Miracle-dz/UniFAR-FTUs huggingface dataset:
An evaluation of the impact of the management practices and how they impact on employee-engagement: Employees perceptions

The employer-employee relationship has always been governed by the understanding that the employee is simply a hired hand to complement the business owner in the process of achieving a firm’s set objectives. The rest of the other activities and phenomena are taken for granted – ‘I employ you, you do your work I pay you’, so the circle continues. The employer drives the employee to perform to enable the firm reach its objectives and give a good return on the investments. The rest of the other activities are merely a means to an end, understood to be merely a symbiotic relation, one hand washing the other. The concept of employee-engagement as a management tool does not seem to hold much strength and appreciation amongst managers whose sole purpose is to produce results. This paper brings into light empirical research indicating that industry captains do not focus on human capital as critical for effective productivity. The managers resort to hiring and firing as a means of boosting productivity, slave driving to increase labour performance. The industry captains are quick to point a finger to the labour as inhibiting free will hiring and firing as a solution to poor productivity. Consequently, the industry may be breeding a generation of non-devoted, convenience employees resulting in mediocre performance. The question asked always is; why does South Africa have low productivity? The paper points the problem to the failure of management to capitalize on the benefits of employee-engagement as an accessory to effective management by impression. Key words: Commitment to the firm, conducive work-environment, employee-engagement, manager-employee-relationship, peer-relationship and productivity.
An Analysis of Naïve Bayes Hypothesis for Web Scraping and Data Mining

This article approaches the utilization of the Naive Bayes (in a matter of moments NB) classifier. It exhibits that the count NB improves the assignments of the Web mining by the precision reports arrange. This recommendation separated the execution of Naïve Bayes count with other gathering frameworks. The probability of making a gathering model for doling out the Scholarships to understudies by focusing on precision of the system, numerous components have been bankrupt down, notwithstanding several them are discovered capable when accuracy was considered
Routing Efficiency with Link Failures using Multiple Routing Configurations

The slow convergence of IGP routing protocols after a topology change has led to several proposals for proactive recovery schemes in IP networks. These proposals are limited to guaranteeing loop-free connectivity after a link or node failure, and do not take into account the resulting load distribution in the network. This can lead to congestion and packet drops. In this work, we show how a good load distribution can be achieved in pure IP networks immediately after a link failure, when Multiple Routing Configurations (MRC) is used as a fast recovery mechanism. This paper is the first attempt to improve the load balancing when a proactive recovery scheme is used. Unlike load balancing methods used with normal IP rerouting, our method does not compromise on the routing performance in the failure free case. Our method is evaluated using simulations on several real and synthetically generated network topologies. The evaluation shows that our method yields good routing performance, making it feasible to use MRC to handle transient network failures.
Signs of life : bio art and beyond

Bio art is a new art form that has emerged from the cultural impact and increasing accessibility of contemporary biotechnology. Signs of Life is the first book to focus exclusively on art that uses biotechnology as its medium, defining and discussing the theoretical and historical implications of bio art and offering examples of work by prominent artists.Bio art manipulates the processes of life; in its most radical form, it invents or transforms living organisms. It is not representational; bio art is in vivo. (A celebrated example is Eduardo Kac's own GFP Bunny, centered on "Alba," the transgenic fluorescent green rabbit.) The creations of bio art become a part of evolution and, provided they are capable of reproduction, can last as long as life exists on earth. Thus, bio art raises unprecedented questions about the future of life, evolution, society, and art.The contributors to Signs of Life articulate the critical theory of bio art and document its fundamental works. The writers--who include such prominent scholars as Barbara Stafford, Eugene Thacker, and Dorothy Nelkin--consider the culture and aesthetics of biotechnology, the ethical and philosophical aspects of bio art, and biology in art history. The section devoted to artworks and artists includes George Gessert's Why I Breed Plants, Oron Catts and Ionat Zurr's Semi-Living Art, Marc Quinn's Genomic Portrait, and Heather Ackroyd and Dan Harvey's Chlorophyll.
Enhancing Learner Engagementin an Online Baccalaureate Programto Improve Student Outcomes

in an Online Baccalaureate Program to Improve Student Outcomes by Kathleen Hughes De Sousa, Ph.D., School of Undergraduate Studies Capella University United States kathleen.desousa@capella.edu Andrea Kozak Miller, Ph.D. School of Undergraduate Studies Capella University United States andrea.miller@capella.edu Barbara Reagle, Ph.D. School of Undergraduate Studies Capella University United States barb.reagle@capella.edu Laura Sullivan, M.S., L.M. F.T, ABD School of Undergraduate Studies Capella University United States laura.sullivan@capella.edu Numerous researchers have described models for learner persistence and academic success as involving social presence and interaction (Garrison, Anderson, & Archer, 2000; Pascarella & Terenzini, 2005; Tinto, 1975). According to Rhoades (2012), faculty play a critical role in learner completion rates. Helping learners build social relationships and develop interpersonal skills impacts their educational outcomes (persistence and graduation) and overall satisfaction with their higher education institution. Additionally, there is a positive effect on career readiness because learner develop the professional skills
Multilevel Classifier in Recognition of Handwritten Arabic Characters

