Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of changes in ownership structure on performance: evidence from the thrift industry

Restrictions on the ownership structure of a public company may harm the company's performance by preventing owners from choosing the best structure. We examine the stock-price performance and ownership structure, before and after the expiration of anti-takeover regulations, of a sample of thrift institutions that converted from mutual to stock ownership. We find that after the anti-takeover provisions expire, firm performance improves significantly, and the portions of the firm owned by managers, noninstitutional outside blockholders, and the firm's employee stock ownership plan increase. Changes in performance are positively associated with changes in ownership by managers and by noninstitutional outside blockholders but negatively associated with changes in ownership by employee stock ownership plans.
Willingness to share knowledge in healthcare organisations: the role of relational perception

Abstract A growing number of studies have been conducted to study the antecedents of employees’ knowledge-sharing behaviours. However, the literature is limited regarding the influence of relational characteristics on knowledge sharing. We conducted a field study in two Dutch health care organisations, and examined employees’ willingness to share knowledge in 488 dyadic relationships. The results showed that an individual’s perceived reciprocity and positivity of a dyadic tie was positively related to that person’s willingness to share knowledge. Moreover, perceived competition was negatively related to willingness to share knowledge. Based on these findings, we discuss how to change organisational culture to encourage knowledge sharing. Suggestions for future research and practical implications are also offered.
Building a Conceptual Framework for Auditory Learning

H ere’s a question: What do you get when you combine a rabbit, a violin, and a patient who is struggling to hear in noise? You probably didn’t guess “a life in auditory neuroscience,” but, when taken together, the three encapsulate my research: the biology of auditory learning. I began my career measuring responses from single neurons in the rabbit auditory cortex. I trained rabbits to associate a particular sound with a particular meaning and found striking changes in neural activity within the auditory cortex following this learning experience. Having witnessed the potential for brain plasticity firsthand, I moved my focus to improving human communication. Since then, I have pursued several lines of work to understand how the brain is changed by experiences such as music training,1 second language learning,2 and computerized brain training (Listening and Communication Enhancement [LACE];3 BrainHQ4). These studies demonstrate the potential for brain plasticity, and we’ve defined signature neural changes stemming from each experience.5 I’ve covered many of these neural signatures in the Hearing Matters columns Samira Anderson, AuD, PhD, and I have written for The Hearing Journal (HJ January 2015 issue, p. 38), but, in this editorial, I want to take a step back and ask: What factors drive the biological changes?
Sharia governance of Islamic financial institutions: a comparative study among Malaysia, Bahrain and Sri Lanka

Islamic finance industry has been widely developing not only in Muslim countries such as Malaysia and Bahrain but also in nonMuslim countries such as Sri Lanka. At the same time, the Shari’ah governance is one of major requirements for Islamic financial institutions to be recognised by the Shariah and the Muslim customers. As such, the Shari’ah governance plays a significant role in the industry to ensure that it meets the objective for the establishment of the Islamic financial institutions. Thus, the purpose of this paper is to investigate the level of Shari’ah governance of Islamic financial institutions in Sri Lanka, Malaysia and Bahrain. Hence, this is a comparative study among three countries. The research paper adopts a qualitative method and content analysis in order to accomplish the objective of the study. The data for the study is based on the primary and secondary sources that could be collected from Parliamentary Acts, books, articles, magazines, online materials and annual report of Islamic financial institutions available in the above three countries. The findings of the study are expected to be greatly useful for the Islamic financial institutions in Sri Lanka and similar countries where there is no proper legislation on Shariah governance.
Presenting modified Servqual model to evaluate flight attendant services: Iran Air case study

Purpose: The investigation of the customer`s viewpoints and utilizing their ideas and expectations in improving the quality of the products, has turned out to be one of the key concerns of the companies working in all fields. Airline industry as one of the most extensive modes of transportation should be strictly accurate in providing services to their customers. This article attempts to investigate important dimensions from passengers' point of view and present a model which would evaluate the flight attendant's performance.Design/methodology: In order to achieve this purpose, on the basis of the literature and experts' and passengers' point of view, the SERVQUAL model has been modified with 26 factors in 6 dimensions. Then 300 data have been gathered for the Factor Analysis Model.Findings: As a result, a model with high goodness of fit has been developed which could be used as a tool of measuring quality of service with a high degree of certainty. In the end, running the model in Iran air, most differences were as below: 1-Improvement 2-Responsiveness 3-Empathy 4-Assurance 5-Tangibles 6-Reliability.Originality/value: In general, in this model, all services with which employees are involved are observed. However, the main issue in this research is related to attendant team. Consequently, considering that many of these indicators have different meanings in assessing customer satisfaction in relation to the performance of flight attendant; modifications should be made to the dimensions of the SERVQUAL model.
Job Accessibility and Urban Transport Connectivity: Evidence from Antananarivo, Madagascar

