nils-herrmann/clean_scirepeval huggingface dataset:
A New Decomposition Method for Multiuser DC Programming and Its Applications
Venue: IEEE Transactions on Signal Processing
Year: 2014

We propose a novel decomposition framework for the distributed optimization of Difference Convex (DC) type nonseparable sum utility functions subject to coupling convex constraints. A major contribution of the paper is to develop for the first time a class of (inexact) best response like algorithms with provable convergence, where a suitably convexified version of the original DC program is iteratively solved. The main feature of the proposed successive convex approximation method is its decomposability structure across the users, which leads naturally to distributed algorithms in the primal and/or dual domain. The proposed framework is applicable to a variety of multiuser DC problems in different areas, ranging from signal processing, to communications and networking. As a case study, in the second part of the paper we focus on two examples, namely: i) a novel resource allocation problem in the emerging area of cooperative physical layer security and ii) and the renowned sum rate maximization of MIMO Cognitive Radio networks. Our contribution in this context is to devise a class of easy to implement distributed algorithms with provable convergence to stationary solution of such problems. Numerical results show that the proposed distributed schemes reach performance close to (and sometimes better than) that of centralized methods.
Slow light III V on silicon hybrid modulator
Venue: 2016 Photonics North (PN)
Year: 2016

A compact optical modulator based on the hybrid integration of a III V photonic crystal based active region in a silicon on insulator waveguide is proposed and designed. An extinction ratio up to 20 dB is obtained in a 18.75 mm long device. A 3 dB cut off frequency of 15 GHz, and an energy consumption of 19 fJ/bit are estimated by an equivalent small signal electrical circuit, while the optical bandwidth is larger than 10 nm, which is higher than for typical low power consumption silicon modulators.
Biotechnology advances for dealing with environmental pollution by micro(nano)plastics: Lessons on theory and practices
Year: 2018

Plastic pollution has become a global problem and a threat for environmental and human health. The management of plastic pollution has been mainly focused on macroplastics, involving several strategies such as legislation and waste management. Education and awareness are increasingly used for controlling the demand of disposable plastic items, for the increase of the recycling effectiveness and for raising consciousness regarding plastic pollution impacts on the environment. Biotechnology tools, as discussed in this review, are currently under development for the remediation of plastics, and particularly, micro(nano)plastics, and demonstrated to be promising in facilitating degradation and subsidizing research on a new generation of biodegradable plastics.
Beyond Belief: Prayer as Communication in Religious Information Seeking
Year: 2013

Prayer role in information seeking has been largely neglected in LIS research. I propose that respondents understood prayer as communication with God. I compared their descriptions of prayer to God with research on interpersonal communication for information seeking. Prayer, for these respondents, met both cognitive and affective information needs.Le role de la priere dans la recherche d'information est un sujet largement neglige en bibliotheconomie et en science de l'information. L'auteur admet que les repondants percoivent la priere comme un acte de communication avec Dieu. La description des prieres a ensuite ete comparee a la recherche sur les communications interpersonnelles dans une optique de recherche d'information. La priere, pour ces repondants, repondait a la fois a des besoins informationnels cognitifs et affectifs.
Parametrization scheme with accuracy and transferability for tight binding electronic structure calculations with extended Huckel approximation and molecular dynamics simulations
Venue: Journal of Molecular Modeling
Year: 2013

A transferable tight binding parametrization procedure for extended Huckel approximation is proposed, with the charge self consistent scheme, that could be applied to the quantum molecular dynamics (MD) simulation for long time dynamics of large scale systems. In this procedure, either a target molecule is divided into small molecules or another realistic set of small molecules characterizing chemical bonds in the complicated target molecule is adopted. Then, the parameters for these small molecules are adjusted and compared with reference results of energy levels and wave functions by, for example, density functional theory. Upon application to the large target molecule, these parameters are then readjusted directly in the target molecule. An example is demonstrated with MD simulation applied to the ionic liquid molecule N methyl N propylpiperidinium bis trifluoromethanesulfonyl imide (PP13 TFSI) The origin and stability of HOMO LUMO gap are discussed.
Investigating the effectiveness of Moodle based Blended Learning in College English course
Venue: Int. J. Inf. Technol. Manag.
Year: 2014

The present study applies Moodle based Blended Learning to College English teaching and conducts an experimental study of 90 non English majors within one semester in order to explore the effectiveness of Moodle based Blended Learning. Forty five students in the experimental group received the Blended Learning model, while 45 students in the control group received the traditional grammar translation method. The effectiveness is quantitatively assessed by Kirkpatrick's evaluation model from four aspects of reaction, learning, behaviour and skills. SPSS17.0 is used to analyse the collected data. In depth interview is also used to confirm the results of quantitative analysis. The results show that compared with the traditional classroom face to face learning model, the Moodle based Blended Learning can greatly improve the language learners' enthusiasm and initiative, effectively promote the learners' English comprehensive competence and strengthen their cooperative learning and team spirit.
Using Altman Z score and Beneish M score Models to Detect Financial Fraud and Corporate Failure: A Case Study of Enron Corporation
Year: 2017

