Miracle-dz/UniFAR-FTUs huggingface dataset:
Review of an alternative seating for Attention Deficit Hyperactivity Disorder (ADHD) children

One of the reasons for a child's academic success is his or her ability to attend to tasks given by the teacher in the classroom and meet the expectation with minimal distraction. For children with Attention Deficit Hyperactivity Disorder (ADHD), one of the biggest issues faced by them is their inability to sit focus and pay attention in the classroom. Without the treatment, ADHD children will face the serious physical injuries and also may impact his or her individual's life, including academic difficulties, social skills problems, and strained parent-child relationships. No treatment has been found to cure this disorder, but many available treatments can reduce the symptoms of ADHD. However, studies that examine the alternative treatment such as seating therapy for ADHD children are still very minimal. The aim of this study is to review various existing alternative seating use in the classroom for ADHD children. The objective of this study is to identify the existing alternative seating and analyze how they use the alternative seating as an intervention for children with ADHD. The study is conducted through a literature review of books, journal articles, and online resources, focusing on the intervention, improvement and treatment of ADHD children. The findings outline the effectiveness of alternative seating in treating ADHD children in reducing their behavior problem such as in-class sleeping behavior and hyperactivity levels. The findings also showed increasing in safety levels and ontask behavior. In addition, there is an increased the class environment in monitoring teaching and learning. Currently, there is still no National Policy specifically for children with disabilities. Therefore, the significant contribution of this study is towards the establishment of the National Policy specifically for children with disabilities; ADHD. The application of therapy treatments for the ADHD children should be spell in the National Policy for Children with Disabilities, to change the conventional treatment using medication that comes with side effects to their health.
A Contemplating approach for Hive and Map reduce for efficient Big Data Implementation

— In the reference current scenario, data is incremented exponentially and speed of data accruing at the rate of petabytes. Big data defines the available amount of data over the different media or wide communication media internet. Big Data term refers to the explosion in the quantity (and quality) of available and potentially relevant data. On the basis of quantity amount of data are very huge and this quantity has been handled by conventional database systems and data warehouses because the amount of data increases similarly complexity with it also increases. Multiple areas are involved in the production, generation, and implementation of Big Data such as news media, social networking sites, business applications, industrial community, and much more. Some parameters concern with the handling of Big Data like Efficient management, proper storage, availability, scalability, and processing. Thus to handle this big data, new techniques, tools, and architecture are required. In the present paper, we have discussed different technology available in the implementation and management of Big Data. This paper contemplates an approach formal tools and techniques used to solve the major difficulties with Big Data, This evaluate different industries data stock exchange to covariance factor and it tells the significance of data through covariance positive result using hive approach and also how much hive approach is efficient for that in the term of HDFS and hive query. and also evaluates the covariance factors after applying hive and map reduce approaches with stock exchange dataset of around 3500.After process data with the hive approach we have conclude that hive approach is better than map reduce and big table in terms of storage and processing of Big Data.
New Optimal High Efficiency Dsp-based Digital Controller Design For Super High-speed Permanent Magnet Synchronous Motor

This dissertation investigates digital controller and switch mode power supply design for super high-speed permanent magnet synchronous motors (PMSM). The PMSMs are a key component for the miniaturic cryocooler that is currently under development at the University of Central Florida with support from NASA Kennedy Space Center and the Florida Solar Energy Center. Advanced motor design methods, control strategies, and rapid progress in semiconductor technology enables production of a highly efficient digital controller. However, there are still challenges for such super high-speed controller design because of its stability, high-speed, variable speed operation, and required efficiency over a wide speed range. Currently, limited research, and no commercial experimental analysis, is available concerning such motors and their control system design. The stability of a super high-speed PMSM is an important issue particularly for open-loop control, given that PMSM are unstable after exceeding a certain applied frequency. In this dissertation, the stability of super high-speed PMSM is analyzed and some design suggestions are given to maximize this parameter. For ordinary motors, the V/f control curve is a straight line with a boost voltage because the stator resistance is negligible and only has a significant effect around the DC frequency. However, for the proposed super high-speed PMSM the situation is quite different because of the motor’s size. The stator resistance is quite large compared with the stator reactive impedance and cannot be neglected when employing constant a V/f control method. The challenge is to design an optimal constant V/f control scheme to raise efficiency with constant V/f control. iii In the development, test systems and prototype boards were built and experimental results confirmed the effectiveness of the dissertation system.
Effects of Corporate Social Responsibility on consumer brand loyalty

