technical services. We think of a business contract as specifying the functional and nonfunctional behaviors of and interactions among the services. In current practice, contracts are produced as text documents. Thus the relevant service capabilities, requirements, qualities, and risks are hidden and difficult to access and reason about. We describe a simple but effective unsupervised information extraction approach and tool, Contract Miner, for discovering service exceptions at the phrase level from a large contract repository. Our approach involves preprocessing followed by an application of linguistic patterns and parsing to extract the service exception phrases. Identifying such (noun) phrases can help build service exception vocabularies that support the development of a taxonomy of business terms, and also facilitate modeling and analyzing service engagements. A lightweight online tool that comes with Contract Miner highlights the relevant text in service contracts and thereby assists users in reviewing contracts. Contract Miner produces promising results in terms of precision and recall when evaluated over a corpus of manually annotated contracts.


GNU Radio Wireless protocol analysis approach Author:


title: Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance

abstract: This paper draws on the social and behavioral sciences in an endeavor to specify the nature and microfoundations of the capabilities necessary to sustain superior enterprise performance in an open economy with rapid innovation and globally dispersed sources of invention, innovation, and manufacturing capability. Dynamic capabilities enable business enterprises to create, deploy, and protect the intangible assets that support superior long- run business performance. The microfoundations of dynamic capabilities—the distinct skills, processes, procedures, organizational structures, decision rules, and disciplines—which undergird enterprise-level sensing, seizing, and reconfiguring capacities are difficult to develop and deploy. Enterprises with strong dynamic capabilities are intensely entrepreneurial. They not only adapt to business ecosystems, but also shape them through innovation and through collaboration with other enterprises, entities, and institutions. The framework advanced can help scholars understand the foundations of long-run enterprise success while helping managers delineate relevant strategic considerations and the priorities they must adopt to enhance enterprise performance and escape the zero profit tendency associated with operating in markets open to global competition. Copyright  2007 John Wiley & Sons, Ltd.


title: Full-system power analysis and modeling for server environments

abstract: The increasing costs of power delivery and cooling, as well as the trend toward higher-density computer systems, have created a growing demand for better power management in server environments. Despite the increasing interest in this issue, little work has been done in quantitatively understanding power consumption trends and developing simple yet accurate models to predict full-system power. We study the component-level power breakdown and variation, as well as temporal workload-specific power consumption of an instrumented power-optimized blade server. Using this analysis, we examine the validity of prior adhoc approaches to understanding power breakdown and quantify several interesting trends important for power modeling and management in the future. We also introduce Mantis, a nonintrusive method for modeling full-system power consumption and providing real-time power prediction. Mantis uses a onetime calibration phase to generate a model by correlating AC power measurements with user-level system utilization metrics. We experimentally validate the model on two server systems with drastically different power footprints and characteristics (a low-end blade and high-end compute-optimized server) using a variety of workloads. Mantis provides power estimates with high accuracy for both overall and temporal power consumption, making it a valuable tool for power-aware scheduling and analysis.


title: Waveform contenders for 5G — OFDM vs. FBMC vs. UFMC

abstract: In this paper we review the waveform design of 4G (based on OFDM) and motivate the need for a redesign for 5G. Both the advent of the Internet of Things (IoT) and the move to user-centric processing are rendering OFDM unfeasible. With FBMC a potential contender has been promoted in recent years. Though FBMC is better suited than OFDM in theory, practical considerations pinpoint many issues of FBMC. Therefore, we have designed a new waveform called Universal Filtered Multi-Carrier (UFMC) collecting the advantages FBMC is promising while avoiding its drawbacks. In contrast to FBMC, UFMC applies a filtering functionality per sub-band instead of per subcarrier.


title: Morfessor 2.0: Toolkit for statistical morphological segmentation

abstract: Morfessor is a family of probabilistic machine learning methods for finding the morphological segmentation from raw text data. Recent developments include the development of semi-supervised methods for utilizing annotated data. Morfessor 2.0 is a rewrite of the original, widely-used Morfessor 1.0 software, with well documented command-line tools and library interface. It includes new features such as semi-supervised learning, online training, and integrated evaluation code.


title: A neural network alternative to non-negative audio models

abstract: We present a neural network that can act as an equivalent to a Non-Negative Matrix Factorization (NMF), and further show how it can be used to perform supervised source separation. Due to the extensibility of this approach we show how we can achieve better source separation performance as compared to NMF-based methods, and propose a variety of derivative architectures that can be used for further improvements.


title: LDAExplore: Visualizing Topic Models Generated Using Latent Dirichlet Allocation

abstract: We present LDAExplore, a tool to visualize topic distributions in a given document corpus that are generated using Topic Modeling methods. Latent Dirichlet Allocation (LDA) is one of the basic methods that is predominantly used to generate topics. One of the problems with methods like LDA is that users who apply them may not understand the topics that are generated. Also, users may find it difficult to search correlated topics and correlated documents. LDAExplore, tries to alleviate these problems by visualizing topic and word distributions generated from the document corpus and allowing the user to interact with them. The system is designed for users, who have minimal knowledge of LDA or Topic Modelling methods. To evaluate our design, we run a pilot study which uses the abstracts of 322 Information Visualization papers, where every abstract is considered a document. The topics generated are then explored by users. The results show that users are able to find correlated documents and group them based on topics that are similar.


title: Session search modeling by partially observable Markov decision process

abstract: Session search, the task of document retrieval for a series of queries in a session, has been receiving increasing attention from the information retrieval research community. Session search exhibits the properties of rich user-system interactions and temporal dependency. These properties lead to our proposal of using partially observable Markov decision process to model session search. On the basis of a design choice schema for states, actions and rewards, we evaluate different combinations of these choices over the TREC 2012 and 2013 session track datasets. According to the experimental results, practical design recommendations for using PODMP in session search are discussed.


title: PlaceAvoider: Steering First-Person Cameras away from Sensitive Spaces.

abstract: As a first step, we introduce PlaceAvoider, a technique for owners of first-person cameras to ‘blacklist’ sensitive spaces (like bathrooms and bedrooms). PlaceAvoider recognizes images captured in these spaces and flags them for review before the images are made available to applications. PlaceAvoider performs novel image analysis using both fine-grained image features (like specific objects) and coarse-grained, scene-level features (like colors and textures) to classify where a photo was taken. PlaceAvoider combines these features in a probabilistic framework that jointly labels streams of images in order to improve accuracy. We test the technique on five realistic firstperson image datasets and show it is robust to blurriness, motion, and occlusion.