The objective of this research is to determine whether Altman Z score and Beneish M model could detect financial fraud and corporate failure of Enron Corporation. Five year financial information was collected from the US SEC Edgar database covering the period 1996 to 2000. The Beneish model revealed that the financial statements for the five years studied were manipulated by management. On the basis of the analysis, the researcher argued that stakeholders would be better protected when the two models are used simultaneously than when only the Altman Z score is used. The paper recommended that Altman Z score and Beneish M Model should be used together as an integral part of every audit.
The Effect of Ocular Demodex Colonization on Schirmer test and OSDI Scores in Newly Diagnosed Dry Eye Patients.
Venue: Eye contact lens
Year: 2019

To determine whether ocular Demodex colonization results in differences in Schirmer test scores and Ocular Surface Disease Index (OSDI) questionnaire values in individuals with dry eye disease (DED) diagnosed for the first time.  Eighty eight adults aged 40 to 68 years who were admitted to Ophthalmology outpatient clinic for routine ophthalmological examination or presbyopia examination and diagnosed with DED for the first time and who do not have any chronic disease were included in the study. All the patients were asked to complete the OSDI, which is widely used for assessing dry eye symptom severity and vision related functioning. The Schirmer test was performed, and then two eyelashes were taken from the inferior eyelids of each eyes. After saline (0.09% NaCl) was added to the sample, it was quickly taken to the microbiology laboratory, which is located next to the Ophthalmology policlinic. The sample was evaluated by a parasitologist experienced in Demodex.  One hundred sixty eight eyes of 84 patients were included in the study. Average Schirmer test score was 2.1+ 0.5, the OSDI questionnaire score was 61.82+ 10.95, and the mean age was 55.36+ 8.74 years in patients who had Demodex colonization (n=30) whereas the average Schirmer test score was 6.6+ 0.9 score, OSDI questionnaire score was 40.96+ 12.73, and the mean age was 49.12+ 6.87 years in patients without Demodex colonization (n=58) It has been observed that dry eye patients with Demodex colonization had a higher mean age (P: 0.001) higher mean OSDI score (P: 0.001) and lower average Schirmer test score (P: 0.001) compared with those without Demodex. The significant relationship between lower Schirmer test score and higher OSDI rates and occurrence of Demodex infestation continued after adjusting for mean age values (P=0.012; P=0.035)  It was determined that the presence of ocular Demodex colonization was associated with the average Schirmer test scores, OSDI scores, and age values in patients with newly diagnosed DED. Demodex quantity was found increased in older aged patients, but the significant relationship between lower Schirmer test score and higher OSDI rates and Demodex infestation persisted even after controlling the mean age values. Supporting these findings with large numbered and randomized controlled studies will help in clarifying the association of the Demodex infestation with etiopathogenesis of dry eye.
Job satisfaction, organizational stress and employee performance a study of NAPIMS
Year: 2013

This study focused on examining job satisfaction, organizational stress, and its effect on employee performance. The study attempts to examine the problems of the employer employee relationship, the issue of feedback to the employees about their performances, promotions, conducive working environments, pay commensurate to their work and going on training programmes when necessary. The main aim was to examine the effect of job satisfaction and organizational stress on employees' performance. This study adopted the survey sampling method carried out in the National Petroleum Investment Management Services (NAPIMS) Ikoyi, Lagos State using 225 employees which were randomly selected from total a staff of 511. The findings revealed that there is a relationship between job satisfaction and employee performance; also there was a negative relationship which states that as organizational stress increases employee performance decreases; furthermore from the findings, as organizational stress increases job satisfaction decreases. Based on these findings recommendations were made that organizations should find ways of improving the level of job satisfaction of employees by giving them training, promotion; and also giving the employees' time to relax like going on vacation so as to be refreshed and highly productive.
Image Forgery Detection: Survey and Future Directions
Year: 2019