Purpose – This paper analyses the influence of CSR associations on brand loyalty. We propose a theoretical model that includes the mediating role of brand awareness, brand attitude and customer satisfaction in the effect of CSR on loyalty, measured as a second-order reflective construct. Design/methodology/approach – We propose a theoretical model estimated via the analysis of covariance structures using EQS 6.1. Data were obtained using an online survey of 351 Spanish sportswear consumers. Findings – This study illustrates that CSR associations have a direct, positive influence on loyalty, and an indirect influence through their positive effect on brand awareness and consumer satisfaction. Brand attitude does not appear to play a significant role in the influence of CSR on loyalty. Originality/value – We study the effect of CSR associations, brand awareness, satisfaction, and brand attitude as drivers of brand loyalty, conceived as a reflective second-order construct with four dimensions: attitudinal loyalty, purchase intention, expenditure level and intention to recommend. It is important to construct relational marketing strategies that integrate CSR with consumer orientation using the three dimensions of the model validated in the study: brand awareness, satisfaction and brand attitude.
Are memories consistent with experience? : exploring temporal aspects of hedonic website UX

Noponen, Sampo Are memories consistent with experience? Exploring temporal aspects of hedonic website UX Jyväskylä: University of Jyväskylä, 2019, 104 p. Information Systems, Master’s thesis Supervisors: Kyppö, Jorma; Silvennoinen, Johanna & Kujala, Tuomo This study explores the progression of single user experience over a short-term period in the context of websites. Depending on temporal distance between user and event of interaction, user experience can be divided into three phases: before, during and after interaction. Momentary emotions of pleasure and pain experienced during interaction largely determine the memory of user experience. Memories, however, do not always correspond with actual experience, and consequently people can form judgements and decisions that do not reflect their experience. Such memory biases might originate from sequencing effects: certain moments of an episode are more impactful to formation of retrospective evaluations than others. Due to the above reasons, this thesis examined how consistent hedonic retrospective website user experience evaluations tends to be with real-time evaluations. Thesis investigated influence of certain sequencing effects, such as peak-end effect, on retrospective evaluations. In recent years, practitioners have been increasingly interested in utilising animated transitions into interfaces. Yet there is scant research addressing how they influence user preferences. Therefore, this study additionally explored influence of animated transitions on user experience. Results were acquired with empirical user experiments where participants interacted with a website and quantitatively evaluated their experience. As it turned out, retrospective evaluations were mainly consistent with real-time evaluations, despite minor differences. Thus, it can be inferred that memory was consistent with actual experience. Strong peak-end, and recency effects were found, although effect size decreased in time. Lastly, animated transitions did not influence user experience. Explanations for these results are considered and future research possibilities are proposed.
Cross-Cultural Encounters in Giving Compliments and Making Requests through Literary Texts: Pedagogical Ramifications

Hall (1976) argued that communication is culturally indexed. In high-context cultures most information exists in the context where it is internalised by people when communicating or it can be found in the physical context (Hall, 1976). The context is essential because sometimes the text does not say what it is trying to convey but the situation and the discourse pattern may help one to determine the essence of the message. This is common in societies where people are indirect in their discourse, often done to minimise face-threatening acts which are considered to be polite. However, some people in other cultures may not view it in the same way and they may consider indirectness as impolite and directness as polite. In this regard, it is evident that different cultures may have different concepts of politeness (Watts, 2003).
Musical Organics: A Heterarchical Approach to Digital Organology

Abstract Gaining a comprehensive understanding and overview of new musical technologies is fraught with difficulties. They are made of digital materials of such diverse origins and nature, that they do not fit comfortably into traditional organological classifications. This article traces the history of musical instrument classifications relevant to the understanding of new digital instruments, and proposes an alternative method to the centuries-old tree-structure of downwards divisions. The proposed musical organics is a multidimensional, heterarchical, and organic approach to the analysis and classification of both traditional and new musical instruments that suits the rhizomatic nature of their material design and technical origins. Outlines of a hypothetical organological informatics retrieval system are also presented.
Accounting students access to social media related resources and the risk of tacit social exclusion

ABSTRACT The use of social media platforms to facilitate teaching and learning requires resources (hardware and Internet access) to enable active student participation. Limited access to these resources may impair students’ learning and, should the students consequently fail to graduate, tacitly contribute to their social exclusion. The results of a survey amongst students at a South African university, identified statistically significant differences relating to hardware and Internet access between more affluent students, and lower income students. Using social media may, therefore, be countering the objective of widening the admissions to universities in South Africa as an attempt to address past exclusionary practices. This study raises awareness with instructors and administrators globally, about the risk of tacit social exclusion, as a result of the tools selected to facilitate learning.
Mining Social Media for Political Communication: Lessons from an Analysis of Twitter Use between Citizens and the African National Congress pre-2014 South African National Elections

