Miracle-dz/UniFAR-FTUs huggingface dataset:
Code coverage, what does it mean in terms of quality?

Unit code test coverage has long been known to be an important metric for testing software, and many development groups require 85% coverage to achieve quality targets. Assume we have a test, T/sub 1/ which has 100% code coverage and it detects a set of defects, D/sub 1/. The question, which is answered here, is "What percentage of the defects in D/sub 1/ will be detected if a random subset of the tests in T/sub 1/ are applied to the code, which has code coverage of X% of the code? " The purpose of this paper is to show the relation between code quality and code coverage. The relationship is derived via a model of code defect levels. A sampling technique is employed and modeled with the hypergeometric distribution while assuming uniform probability and a random distribution of defects in the code, which invokes the binomial distribution. The result of this analysis is a simple relation between defect level and quality of the code delivered after the unit code is tested. This model results in the rethinking of the use of unit code test metrics and the use of support tools.
Supervisory Empowerment Behaviors, Psychological Empowerment and Work Outcomes among Egyptian Managers and Professionals: A Preliminary Study

Abstract Objective: This research examined the relationship of perceived supervisor empowerment behaviors with important work and well-being outcomes in a sample of Egyptian managers and professionals. Relatively little research has been undertaken on human resource management in Egyptian organizations and even less during and following the Arab spring. Methodology: Data were collected from 121 managerial and professional employees using anonymously completed questionnaires. Respondents were relatively young, had university educations, had short job and organizational tenures, and held lower level -management jobs. All measures used here had been used and validated previously by other researchers. Findings: Work outcomes included job satisfaction, organizational commitment, work engagement, exhibiting voice behaviors, workplace learning opportunities, psychological well-being and intent to quit. Employee perceptions of supervisory empowering behaviors predicted their levels of psychological empowerment. And both perceived levels of supervisory/leader empowerment behaviors and self-reported feelings of empowerment had significant relationships with the majority of work and well-being outcomes Value Added: Relatively little research has been undertaken on human resource management in Egyptian organizations and even less during and following the Arab spring. This will add to the body of knowledge about Egyptian managers and other Arab regions. Recommendations: Practical implications of these findings along with future research directions are offered. Practical applications include training supervisors on empowerment behaviors, and training all employees on the benefits of personal empowerment and efficacy and ways to increase them.
An Evolutionary Computational Approach to Humanoid Motion Planning

The theme of our work is centred on humanoid motion planning and balancing using evolutionary computational techniques. Evolutionary techniques, inspired by the Darwinian evolution of biological systems, make use of the concept of the iterative progress of a population of solutions with the aim of finding an optimally fit solution to a given problem. The problem we address here is that of asymmetric motion generation for humanoids, with the aim of automatically developing a series of motions to resemble certain predefined postures. An acceptable trajectory and stability is of the utmost concern in our work. In developing these motions, we are utilizing genetic algorithms coupled with heuristic knowledge of the problem domain. Unlike other types of robots, humanoids are complex in both construction and operation due to their myriad degrees of freedom and the difficulty of balancing on one or more limbs. The work presented in this paper includes the adopted methodology, experimental setup, results and an analysis of the outcome of a series of evolutionary experiments conducted for generating the said asymmetric motions.
The impact of the logistics management in customer satisfaction

Abstract Logistics management is one of nowadays tools to face economic challenges; it’s a mix of business and core activities of the organization. The supply and distribution activities integrated together form what’s known as logistics activities. The logistics activities within a business organization attempt to satisfy customers through achieving the time and location related market challenges and also through the cost of the service provided as well as the quality, taking into consideration customers needs and purchase power. Customer satisfaction is important because it provides marketers and business owners with a metric that they can use to manage and improve their businesses. Customer satisfaction is also a way to determinate the continuity of the business or of a product life by measuring the loyalty of the customers. If the customers are happy and satisfied, it will ensure the continuity of sales which means the continuity of the business. In the past customer satisfaction was more focused on requirements such as quality and reliability reducing costs of poor quality. In mid 50’s the production costs were continuously increasing, The way to maintain the company’s position within a changing market and increase profit starts by focusing on the service provided to the customer and on decreasing the cost, logistics activities became the backbone of these organizations that target the customer satisfaction while achieving competitive advantage. This study aims to show the impact of the logistics management on customer satisfaction in small and mid-sized Algerian industrial companies, by interviewing the companies managers and everybody in charge of the logistic process, the interview questions will be based on some literature review issues.
Nonlinear ∗-Jordan triple derivations on von Neumann algebras