In this age of digitization, digital images are used as a prominent carrier of visual information. Images are becoming increasingly ubiquitous in everyday life. Unprecedented involvement of digital images can be seen in various paramount fields like medical science, journalism, sports, criminal investigation, image forensic, etc. where authenticity of image is of vital importance. Various tools are available free of cost or with a negligible amount of cost for manipulating images. Some tools can manipulate images to such an extent that it becomes impossible to discriminate by human visual system that image is forged or genuine. Hence, image forgery detection is a challenging area of research. It is evident that good quality work has been carried out in the past decade in the field of image forgery detection. However, there is still a need to pay much attention in this field, as image manipulation tools are becoming more and more sophisticated. The main purpose of this paper is to review the various existing methods developed for detecting the image forgery. A categorization of various forgery detection techniques has been presented in the paper.
Pilot Test of an Adapted, Evidence Based Intervention for Preventing HIV for Women Residing in Domestic Violence Shelters
Venue: Violence against women
Year: 2019

This pilot study examined whether an evidence based intervention for preventing HIV that was adapted for women residing in domestic violence shelters improved residents' HIV knowledge and condom use self efficacy. The intervention acceptability, feasibility, and fidelity were also assessed. Seven domestic violence shelter workers facilitated the intervention to 32 shelter residents. Residents had significantly higher HIV knowledge and condom use self efficacy after the intervention. Residents found the intervention highly acceptable. Intervention facilitators generally agreed that the intervention was acceptable and feasible. Facilitators taught the intervention mostly as suggested, but with some changes. Study implications are discussed.
Influencia de los distintos tratamientos superficiales de las barras de fibra de carbono en su comportamiento adherente con el hormigon
Year: 2014

En los ultimos anos, debido al elevado coste de la reparacion de las estructuras de hormigon armado con acero por el efecto de la corrosion, se ha tomado conciencia de la necesidad de utilizar nuevos materiales sustitutivos de las barras de acero corrugado. Estos materiales deben garantizar la seguridad y las condiciones de servicio, esteticas y funcionales de la estructura durante el periodo de vida util para el cual fue disenado. En la busqueda de nuevos materiales que sustituyan a las barras de acero corrugado, aparecen hace pocos anos las barras de polimero reforzado con fibras carbono (CFRP) Este tipo de materiales es mas ligero, posee una resistencia a traccion superior a las barras de acero y, ademas, solucionan el problema de la corrosion. Antes de introducir este nuevo tipo de barras es necesaria la comprobacion de la adherencia con el hormigon en las distintas condiciones termicas a las que se encuentran expuestas las estructuras, debido a que este es uno de los parametros mas importantes en el diseno de la estructura. Ademas, de ser una de las hipotesis en las que se basan las normativas actuales de diseno de estructuras de hormigon armado. Este trabajo estudia el comportamiento adherente entre las barras de CFRP y el hormigon en diferentes condiciones termicas. Para ello, se lleva a cabo una campana de 175 ensayos experimentales de pullout. Estos ensayos se realizan en condiciones termicas de Hielo/Deshielo, 5 oC, 20 oC, 40 oC y 80 oC, tanto en barras de CFRP con tratamientos superficiales de arenado, texturizado y corrugado, como en barras de acero corrugado. Previamente a la realizacion de los ensayos experimentales de pullout, se realizan 21 ensayos de diametro equivalente y 21 ensayos de traccion longitudinal en ambos tipos de barras. Ademas, en las barras de CFRP se realizan ensayos complementarios de analisis termogravimetrico (TGA) de calorimetria diferencial de barrido (DSC) y microdureza. Al mismo tiempo, se obtienen imagenes con microscopia optica, microscopia electronica de barrido (SEM) y microscopia de fuerza atomica (AFM) de las muestras ensayadas a pullout. Los resultados obtenidos muestran que los diferentes tratamientos superficiales de las barras de CFRP, que a diferencia del acero no se encuentran estandarizados, movilizan distintos mecanismos adherentes y modifican el comportamiento adherente de las barras de CFRP, siendo el tratamiento de corrugado el unico que produce una adherencia similar a las barras de acero corrugado. Ademas, se comprueba que las condiciones termicas afectan de forma diferente a los distintos tipos de barras de CFRP.
Diversity driven generation of link based cluster ensemble and application to data classification
Venue: Expert Syst. Appl.
Year: 2015

