nils-herrmann/clean_scirepeval huggingface dataset:
Development of the Multidimensional Readiness and Enablement Index for Health Technology (READHY) Tool to Measure Individuals' Health Technology Readiness: Initial Testing in a Cancer Rehabilitation Setting
Venue: Journal of medical Internet research
Year: 2019

The increasing digitization of health care services with enhanced access to fast internet connections, along with wide use of smartphones, offers the opportunity to get health advice or treatment remotely. For service providers, it is important to consider how consumers can take full advantage of available services and how this can create an enabling environment. However, it is important to consider the digital context and the attributes of current and future users, such as their readiness (ie, knowledge, skills, and attitudes, including trust and motivation)  The objective of this study was to evaluate how the eHealth Literacy Questionnaire (eHLQ) combined with selected dimensions from the Health Education Impact Questionnaire (heiQ) and the Health Literacy Questionnaire (HLQ) can be used together as an instrument to characterize an individual's level of health technology readiness and explore how the generated data can be used to create health technology readiness profiles of potential users of health technologies and digital health services.  We administered the instrument and sociodemographic questions to a population of 305 patients with a recent cancer diagnosis referred to rehabilitation in a setting that plans to introduce various technologies to assist the individuals. We evaluated properties of the Readiness and Enablement Index for Health Technology (READHY) instrument using confirmatory factor analysis, convergent and discriminant validity analysis, and exploratory factor analysis. To identify different health technology readiness profiles in the population, we further analyzed the data using hierarchical and k means cluster analysis.  The confirmatory factor analysis found a suitable fit for the 13 factors with only 1 cross loading of 1 item between 2 dimensions. The convergent and discriminant validity analysis revealed many factor correlations, suggesting that, in this population, a more parsimonious model might be achieved. Exploratory factor analysis pointed to 5 to 6 constructs based on aggregates of the existing dimensions. The results were not satisfactory, so we performed an 8 factor confirmatory factor analysis, resulting in a good fit with only 1 item cross loading between 2 dimensions. Cluster analysis showed that data from the READHY instrument can be clustered to create meaningful health technology readiness profiles of users.  The 13 dimensions from heiQ, HLQ, and eHLQ can be used in combination to describe a user's health technology readiness level and degree of enablement. Further studies in other populations are needed to understand whether the associations between dimensions are consistent and the number of dimensions can be reduced.
Stock markets' reaction to Covid 19: Moderating role of national culture
Venue: Finance Research Letters
Year: 2021

Recent literature reports stock markets around the world reacted to the Covid 19 pandemic with negative returns. However, this reaction was not uniform across countries. In this paper, we postulate that the national level uncertainty avoidance, which determines how sensitive members of a nation are to uncertainty, moderates the stock markets' reaction to the pandemic. Using daily data of Covid 19 confirmed cases and stock market returns from 43 countries, we find robust evidence that the decline in stock market returns in response to one percent increase in growth in confirmed cases is stronger for the countries with higher national level uncertainty aversion.
"They arrested me for loving a schoolgirl" ethnography, HIV, and a feminist assessment of the age of consent law as a gender based structural intervention in Uganda.
Venue: Social science medicine
Year: 2012

In 1990 women's rights activists in Uganda successfully lobbied to amend the Defilement Law, raising the age of sexual consent for adolescent females from fourteen to eighteen years old and increasing the maximum sentence to death by hanging. The amendment can be considered a macro level intervention designed to address the social and health inequalities affecting young women and girls, particularly their disproportionately high rate of HIV as compared to their male counterparts. While the intention of the law and aggressive campaign was to prosecute "sugar daddies" and "pedophiles," the average age of men charged with defilement was twenty one years old and many were believe to be "boyfriends" in consensual sexual liaisons with the alleged victims. This article uses court records, case studies, and longitudinal ethnographic data gathered in east central Uganda to examine the impact of the age of consent law at national and local levels, and specifically what the disjunctures between national intentions and local uses reveal about conflicting views about sexual privilege and rights. I argue that existing class, gender, and age hierarchies have shaped how the Defilement Law has been applied locally, such that despite the stated aim of "protecting" young women, the law reinstates patriarchal privilege (especially against men of lower social class) while simultaneously increasing the regulation of adolescent female sexuality and undermining their autonomy. This paper demonstrates how ethnography and critical gender theory which emphasizes the intersectionality of gender, age, and class in the (re)production of inequalities can be used to examine consequences of macro level interventions in ways that may be undetected in conventional public health evaluation techniques but that are crucial for designing and modifying effective interventions.
3 Degrees of Freedom Cabel Control Robot for Upper Limbs Rehabilitation
Year: 2013