ABSTRACT Politweeting is becoming increasingly popular globally. It offers benefits to politicians and to citizens, especially during election periods. Twitter users in Africa are five times more likely to use the platform to voice their political views than those in the US and UK. Yet, few studies from African countries provide insight into such use. This paper attempts to provide insight into the use of the African National Congress (ANC) Twitter account by citizens and politicians in the run-up to the 2014 general elections. The Adaptive Structuration Theory is relevant to the study and netnography was applied to the study. Findings show that the platform was mostly used by citizens rather than the political party and its politicians. Citizens mostly engaged in political commentary amongst each other about party activities and officials. The political organisation mostly used it for image management for the party and its officials. If harnessed through planned design and implementation of digital communication strategies, social media has the potential to be used as effectively for mass communication, yet simultaneously enable interpersonal persuasion between participants, especially during times of elections.
The development of a concentration training model on free throw shots basketball players

The purposes of this study were to develop a concentration training model on free throw shots basketball players and to measure the extent of the process of concentration training model on free throw shots basketball players. The process of this research began with a need analysis with field observation method and continued with the process of the development of a concentration training model on free throw shots basketball players according to the characteristics needed. The development of this training model was carried out by applying 10 steps according to Brog and Gall and producing a product from concentration training model on free throw shots basketball players according to the needs and the suitability needed. Based on the results of the analysis on the small group trials the average choice was 82.10%, whereas in the medium group trials the average values obtained was 87.56%, while in the large group trials the average choice was 90.49 %. This stated that the concentration training model on free throw shots basketball players was very feasible to use.
Measuring Factors Affecting the Autonomy of Nurses Work

Research Aim: The research aimed to examine the factors that affecting the autonomy of nurses' work. Method: A cross sectional descriptive design was conducted in two of public hospitalsin KSA using a developed questionnaire. Randomsampling technique was utilized to choose 400 nurses in the participated hospitals. The collected data was analyzed using SPSS software version 21. Results: The findings showed there wasa significant correlation between nurses’ perception of autonomy of their work and organization culture and climate; relation and cooperation; training and development; compensation and rewards; and adequacy of resources and facilities. Conclusion: Many factor affecting the nurses' perception of their work including organization culture, relation and cooperation, compensation and rewards, training and development, and adequacy of resources.
Query Privacy And Data Confidentiality Using Random Space Perturbation In The Cloud

With the wide deployment of public cloud computing infrastructures, using clouds to host data query services has become an appealing solution for the advantages on scalability and cost-saving. However, some data might be sensitive that the data owner does not want to move to the cloud unless the data confidentiality and query privacy are guaranteed. On the other hand, a secured query service should still provide efficient query processing and significantly reduce the in-house workload to fully realize the benefits of cloud computing. We propose the random space perturbation (RASP) data perturbation method to provide secure and efficient range query and kNN query services for protected data in the cloud. The RASP data perturbation method combines order preserving encryption, dimensionality expansion, random noise injection, and random projection, to provide strong resilience to attacks on the perturbed data and queries. It also preserves multidimensional ranges, which allows existing indexing techniques to be applied to speedup range query processing. The kNN-R algorithm is designed to work with the RASP range query algorithm to process the kNN queries. We have carefully analyzed the attacks on data and queries under a precisely defined threat model and realistic security assumptions. Extensive experiments have been conducted to show the advantages of this approach on efficiency and security.
Mining strong jumping emerging patterns with a novel list data structure

Strong Jumping Emerging Patterns (SJEPs) are data mining patterns which have strong discriminating abilities in classification. However, SJEPs mining algorithms in current years are usually achieved by the data structure, tree. These existing algorithms using the tree structure are difficult to achieve excellent performance. In this paper, we propose a novel method of mining SJEPs named PPSJEP. This algorithm is based on a novel data structure called NSJEP-list, which is improved from the N-list. We use the NSJEP-lists to replace the tree structure. First, we get the individual items’ NSJEP-lists from the tree. Then we use the intersection of NSJEP-lists to get the longer itemsets’ NSJEP-lists which includes the information of the position and the count in each class. And we mine the SJEPs through the information. Experiments are performed on six UCI datasets. Compared with existing algorithm in running time and classification accuracy, the experimental results show that our algorithm uses less time to mine SJEPs and get the same classification accuracy, especially in lower minimum support threshold.
Size and Value Premium in Karachi Stock Exchange