title: Comparison of Performance of Decision Tree Algorithms and Random Forest: An Application on OECD Countries Health Expenditures

abstract: trees and Random Forest are most popular methods of machine learning techniques. C4.5 which is an extension version of ID.3 algorithm and CART are one of these most commonly use algorithms to generate decision trees. Random Forest which constructs a lot of number of trees is one of another useful technique for solving both classification and regression problems. This study compares classification performances of different decision trees (C4.5, CART) and Random Forest which was generated using 50 trees. Data came from OECD countries health expenditures for the year 2011. AUC and ROC curve graph was used for performance comparison. Experimental results show that Random Forest outperformed in classification accuracy (AUC=0.98) in comparison with CART (0.95) and C4.5 (0.90) respectively. Future studies more focus on performance comparisons of different machine learning techniques using several datasets and different hyperparameter optimization techniques.


title: Nomadic Computing for Big Data Analytics

abstract: Analyzing the massive datasets of today's applications will require scalable and sophisticated machine-learning methods. NOMAD, a novel nomadic framework, combines two common approaches: stochastic optimization and distributed computing.


title: Drawing graphs nicely using simulated annealing

abstract: The paradigm of simulated annealing is applied to the problem of drawing graphs “nicely.” Our algorithm deals with general undirected graphs with straight-line edges, and employs several simple criteria for the aesthetic quality of the result. The algorithm is flexible, in that the relative weights of the criteria can be changed. For graphs of modest size it produces good results, competitive with those produced by other methods, notably, the “spring method” and its variants.


title: Manifold Elastic Net: A Unified Framework for Sparse Dimension Reduction

abstract: It is difficult to find the optimal sparse solution of a manifold learning based dimensionality reduction algorithm. The lasso or the elastic net penalized manifold learning based dimensionality reduction is not directly a lasso penalized least square problem and thus the least angle regression (LARS) (Efron et al., Ann Stat 32(2):407---499, 2004), one of the most popular algorithms in sparse learning, cannot be applied. Therefore, most current approaches take indirect ways or have strict settings, which can be inconvenient for applications. In this paper, we proposed the manifold elastic net or MEN for short. MEN incorporates the merits of both the manifold learning based dimensionality reduction and the sparse learning based dimensionality reduction. By using a series of equivalent transformations, we show MEN is equivalent to the lasso penalized least square problem and thus LARS is adopted to obtain the optimal sparse solution of MEN. In particular, MEN has the following advantages for subsequent classification: (1) the local geometry of samples is well preserved for low dimensional data representation, (2) both the margin maximization and the classification error minimization are considered for sparse projection calculation, (3) the projection matrix of MEN improves the parsimony in computation, (4) the elastic net penalty reduces the over-fitting problem, and (5) the projection matrix of MEN can be interpreted psychologically and physiologically. Experimental evidence on face recognition over various popular datasets suggests that MEN is superior to top level dimensionality reduction algorithms.


title: Multimodal Network Alignment

abstract: A multimodal network encodes relationships between the same set of nodes in multiple settings, and network alignment is a powerful tool for transferring information and insight between a pair of networks. We propose a method for multimodal network alignment that computes a matrix which indicates the alignment, but produces the result as a low-rank factorization directly. We then propose new methods to compute approximate maximum weight matchings of low-rank matrices to produce an alignment. We evaluate our approach by applying it on synthetic networks and use it to de-anonymize a multimodal transportation network.


title: Design of an X-band feed system for the Auckland University of Technology 30m diameter warkworth radio telescope

abstract: An innovative way to nest a new X-band feed system inside an existing C-band feed system is proposed.


title: Towards a classification model for tasks in crowdsourcing

abstract: Crowdsourcing is an increasingly popular approach for utilizing the power of the crowd in performing tasks that cannot be solved sufficiently by machines. Text annotation and image labeling are two examples of crowdsourcing tasks that are difficult to automate and human knowledge is often required. However, the quality of the obtained outcome from the crowdsourcing is still problematic. To obtain high-quality results, different quality control mechanisms should be applied to evaluate the different type of tasks. In a previous work, we present a task ontology-based model that can be utilized to identify which quality mechanism is most appropriate based on the task type. In this paper, we complement our previous work by providing a categorization of crowdsourcing tasks. That is, we define the most common task types in the crowdsourcing context. Then, we show how machine learning algorithms can be used to infer automatically the type of the crowdsourced task.


title: Path Aggregation Network for Instance Segmentation

abstract: The way that information propagates in neural networks is of great importance. In this paper, we propose Path Aggregation Network (PANet) aiming at boosting information flow in proposal-based instance segmentation framework. Specifically, we enhance the entire feature hierarchy with accurate localization signals in lower layers by bottom-up path augmentation, which shortens the information path between lower layers and topmost feature. We present adaptive feature pooling, which links feature grid and all feature levels to make useful information in each feature level propagate directly to following proposal subnetworks. A complementary branch capturing different views for each proposal is created to further improve mask prediction. These improvements are simple to implement, with subtle extra computational overhead. Our PANet reaches the 1st place in the COCO 2017 Challenge Instance Segmentation task and the 2nd place in Object Detection task without large-batch training. It is also state-of-the-art on MVD and Cityscapes. Code is available at https://github.com/ShuLiu1993/PANet


title: Median-based Image Thresholding

abstract: In order to select an optimal threshold for image thresholding that is relatively robust to the presence of skew and heavy-tailed class-conditional distributions, we propose two median-based approaches: one is an extension of Otsu's method and the other is an extension of Kittler and Illingworth's minimum error thresholding. We provide theoretical interpretation of the new approaches, based on mixtures of Laplace distributions. The two extensions preserve the methodological simplicity and computational efficiency of their original methods, and in general can achieve more robust performance when the data for either class is skew and heavy-tailed. We also discuss some limitations of the new approaches.


title: Consciousness in the Universe: Neuroscience, Quantum Space-Time Geometry and Orch OR Theory

abstract: The nature of consciousness, its occurrence in the brain, and its ultimate place in the universe are unknown. We proposed in the mid 1990's that consciousness depends on biologically 'orchestrated' quantum computations in collections of microtubules within brain neurons, that these quantum computations correlate with and regulate neuronal activity, and that the continuous Schrodinger evolution of each quantum computation terminates in accordance with the specific Diosi‐Penrose (DP) scheme of 'objective reduction' of the quantum state (OR). This orchestrated OR activity (Orch OR) is taken to result in a moment of conscious awareness and/or choice. This particular (DP) form of OR is taken to be a quantum-gravity process related to the fundamentals of spacetime geometry, so Orch OR suggests a connection between brain biomolecular processes and fine-scale structure of the universe. Here we review and update Orch OR in light of criticisms and developments in quantum biology, neuroscience, physics and cosmology. We conclude that consciousness plays an intrinsic role in the universe.


