Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effects of Core Stabilization Training on Balance and Reaction Time in Children with Developmental Coordination Disorder

رب یاهدرکلمع یلیصحت و یعامتجا یم نانآ . دراذگ ینغ هک دراد دوجو لامتحا نیا ندومن ،یتکرح براجت ییاناوت کدوک ار رد کرد و تخانش فده یاه ،یتخانش هطیح یفطاع و یناور یتکرح شیازفا . دهد ماجنا زا فده اذل شهوژپ سکع نامز و لداعت رب یزکرم تابث تانیرمت ریثأت رضاح شهوژپ نیا . تسا یدشر یگنهامه للاتخا اب ناکدوک لمعلا یبرجت همین عون زا تسا ناکدوک نیب زا . 6 ات 21 لاس هعجارم یدشر یگنهامه للاتخا هب لاتبم ناوت زکارم هب هدننک شخب ی ،نارهت رهش 12 باختنا یفداصت روط هب رفن نامز تاعلاطا یروآدرگ یارب . دندش میسقت لرتنک و یبرجت هورگ ود رد و نومزآ زا بیترت هب ایوپ لداعت و اتسیا لداعت ،شنکاو حلاصا ،هتسویپ درکلمع یاه دافتسا یاو لداعت و کل کل هدش . دش ه شیپ زا دعب تدم هب یبرجت هورگ ،نومزآ تشه هتفه ره ،هتفه هس هسلج ره و هسلج 54 ت هقیقد ار یزکرم تابث تانیرم یرادانعم تفرشیپ یبرجت هورگ هک داد ناشن جیاتن . دش هدافتسا جیاتن لیلحت یارب سنایراووک لیلحت نومزآ زا . دنداد ماجنا ( تسا هدرک بسک ایوپ و اتسیا لداعت ،شنکاو نامز ریغتم هس ره رد ار 24 / 2 ≥ P توافت لرتنک هورگ رد هک یلاح رد ؛) دشن هدهاشم یرادانعم ( 24 / 2 ≤ P هتفای .) ىاه شهوژپ رضاح ناشن داد هک یارب ءاقترا حطس تراهم یاه ناکدوک یتکرح همانرب ،یدشر یگنهامه للاتخا اب یاه تیلاعف یندب هژیو تانیرمت لماش هک یا نامز و لداعت دوبهب تهج یزکرم تابث شنکاو رد دشاب رانک رگید همانرب یم یشزومآ یاه . دوش عقاو دیفم دناوت هژاو :یدیلک یاه . یزکرم تابث تانیرمت ،ایوپ لداعت ،اتسیا لداعت ،شنکاو نامز ،یدشر یگنهامه للاتخا
Analysis of a Content-based Needs Assessment Survey for Physics Teachers

The purpose of the study is to develop and analyze a content-based needs assessment survey for physics teachers. For this aim, a Teacher Survey on the Nature of Physics (TSNOP) was developed as a measurement instrument for the study. The TSNOP was used to identify inservice physics teachers’ needs, wishes, expectations and problems for the Nature of Physics (NOP) unit of a Professional Development Program (PDP). A total of 60 inservice physics teachers participated in the study. TSNOP includes four specific content areas; NOP knowledge and its misconceptions, teaching strategies (methods, techniques), materials and technology, and assessment techniques. The TSNOP consists of structured and unstructured question formats. The survey was analyzed based on dimensions and thematic coding, followed by frequency analysis with data was represented through tables. The TSNOP results are presented and discussed under four dimensions; (a) participant demographics, (b) teachers’ previous professional experience, (c) how PDPs can be organized (e.g., type, context, roles, time), and (d) teachers’ opinions about the training. Implications for teacher training and professional development were also discussed in the study.
LEACH: Energy Efficient Routing Protocol for WSNs along with its Enhancements