In recent years, there has been renewed interest in access to jobs in relation to transport connectivity. In Sub-Saharan Africa, about 14 million working age people are added to the labor market every year. Ensuring sustained access to jobs seems to be a prerequisite for inclusive and robust economic growth. The paper examines the impact of public transit connectivity on access to jobs, especially focusing on wages. Using data from Antananarivo, Madagascar, it is shown that the wages earned by commuters are systematically higher than the wages earned by those who decided not to commute and are self-employed or engaged with family businesses around their neighborhood. Proximity to public transport, especially taxi-be, is important to promote people's access to jobs. It is also found that there is a substantial gender inequality in wages in the country: Women are more likely to use buses to commute, and yet, they earn less than men. In addition, the poor tend to benefit less from public transportation. Public bus services are affordable, however, the quality of the services may remain low.
ADAMS-MATLAB co-simulation for kinematics, dynamics, and control of the Stewart–Gough platform

The mechanical structure known as Stewart–Gough platform is the most representative parallel robot with a wide variety of applications in many areas. Despite the intensive study on the kinematics, dynamics, and control of the Stewart–Gough platform, many details about these topics are still a challenging problem. In this work, the use of automatic dynamic analysis of multibody systems software for the kinematic and dynamic analysis of the Stewart–Gough platform is proposed. Moreover, a co-simulation automatic dynamic analysis of multibody systems (ADAMS)-MATLAB is developed for motion control of the Stewart–Gough platform end-effector. This computational approach allows the numerical solution for the kinematics, dynamics, and motion control of the Stewart–Gough platform and a considerable reduction on the analytical and programming effort. The obtained results in the three topics (kinematics, dynamics, and control) are validated by comparing them with analytical results reported in the literature. This kind of computational approach allows for the creation of virtual prototypes and saves time and resources in the development of Stewart–Gough platform-based robots applications.
A Dehazing Algorithm using the Prediction of Adaptive Transmission Map for Each Pixel

We propose the dehazing algorithm which consists of two main parts, the derivation of the Atmospheric light and adaptive transmission map. In the getting the Atmospheric light value, we utilize the quad-tree partitioning where the depth of the partitioning is decided based on the difference between the averaged pixel values of the parent and children blocks. The proposed transmission map is adaptive for each pixel by using the parameter  to make the histogram of the pixel values in the map uniform. The simulation results showed that the proposed algorithm outperforms the conventional methods in the respect of the visual quality of the dehazed images and the computational complexity
Performance analysis on spark and map reduce using streaming data

Dynamic information stream handling utilizing constant programming model for processing large data sets with a parallel, distributed algorithm on a cluster is at present a high worry as the measure of information being created is expanding step by step with the development of the Internet of Things, Big Data and Cloud. Big data are portrayed by immense volume that can land with a high speed and in various organizations from numerous sources. Accordingly, continuous programming model strategies ought to be fit for preparing the information to separate an incentive out of it by tending to the issues identified with these qualities that are related to information streams. In this work, we asses and break down the ability to exist Map-Reduce and Spark procedures to deal with dynamic information streams and we introduce whether the current systems are important in the current circumstance.
Coupling problem in thermal systems simulations

Building energy simulation is playing a key role in building design in order to reduce the energy consumption and, consequently, the CO2 emissions. An object-oriented tool called NEST is used to simulate all the phenomena that appear in a building. In the case of energy and momentum conservation and species transport, the current solver behaves well, but in the case of mass conservation it takes a lot of time to reach a solution. For this reason, in this work, instead of solving the continuity equations explicitly, an implicit method based on the Trust Region algorithm is proposed. Previously, a study of the properties of the model used by NEST-Building software has been done in order to simplify the requirements of the solver. For a building with only 9 rooms the new solver is a thousand times faster than the current method.
Microbiological quality determination of pasteurized, UHT and flavoured milk sold in Dhaka, Bangladesh