Abstract Let B(H) be the algebra of all bounded linear operators on a complex Hilbert space H and 𝓐 ⊆ B(H) be a von Neumann algebra with no central summands of type I1. For A, B ∈ 𝓐, define by A ∙ B = AB+BA∗ a new product of A and B. In this article, it is proved that a map Φ: 𝓐 → B(H) satisfies Φ(A ∙ B ∙ C) = Φ(A) ∙ B ∙ C+A ∙ Φ(B) ∙ C+A ∙ B ∙Φ(C) for all A, B,C ∈ 𝓐 if and only if Φ is an additive *-derivation.
Learning to predict demand in a transport-resource sharing task

Abstract : Resource allocation problems occur in many applications. One example is bike-sharing systems, which encourage the use of public transport by making it easy to rent and return bicycles for short transits. With large numbers of distributed kiosks recording the time and location of rental transactions, the system acts like a sensor network for movement of people throughout the city. In this thesis, we studied a range of machine-learning algorithms to predict demand (ridership) in a bike-sharing system, as part of an online competition. Predictions based on the Random Forest and Gradient Boosting algorithms produced results that ranked amongst the top 15 of more than 3,000 team submissions. We showed that the mandated use of logarithmic error as the evaluation metric overemphasizes errors made during off-peak hours. We systematically experimented with model refinements and feature engineering to improve predictions, with mixed results. Reduction in cross-validation errors did not always lead to a reduction in test set errors. This could be due to overfitting and the fact that the competition test set was not a random sample. The approach in this thesis could be generalized to predict use of other types of shared resources.
Calendering of non-isothermal Rabinowitsch fluid

Abstract: A non-isothermal analysis of calendering by using the Rabinowitsch fluid model is presented in this article. The flow equations are simplified by utilizing the lubrication approximation theory. The exact expressions of velocity and pressure gradient are obtained. The pressure distribution and engineering quantities are computed numerically by employing the Runge-Kutta algorithm. The temperature distribution is obtained by solving the energy equation numerically using the hybrid numerical method. The influence of the involved parameters on the velocity profile, pressure, pressure gradient and mechanical quantities such as roll-separating force, power function and exiting sheet thickness are shown graphically. The temperature distribution at various axial points is also shown through graphs.
How the Equity Terminal Value Influences the Value of the Firm?

Abstract The discounted cash flow model (DCFM) views the intrinsic value of common stock as the present value of its expected future cash flows. This paper analyses whether the equity terminal value (EqTV) of the firm calculated by fundamentals is appreciated by the market. It also studies the impact of variations in EqTV and the extent to which the market perceives these variations. Using a sample of 62 Spanish listed companies, this paper shows that EqTV and its variations are positively and significantly correlated with EqTV assigned by the market and its corresponding variations. It therefore corroborates the validity and relevance of the valuation model.
Non-Markovian Reinforcement Learning for Reactive Grid scheduling

Two recurrent questions often appear when solving numerous real world policy search problems. First, the variables defining the so called Markov Decision Process are often continuous, that leads to the necessity for discretization of the considered state/action space or the use of a regression model, often non-linear, to approach the Q-function nee- ded in the reinforcement learning paradigm. Second, the markovian hypothesis is made which is often strongly discutable and can lead to unacceptably suboptimal resulting policies. In this paper, the job scheduling problem in grid infrastructure is modeled as a continuous action-state space, multi-objective reinforcement learning problem, under realistic assumptions ; the high level goals of users, administrators, and shareholders are captured through simple utility functions. So, formalizing the problem as a par- tially observable Markov decision process (POMDP), we detail the algorithm of fitted Q-function learning using an Echo State Network. The experiment, conducted on simu- lation of real grid activity will demonstrate the significative gain of the method against native scheduling infrastructure and a classic feed forward back-propagated neural net- work (FFNN) for Q function learning in the most difficult cases.
Operational amplifier with 1-V rail-to-rail multipath-driven output stage

A bipolar operational amplifier (op amp) with a rail-to-rail multipath-driven output stage that operates at supply voltages down to 1 V is presented. The bandwidth of this output stage is as high as possible, viz, equal to that of one of the output transistors, loaded by the output capacitance. The output voltage can reach both supply rails within 100 mV and the output current is +or-15 mA. The op amp is designed to be loaded by a 100-pF capacitor and the unity-gain bandwidth is 3.4 MHz at a 60 degrees phase margin. The voltage gain is 117 dB and the CMRR is 100 dB. The frequency behavior of the multipath-driven (MPD) topology has an improved performance when compared to that of previously presented low-voltage output stages. A figure of merit F/sub M/ for low-voltage op amps has been defined as the bandwidth-power ratio. >
Image-based visual servoing for mobile robots using neural networks and fuzzy-evolutionary methods