-Wireless Sensor networks are a standout in the midst of the many recent and rousing research disciplines of our time. They comprise impending to be employed for a variety of mission-critical applications. The biggest and most imperative challenge that wireless sensor network is facing these days is energy. There are numerous constraints in the minute sensor nodes like limited memory, power, bandwidth and processing capability. Since the nodes are deployed in an unattended area it makes the energy requirements of these nodes a big concern. Lot of investigation is done in command to formulate proficient routing algorithms which make nominal use of energy giving energy efficient routing protocols for WSNs. This paper gives a concise introduction to wireless sensor networks and its routing schemes classified on the root of network structure. The key focus of this study is on LEACH which is a cluster based routing protocol for sensor networks and several modifications made to LEACH resulting in Modified LEACH (MODLEACH) that boasts the performance even more. MODLEACH is further enhanced to improve energy efficiency for routing protocols in WSNs resulting in EMODLEACH. Finally a comparison is carried out among the different variants of LEACH routing protocol taking several metrics like network lifetime, throughput and cluster head replacements under consideration.
Evaluation of Dennettia tripetala Baker F. Leaf Aqueous Extract Effect on Hyperthyroidism in Albino Rats

This study evaluated Dennettia tripetala leaf aqueous extract effect on hyperthyroidism in albino rats ( Rattus norvegicus ). It was conducted at the Department of Zoology and Environmental Biology, University of Nigeria, Nsukka. It lasted for seven weeks. Seventy-two male albino rats (Rattusnovergicus) weighing 66 – 108 g were assigned into six groups (A – F) with twelve rats (replicated three times, four rats per replicate) in each group. Three rats from each group were randomly selected and weighed before samples of blood were collected at days 7, 14, 21 and 28. Hyperthyroidism was induced in rats of groups B – F, orally with 600 µg/kg Levothyroxine for 14 days. Phytochemical screening of the extract was conducted. Whereas normal control (group A) and hyperthyroid control (group B) were fed water and food only, standard control (group C) received 1.35mg/kg of Carbimazole orally. The treatment groups were D – 100 mg/kg, E – 250 mg/kg and F – 500 mg/kg. Rats’body weights were determined at days 0, 7, 14, 21 and 28 during treatment. The extract’s effect on hyperthyroid induced rats total cholesterol (TC), triglyceride (TG), low-density lipoproteins (LDL), high-density lipoproteins (HDL), thyroid stimulating hormone (TSH), triiodothyronine (T3), tetraiodothyronine(T4) and histology of thyroid gland were evaluated. Phytochemical screening recorded some secondary metabolites. Toxicity (LD50) test recorded no lethal effect at the highest dose (5000 mg/kg) administered. The extract graded dose effect was most effective on body weight on Day 7. It also caused a significant increase (P<0.05) in TC, LDL-C, TG, and TSH but significantly decreased (P<0.05) HDL-C and T3 and T4 compared with hyperthyroid control. Micrographs from extract treated rats showed no histologic alteration. However, there were observed variations in body weight, LDL-C, TG, TSH and T 4 the body weight at day 0 due to age differences among animals used. Aqueous Dennettiatripetala leaf extract seems to possess potential for ameliorating post induced hyperthyroidism effects in rat. Keywords: Albino rat, Dennettia tripetala , Hyperthyroidism, Phytochemical screening, Lipid profile, Histopathology DOI : 10.7176/JNSR/9-8-05 Publication date : April 30 th 2019
Desarrollo de un estabilizador de potencia para una máquina síncrona usando técnicas de auto-sintonización Development of a Power Stabilizer for a Synchronous Machine Using Self-Tuning Techniques

One of the problems that affect power quality is related to oscillatory instability of synchronous machines. Supplementary field controls as the power system stabilizer (PSS) are normally used to maintain the stability. This paper shows a PSS implementation by using an adaptive technique to . COn-CienCiaS overcome sorne instability problems, mainly caused by sudden load ofvoltage reference variations. As a result, tests performed in a real machine show the good behavior of the PSS. This experimental validation of the theoretical postulates shows the applicability and the efficiency of the approach proposed here.
Blurring the Line Between Human and Machine: Marketing Artificial Intelligence