Problem statement: Arabic offline handwriting recognition is considered one of the most challenging topics. This is probably caused by the fact that Arabic recognition system faced many problems during the development stage. It faces the usual problems of character recognition in general, in addition to the problems that are specific to Arabic language only. The aim of this study was to build a classifier to solve Arabic text ambiguity; to be used in text recognition applications. Approach: A multilevel classifier based on pattern recognition techniques, is proposed. The proposed classifier was implemented using MATLAB and also tested with a large sample of handwritten datasets. Results: Pattern recognition techniques are used to identify Arabic handwritten text. After testing, the recognition rates reached {93, 84, 89 and 85%} for the isolated letters, letters at the beginning, at the middle and at the end of the word respectively. Conclusion: Even that the Arabic letters change their shape depending on their position in a word, the proposed classifier, using the powerful set of features, is proved to be effective in the recognition of Arabic letters.
Analysts and stock liquidity – Global evidence

Abstract This paper investigates the relation between analyst coverage and stock liquidity with a focus on the role of information produced by financial analysts. Using a comprehensive dataset across 41 countries for the period 2000–2010, we document two novel findings. First, analyst coverage is positively correlated with stock liquidity. Second, the positive effect of analyst following on stock liquidity is attributed to the weak institutional environment. These findings suggest that financial analysts provide more public information to market participants and thus improve stock liquidity. This effect is attenuated in a country with a stronger institutional environment.
Untersuchungen zur Spezifität und Sensitivität transienter click-evozierter otoakustischer Emissionen (TEOAE)

: Transient click evoked otoacoustic emissions (TEOAE) have been shown to be a good test of hearing impairment especially when used for infant screening. However, occasional cases of false positive results--TEOAEs in spite of severe hearing loss--have been reported. This study encompasses 243 children whose hearing thresholds were known from subjective hearing tests and--in questionable cases--derived from additional auditory evoked potentials. The TEOAEs proved to have a high sensitivity (93%) and a reasonable specificity (67%), if the margin between good and bad hearing was set at 30 dB. However, four ears showed good TEOAEs in spite of poor hearing thresholds. In three cases, the children proved to have a central auditory hearing loss due to a cerebral disorder. One child with bilaterally superb TEOAEs had a unilateral deafness of unclear origin with no obvious retrocochlear or central disorder. Possible explanations under discussion included the presence of a retrocochlear lesion which was too small to show up in the tests used or that the defect was located just between the outer hair cells and the first neuron, for example in the inner hair cells. Additionally, efferent inhibition might cause a functional deafness as described by Rajan (1989) for the guinea pig. The results also show that TEOAEs should always be used in the differential diagnosis of hearing impairment in generally disabled children. The need for hearing aids and especially their adjustment has to be discussed in case of good TEOAEs, i.e., normal peripheral hearing. (ABSTRACT TRUNCATED AT 250 WORDS)
Effect of 12-week dark chocolate intake combined with low-energy diet and exercise on weight loss in obese adults: a phase II randomized controlled trial protocol

Background : Obesity is a public health problem affecting 35% of the adult population in the US.A 5-10% weight loss decreases the risk of cardiovascular disease and diabetes mellitus. Diet and exercise have shown to be effective in the treatment of obesity, but adherence is a limitation. Dark chocolate (DC) polyphenols were proven to have beneficial effects on blood pressure, endothelial function, HDL cholesterol, lipoprotein ratios and inflammation markers. Also, it might play a role in improving fat metabolism and satiety; however, its effects on weight loss are still not clear. We propose a protocol to explore the effects of DC associated with hypocaloric diet and exercise on weight loss during a 12-week period in obese adults. Methods and Design: The study is a randomized controlled trial with 2 parallel arms comparing hypocaloric diet + exercise with hypocaloric diet + exercise + 50g dark chocolate/day during a 12 week period. A total of 408 obese adults (18 to 45 years old) with no comorbidities that could compromise the exercise program will be recruited. Primary outcome is proportion of patients who had 5% or more weight loss after 12 weeks. Secondary outcomes are glucose levels and insulin resistance (HOMA-IR), lipid profile, abdominal circumference, body fat mass (estimated by skinfold thickness) and blood pressure, satiety perception and drop-out rates. Primary outcome (percentage of patients achieving 5% or more weight loss) will be analyzed by chi-square test with an Intention-to-Treat approach. Conclusions: This phase II randomized controlled trial has the aim to explore the effects of including dark chocolate as an adjuvant to classical therapies (hypocaloric diet and exercise) on weight loss in a 12-week period Trial registration : the trial will be registered at www.clinicaltrials. gov
Machine Learning Techniques for Gesture Recognition