title: Monte Carlo sampling methods using Markov chains and their applications

abstract: SUMMARY A generalization of the sampling method introduced by Metropolis et al. (1953) is presented along with an exposition of the relevant theory, techniques of application and methods and difficulties of assessing the error in Monte Carlo estimates. Examples of the methods, including the generation of random orthogonal matrices and potential applications of the methods to numerical problems arising in statistics, are discussed. For numerical problems in a large number of dimensions, Monte Carlo methods are often more efficient than conventional numerical methods. However, implementation of the Monte Carlo methods requires sampling from high dimensional probability distributions and this may be very difficult and expensive in analysis and computer time. General methods for sampling from, or estimating expectations with respect to, such distributions are as follows. (i) If possible, factorize the distribution into the product of one-dimensional conditional distributions from which samples may be obtained. (ii) Use importance sampling, which may also be used for variance reduction. That is, in order to evaluate the integral J = X) p(x)dx = Ev(f), where p(x) is a probability density function, instead of obtaining independent samples XI, ..., Xv from p(x) and using the estimate J, = Zf(xi)/N, we instead obtain the sample from a distribution with density q(x) and use the estimate J2 = Y{f(xj)p(x1)}/{q(xj)N}. This may be advantageous if it is easier to sample from q(x) thanp(x), but it is a difficult method to use in a large number of dimensions, since the values of the weights w(xi) = p(x1)/q(xj) for reasonable values of N may all be extremely small, or a few may be extremely large. In estimating the probability of an event A, however, these difficulties may not be as serious since the only values of w(x) which are important are those for which x -A. Since the methods proposed by Trotter & Tukey (1956) for the estimation of conditional expectations require the use of importance sampling, the same difficulties may be encountered in their use. (iii) Use a simulation technique; that is, if it is difficult to sample directly from p(x) or if p(x) is unknown, sample from some distribution q(y) and obtain the sample x values as some function of the corresponding y values. If we want samples from the conditional dis


title: Load Balancing in Cloud Computing

abstract: Cloud computing is the next generation of computation. Possibly people can have everything they need on the cloud. Cloud computing provides resources to client on demand. The resources may be software resources or hardware resources. Cloud computing architectures are distributed, parallel and serve the needs of multiple clients in different scenarios. This distributed architecture deploys resources distributive to deliver services efficiently to users in different geographical channels. Clients in a distributed environment generate request randomly in any processor. So the major drawback of this randomness is associated with task assignment. The unequal task assignment to the processor creates imbalance i.e., some of the processors are overloaded and some of them are under loaded. The objective of load balancing is to transfer the load from overloaded process to under loaded process transparently. Load balancing is one of the central issues in cloud computing. To achieve high performance, minimum response time and high resource utilization ratio we need to transfer the tasks between nodes in cloud network. Load balancing technique is used to distribute tasks from over loaded nodes to under loaded or idle nodes. In following sections we are discuss about cloud computing, load balancing techniques and the proposed work of our load balancing system.


title: A novel dual-slope mm-Wave channel model based on 3D ray-tracing in urban environments

abstract: To solve mobile traffic crunch, the usage of enormous bandwidth in millimeter wave (mm-Wave) is under discussion. In this paper, we investigate radio channel characteristics of mm-Wave frequency in the downtown area of Ottawa using 3D ray-tracing technique. In the results, important parameters of the radio channel model, such as path loss exponent, shadow fading, delay spread and angle spread, are provided. Especially, in case of path loss model in non-line of sight, a novel dual-slope approach is proposed for two conventional deployment scenarios. Comparing to traditional single-slope path loss model, the proposed method has smaller RMS errors in terms of local mean of path loss observations. We believe that the proposed method is appropriate to evaluate performance of the mm-Wave system in dense urban environments.


title: Full 3D spatial decomposition for the generation of navigation meshes

abstract: We present a novel algorithm developed for decomposing world-space into arbitrary sided high-order polyhedrons for use as navmeshes or other techniques requiring 3D world spatial decomposition. The Adaptive Space Filling Volumes 3D (ASFV3D) algorithm works by seeding world-space with a series of unit cubes. Each cube is then provided with the opportunity to grow to its maximum extent before encountering an obstruction. ASFV3D implements an automatic subdividing system to convert cubes into higher-order polyhedrons while still maintaining the convex property. This allows for the generation of navigation meshes with high degrees of coverage while still allowing the use of large navigation regions—providing for easier agent navigation in virtual worlds. Compared to the Space-filling Volumes and Automatic Path Node Generation navigation mesh decomposition methods, ASFV3D provides more complete coverage and a less complex navigation mesh.


title: Value of trichoscopy versus trichogram for diagnosis of female androgenetic alopecia

abstract: Background: Female androgenetic alopecia (FAGA) is a frequent cause of hair loss in women. Standard diagnostic methods are clinical inspection, pull test, and trichogram. It has been suggested that scalp dermoscopy (trichoscopy) revealing diversity of hair shaft diameter >20% is diagnostic of FAGA. Objective: To evaluate the value of trichoscopy as compared to the trichogram for the diagnosis of FAGA. Patients and Methods: Retrospective case study of 162 women with the complaint of hair loss who underwent trichoscopic examination and trichograms. Results: Of all women diagnosed FAGA (55%), 62% were diagnosed by trichogram, 72% by trichoscopy with a cut-off point of 20%, and 100% irrespective of the degree of diversity of hair shaft diameter. Conclusions: Trichoscopy is a valuable and superior method to the trichogram for diagnosis of FAGA, especially in early cases, with the highest yield irrespective of the suggested cut-off of 20% diversity of hair shaft.


title: Masturbation is Related to Psychopathology and Prostate Dysfunction: Comment on Quinsey (2012)

