Miracle-dz/UniFAR-FTUs huggingface dataset:
LEADERSHIP STYLES AS PREDICTORS TO SUCCESS OF SCIENTIFIC-RESEARCH INSTITUTIONS IN BOSNIA AND HERZEGOVINA

Changes that accompany the 21st century require, as well as to various economic subjects as well as scientific-research institutions, constant awareness and readiness to expedite endeavors. Searching for competitiveness, and thus success, management requires that almost all resources are provided to meet the fulfillment of goals, and establish adequate relationships and culture within the organization. Significant role in this process certainly has a leadership phenomenon that is a key function in business. The leader of scientific-research institutions must possess charisma, a clear vision, and there is also a person the followers point loyalty to. The paper presents the results of the research conducted with the aim to determine the influence of leading styles on better business results and greater competitiveness of the scientific research institutions (43 institutions) of Bosnia and Herzegovina. The results showed that management of 79% of institutions preferred the transactional style of leadership. The results (F (3,326) = 11.20; p=. 03; f²=. 26)) also show that leadership styles can explain 20.4% of the mid-effect criterion variance and the model as a whole is statistically significant. In addition - a statistically significant unique contribution gives only the transactional style of leadership (β =.487; p=.014). Keywords: Styles of leadership, scientific-research institutions, performance indicatorsJEL:I31, M12, M19
A Ontology-based Document Feature Extraction

To effectively reduce the dimension of document vectors,we introduce a novel method employing domain ontology to extract feature concept. For all document categories,all raw words in each category are mapped to concepts in their relative concept tree derived from the domain ontology. At the same time the frequency of raw words is transformed into the frequency of concepts. Experimental results show that this method can effectively reduce the dimension of document vectors without loss of categorization accuracy,compared with traditional document vectors.
Design of order statistics filters using feedforward neural networks

In recent years significant progress have been made in the development of nonlinear data processing techniques. Such techniques are widely used in digital data filtering and image enhancement. Many of the most effective nonlinear filters based on order statistics. The widely used median filter is the best known order statistic filter. Generalized form of these filters could be presented based on Lloyd's statistics. Filters based on order statistics have excellent robustness properties in the presence of impulsive noise. In this paper, we present special approach for synthesis of order statistics filters using artificial neural networks. Optimal Lloyd's statistics are used for selecting of initial weights for the neural network. Adaptive properties of neural networks provide opportunities to optimize order statistics filters for data with asymmetric distribution function. Different examples demonstrate the properties and performance of presented approach.
Revisiting How and Why Educators Use Twitter: Tweet Types and Purposes in #Edchat

Abstract This study revisits the Carpenter and Krutka survey of how and why educators use Twitter, through exploring one of Twitter’s oldest education hashtags: #Edchat. From October 1, 2017, to June 5, 2018, more than 1.2 million unique #Edchat tweets were collected from approximately 200,000 different tweeters. Machine coding was used to answer “What types of tweets did users contribute to #Edchat? ” and human coding to answer “What purposes are observable in these tweets? ” The results showed that #Edchat has been used effectively for exploring ideas but underutilized for sharing emotions—with mixed results for capitalizing on the advantages of Twitter’s online environment. Further research is required to explore combating teacher isolation and experiencing a sense of camaraderie. Taking into account these results, practitioners should be clear regarding their goals for Twitter education hashtag use when considering #Edchat, and researchers studying different education hashtags should keep in mind various tweet types, modes, and purposes. (Keywords: Twitter, hashtag, affinity space, social media, teacher)
Design and Development of Stemmer for Tamil Language: Cluster Analysis

Stemming is a technique to transform different inflections and derivations of the same word to one root word "stem". Stemming means removal of both prefix and suffix. It is useful in many areas of computational linguistics and information retrieval work for improving their performance. This paper proposes improved light stemming algorithm for getting stemmed Tamil word with less computational steps. Further K-Means clustering algorithm utilized to cluster the stemmed Tamil Words in order to improve the performance of Tamil language Information Retrieval System. The experimental results clearly shows that the words stemmed after clustering gives better result compared to words stemmed before clustering. This may increases performance of the Tamil language Information Retrieval System.
“I'm not the anti-smoker now. I just don't smoke anymore”: social obstacles to quitting smoking among emerging adults