Blurring the Line Between Human and Machine: Marketing Artificial Intelligence Noah Castelo One of the most prominent and potentially transformative trends in society today is machines becoming more human-like, driven by progress in artificial intelligence. How this trend will impact individuals, private and public organizations, and society as a whole is still unknown, and depends largely on how individual consumers choose to adopt and use these technologies. This dissertation focuses on understanding how consumers perceive, adopt, and use technologies that blur the line between human and machine, with two primary goals. First, I build on psychological and philosophical theories of mind perception, anthropomorphism, and dehumanization, and on management research into technology adoption, in order to develop a theoretical understanding of the forces that shape consumer adoption of these technologies. Second, I develop practical marketing interventions that can be used to influence patterns of adoption according to the desired outcome. This dissertation is organized as follows. Essay 1 develops a conceptual framework for understanding what AI is, what it can do, and what are some of the key antecedents and consequences of its’ adoption. The subsequent two Essays test various parts of this framework. Essay 2 explores consumers’ willingness to use algorithms to perform tasks normally done by humans, focusing specifically on how the nature of the task for which algorithms are used and the human-likeness of the algorithm itself impact consumers’ use of the algorithm. Essay 3 focuses on the use of social robots in consumption contexts, specifically addressing the role of robots’ physical and mental human-likeness in shaping consumers’ comfort with and perceived usefulness of such robots. Together, these three Essays offer an empirically supported conceptual structure for marketing researchers and practitioners to understand artificial intelligence and influence the processes through which consumers perceive and adopt it. Artificial intelligence has the potential to create enormous value for consumers, firms, and society, but also poses many profound challenges and risks. A better understanding of how this transformative technology is perceived and used can potentially help to maximize its potential value and minimize its risks.
Feature aware sampling and reconstruction

Feature-aware sampling and reconstruction are important and widely studied topics in computer graphics. There has been a large amount of work proposed in the past decades for different applications. Nevertheless, the problems remain challenging. Among them, two of the challenges caught particular attentions. One is the lack of a universal definition of “feature” and the other is the lack of effective algorithmic tools to describe, extract as well as manipulate shapes and their features, especially for high dimensional complex data. This dissertation work is dedicated to tackling these two challenges. First, we focus on two and three dimensional shapes, and propose a generic feature aware sampling strategy that is applicable in a general setting. Secondly, for more complex and potentially high dimensional shape/spaces, we provide a study focusing on reconstructing a specific family of feature structure – 1D skeleton, which has many applications in modern data analysis. Specifically, we achieve both of them by using geometric and topological methods. Sampling a domain embedded in two or three-dimensional space is a fundamental topic in computer graphics. Recently, sampling methods with both randomness and uniformity have attracted great attention. At this frontier, blue noise sampling has been widely used for its effectiveness in reducing both the reconstruction artifacts and the information bias. However, most traditional uniform blue noise sampling
Objectively estimating the temporal evolution of accuracy and skill in a global ocean reanalysis

The accuracy of ocean reanalyses is acknowledged to have increased dramatically during the last few decades, as a consequence of the evolution of the oceanic and atmospheric observing networks. Because of evolution of the atmospheric observing system, a similar accuracy increase also occurs in assimilation‐free global ocean simulations. However, the temporal evolution of traditional accuracy metrics based on comparing reanalyses with observations is affected by the change in the number and spatial sampling of the verifying observations themselves. To disentangle the accuracy evolution and the changes in the verifying dataset, procedures insensitive to the latter are recommended. A simple and easy‐to‐implement methodology inspired by bootstrapping is proposed, specifically conceived for objectively estimating the accuracy and skill evolution of reanalyses over long (e.g. inter‐decadal) periods. This allows the artificial impact of the observational network evolution on the verification metrics, which generally led to under‐estimated accuracy at the beginning of the reanalysis period and much too sharp an increase later, to be overcome. Applied to the assessment of ocean temperature accuracy and skill in a state‐of‐the‐art eddy‐permitting global ocean reanalysis covering the period 1982–2012, the methodology illuminates the crucial impact on the upper ocean (top 100 m) reanalysis skill of both the atmospheric and oceanic observing network evolution, the former leading to a quicker skill increase. Conversely, the fundamental effect of the oceanic observing network below 100 m emerges from the study, as the assimilation‐free simulation shows no skill at any time in the comparison against observations.
An Integration Framework on Cloud for Cyber-Physical-Social Systems Big Data