Classification of human movement is a large field of interest to Human-Machine Interface researchers. The reason for this lies in the large emphasis humans place on gestures while communicating with each other and while interacting with machines. Such gestures can be digitized in a number of ways, including both passive methods, such as cameras, and active methods, such as wearable sensors. While passive methods might be the ideal, they are not always feasible, especially when dealing in unstructured environments. Instead, wearable sensors have gained interest as a method of gesture classification, especially in the upper limbs. Lower arm movements are made up of a combination of multiple electrical signals known as Motor Unit Action Potentials (MUAPs). These signals can be recorded from surface electrodes placed on the surface of the skin, and used for prosthetic control, sign language recognition, human machine interface, and a myriad of other applications. In order to move a step closer to these goal applications, this thesis compares three different machine learning tools, which include Hidden Markov Models (HMMs), Support Vector Machines (SVMs), and Dynamic Time Warping (DTW), to recognize a number of different gestures classes. It further contrasts the applicability of these tools to noisy data in the form of the Ninapro dataset, a benchmarking tool put forth by a conglomerate of universities. Using this dataset as a basis, this work paves a path for the analysis required to optimize each of the three classifiers. Ultimately, care is taken to compare the three classifiers for their utility against noisy data, and a comparison is made against classification results put forth by other researchers in the field. The outcome of this work is 90+ % recognition of individual gestures from the Ninapro dataset whilst using two of the three distinct classifiers. Comparison against previous works by other researchers shows these results to outperform all other thus far. Through further work with these tools, an end user might control a robotic or prosthetic arm, or translate sign language, or perhaps simply interact with a computer.
Politicizing Europe in times of crisis

ABSTRACT This paper starts from the premise that the politicization of Europe is indicative of a new structuring conflict that involves a set of processes which put the national political community under strain. This structuring conflict has been emerging long before the Euro and refugee crises. However, these crises may have reinforced and potentially reshaped public conflicts within and across countries. Therefore, the paper traces the politicization of Europe during national election campaigns in fifteen countries from the early 2000s up to 2017. The analysis focuses on the way the multiple crises have affected the level of politicization, its driving forces, and the location of European issues in the political space. Overall, the results indicate a substantive increase in politicization, but they also point to strong region and crisis-specific varieties which should be considered in scholarly discussions on the relative impact of domestic conflicts on the future course of European integration.
Prevalence and risk factors of anaemia among ever-married women in Jordan.

Background Anaemia is associated with poor health outcomes and is considered a serious public health problem particularly in low- and middle-income countries. Specific subgroups are at higher risk of anaemia, such as women of reproductive age. Aims This study examined the prevalence and risk factors of anaemia among ever-married women in Jordan using a secondary analysis of the Jordan Population and Family Health Survey. Methods This is a secondary analysis of data from a nationally representative sample of ever-married women aged 15-49 years that were tested for haemoglobin levels in the 2012 JPFHS. Anaemia was categorized according to the WHO criteria. Univariate and multivariate logistic regression analyses were used to investigate risk factors associated with anaemia. Results The prevalence of any anaemia was 37.3%; specifically, 20% had mild anaemia (haemoglobin 11.0-11.9 g/dl), 16.3% had moderate anaemia (hemoglobin 8.0-10.9 g/dl) and 1% had severe anaemia (haemoglobin < 8.0 g/dl). Factors that were associated with anaemia in the multivariate regression included urban women (P = 0.01), living in the north (P = 0.014) or south regions (P = 0.013) of Jordan, having multiple children (P < 0.001), being pregnant (P < 0.01), and using IUD as a contraceptive method (P < 0.001). Conclusions A high prevalence of anaemia among ever-married women of reproductive age in Jordan was noticed. The results emphasize the importance of urgent public health interventions to prevent anaemia in Jordan, particularly among high-risk subgroups.
Trato de remar contra la corriente: Narrativas del padecimiento de personas que viven con VIH en México