Presents an image based visual servoing method, which plans the navigation trajectory in the image plane for non-holonomic mobile robots. It does not require camera calibration nor coordinate transformation from image space to workspace. The robot navigates along a preplanned workspace trajectory while at the same time it learns, using neural networks, a desired or reference landmark trajectory in the image space. Each point of the reference trajectory is basically what is seen of the target landmark at each control cycle. After this network training, the robot compares the current landmark with not only the target landmark but also the reference landmark along the way. Using a fuzzy logic to control this error the mobile robot navigates through the learned trajectory in the workspace. The fuzzy logic is optimized by an evolutionary algorithm to meet a user-defined objective. The proposed algorithm has been verified via simulation.
Optimizing dual threshold shocks with right- and left-ventricular electrodes: simulating defibrillation with a human thorax model

This research focuses on developing new implantable cardioverter defibrillator (ICD) dual lead configurations that reduce the defibrillation threshold (DFT) energy by delivering a second threshold shock in the area where the conventional shock's electric field is weakest. The objective of this study is to optimize electrode placements for lead systems including left-ventricular (LV) electrodes. A physiologically realistic 3D finite element model of the human thorax is employed to compute DFTs. The lead configurations investigated consist of a conventional lead system (TRIAD/sup TM/, Guidant Corporation) and additional LV shocking electrodes placed in the apical and basal portion of the posteriolateral coronary vein or directly within the TRIAD system's weak field region. The LV electrodes measure 50 mm in length and 1 mm in diameter. The computed DFT energy for the TRIAD is 6.2 J, falling within one standard deviation of the mean DFT reported in clinical studies using the TRIAD leads. LV leads located in the apical and basal portion of the posteriolateral coronary vein result in a DFT of 3.1 J, a 50% reduction from the TRIAD alone. LV leads placed in the anterior, middle, and posterior TRLAD weak field result in a DFT of 2.9 J, 2.7 J., and 3.5 J, respectively, corresponding to a 44-56% reduction in DFT from the TRIAD. The results indicate that an additional electrode placed in the proximity of the TRIAD weak field is just as effective in reducing DFTs as one placed directly within the weak field.
Frame-level features conveying phonetic information for language and speaker recognition

This Thesis, developed in the Software Technologies Working Group of the Departmentof Electricity and Electronics of the University of the Basque Country, focuseson the research eld of spoken language and speaker recognition technologies.More specically, the research carried out studies the design of a set of featuresconveying spectral acoustic and phonotactic information, searches for the optimalfeature extraction parameters, and analyses the integration and usage of the featuresin language recognition systems, and the complementarity of these approacheswith regard to state-of-the-art systems. The study reveals that systems trained onthe proposed set of features, denoted as Phone Log-Likelihood Ratios (PLLRs), arehighly competitive, outperforming in several benchmarks other state-of-the-art systems.Moreover, PLLR-based systems also provide complementary information withregard to other phonotactic and acoustic approaches, which makes them suitable infusions to improve the overall performance of spoken language recognition systems.The usage of this features is also studied in speaker recognition tasks. In this context,the results attained by the approaches based on PLLR features are not as remarkableas the ones of systems based on standard acoustic features, but they still providecomplementary information that can be used to enhance the overall performance ofthe speaker recognition systems.
Two-Questions Vocabulary Assessment: Developing a New Method for Group Testing in Kindergarten through Second Grade

Methods of primary grades vocabulary assessment are inadequate for classroom teachers and researchers because they require one-on-one testing and much time. This study validates a new method of vocabulary assessment for use with a whole classroom at one time. With an individually-administered vocabulary test and a group-administered test created with the same words, we assessed 257 students in K-2 using both methods. Results showed that the group method yielded reasonable correlations with the one-on-one method (r=.69 to .75). This group method can now be used by primary grades teachers and researchers to quickly assess general vocabulary and instructed word meanings. This study describes an effort to validate a new and more practical method for assessing primary-grade vocabulary knowledge, which can be used with groups of students or with whole classes. The authors sought evidence that the method is reasonably accurate when compared with results obtained with a widely used individually administered vocabulary test for primarygrade children. If the new group method, called the “Two-Questions” method, could be shown to yield reasonably valid estimates of word meaning knowledge, it could be used to assess both general vocabulary knowledge and gains in vocabulary taught within the classroom. For this study, we selected word meaning items from the Peabody Picture Vocabulary Test-III, Form A (PPVT-III) (Dunn & Dunn, 1997) for use in the whole class assessment with the Two-Questions method. In each classroom our Two-Questions Vocabulary Measure (TQVM) was first administered to the whole class. The PPVT was then administered individually to those children for whom parental permission had been obtained. Group test results were not known prior to administering the PPVT-III. We assessed 259 students from 24 Kindergarten, Grade 1, and Grade 2 classrooms in three New England elementary schools with both measures to provide validation for the new group assessment method. The students and the schools are described, as are the two measures and their use. The need for the new method of assessing vocabulary for students in grades K–2 and the process used to create the measure are explained. The results of the scores on the group test and their correlation with the scores on the individually administered test are presented. We also discuss how the new Two-Questions method may be used to assess general vocabulary on an occasional basis and vocabulary taught in the classroom on an ongoing basis. Suggestions are provided for improving the method and for using this new assessment method to increase student achievement in reading beyond the primary grades.
Is theta burst stimulation ready as a clinical treatment for depression?