A tremendous challenge in the development of Cyber-Physical-Social Systems (CPSS) is to integrate the growing volume and wide variety of data generated from multiple sources. To address the challenge, this paper presents an integration framework on cloud consisting of five functionally complementary processes, namely data representation, dimensionality reduction, relation establishment, data rank and data retrieval. The unstructured, semi-structured and structured data in the cyber, physical and social space are first represented as low-order data tensors, and then transformed to a three-order feature tensor for relation establishment. A similarity-based multi-linear data rank approach is proposed to measure the importance of the CPSS big data, and an incremental method is explored to rapidly and accurately update the rank vector. This paper, through a smart home case study, illustrates a practical application of the proposed integration framework, and evaluates the performance of the multi-linear data rank approach as well as the incremental rank update method. The results reveal that the proposed framework is feasible and competitive to integrate the CPSS big data on cloud.
Directive-based General-purpose GPU Programming

Directive-based General-Purpose GPU Programming Tian Yi David Han Master of Applied Science Graduate Department of Electrical and Computer Engineering University of Toronto 2009 Graphics Processing Units (GPUs) have become a competitive accelerator for nongraphics applications, mainly driven by the improvements in GPU programmability. Although the Compute Unified Device Architecture (CUDA) is a simple C-like interface for programming NVIDIA GPUs, porting applications to CUDA remains a challenge to average programmers. In particular, CUDA places on the programmer the burden of packaging GPU code in separate functions, of explicitly managing data transfer between the host and GPU memories, and of manually optimizing the utilization of the GPU memory. We have designed hiCUDA, a high-level directive-based language for CUDA programming. It allows programmers to perform these tedious tasks in a simpler manner, and directly to the sequential code. We have also prototyped a compiler that translates a hiCUDA program to a CUDA program and can handle real-world applications. Experiments using seven standard CUDA benchmarks show that the simplicity hiCUDA provides comes at no expense to performance.
Digital labour shortage : a new divide in library and information studies education?

This paper offers a preliminary reflection on the degree to which the concept of 'digital labour' appears in current library and information studies (LIS) education language, including in course titles, course descriptions, and course content. A basis for this paper was established from September 2010 to April 2011 through examination of a global range of online publicly accessible LIS program information. First stage analysis indicates that LIS education language appears to treat digital labour reductively; it fails to account for the labour conditions that frame the work. A tightening of the search examined evidence of critical teaching and learning of digital labour that allow for determinations of how the digital work environment relates to library labour rights and movements. This resulted in a scan of English language and translated information for a total of 121 individual LIS programs. Several trends emerged, which suggest that digital labour is generally, and most often out of necessity, inherently connected to other issues studied in LIS programs. A potential, yet unborn, paradigm in LIS education negates the basic notion of digital labour movement. Recommendations include research into the potential value of teaching and learning about the theory and practice of digital labour, a more sufficient and sophisticated approach to digital labour within LIS education in foundations courses, and a proposed set of possible advanced topics for teaching and learning in LIS education. Limitations of this topical exploration include what might be explained by the unknown factor of what is actually unseen from publicly accessible documents. To test the meaning of our first-stage work, future inquiry might involve interviews with teachers and looking into classroom communication of learners to see how the idea of digital labour is being addressed by them even if it is only in the most subtle manner.
INDEX-BASED JOIN IN MAPREDUCE USING HADOOP MAPFILES

Map Reduce stays an important method that deals with semi-structured or unstructured big data files, however, querying data mostly needs a Join procedure to accumulate the desired result from multiple huge files. Indexing in another hand, remains the best way to ease the access to a specific record(s) in a timely manner. In this paper, the authors are investigating the performance gain by implementing Map File indexing and Join algorithms together. Article DOI: https://dx.doi. org/10.20319/mijst.2016. s21.200213 This work is licensed under the Creative Commons Attribution-Non-commercial 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.
A proof method for run—time properties of Prolog programs