This article explores illness narratives built by people living with HIV in order to understand the meanings given to this illness in their lives. Three types of narratives have been identified. Firstly, progressive narratives where a positive meaning is given to the course of HIV-infection due to personal transformations, physical and emotional recovery that people shows. Secondly, stable narratives where illness normalization is restricted by many psychosocial problems. Finally regressive narratives where a negative or tragic meaning is given to illness due to the stigmas, discrimination, mental health issues, a lack of adherence and the emergence of diseases owing the advance of HIV-infection. Illness narratives are considered a strategy to understand the way patients cope with illness, identify the psychosocial consequences of this illness and assess possible difficulties in terms of the patient ́s emotional recovery and adherence to treatment.
Classification of identity documents using a deep convolutional neural network

In this work, we review the main subjects that we have to serve to build an image classifier, then we design and implement a system to classify identity documents. Especially relevant is the description of the workflow that we have come up with after several ways of approaching the problem and which we hope can serve other machine learning practitioners. We evaluate some feature extractor algorithms to find the most suitable for identity documents classification purposes. Using virtual machines on the cloud, we run feature extractors in parallel to label at a speed of 16 images/s. Then, we select a neural network architecture and hyperparameters to train a convolutional neural network. Our results give an accuracy of 98%. We detail the responses of the convolutional filters over the images. Results and source code in the appendix.
PLAE: A model for planning successful independent learning

Most investigations have examined an isolated task, which according to Bransford's model (1979) neglects other factors of successful independent learning. Moreover, most of the investigations labeled as "metacognitive research" have virtually ignored planning or the regulation of cognition. When properly carried out, planning involves the learners in predicting and defining tasks, scheduling appropriate strategies for those tasks, and checking those strategies and outcomes in terms of effectiveness and
The Significance of Theoretical Foundations in Enhancing Teaching Practices: Teachers’ Perceptions and Use of Learner-centered Approach in EFL Classrooms

Undeniably, the realm of teaching English as a foreign language still embraces active research that continuously looks for approaches and methods which may contribute to a more efficient instruction of the target language. These theoretical foundations enable the instructor to appropriately implement the outlined approach along its salient features to achieve the desired outcomes. Despite this tight rapport, teachers of English at the University of Mostaganem tend to rely on their common-sense teaching practices that are mainly informed by their experience of teaching EFL. The gap between the two extremes theory and practice, the premise of this paper, may be widened as teachers do not develop accurate and scientific understandings of certain pedagogical concepts, in this case, learner-centeredness as agreed on by professional academics, let alone to apply it along its proper standards. The pedagogical sequel of such misunderstanding mainly relate to random references to both teacher and learner-centered approaches in classroom teaching practices. The study via a detailed teachers’ questionnaire revealed that teachers of English, in addition to the cursory understandings they develop in relation to the very meaning of a learner-centered approach, tend to eschew developing learners’ metacognitive skills in their teaching practices. Most importantly, they are likely to rely on traditional ways of assessment instead of authentic frameworks, a cardinal feature within the current paradigm.
Massively parallel MIMD solution of the parabolized Navier-Stokes equations

Reaching new milestones in science and engineering will require the speed and scalability offered by massively parallel computers. The primary challenge to the users of this technology will be the development of scalable software. All the software's functionality, including the generation of grids, the algorithmic solvers, and the production of output for interpretation and visualization, must scale across multiple processors. As an example of the scalable application concept, the authors have developed a highly parallel, scalable version of a parabolized Navier-Stokes (PNS) code used to simulate steady three-dimensional flow past supersonic and hypersonic flight vehicles. The primary goal of this research has been to develop a fully scalable version of the PNS procedure and to demonstrate that it can achieve high performance on a massively parallel, multiple instruction multiple data (MIMD) computer. <<ETX>>
Parallel-machine batching and scheduling to minimize total completion time

We consider a scheduling problem in which n independent and simultaneously available jobs are to be processed on m identical parallel machines. The jobs have to be batched as well as scheduled. The completion time of a job is defined as the completion time of the batch containing it. A constant set-up time is incurred whenever a batch is formed. The problem is to batch and schedule jobs so that the total completion time of the jobs is minimized. We first present some properties and then develop a dynamic programming algorithm to solve this problem. The running time of our algorithm is O(mnm+1). When job processing times are identical, we show that the problem reduces to the corresponding single-machine problem, which has been well solved in the literature.