To design upper limbs rehabilitation training system. The system consisted of 3 dimension of freedom robotic arm,cable transmission component and central drive and control component.The central drive and control system were posed at the base and the movements were transmitted from the base to the upper 3 DOF robotic arm by the cable transmission component.3 dimensional model of the device were developed and the kinematic was simulated in SolidWorks.The first prototype was made and tested. The device could execute the designing training steps exactly and meet the design requirements.The system could recognize the intent of users exactly and response well when the auto movement trigger angle was more than 3.6deg.
Autonomous Cognitive GPR Based on Edge Computing and Reinforcement Learning
Venue: 2019 IEEE International Conference on Industrial Internet (ICII)
Year: 2019

Autonomous cognitive ground penetrating radar (ACGPR) carried by drones or other robotic platforms, may perform robust and accurate subsurface object detection and recognition in varying environments based on real time data processing and decision making. However, limited system computing resources and intelligence generating capability pose significant challenges for the operations of such systems. To address these challenges, in this paper we propose an ACGPR enabled by edge computing (EC) and reinforcement learning. Specifically, an edge computing based system architecture is presented to utilize edge resources for real time intelligence generation. A reinforcement learning approach is developed as the decision making model for the ACGPR to adaptively adjust its operational parameters. Simulation results show the accuracy and efficacy of the proposed ACGPR system. The framework also provides insight into the design of autonomous cognitive industrial Internet of things (IoT) supported by edge computing and machine learning.
Automatic classification of complaint letters according to service provider categories
Venue: Inf. Process. Manag.
Year: 2019

In the technological age, the phenomenon of complaint letters published on the Internet is increasing. Therefore, it is important to automatically classify complaint letters according to various criteria, such as company categories. In this research, we investigated the automatic text classification of complaint letters written in Hebrew that were sent to various companies from a wide variety of categories. The classification was performed according to company categories such as insurance, cellular communication, and rental cars. We conducted an extensive set of classification experiments of complaint letters to seven/six/five/four company categories. The classification experiments were performed using various sets of word unigrams, four machine learning methods, two feature filtering methods, and parameter tuning. The classification results are relatively high for all six measures: accuracy, precision, recall, F1, PRC area, and ROC area. The best accuracy results for seven, six, five, and four categories are 84.5% 88.4% 91.4% and 93.8% respectively. An analysis of the most frequently occurring words in the complaints about almost all categories revealed that the most significant issues were related to poor service and delayed delivery. An interesting result shows that only in the domain of hospitals was the subject of the domain itself (i.e. the patient, the medical treatment, the place of the treatment, and the medical staff) the most important issue. Another interesting finding is that the issue of "price" was of little or no importance to the complainants. These findings suggest that in their preoccupation with their bottom line of profitability, many service providers are blind to how paramount good service and timely delivery (and, in the case of hospitals, the domain itself) are to their clientele.
Comparison of the contact angle of water on set elastomeric impression materials.
Venue: Journal
Year: 2018

The hydrophilicity of some elastomeric impression materials has not been fully established. The purpose of this study was to measure and compare the advancing contact angle of water on the surface of several set elastomeric impression materials.  We tested various consistencies of vinyl polysiloxane (VPS; Imprint 4) and vinyl polyether silicone (VPES; EXA'lence) with a polyether (PE; Impregum Soft) control. Impression discs (25.07 mm) were made using a metal die and ring. Deionized ultra filtered water was placed on each disc and contact angle measurements were made at 0, 15, 30, 45 and 60 s using a video contact angle drop shape analysis machine. The data were analyzed using repeated ANOVA and a post hoc test with Bonferroni correction.  VPS contact angles reached a mean of 10.1deg 0.2deg at 60 s vs. 40.7deg 0.1deg for VPES. Overall, VPS contact angles were smaller than those for VPES at all measured times. However, heavy and super quick heavy VPS had much higher contact angles at 0 s compared with other VPS consistencies. There was a significant difference in contact angles between VPS and VPES (mean difference 33.9deg, p 0.05) and between VPS and PE (mean difference 32.8deg, p 0.05) but not between VPES and PE (P 0.196) VPS heavy and super quick heavy were significantly different from other VPS materials (p 0.05) but not from each other (p 1.00) CONCLUSIONS Set VPS is more hydrophilic than VPES. Contact angle values of VPS indicated super hydrophilicity. VPES was hydrophilic, with measurements similar to the PE control. Thus, VPS impression materials may be excellent in terms of spreading and copying wet surfaces.
Subjective Quality Estimation Using PESQ For Hands Free Terminals
Venue: ICASSP 2020 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2020