HighlightsNew data transformation method that makes use of link based cluster ensemble (LCE).For accurate clustering, LCE is coupled with diversity driven ensemble generation.Evaluated on published datasets with C4.5, NB, KNN, ANN and Random Forest models.New method usually performs better than benckmark techniques. Over decades, a large number of research studies have concentrated on improving the accuracy of classification model. This is the case as several types of classifiers prove to be useful in real life problems, including the prediction of system failure risk and microarray based cancer diagnosis. Despite this, the accuracy of existing classifiers has been constrained by uninformative variables typically observed in modern data. In addition to feature selection, one may transform the original data to another variation, where only key feature components are included. Unlike conventional transformation based techniques found in the literature, this paper presents a novel method that makes use of cluster ensembles, specifically the summarized information matrix, as the transformed data for the following classification step. Among different state of the art methods, the link based cluster ensemble approach (LCE) provides a highly accurate clustering, and thus particularly employed here. This is uniquely coupled with a diversity driven generation of ensemble, which provides informative and diverse sets of clusterings. The performance of this transformation model is evaluated on published synthetic, standard and gene expression datasets; using C4.5, Naive Bayes, KNN, Neural Network and Random Forest classifiers; in comparison with benchmark techniques. The findings suggest that the new model can improve the classification accuracy of original data and performs better than the other transformation methods investigated in the empirical study.
Scale Aware Hierarchical Detection Network for Pedestrian Detection
Venue: IEEE Access
Year: 2020

Several or even dozens of times spatial scale variation is one of the major bottleneck for pedestrian detection. Although the Region based Convolutional Neural Network (R CNN) families have shown promising results for object detection, they are still limited to detect pedestrians with large scale variations due to the fixed receptive field sizes on a single convolutional output layer. In contrast to previous methods that simply combined pedestrian predictions on feature maps with different resolution, we propose a scale aware hierarchical detection network for pedestrian detection under large scale variations. First, we introduce a cross scale features aggregation module to accomplish feature augmentation for pedestrian representation through merging the lateral connection, the top down path and bottom up path. Specifically, the cross scale features aggregation module can adaptively fuse hierarchical features to enhance feature pyramid representation for robust semantic and accurate localization. Further, we design a scale aware hierarchical detection network to effectively integrate multiscale pedestrian detection into a unified framework by adaptively perceiving the augmented feature level for special scale pedestrian detection. Experimentally, the proposed scale aware hierarchical detection network forms a more robust and discriminative model for pedestrian instances with different scales on widely used ETH and Caltech benchmarks. In particular, compared with the state of the art method FasterRCNN+ATT, the log average miss rate of pedestrian detection is reduced by 11.98% for medium scale pedestrians (between 30 80 pixels in height) and 14.12% for whole scale pedestrians (above 20 pixels in height) on Caltech benchmark.
Machine Learning and Data Mining for Sports Analytics
Venue: Lecture Notes in Computer Science
Year: 2018

Sports analytics had its public breakthrough as early as the 1970s when baseball enthusiasts started developing a range of statistical tools for analyzing players, teams, and strategies. Due to a combination of early successes, increased computational power and advanced, automated data collection methods, sports analytics has been a steadily growing area in the last decade. The discipline is no longer restricted to designing new statistics and building simple statistical models. Moreover, sports analytics has found its way in other professional sports as well. Many professional sports clubs have started hiring performance analysts whose main task is to analyze the large quantities of data that are being collected nowadays, including play by play data, video tracking data, and sensor readings. In hindsight, the success of sports analytics in baseball is not surprising. Baseball matches can easily be split into distinct events, which can be analyzed using simple statistical tools. However, more sophisticated techniques are needed to analyze more fluid sports such as basketball and soccer. In these sports, it is much harder to distinguish between events which are also not necessarily sequential and have more complex interrelations. In order to address this additional complexity and to deal with the large quantities of data that are available, we are applying machine learning and data mining techniques to this type of data. In terms of soccer, we are looking at predicting match outcomes using raw statistics and match ratings  predicting and preventing injuries using test results and workloads, automatically generating match reports from play by play data, and identifying players' playing styles in play by play data. In terms of basketball, we are looking at predicting match outcomes using raw statistics  identifying playing styles of both teams and players, and determining optimal player rotations using play by play data as any number of substitutions can be made during a basketball match.
Effects of Issue Ownership, Perceived Fit, and Authenticity in Corporate Social Advocacy on Corporate Reputation
Year: 2021

Based on the issue ownership theory and corporate reputation, this study examines the effect of corporate social advocacy (CSA) on corporate reputation, focusing on the relative impact of perceived fit between CSA and brand identity (CSA brand fit) and CSA authenticity. To this end, this study first examined how Ben Jerry's advocacy of lesbian, gay, bisexual, transgender, and queer (LGBTQ) rights through social media channels has influenced the assessment of issue ownership by comparing social analytics data with public survey data. Spearman's rank order correlation revealed a high correlation between the salience of Ben Jerry's LGBTQ related social media posts and its top of mind ranking within the ten companies associated with the LGBTQ rights issue. Results of survey data showed the relative impacts of CSA brand fit and authenticity on Ben Jerry's issue specific corporate reputation. Consistent with the predictions, both perceived authenticity and perceived fit turned out to be positive predictors for corporate reputation. Between the two theory driven variables, perceived authenticity was the strongest predictor for corporate reputation.