abstract: In an interesting discussion about which criteria should guide the diagnoses of paraphilias, Quinsey (2012) observed that‘‘in order for a condition to be considered a mental disorder, the condition must represent the failure of some mental mechanism to perform the function for which it was designed by natural selection and the condition must cause some deprivation of benefit (defined in terms of the society within which the affected individual lives)’’ (p. 218). Furthermore, it is noted that, from an evolutionary perspective, a deprivation of benefit should carry costs of reduced fitness (Quinsey, 2012). Consequently, Quinsey concluded that most actual and proposedDSMparaphiliasdonotclearlymeet thesecriteria,because it is not clear if they diminish reproductive fitness by reducing the likelihood of penile-vaginal intercourse (PVI) with fertile partners. In sodoing,heoffers theexampleofmasturbationasbeinga healthy behavior that appears to have no such interference. He asserted that masturbation is healthy by‘‘for example, lessening the likelihood ofdevelopingprostatecancer, improving mood, developing sexual interests, and perhaps even ridding oneself of tired sperm’’ (p. 219). However, these unreferenced claims contrast sharply with the best available empirical evidence. It is difficult to reconcile the view that masturbation improves mood with the findings in both sexes that greater masturbation frequency is associated with more depressive symptoms (Cyranowski et al., 2004; Frohlich & Meston, 2002; Husted & Edwards, 1976), less happiness (Das, 2007), and several other indicators of poorer physical and mental health, which include anxious attachment (Costa & Brody, 2011), immature psychological defense mechanisms, greater blood pressure reactivity to stress, and dissatisfaction with one0s mental health and life in general (for a review, see Brody, 2010). It is equally difficult to see how masturbationdevelopssexual interests,whengreatermasturbation frequency is sooftenassociatedwith impairedsexual function inmen (Brody & Costa, 2009; Das, Parish, & Laumann, 2009; Gerressu, Mercer, Graham, Wellings, & Johnson, 2008; Lau, Wang, Cheng, & Yang, 2005; Nutter & Condron, 1985) and women (Brody & Costa, 2009; Das et al., 2009; Gerressu et al., 2008; Lau, Cheng, Wang, & Yang, 2006; Shaeer, Shaeer, & Shaeer, 2012; Weiss & Brody, 2009). Greater masturbation frequency is also associated with more dissatisfaction with relationships and less love for partners (Brody, 2010; Brody & Costa, 2009). In contrast, PVI is very consistently related to better health (Brody, 2010; Brody & Costa, 2009; Brody & Weiss, 2011; Costa & Brody, 2011, 2012), better sexual function (Brody & Costa, 2009; Brody & Weiss, 2011; Nutter & Condron, 1983, 1985; Weiss & Brody, 2009), and better intimate relationship quality (Brody, 2010; Brody & Costa, 2009; Brody & Weiss, 2011). Moreover, although less risk of prostate cancer was associated with greater number of ejaculations (without specification of the sexualbehavior) (Gilesetal., 2003), it isPVIfrequency that is specifically associated with reduced risk, whereas masturbation frequency is more often related to increased risk (for a review on the subject,seeBrody,2010). Inthisregard, it is interestingtonote that masturbation isalsoassociatedwithotherproblemsof theprostate (higher prostate specific antigen levels and swollen or tender prostate)and,comparedwiththeejaculateobtainedfromPVI, theejaculate obtained from masturbation has markers of poorer prostatic function and lesser elimination of waste products (Brody, 2010). The only sexual behavior consistently related to better psychological and physical health is PVI. In contrast, masturbation is frequently associated with indices of poorer health (Brody, 2010; Brody & Costa, 2009; Brody & Weiss, 2011; Costa & Brody, 2011, 2012). There are several possible psychological and physiological mechanisms, which are a likely consequence R. M. Costa (&) ISPA-Instituto Universitario, Unidade de Investigacao em Eco-Etologia, Rua do Jardim do Tabaco 34, 1149-041 Lisbon, Portugal e-mail: rmscosta@gmail.com


title: The simple temperature control for induction cooker based on class-E resonant inverter

abstract: This paper presents a simple temperature control for high efficiency induction cooker based on class-E DC-AC resonant inverter. The active switch can be operated under the zero-voltage switching conditions. The conduction loss of the anti-parallel diode of the active switch and the harmonic currents injected into the public supply system can be reduced. The high power-factor and low line current harmonic distortion can be obtained, which are very attractive in term of commercial production. In order to achieve upon this objective, the induction cooker's parameters need to be designed properly and details of analysis and design of this induction cooker's components are described. A proposed high efficiency induction cooker is designed for an operating at a 32-kHz frequency, a 220-V line rms voltage, a 50-Hz line frequency and a 1.2-kW output power.


title: DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices

abstract: Breakthroughs from the field of deep learning are radically changing how sensor data are interpreted to extract the high-level information needed by mobile apps. It is critical that the gains in inference accuracy that deep models afford become embedded in future generations of mobile apps. In this work, we present the design and implementation of DeepX, a software accelerator for deep learning execution. DeepX signif- icantly lowers the device resources (viz. memory, computation, energy) required by deep learning that currently act as a severe bottleneck to mobile adoption. The foundation of DeepX is a pair of resource control algorithms, designed for the inference stage of deep learning, that: (1) decompose monolithic deep model network architectures into unit- blocks of various types, that are then more efficiently executed by heterogeneous local device processors (e.g., GPUs, CPUs); and (2), perform principled resource scaling that adjusts the architecture of deep models to shape the overhead each unit-blocks introduces. Experiments show, DeepX can allow even large-scale deep learning models to execute efficently on modern mobile processors and significantly outperform existing solutions, such as cloud-based offloading.


title: Frontiers of biomedical text mining:

abstract: It is now almost 15 years since the publication of the first paper on text mining in the genomics domain, and decades since the first paper on text mining in the medical domain. Enormous progress has been made in the areas of information retrieval, evaluation methodologies and resource construction. Some problems, such as abbreviationhandling, can essentially be considered solved problems, and others, such as identification of gene mentions in text, seem likely to be solved soon. However, a number of problems at the frontiers of biomedical text mining continue to present interesting challenges and opportunities for great improvements and interesting research. In this article we review the current state of the art in biomedical text mining or ‘BioNLP’ in general, focusing primarily on papers published within the past year.


title: Creating adaptive Web sites through usage-based clustering of URLs

abstract: We describe an approach to usage based Web personalization taking into account both the offline tasks related to the mining of usage data, and the online process of automatic Web page customization based on the mined knowledge. Specifically, we propose an effective technique for capturing common user profiles based on association rule discovery and usage based clustering. We also propose techniques for combining this knowledge with the current status of an ongoing Web activity to perform real time personalization. Finally, we provide an experimental evaluation of the proposed techniques using real Web usage data.


title: Fast personalized PageRank on MapReduce

abstract: In this paper, we design a fast MapReduce algorithm for Monte Carlo approximation of personalized PageRank vectors of all the nodes in a graph. The basic idea is very efficiently doing single random walks of a given length starting at each node in the graph. More precisely, we design a MapReduce algorithm, which given a graph G and a length », outputs a single random walk of length » starting at each node in G. We will show that the number of MapReduce iterations used by our algorithm is optimal among a broad family of algorithms for the problem, and its I/O efficiency is much better than the existing candidates. We will then show how we can use this algorithm to very efficiently approximate all the personalized PageRank vectors. Our empirical evaluation on real-life graph data and in production MapReduce environment shows that our algorithm is significantly more efficient than all the existing algorithms in the MapReduce setting.