We propose a notion of correctness with respect to types for pure Prolog programs, which naturally combines types and directionalities. On this basis, we develop a simple method for proving various run-time properties of pure Prolog programs. These include analysis of generalized directlonalities, verification of absence of errors in programs extended with arithmetic built-in's, and absence of floundering in programs with negation. The method is illustrated on a number of realistic programs, including some operating on incomplete data structures. An adaptation of the method to logic programming is also provided.
Digital Video Scrambling Method using Intra Prediction Mode of H.264

The amount of digitalized contents has been rapidly increased, but the main distribution channel of them is Internet which is easily accessible. Therefore 'security' necessarily arises as one of the most important issues and the method of protecting contents becomes a major research topic as much as data coding techniques. In recent years, many developers have studied on techniques that allow only authorized person to access contents. Among them the scrambling method is one of well-known security techniques. In this paper, we propose a simple and effective digital video scrambling method which utilizes the intra block properties of a recent video coding technique, H.264. Since intra prediction modes are adopted in H.264 standard, it is easy to scramble a video sequence with modification of the intra prediction modes. In addition to its simplicity, the proposed method does not increase bit rate after scrambling. The inter blocks are also distorted by scrambling intra blocks only. This paper introduces a new digital video scrambling method and verifies its effectiveness through simulation.
Survey :Various Prediction Algorithms for Chemical Bond Formation on GPU

Nowadays, the persuit of prediction of chemical bond formation among researchers is evident to discover new drugs or for new discovery of chemicals. Predictive modeling gives statistics to predict outcomes. Most of time the event one wants to predict is in the future, but predictive modeling applicable to any type of event, regardless of when it occurred. In this paper, we focused on comparative analysis of various Prediction algorithms to estimate the best algorithm for the prediction of chemical bond formation with observations. The performances of these techniques are compared and it is observed that parallel Genetic Algorithm provides better performance results in accuracy and speedup as compared to other prediction techniques on GPU.
Elementary Teacher Professional Development for Computer Science and Digital Game-Based Learning

ii Dedication . iii Acknowledgments. iv List of Tables . x Chapter 1: Introduction to the Problem . 1 Conceptual Framework for the Problem . 4 Statement of the Problem . 5 Purpose of the Study . 6 Research Questions . 7 Rationale, Relevance, and Significance of the Study. 7 Definition of Terms . 9 Assumptions, Limitations, Delimitations . 12 Summary . 13 Chapter 2: Literature Review . 16 Conceptual Framework . 17 Review of Research Literature and Methodological Literature . 19 Search Strategy . 19 Federal Computer Science for All Initiative . 20 New York City Computer Science for All . 21 Florida Computer Science for All . 23 Technology Education Research in Florida . 25 Current State of Computer Science in Education . 28
A new min-cut problem with application to electric power network partitioning

The problem of partitioning a graph into two or more subgraphs that satisfies certain conditions is encountered in many different domains. Accordingly, graph partitioning problem has been studied extensively in the last 50 years. The most celebrated result among this class of problems is the max flow = min cut theorem due to Ford and Fulkerson. Utilizing the modifications suggested by Edmonds and Karp, it is well known that the minimum capacity cut in the directed graph with edge weights can be computed in polynomial time. If the partition divides the node set V into subsets V1 and V2, where V1 contains one of the specified nodes s and V2 contains the other specified node t, the capacity of a cut is defined as the sum of the edge weights going from V1 to V2. In electrical power distribution networks, a slow-coherency-based islanding strategy is used as a prevention against the cascading failures. In this paper, we concentrate on the graph partition problems which are encountered in electric power distribution networks. In this environment, two different definitions of capacity of a cut are used. In the first definition, capacity of a cut is taken to be the difference of the edge weights going from V1 to V2 and from V2 to V1. In the second definition, the capacity of a cut is taken to be the maximum of sum of the edge weights going from V1 to V2 and from V2 to V1. Surprisingly, with slight change of the definition of the capacity of a cut, the computational complexity of the problem changes significantly. In this paper, we show that with the new definitions of the capacity of a cut, the minimum cut computation problem becomes NP-complete. We provide an optimal solution to the problems using mathematical programming techniques. In addition, we also provide heuristic solutions and compare the performance with that of the optimal solution. Copyright © 2008 John Wiley & Sons, Ltd.