Previous reports have mentioned the possibility that subjective quality of the echo suppressed speech signal can be estimated based on perceptual evaluation of speech quality (PESQ) but there are few experimental results. We propose third party listening and conversational test procedures to assess whether PESQ can be used for predicting the subjective quality of an acoustic echo canceler. In the proposed third party listening test procedure, near end and far end signals are presented separately in the left and right channels of stereo playback and differential category rating evaluation is applied to those stimuli for obtaining differential mean opinion scores. In the proposed conversational test procedure, impaired and non impaired reference signals are recorded during a conversation to make PESQ processing possible. Experimental results indicate that there is a strong correlation between PESQ and subjective scores.
Characterization of Virulence and Persistence Abilities of Listeria monocytogenes Strains Isolated from Food Processing Premises.
Venue: Journal of food protection
Year: 2019

We report the characterization of 15 Listeria monocytogenes strains isolated from various food processing plants by multivirulence locus sequence typing to determine virulence types (VTs) and epidemic clones. Molecular mechanisms involved in adaptation to food processing environments and related to virulence were also studied. Phenotypic behaviors associated with various antimicrobials, biofilm formations, and invasiveness were assessed. There were 11 VTs among the 15 L. monocytogenes strains. Strains belonging to six VTs were stress survival islet 1 (SSI 1) and one strain of VT94 was SSI 2. Tn6188 was found in VT6 and VT94 strains, and bcrABC cassette genes were identified in VT21, VT60, and VT63 strains. Only one strain, in VT20, showed llxS, whereas a full size inlA was detected in strains belonging to VT8, VT20, VT21, and VT63. VT10, VT20, VT21, VT60, and VT63 strains were the most tolerant to studied disinfectants. A VT6 strain showed the strongest biofilm formation ability in polyvinyl chloride, and strains belonging to VT10, VT11, VT20, and VT94 had moderate abilities. Antimicrobial sensitivity tests showed that all the L. monocytogenes strains were multidrug resistant. F tests revealed that only strains of VT10, VT60, and VT94 were significantly noninvasive (P 0.05) in Caco 2 cells. Our findings illustrate how L. monocytogenes isolates exploit diverse mechanisms to adapt to adverse conditions. Consequently, detailed characterization of L. monocytogenes isolates is required for comprehensive elimination of this pathogenic bacterium in food processing environments.
Probabilistic asr feature extraction applying context sensitive connectionist temporal classification networks
Venue: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing
Year: 2013

This paper proposes a novel automatic speech recognition (ASR) front end that unites the principles of bidirectional Long Short Term Memory (BLSTM) Connectionist Temporal Classification (CTC) and Bottleneck (BN) feature generation. BLSTM networks are known to produce better probabilistic ASR features than conventional multilayer perceptrons since they are able to exploit a self learned amount of temporal context for phoneme estimation. Combining BLSTM networks with a CTC output layer implies the advantage that the network can be trained on unsegmented data so that the quality of phoneme prediction does not rely on potentially error prone forced alignment segmentations of the training set. In challenging ASR scenarios involving highly spontaneous, disfluent, and noisy speech, our BN CTC front end leads to remarkable word accuracy improvements and prevails over a series of previously introduced BLSTM based ASR systems.
Fungsi Pengawasan DPRD Riau: (Dilema Kepentingan Partai Politik dan Kepentingan Publik)
Venue: MOMENTUM Jurnal Sosial dan Keagamaan
Year: 2019

The supervision function of Riau DPRD becomes stronger since otonomy has been ratified. Unhappily, the strength his of tenre directed to infiltrate the political party interest. In the after mach, the role of DPRD is n'tinan optimal fashion because it'strapped in transactiona lpolitics, which bets political party interst with public interest. Researcher, by using descriptive analysis method, describes and analyzes the problem to look for the solution. As aresult, the supervision function of Riau DPRD on public interestis in poor support by asystem that be in dsover the legislators. Besides that, as the initiators of public policy, the legislators of tenignore the public interest, and will helda brieffor public if the rearedemons trant agitations and mass media issues tha tblow up the irwrong policies.
Numpywren: Serverless Linear Algebra
Venue: ArXiv
Year: 2018