title: Session State: Beyond Soft State

abstract: The cost and complexity of administration of large systems has come to dominate their total cost of ownership. Stateless and soft-state components, e.g. Web servers or network routers, are easy to manage: capacity can be scaled incrementally by adding more nodes, rebalancing of load after failover is easy, and reactive or proactive ("rolling") reboots can be used to handle transient failures. We show that it is possible to achieve the same ease of management for the state-storage subsystem by subdividing persistent state according to the specific guarantees needed by each type. While other systems [19,17] have addressed persistent-until-deleted state, we describe SSM, a store for a previously unaddressed class of state - user-session state - that exhibits the same manageability properties as stateless nodes while providing firm storage guarantees. Any node can be proactively or reactively rebooted at any time to recover from transient faults, without impacting online performance or losing data. We exploit this simplified manageability by pairing SSM with an application-generic, statistical-anomaly-based framework that detects crashes, hangs, and performance failures, and automatically attempts to recover from them by rebooting faulty nodes. Although the detection techniques generate some false positives, the cost of recovery is so low that the false positives have low impact. We provide microbenchmarks to demonstrate SSM's built-in overload protection, failure management and self-tuning. We benchmark SSM integrated into a production enterprise-scale interactive service to demonstrate that these benefits need not come at the cost of significantly decreased throughput or response time.


title: A stable projection method for the incompressible Navier-Stokes equations on arbitrary geometries and adaptive Quad/Octrees

abstract: We present a numerical method for solving the incompressible Navier-Stokes equations on non-graded quadtree and octree meshes and arbitrary geometries. The viscosity is treated implicitly through a finite volume approach based on Voronoi partitions, while the convective term is discretized with a semi-Lagrangian scheme, thus relaxing the restrictions on the time step. A novel stable implementation of the projection step is introduced, making use of the Marker And Cell layout for the data. The solver is validated numerically in two and three spatial dimensions.


title: Does amplify-and-forward cooperative relay improve OFDM/OFDMA ergodic capacity?

abstract: The ergodic information rate for Orthogonal Frequency-Division Multiplexing / Orthogonal Frequency-Division Multiple Access with amplify-and-forward (AF) relaying systems in the presence of frequency offsets is evaluated. Unlike previous work, per-subcarrier adaptive power allocation is performed on each relay to optimize the system ergodic information rate. For a given frequency offset and total number of relays M, the AF ergodic information rate is proven to be a monotonically increasing function of a (the ratio of the power allocated to the source node and the total transmit power), implying that the maximum ergodic information rate can be obtained at ?=1 (i.e., there is no cooperative relay). Furthermore, the proof of ?cooperative relays cannot improve the AF ergodic information rate in a quasi-static wireless channel? is also provided in this letter.


title: A Stability Indicating HPLC Method to Determine Actual Content and Stability of Nicotine within Electronic Cigarette Liquids

abstract: (1) Background: Despite the growing use of e-cigarettes, in most countries, there is no regulation covering manufacturing standards of the solution ('e-liquid'), leading to concerns over the accuracy of labelling and stability of the products under a range of conditions. Following the United States (US) Food and Drug Administration (FDA) requirements for manufacture of e-liquids, we aimed to develop a simple high-performance liquid chromatography (HPLC) method to determine nicotine content in nicotine-containing e-liquids, even in the presence of degradation products; (2) Methods: We developed an HPLC method to quantify nicotine in the presence of the two major constituents of all e-liquids, glycerine and propylene glycol, and in the presence of degradation products; (3) Results: Our HPLC method performed strongly and was validated it according to international guidelines. For the e-liquids tested, nicotine content levels were all higher than labelled (up to 117.9 ± 1.87% of the labelled content). While nicotine was shown to be unstable at 60 °C, it was stabilized at this temperature in the e-liquid formulations for up to 10 days; and (4) Conclusions: The HPLC method is suitable for adoption by laboratories to determine the actual content and stability of nicotine-containing products. The higher than labelled nicotine levels in e-liquids raises clinical and public health concerns.


title: 3D Compression Made Simple: Edgebreaker on a Corner-Table

abstract: Edgebreaker is a simple technique for compressing 3D triangle meshes. We introduce here a new formulation, which leads to a simple implementation. We describe it in terms of a simple data structure, the Corner Table, which represents the connectivity of any manifold triangle mesh as two table of integers. For meshes that are homeomorphic to a sphere, Edgebreaker encodes these two tables with less than 2 bits per triangle. It compresses vertex locations using a parallelogram predictor. Entropy encoding reduces this cost in practice to less than a bit per triangle when the mesh is large. The detailed source code for the compression and the decompression algorithms fits on a single page. Through minor modifications, the Edgebreaker algorithm has been adapted to manifold meshes with holes and handles, to nontriangle meshes, and to non-manifold meshes. A Corner-Table implementation of these extensions will be described elsewhere.


title: Towards Cloud Based Smart Cities Data Security and Privacy Management

abstract: Smart cities accumulate and process large amount of data streams which raise security and privacy concerns at individual and community levels. Sizeable attempts have made to ensure security and privacy of inhabitants' data. However, security and privacy issues of smart cities are not confined to inhabitants only, service provider and local government have their own reservations -- service provider trust, reliability of the sensed data, and data ownership, to name a few. In this research work we identified a comprehensive list of stakeholders and model their involvement in smart cities by using Onion Model approach. Based on the stakeholder model we presented a security and privacy framework for secure and privacy-aware service provisioning in smart cities. Our framework aims to provide end-to-end security and privacy features for trustable data acquisition, transmission, processing and legitimate service provisioning. As a proof of concept we tested core functionalities of authentication protocol for data acquisition and service provisioning using Scyther automated verification tool that demonstrated that the proposed framework mitigates security and privacy concerns of different stakeholders identified in the stakeholder model.


title: Wireless Power Transfer Using Oscillating Magnets

abstract: The advancement of portable and implantable electronic devices has driven active research into wireless power transfer (WPT) methods. Current commercial WPT techniques using coil coupling have limitations, such as range, frequency, safety, line of sight, orientation, and concurrency. This paper presents a system utilizing oscillating magnets to extract power from a low-level ac magnetic field. This system enables the simultaneous powering of multiple low-power devices in an environment that meets human safety requirements. Compared with conventional WPT techniques, such as RF or acoustic power transfer, the proposed system transfers stable power to electronic nodes placed anywhere within the magnetic field under low driving frequency. Theoretical power calculations and experimental demonstrations are presented to prove the concepts and quantify performance. A custom three-dimensional printed millimeter-size oscillator loaded with two 8 ${\text{mm}^{3}}$ cubic permanent magnets is employed as the energy receiver to experimentally validate the proposed system. Measurements show that the raw ac electrical power and rectified dc power received by the oscillator achieve 269 and 135 ${\mu {\text{W}}}$ , respectively, under 400 ${\mu{\text{T}}}$ excitation magnetic field amplitude at 355 ${\text{Hz}}$ .