This study evaluates the ability of the Fama and French Three Factor model to explain a cross section of stock returns in the Karachi Stock Exchange (KSE). Following Fama and French factor approach, we sorted six portfolios by size and book to market. The sorted portfolios were constituted to represent stocks from each and every sector of KSE. Using Daily returns from January 2003 to December 2007, the excess returns for each portfolio were regressed on market, size and value factors. Our findings, in general, supported the notion of the three factor model. The three factor model was able to explain the variations in returns for most of the portfolios and the results remain robust when the sample was reduced to control for the size effect. Our findings are consistent with most of the studies that suggested the validity of the three factor model in emerging markets. These results warrant for the inclusion of size and value factors for valuation, capital budgeting and project appraisals, thus, having substantial implications for fund managers, analysts and investors.
Pre-stimulus Brain Activity Is Associated With State-Anxiety Changes During Single-Session Transcranial Direct Current Stimulation

Transcranial direct current stimulation is a promising neuromodulation method for treating depression. However, compared with pharmacological treatment, previous studies have reported that a relatively limited proportion of patients respond to tDCS treatment. In addition, the neurophysiological mechanisms underlying tDCS treatment remain unclear, making it difficult to identify response predictors for tDCS treatment based on neurophysiological function. Because treatment effects are achieved by repetitive application of tDCS, studying the immediate effects of tDCS in depressive patients could extend understanding of its treatment mechanisms. However, immediate changes in a single session of tDCS are not well documented. Thus, in the current study, we focused on the immediate impact of tDCS and its association with pre-stimulus brain activity. To address this question, we applied anodal tDCS to the left dorsolateral prefrontal cortex (DLPFC) or dorsomedial prefrontal cortex (DMPFC) in 14 patients with major depressive disorder (MDD) and 19 healthy controls (HCs), at an intensity of 1.0 mA for 20 min in a single session. To evaluate anxiety, the state trait anxiety inventory was completed before and after tDCS. We recorded resting electroencephalography before tDCS, and calculated electrical neuronal activity in the theta and alpha frequency bands using standardized low-resolution electromagnetic tomography. We found that, during application of left DLPFC tDCS to patients with MDD, the anxiety reduction effect of tDCS was related to higher baseline theta-band activity in the rostral anterior cingulate cortex (rACC) and no medication with benzodiazepine used as hypnotic. For DMPFC stimulation in MDD, the anxiety reduction effect was associated with lower baseline alpha-band activity in the left inferior parietal lobule. In contrast, in HCs, the anxiety reduction effect was associated with higher baseline alpha activity in the precuneus during DMPFC stimulation. The current results suggest that the association between pre-tDCS brain activity and the anxiety reduction effect of tDCS depends on psychopathology (depressed or non-depressed) as well as the site of stimulation (DMPFC or left DLPFC) and insomnia. Furthermore, the results suggest that tDCS response might be associated with baseline resting state electrophysiological neural activity.
La inhibición, el autocontrol emocional, la memoria de trabajo y la supervisión ¿predicen las manifestaciones típicas de adultos con TDAH?

Introducción. Los déficits en inhibición, control emocional, memoria de trabajo y supervisión se han evidenciado en numerosas investigaciones focalizadas en el trastorno por déficit de atención con hiperactividad (TDAH), pero la información sobre su posible influencia diferencial en las manifestaciones características del trastorno es escasa. Objetivos. El presente estudio se propuso analizar las relaciones de las funciones ejecutivas de regulación (inhibición y control emocional) y metacognitivas (memoria de trabajo y supervisión) con manifestaciones del TDAH y determinar el poder de predicción de esas cuatro funciones ejecutivas en dichas manifestaciones. Método. Sesenta y un jóvenes adultos entre18 y 24 años con un diagnóstico clínico de subtipo combinado de TDAH en la infancia completaron la Escala Conners de síntomas de TDAH y el Inventario de Funcionamiento Ejecutivo (BRIEF). Resultados. Se encontraron relaciones estadísticamente significativas entre inhibición, regulación emocional, memoria de trabajo y supervisión y las subescalas del Conners. Además, los déficits en las funciones ejecutivas fueron diferencialmente sensibles en la predicción de problemas significativos del TDAH. La memoria de trabajo y la supervisión fueron predictores de los problemas de atención, la inhibición predijo los problemas de autoconcepto y la hiperactividad/ inquietud mientras que el autocontrol emocional fue el mejor predictor de la impulsividad. Conclusiones. La medida de funciones ejecutivas de regulación y metacognitivas pueden ayudar tanto en el diagnóstico como en las evaluaciones de seguimiento del tratamiento de adultos con TDAH.