Linear algebra operations are widely used in scientific computing and machine learning applications. However, it is challenging for scientists and data analysts to run linear algebra at scales beyond a single machine. Traditional approaches either require access to supercomputing clusters, or impose configuration and cluster management challenges. In this paper we show how the disaggregation of storage and compute resources in so called "serverless" environments, combined with compute intensive workload characteristics, can be exploited to achieve elastic scalability and ease of management. We present numpywren, a system for linear algebra built on a serverless architecture. We also introduce LAmbdaPACK, a domain specific language designed to implement highly parallel linear algebra algorithms in a serverless setting. We show that, for certain linear algebra algorithms such as matrix multiply, singular value decomposition, and Cholesky decomposition, numpywren's performance (completion time) is within 33% of ScaLAPACK, and its compute efficiency (total CPU hours) is up to 240% better due to elasticity, while providing an easier to use interface and better fault tolerance. At the same time, we show that the inability of serverless runtimes to exploit locality across the cores in a machine fundamentally limits their network efficiency, which limits performance on other algorithms such as QR factorization. This highlights how cloud providers could better support these types of computations through small changes in their infrastructure.
Towards a conceptual framework for provider information behaviour
Venue: J. Documentation
Year: 2013

The purpose of this paper is to provide a critical discussion of the paucity of research on information behaviour of information providers and to propose a framework for investigating the emerging area of provider information behaviour. The approach takes the form of a conceptual analysis and literature review. A multidisciplinary framework is provided to form the basis of further exploration of provider information behaviour. There are various types of information providers and they provide opportunities for exploring and comparing their range of information activities and developing models of provider information behaviour. The paper argues for a new perspective to the study of information behaviour. The paucity of research on internal users of information has not matched those on external users of information over the years. An exploration of provider information behaviour together with its internal i.
Design of inclined coupling slot loaded CPW fed circularly polarized slot antenna for wireless applications
Year: 2018

A new structure for wideband circularly polarized (CP) slot antenna is proposed in this article. The designed antenna consists of a circular patch with two rectangular slots, which are parallel to CPW feed line, excites two resonance modes for wideband performance. To achieve CP operation, an inclined coupling slot loaded feed line on the ground is used. Furthermore, the proposed antenna is an enhanced version of earlier wideband CP antennas having a compact structure with a low profile of 0.023lo (lo stands for the free space wavelength at 4.46 GHz) and ground size of 30 mm x 30 mm. It operates over the impedance bandwidth of 88.9% (relative to the center frequency of 4.5 GHz) and 3 dB axial ratio bandwidth found for this band is 2.7% (relative to the center frequency of 4.46 GHz) To verify the performance of the designed antenna, the experimental results match well with the simulated results.
Intelligent Financial Fraud Detection Practices: An Investigation
Venue: SecureComm
Year: 2014

Financial fraud is an issue with far reaching consequences in the finance industry, government, corporate sectors, and for ordinary consumers. Increasing dependence on new technologies such as cloud and mobile computing in recent years has compounded the problem. Traditional methods of detection involve extensive use of auditing, where a trained individual manually observes reports or transactions in an attempt to discover fraudulent behaviour. This method is not only time consuming, expensive and inaccurate, but in the age of big data it is also impractical. Not surprisingly, financial institutions have turned to automated processes using statistical and computational methods. This paper presents a comprehensive investigation on financial fraud detection practices using such data mining methods, with a particular focus on computational intelligence based techniques. Classification of the practices based on key aspects such as detection algorithm used, fraud type investigated, and success rate have been covered. Issues and challenges associated with the current practices and potential future direction of research have also been identified.
Telemedicine as the New Outpatient Clinic Gone Digital: Position Paper From the Pandemic Health System REsilience PROGRAM (REPROGRAM) International Consortium (Part 2)
Venue: Frontiers in Public Health
Year: 2020

Technology has acted as a great enabler of patient continuity through remote consultation, ongoing monitoring, and patient education using telephone and videoconferencing in the coronavirus disease 2019 (COVID 19) era. The devastating impact of COVID 19 is bound to prevail beyond its current reign. The vulnerable sections of our community, including the elderly, those from lower socioeconomic backgrounds, those with multiple comorbidities, and immunocompromised patients, endure a relatively higher burden of a pandemic such as COVID 19. The rapid adoption of different technologies across countries, driven by the need to provide continued medical care in the era of social distancing, has catalyzed the penetration of telemedicine. Limiting the exposure of patients, healthcare workers, and systems is critical in controlling the viral spread. Telemedicine offers an opportunity to improve health systems delivery, access, and efficiency. This article critically examines the current telemedicine landscape and challenges in its adoption, toward remote/tele delivery of care, across various medical specialties. The current consortium provides a roadmap and/or framework, along with recommendations, for telemedicine uptake and implementation in clinical practice during and beyond COVID 19.