OF HEALTH AND HUMAN SERVICES Food and Drug Administration


Nanoscale Structural and Mechanical Characterization of MWCNT-Reinforced Polymer Composites


title: Why Interventions to Influence Adolescent Behavior Often Fail but Could Succeed

abstract: We provide a developmental perspective on two related issues: (a) why traditional preventative school-based interventions work reasonably well for children but less so for middle adolescents and (b) why some alternative approaches to interventions show promise for middle adolescents. We propose the hypothesis that traditional interventions fail when they do not align with adolescents’ enhanced desire to feel respected and be accorded status; however, interventions that do align with this desire can motivate internalized, positive behavior change. We review examples of promising interventions that (a) directly harness the desire for status and respect, (b) provide adolescents with more respectful treatment from adults, or (c) lessen the negative influence of threats to status and respect. These examples are in the domains of unhealthy snacking, middle school discipline, and high school aggression. Discussion centers on implications for basic developmental science and for improvements to youth policy and pr...


title: Optimal Harvesting Effort for Nonlinear Predictive Control Model for a Single Species Fishery

abstract: We use nonlinear model predictive ::: control to find the optimal harvesting effort of a renewable resource system ::: with a nonlinear state equation that maximizes a nonlinear profit function. ::: A solution approach is proposed ::: and discussed and satisfactory numerical illustrations are provided.


title: Service quality perceptions and patient satisfaction: a study of hospitals in a developing country.

abstract: Patients'perceptions about health services seem to have been largely ignored by health care providers in developing countries. That such perceptions, especially about service quality, might shape confidence and subsequent behaviors with regard to choice and usage of the available health care facilities is reflected in the fact that many patients avoid the system or avail it only as a measure of last resort. Those who can afford it seek help in other countries, while preventive care or early detection simply falls by the wayside. Patients'voice must begin to play a greater role in the design of health care service delivery processes in the developing countries. This study is, therefore, patient-centered and identifies the service quality factors that are important to patients; it also examines their links to patient satisfaction in the context of Bangladesh. A field survey was conducted. Evaluations were obtained from patients on several dimensions of perceived service quality including responsiveness, assurance, communication, discipline, and baksheesh. Using factor analysis and multiple regression, significant associations were found between the five dimensions and patient satisfaction. Implications and future research issues are discussed.


Phrase Representations for Multiword Expressions


title: Measuring Relations Between Concepts In Conceptual Spaces

abstract: The highly influential framework of conceptual spaces provides a geometric way of representing knowledge. Instances are represented by points in a high-dimensional space and concepts are represented by regions in this space. Our recent mathematical formalization of this framework is capable of representing correlations between different domains in a geometric way. In this paper, we extend our formalization by providing quantitative mathematical definitions for the notions of concept size, subsethood, implication, similarity, and betweenness. This considerably increases the representational power of our formalization by introducing measurable ways of describing relations between concepts.


title: Safe Exploration of State and Action Spaces in Reinforcement Learning

abstract: In this paper, we consider the important problem of safe exploration in reinforcement learning. While reinforcement learning is well-suited to domains with complex transition dynamics and high-dimensional state-action spaces, an additional challenge is posed by the need for safe and efficient exploration. Traditional exploration techniques are not particularly useful for solving dangerous tasks, where the trial and error process may lead to the selection of actions whose execution in some states may result in damage to the learning system (or any other system). Consequently, when an agent begins an interaction with a dangerous and high-dimensional state-action space, an important question arises; namely, that of how to avoid (or at least minimize) damage caused by the exploration of the state-action space. We introduce the PI-SRL algorithm which safely improves suboptimal albeit robust behaviors for continuous state and action control tasks and which efficiently learns from the experience gained from the environment. We evaluate the proposed method in four complex tasks: automatic car parking, pole-balancing, helicopter hovering, and business management.


title: Cyber-Atvs: Dynamic And Distributed Reconnaissance And Surveilllance Using All Terrain Ugvs

abstract: This paper describes our current effort to develop robotic vehicles for tactical distributed surveillance. Our research is focused on multi-agent collaboration, reconfigurable systems, efficient perception and sensor fusion, distributed command and control, and task decomposition. In particular, this paper describes the main features and capabilities of our All Terrain Vehicles (ATVs), concentrating on their autonomous navigation capabilities.


title: Automatic Production of an Ontology with NLP: Comparison between a Prolog Based Approach and a Cloud Approach Based on Bluemix Watson Service

abstract: Nowadays, most of the information available on the web is in Natural Language. Extracting such knowledge from Natural Language text is an essential work and a very remarkable research topic in the Semantic Web field. The logic programming language Prolog, based on the definite-clause formalism, is a useful tool for implementing a Natural Language Processing (NLP) systems. However, web-based services for NLP have also been developed recently, and they represent an important alternative to be considered. In this paper we present the comparison between two different approaches in NLP, for the automatic creation of an OWL ontology supporting the semantic annotation of text. The first one is a pure Prolog approach, based on grammar and logic analysis rules. The second one is based on Watson Relationship Extraction service of IBM Cloud platform Bluemix. We evaluate the two approaches in terms of performance, the quality of NLP result, OWL completeness and richness.


title: Monalytics: online monitoring and analytics for managing large scale data centers

abstract: To effectively manage large-scale data centers and utility clouds, operators must understand current system and application behaviors. This requires continuous monitoring along with online analysis of the data captured by the monitoring system. As a result, there is a need to move to systems in which both tasks can be performed in an integrated fashion, thereby better able to drive online system management. Coining the term 'monalytics' to refer to the combined monitoring and analysis systems used for managing large-scale data center systems, this paper articulates principles for monalytics systems, describes software approaches for implementing them, and provides experimental evaluations justifying principles and implementation approach. Specific technical contributions include consideration of scalability across both 'space' and 'time', the ability to dynamically deploy and adjust monalytics functionality at multiple levels of abstraction in target systems, and the capability to operate across the range of application to hypervisor layers present in large-scale data center or cloud computing systems. Our monalytics implementation targets virtualized systems and cloud infrastructures, via the integration of its functionality into the Xen hypervisor.


title: doi:10.1155/2008/783898 Research Article Fabric Defect Detection Using Modified Local Binary Patterns

abstract: Local binary patterns (LBPs) are one of the features which have been used for texture classification. In this paper, a method based on using these features is proposed for fabric defect detection. In the training stage, at first step, LBP operator is applied to an image of defect free fabric, pixel by pixel, and the reference feature vector is computed. Then this image is divided into windows and LBP operator is applied to each of these windows. Based on comparison with the reference feature vector, a suitable threshold for defect free windows is found. In the detection stage, a test image is divided into windows and using the threshold, defective windows can be detected. The proposed method is multiresolution and gray scale invariant and can be used for defect detection in patterned and unpatterned fabrics. Because of its simplicity, online implementation is possible as well.


title: Variational circular treemaps for interactive visualization of hierarchical data

abstract: Visualization of hierarchical data is of great importance in information visualization. We present variational circular treemaps with a novel layout algorithm by solving disk packing as a continuous optimization problem. Our variational circular treemaps achieve higher space utilization ratio compared with the traditional circular treemaps and support natural interactions as focus+context distortions and drill-down and roll-up operations for data navigation. Experimental results show the effectiveness of our method for visualization and interaction.