ABSTRACT Introduction: Major depression is a common and debilitating mental disorder that can be difficult to treat. Substantive evidence over the past two decades has established repetitive transcranial magnetic stimulation (rTMS) as an effective antidepressant therapy, although scope exists to improve its efficacy and efficiency. Theta burst stimulation (TBS) is a novel rTMS pattern attracting much research interest as a tool to study neurophysiology and treat neuropsychiatric disorders. Areas covered: This article outlines rTMS’ state of development and explores the physiology studies underpinning TBS development and its observable neuronal conditioning and metabolic effects. We present a systematic review of studies that applied TBS to treat depression, followed by commentary on safety and practical considerations. Expert opinion: Much experimental and clinical research have advanced our understanding of the antidepressant effects of TBS, although unanswered questions remain relating to its physiological effects, response variability and optimal parameters for therapeutic purposes. A small number of sham-controlled trials, and one large comparative trial, support the therapeutic efficacy of TBS and demonstrates its non-inferiority relative to traditional rTMS. In this light, TBS can reasonably be offered as an alternative to rTMS in treatment-resistant depression, while ongoing research is likely to inform its therapeutic potential.
A SOFTWARE TOOL FOR FASTER DEVELOPMENT OF COMPLEX MUSCULOSKELETAL MODELS IN SIMULINK

SIMM (Musculographics Inc., USA) is the only commercial software for developing anatomically realistic musculoskeletal models (Delp and Loan 2000). The user generates a set of input files describing bone surfaces, articulations, and muscle-tendon parameters, and uses SIMM to assemble these graphically into an anatomically realistic model (Fig. 1). With the help of SD/Fast (Symbolic Dynamic Inc., USA) SIMM generates a set of files in the programming language “C” containing the equations of motion for the musculoskeletal model. This process requires the user to understand the structure of the SIMMgenerated C-programs and to write additional programs for any other components required by the system under study (e.g. sensors, controllers). SIMM also has substantial limitations on its ability to incorporate run-time changes of muscle excitation, external forces, prescribed motion, and initial conditions, which handicap its use to study control algorithms. For example, the muscles can only be excited in an open-loop manner while many applications involve closed-loop control of muscles. Our main objective is to build reusable I/O blocks for different components of the neuromusculoskeletal systems. We have chosen to do this in Simulink (Mathworks Inc., USA), an attractive, easy to use, and popular software package for simulation of complex systems. One particularly relevant source of such component blocks is the Virtual Muscle package developed by Cheng et al. (2000), which generates Simulink blocks representing the forcegenerating properties of realistic muscle models with user-specifiable parameters.
Using Google Trends to understand information-seeking behaviour about throat cancer

Abstract Objective Many people seek health information from internet sources. Understanding this behaviour can help inform healthcare delivery. This study aimed to review Google Trends as a method for investigating internet-based information-seeking behaviour related to throat cancer in terms of quantity, content and thematic analysis. Method Data was collected using Google Trends. Normalised data was created using the search terms ‘throat cancer’, ‘cancer’, ‘HPV’, ‘laryngeal cancer’ and ‘head and neck cancer’. The search data was used to analyse the temporal and geographical interest pattern of these terms from 2004 to 2015. Results Three important peaks in searches for ‘throat cancer’ were identified. The first and greatest increase in interest was in September 2010, and there were also peaks in June 2013 and in October 2011. Conclusion Internet-search analysis can provide an insight into the information-seeking behaviour of the public. Mass media can hugely affect this information-seeking behaviour. Possessing tools to investigate and understand information-seeking behaviour may be used to improve healthcare delivery.
Burst-Correcting Codes for the Classic Bursty Channel

The purpose of this paper is to organize and clarify the work of the past decade on burst-correcting codes. Our method is, first, to define an idealized model, called the classic bursty channel, toward which most burst-correcting schemes are explicitly or implicitly aimed; next, to bound the best possible performance on this channel; and, finally, to exhibit classes of schemes which are asymptotically optimum and serve as archetypes of the burstcorrecting codes actually in use. In this light we survey and categorize previous work on burst-correcting codes. Finally, we discuss qualitatively the ways in which real channels fail to satisfy the assumptions of the classic bursty channel, and the effects of such failures on the various types of burst-correcting schemes. We conclude by comparing forward-error-correction to the popular alternative of automatic repeat-request (ARQ).