The present study was undertaken to determine the microbiological quality of pasteurized milk, UHT milk and flavoured milk samples collected from different locations in Dhaka, Bangladesh. Twenty pasteurized milk samples, fifteen UHT milk samples and fifteen flavoured milk samples of different brand were collected and different batch were analyzed for enumerating the total viable bacterial count (TVBC), total coliform count (TCC) and physiochemical tests (sensory test, alcohol test, acidity test, fat test, CLR test, SNF). The range of TVBC and pasteurized milk samples was between 2.3×102 cfu/ml to 4.69×103 cfu/ml. TVBC range of flavoured milk samples was between 5.0×101 cfu/ml to 1.8×102 and no TVBC was detected for any of the UHT milk samples. No TVBC was found for flavoured milk samples of company-8 (UHT). Because it was processed with ultra high temperature, slightly lower than that recommended by BSTI (not exceeding 20,000 cfu/ml). Coliform bacteria were present only for pasteurized milk samples in one brand, though the count was under acceptable range according to BSTI recommendation (<10/ml coliform in pasteurized milk). Physiochemical tests are also very important to detect the quality of milk samples. Acidity range should not exceed 0.14, for this study fat range should be minimum 3.5% and SNF should be minimum 8%. In this study, for pasteurized milk samples acidity range was between 0.14-0.16, fat range was between 3.5-3.9% and SNF was between the ranges of 8-9.784%. For UHT milk samples acidity range was between 0.13-0.16, fat range was between 3.5-3.8% and SNF was between 8.034-9.012. All the results of sensory and physiochemical tests for pasteurized and UHT milk samples were satisfactory. So, UHT processed milk and flavoured milk can be considered as safe for consumption within the mentioned expiry date without heat treatment. Stamford Journal of Microbiology, Vol.8(1) 2018: 1-6
ORGANIZATION OF SERVICE CONSUMPTION WITH CONCEALMENT NETWORK LOAD IN CHATTING APPS

Mobile companies monetize their knowledge of messaging Apps. Therefore, service usage analytics in messaging Apps becomes crucial for business, because it can benefit understand in-Application behaviors of finish users, and so enables numerous applications. However, you will find emerging challenges for inspecting IP packet content. For instance, messaging Apps are more and more using unpredictable port figures. Also, customers may secure the information of packets. Particularly, we first segment Internet traffic from traffic-flow to sessions to dialogs by mixing hierarchical clustering in addition to thresholding heuristics. we use a trained HMM model for disaggregating mixed usage types. Our jobs are carefully connected within-Application usage analysis. In addition, we create a system, named CUMMA, for classifying service usages in mobile messaging Apps when using the suggested method. Given a string of packet lengths, we first know about minimum and maximum values of IP packet lengths. You have to split the quantity from minimum to maximum into K equal-sized sub ranges. our work has apparent benefits for enabling important applications in analyzing and improving buyer understanding about mobile phone applications. The experiments show whenever achievable correctly choose classifiers and precisely design highlights of Internet traffic, it could considerably boost the overall precision for in-Application behavior analytics.
Teaching for effective learning in higher education: Focusing on learning and moving from a "based learning" mind-set

Recent educational reforms in universities, and other institutes of higher education, have pressured educators to select newer content delivery methods and move away from “traditional” modalities. Whilst this is a favourable shift towards introducing a studentcentred approach, it has led to the emergence of a culture of based learning techniques, with a strong emphasis on the method, rather than applying and understanding the pedagogical underpinnings – i.e. theories of learning. This issue has been exploited by the use of persuasive “marketing” techniques by the proponents of based learning. The popularity of such methods to busy teachers lies in the ready availability of a convenient “off the shelf” content delivery method. This article discusses the strengths, and limitations, of some popular based learning methods, and focuses on how to integrate the three important principles of learning when applying based learning methods or delivering content.
Convex Optimized Population Receptive Field (CO-pRF) Mapping

Population receptive field (pRF) mapping represents an invaluable non-invasive tool for the study of sensory organization and plasticity within the human brain. Despite the very appealing result that fMRI derived pRF measures agree well with measurements made from other fields of neuroscience, current techniques often require very computationally expensive non-linear optimization procedures to fit the models to the data which are also vulnerable to bias due local minima issues. In this work we present a general framework for pRF model estimation termed Convex Optimized Population Receptive Field (CO-pRF) mapping and show how the pRF fitting problem can be linearized in order to be solved by extremely fast and efficient algorithms. The framework is general and can be readily applied to a variety of pRF models and measurement schemes. We provide an example of the CO-pRF methodology as applied to a computational neuroimaging approach used to map sensory processes in human visual cortex - the CSS-pRF model. Via simulation and in-vivo fMRI results we demonstrate that the CO-pRF approach achieves robust model fitting even in the presence of noise or reduced data, providing parameter estimates closer to the global optimum across 93% of in-vivo responses as compared to a typical nonlinear optimization procedure. Furthermore the example CO-pRF application substantially reduced model fitting times by a factor of 50. We hope that the availability of such highly accelerated and reliable pRF estimation algorithms will facilitate the spread of pRF techniques to larger imaging cohorts and the future study of neurological disorders and plasticity within the human brain. Highlights Adaptable to an arbitrary computational pRF model, sensory modality and imaging modality. Model fitting accelerated by up to a factor of 50. CO-pRF parameter estimates achieve a better fit, closer to the global optimum, as compared to typical nonlinear implementations which suffer from local minima issues. Robust parameter estimation even at low CNR and reduced scan time.
Realtime Query Completion via Deep Language Models