Improving Generalization for Abstract Reasoning Tasks Using Disentangled Feature Representations


title: SIFT-MS a novel tool for monitoring and evaluating a biofilter performance

abstract: Abstract Biofilters are suitable to treat industrial emissions polluted with volatile organic compounds. This study investigates the selected ion flow tube mass spectrometer (SIFT-MS) as a new and fast analysis apparatus to determine the performance, the biokinetic parameters and the external porosity of a biofilter. The SIFT-MS was also used to obtain more information about mass transfer resistance and reaction limitation which can occur in bioreactors. Online analyses were performed on a biofilter packed with a mixture of compost and wooden dowels, treating an air stream contaminated with dimethyl sulphide (DMS), hexane and toluene. Measurements to determine the biokinetic parameters were performed in less than three days to keep the biomass about constant. The Michaelis–Menten half saturation constant, Km, and the maximal volumetric elimination rate, r m , were calculated for the removal of DMS based on measurements at 35, 60 and 90 s empty bed residence time (EBRT). Using pulse injections, the external porosity of the biofilter, 40.2 ± 0.3% could be determined online and information about mass transfer resistance and reaction limitation could be retrieved. Mass transfer resistance becomes significant for compounds with a high Henry coefficient at lower gas velocities.


title: Fast and accurate switching transient calculations on transmission lines with ground return using recursive convolutions

abstract: The paper presents a new approach to the calculation of transients on transmission lines with frequency-dependent parameters. Its purpose is to obtain significant computer-time savings by avoiding convolutions. This is achieved by approximating all line and ground distortions and also time variable characteristic admittances by exponential functions, i.e. solutions of linear differential equations. The method produces a simple Norton-type line equivalent which permits its incorporation into an existing system representation like the B.P.A. program for the calculation of transients. The program has been tested on systems of different degrees of complexity and proved to be superior, in terms of speed and accuracy, to other advanced methods.


title: An Efficient Brain Tumor Detection Algorithm Using Watershed & Thresholding Based Segmentation

abstract: During past few years, brain tumor segmentation in magnetic resonance imaging (MRI) has become an emergent research area in the field of medical imaging system. Brain tumor detection helps in finding the exact size and location of tumor. An efficient algorithm is proposed in this paper for tumor detection based on segmentation and morphological operators. Firstly quality of scanned image is enhanced and then morphological operators are applied to detect the tumor in the scanned image.


title: Patient specific ankle-foot orthoses using rapid prototyping

abstract: BackgroundPrefabricated orthotic devices are currently designed to fit a range of patients and therefore they do not provide individualized comfort and function. Custom-fit orthoses are superior to prefabricated orthotic devices from both of the above-mentioned standpoints. However, creating a custom-fit orthosis is a laborious and time-intensive manual process performed by skilled orthotists. Besides, adjustments made to both prefabricated and custom-fit orthoses are carried out in a qualitative manner. So both comfort and function can potentially suffer considerably. A computerized technique for fabricating patient-specific orthotic devices has the potential to provide excellent comfort and allow for changes in the standard design to meet the specific needs of each patient.MethodsIn this paper, 3D laser scanning is combined with rapid prototyping to create patient-specific orthoses. A novel process was engineered to utilize patient-specific surface data of the patient anatomy as a digital input, manipulate the surface data to an optimal form using Computer Aided Design (CAD) software, and then download the digital output from the CAD software to a rapid prototyping machine for fabrication.ResultsTwo AFOs were rapidly prototyped to demonstrate the proposed process. Gait analysis data of a subject wearing the AFOs indicated that the rapid prototyped AFOs performed comparably to the prefabricated polypropylene design.ConclusionsThe rapidly prototyped orthoses fabricated in this study provided good fit of the subject's anatomy compared to a prefabricated AFO while delivering comparable function (i.e. mechanical effect on the biomechanics of gait). The rapid fabrication capability is of interest because it has potential for decreasing fabrication time and cost especially when a replacement of the orthosis is required.


title: Three-Port DC–DC Converter for Stand-Alone Photovoltaic Systems

abstract: System efficiency and cost effectiveness are of critical importance for photovoltaic (PV) systems. This paper addresses the two issues by developing a novel three-port dc–dc converter for stand-alone PV systems, based on an improved Flyback-Forward topology. It provides a compact single-unit solution with a combined feature of optimized maximum power point tracking (MPPT), high step-up ratio, galvanic isolation, and multiple operating modes for domestic and aerospace applications. A theoretical analysis is conducted to analyze the operating modes followed by simulation and experimental work. This paper is focused on a comprehensive modulation strategy utilizing both PWM and phase-shifted control that satisfies the requirement of PV power systems to achieve MPPT and output voltage regulation. A 250-W converter was designed and prototyped to provide experimental verification in term of system integration and high conversion efficiency.


title: Android and iOS users' differences concerning security and privacy

abstract: We compare Android and iOS users according to their demographic differences, security and privacy awareness, and reported behavior when installing apps. We present an exploratory study based on an online survey with more than 700 German students and describe directions for further research.


Differential Privacy: A Primer for a Non-Technical Audience


title: Making B+- trees cache conscious in main memory

abstract: Previous research has shown that cache behavior is important for main memory index structures. Cache conscious index structures such as Cache Sensitive Search Trees (CSS-Trees) perform lookups much faster than binary search and T-Trees. However, CSS-Trees are designed for decision support workloads with relatively static data. Although B+-Trees are more cache conscious than binary search and T-Trees, their utilization of a cache line is low since half of the space is used to store child pointers. Nevertheless, for applications that require incremental updates, traditional B+-Trees perform well. ::: Our goal is to make B+-Trees as cache conscious as CSS-Trees without increasing their update cost too much. We propose a new indexing technique called “Cache Sensitive B+-Trees” (CSB+-Trees). It is a variant of B+-Trees that stores all the child nodes of any given node contiguously, and keeps only the address of the first child in each node. The rest of the children can be found by adding an offset to that address. Since only one child pointer is stored explicitly, the utilization of a cache line is high. CSB+-Trees support incremental updates in a way similar to B+-Trees. ::: We also introduce two variants of CSB+-Trees. Segmented CSB+-Trees divide the child nodes into segments. Nodes within the same segment are stored contiguously and only pointers to the beginning of each segment are stored explicitly in each node. Segmented CSB+-Trees can reduce the copying cost when there is a split since only one segment needs to be moved. Full CSB+-Trees preallocate space for the full node group and thus reduce the split cost. Our performance studies show that CSB+-Trees are useful for a wide range of applications.


title: High-Frequency Model of the Rogowski Coil With a Small Number of Turns

abstract: In this paper, the Rogowski coil is modeled as a distributed-element transmission line. The elements in the distributed transmission line are modeled using physically based equations. It allows self and transfer impedances of the Rogowski coil to be modeled using the physical dimensions and the material properties of the coil. The models of the impedances were verified by measurements in the frequency domain on three Rogowski coils. The coils mounted on the power cable were modeled and simulated in the time domain and afterward compared with the measurements.


title: Determinants of Foreign Direct Investment Inflows to Africa, 1980-2007

abstract: The central concern of this paper is to respond to the question: what determines FDI inflows to Africa? An understanding of such factors will assist African policymakers to formulate and execute policies for attracting FDI. Our estimation results from a panel of seven five-year nonoverlapping windows for the period 19802007 indicate that: (i) there is a positive relationship between market size and FDI inflows; (ii) openness to trade has a positive impact on FDI flows; (iii) higher financial development has negative effect on FDI inflows; (iv) high government consumption expenditure attracts FDI inflows to Africa; (v) higher FDI goes where international remittances also goes in Africa; (vi) agglomeration has a strong positive impact on FDI inflows to Africa; (vii) natural resource endowment and exploitation (especially for oil) attracts huge FDI into Africa; (viii) East and Southern African sub-regions appear positively disposed to obtain higher levels of inward FDI. The key policy implications are discussed.


title: Effectiveness of Teaching with Movies to Promote Positive Characteristics and Behaviors

abstract: Abstract The purpose of this study was to determine whether a systematic movie-based teaching course can promote positive characteristics and behaviors of Thai students. The sample of this study was 156 undergraduate students of a public university in northern Thailand. The research was conducted in two semester of the 2014 academic year. The experimental groups consisted of 41 and 44 students in the first and second semester, and the control group consisted of 35 and 36 students. Both experimental groups enrolled the “teaching-with-movie” class for credits, and viewed 11 movies during the semester. In addition, both experimental groups participated in a 30-minute discussion after viewing each movie. For the control groups, participants enrolled in social psychology course and received no intervention. Through a pretest, posttest control group quasi-experimental design, the two experimental groups showed a significant increase in positive characteristics and behaviors, while the control group showed no significant increase. In addition, results of the analysis of covariance showed that a systematic movie-based teaching course positively developed positive characteristics and behaviors, as the group variable predicted positive characteristics and behaviors at posttest while controlling for pretest scores. Overall, the results of this study provide support that positive characteristics and behaviors can be enhanced through a systematic movie-based teaching course.


title: Unsupervised approach for object matching using Speeded Up Robust Features

abstract: Autonomous object counting system is of great use in retail stores, industries and also in research processes. In this paper, a Speeded Up Robust Feature (SURF) based robust algorithm for identifying, counting and locating all instances of a defined object in any image, has been proposed. The defined object is referred to as prototype and the image in which one wishes to count the prototype is referred to as scene image. The algorithm starts by detecting the interest points for SURF in both, prototype and scene images. The SURF points on prototype are first clustered using density based clustering; then SURF points in each cluster are matched with those in scene image. The SURF points in scene image that have been matched w.r.t. a single cluster, are clustered using the same clustering algorithm. Each cluster formed in scene image represents an instance of prototype object in the image. Homography transforms are further used to give exact location and span of each prototype object in the scene image. Once the span of each prototype is defined, SURF points within this span are matched with the prototype image and then Homography transform is once again applied while considering the newly matched SURF points; thus eliminating noisy detection/s of prototype. While the same process is repeated with each cluster, a novel centroid based algorithm for merging repeated detections of same prototype instance is used. Carrying the benefits of SURF and Homography transforms, the algorithm is capable of detecting all prototype instances present in scene image, irrespective of their scale and orientation. The complete algorithm has also been integrated into a desktop application, which uses camera feed to report the real time count of the prototype in the scene image.


title: Subacute toxicity of the water-soluble fractions of Kuwait crude oil and partially combusted crude oil on Menidia beryllina and Palaemonetes pugio.

abstract: As a consequence of the 1991 Gulf War, a substantial amount of crude oil (CO) and partially combusted crude oil (PCO) were emitted into the environment. Therefore, the study objective was to evaluate the toxicity of the water soluble fraction (WSF) of CO and PCO on a fish, Menidia beryllina, and an invertebrate, Palaemonetes pugio, in 16-d flow-through tests. Specific growth rate (SGR) was studied as a function of total petroleum hydrocarbon (TPHC) concentration in water. Reductions in SGR were observed in fish exposed to PCO and CO WSFs, with TPHC water concentration being 10-fold higher in CO exposures (67-145 microg/L) than in PCO exposures (4-12 microg/L). Significant negative correlations were observed between TPHC concentration and fish SGR in both CO (r2=0.730) and PCO (r2=0.867) exposures, with the slope being significantly lower for PCO exposures (-0.169) than CO exposures (-0.009). Differences between CO and PCO toxicity were not as clear in shrimp exposures due to slow growth rates and variability in TPHC concentrations. Qualitative PAH analysis indicated that naphthalene was present in the CO WSF whereas chrysene and benzo(a)pyrene were present in the PCO WSF. Heavy metal analysis of concentrated stock solutions indicated that the PCO WSF had substantially higher concentrations of some metals (Sr=2,521 microg/L, B=556 microg/L, and Ba=130 microg/L) than the CO WSF in which concentrations were less than 55 microg/L. Fish and shrimp tissue analysis did not reveal any uptake of parent PAH compounds from the water, which may be attributed to the formation of PAH metabolites.


title: Algorithmic Transparency in the News Media

abstract: The growing use of difficult-to-parse algorithmic systems in the production of news, from algorithmic curation to automated writing and news bots, problematizes the normative turn toward transparency as a key tenet of journalism ethics. Pragmatic guidelines that facilitate algorithmic transparency are needed. This research presents a focus group study that engaged 50 participants across the news media and academia to discuss case studies of algorithms in news production and elucidate factors that are amenable to disclosure. Results indicate numerous opportunities to disclose information about an algorithmic system across layers such as the data, model, inference, and interface. Findings underscore the deeply entwined roles of human actors in such systems as well as challenges to adoption of algorithmic transparency including the dearth of incentives for organizations and the concern for overwhelming end-users with a surfeit of transparency information.