Search engine users nowadays heavily depend on query completion and correction to shape their queries. Typically, the completion is done by database lookup which does not understand the context and cannot generalize to prefixes not in the database. In this paper, we propose to use unsupervised deep language models to complete and correct the queries given an arbitrary prefix. We address two main challenges that renders this method practical for large-scale deployment: 1) we propose a modified beam search process which integrates with a completion distance based error correction model, combining the error correction process (as a potential function) together with the languagemodel; and 2) we show how to efficiently perform our modified beam search process on CPU to complete the queries with error correction in real time, by exploiting the greatly overlapped forward propagation process and conducting amortized dynamic programming on the search tree, along with both SIMD-level and thread level parallelism. We outperform the off-the-shelf Keras implementation by a factor of 50, thus allowing us to generate query suggestions in real time (generating top 16 completions within 16 ms). Experiments on two large scale datasets from AOL and Amazon.com show that the method substantially increases hit rate over standard approaches, reduces the memory footprint of database lookup based approach by over two orders of magnitude, and is capable of handling tail queries.
Classification and Processing of 24-Hour Wrist Accelerometer Data

Background: An important step in accelerometer data analysis is the classification of continuous, 24-hour data into sleep, wake, and non-wear time. We compared classification times and physical activity metrics across different data processing and classification methods.Methods: Participants (n = 576) from the Finnish Retirement and Aging Study (FIREA) wore an accelerometer on their non-dominant wrist for seven days and nights and filled in daily logs with sleep and waking times. Accelerometer data were first classified as sleep or wake time by log, and Tudor-Locke, Tracy, and ActiGraph algorithms. Then, wake periods were classified as wear or non-wear by log, Choi algorithm, and wear sensor. We compared time classification (sleep, wake, and wake wear time) as well as physical activity measures (total activity volume and sedentary time) across these classification methods.Results:M(SD) nightly sleep time was 467 (49) minutes by log and 419 (88), 522 (86), and 453 (74) minutes by Tudor-Locke, Tracy, and ActiGraph algorithms, respectively. Wake wear time did not differ substantially when comparing Choi algorithm and the log. The wear sensor did not work properly in about 29% of the participants. Daily sedentary time varied by 8–81 minutes after excluding sleep by different methods and by 1–18 minutes after excluding non-wear time by different methods. Total activity volume did not substantially differ across the methods.Conclusion: The differences in wear and sedentary time were larger than differences in total activity volume. Methods for defining sleep periods had larger impact on outcomes than methods for defining wear time.
Un cas d'incarnation linguistique : implication du système moteur orofacial dans les ruminations mentales

Deux conceptions de la nature de la parole interieure s'opposent sur le plan theorique. Dans la lignee de la conception incarnee du langage, l'hypothese de la Simulation Motrice concoit la parole interieure comme un acte moteur imagine, simule. Dans la conception mentaliste du langage, les tenants de l'hypothese de l'Abstraction soutiennent que la parole interieure est abstraite, appauvrie sur le plan articulatoire, voire amodale, et ne necessite pas l'implication du systeme moteur. Prenant pour cas d'etude les ruminations mentales verbales, une forme de parole interieure negative, repetitive, excessive et par consequent abondante, nous proposons deux tests experimentaux de ces hypotheses opposees. Le premier test examine si les ruminations mentales provoquees par un paradigme classique d'induction sont associees ou non a une activation motrice labiale, en mesurant l'activite electromyographique des levres. Le deuxieme test evalue la contraposee de l'hypothese de la Simulation Motrice, c'est-a-dire examine l'effet de la reduction de l'activite motrice orofaciale sur les ruminations, grâce a un protocole de relaxations ciblees. Nos resultats preliminaires semblent dans l'ensemble en faveur d'une nature incarnee et motrice des ruminations mentales. Le premier test montre en effet l'implication de la musculature labiale durant les ruminations. Le deuxieme test suggere que le type de rumination induit par notre paradigme peut etre reduit en relaxant specifiquement les muscles de la parole, tels que les muscles des levres. Des etudes complementaires sont envisagees pour confirmer ces resultats preliminaires, qui semblent soutenir l'hypothese de la Simulation Motrice, selon laquelle la parole interieure correspond a de la parole a voix haute simulee articulatoirement et inhibee avant l'execution motrice.