Abstract Background: Emerging adulthood presents unique challenges to smoking cessation that are not well understood. During this phase, smoking identities can develop that become obstacles for quitting, particularly in social situations where smoking is accepted and expected. Using a social identity approach, this study explores how social relationships and normative group behaviours can be barriers to transitioning from a smoker to non-smoker identity. Method: Six focus groups of five participants (N = 30) were conducted with participants aged 18-25 years (57% male). Participants’ smoking status was ascertained to construct six groups, two each of daily smokers, occasional (non-daily) smokers, and ex-smokers. Results: Salient in-group identities invoked out-group comparisons that could create barriers to change including feeling conflicted about becoming a “non-smoker”, and maintenance of pro-smoking group norms. Three subthemes were identified: 1) Managing the division between smoker and non-smoker groups; 2) The isolation associated with navigating others’ expectations about quitting when attempting to quit; and 3) Encountering normative in-group smoking-related behaviours when attempting to quit. Conclusions: The transition from smoker to non-smoker, when understood from a social identity approach, is not straightforward. Identifying as a smoker can invoke negative judgements from non-smokers while, conversely, attempting to quit may lead to perceived rejection among smokers. Further research is needed to explore whether perceptions of social risk can be reduced by increasing the salience of a transitional “quitter” identity that helps to reduce the perceived gap between “smoker” and “non-smoker”.
An Improved Loop Closure Detection Algorithm Based on Historical Model Set

An improved loop closure detection algorithm based on historical model set is proposed to improve the precision ratio and real-time performance of loop closure detection in mobile robot SLAM(simultaneous localization and mapping). First of all, the descriptor of feature is added to the model on the basis of frame-to-model registration model based on Kinect sensor, and it is updated with a weighting method to construct historical model set. A visual vocabulary tree is used for scene description of the historical model set and current frame. Then the pyramid TF-IDF(term frequency-inverse document frequency) scoring match scheme is improved by using inverse proportional function instead of minimum function to optimize the similarity score at a single node between two images. On one hand, the perceptual aliasing can be reduced with the improved scoring match scheme, and thus the precision ratio of loop closure detection is increased. On the other hand,by using the improved scoring match scheme, the affiliation between current frame and historical model set can be judged effectively with fewer number of comparison than the traditional frame-by-frame comparison method, so that the real-time performance of loop closure detection is improved. Next, the improved pyramid TF-IDF scoring match scheme is utilized for the similarity analysis between current frame and the keyframes affiliated to the candidate historical model set to extract candidate loop closure. Finally, the outliers in the candidate loop closure are discarded according to temporal continuity and epipolar geometry constraints. Contrast experiments based on the datasets and the actual scene show that, compared with the IAB-MAP(incremental appearance-based mapping), FAB-MAP(fast appearance-based mapping) and RTAB-MAP(realtime appearance-based mapping), the improved loop closure detection algorithm proposed has better real-time performance and higher recall ratio in the case of 100% precision ratio.
Study and Simulation of the Acoustic Features in Speaker Recognition System

In speaker recognition system, it抯 one of the key problems to extract the valid acoustic features that can represent speaker抯 characters. Several kinds of important features are studied and extracted, include linear prediction cepstrum coefficients (LPCC), mel-frequency cepstrum coefficients (MFCC), acoustic dynamic feature etc. These features are analyzed and compared, and the mixed features? effect on the performance of the recognition system is also researched. The simulation results show that the mixed features can obviously improve the recognition accuracy of the speaker recognition system.
A statistical approach for studying urban human dynamics

espanolEsta tesis doctoral propuso varios enfoques estadisticos para analizar la dinamica urbana con el objetivo de proporcionar herramientas para los procesos de toma de decisiones y estudios urbanos. Supuso que la actividad humana y la movilidad humana componen dinamicas urbanas. Inicialmente, estudio datos de redes sociales geolocalizados y los considero como un proxy de donde y cuando las personas realizan lo que se define como la actividad humana. Se emplearon tecnicas asociadas con modelos lineales generalizados, analisis de datos funcionales, agrupacion jerarquica y datos epidemicos, para explicar la distribucion espacio-temporal de los lugares donde las personas interactuan con sus redes sociales. Posteriormente, para comprender la movilidad en entornos urbanos, se utilizaron datos provenientes de un sistema de ferrocarril subterraneo. La informacion se considero medidas diarias repetidas para capturar la regularidad del comportamiento humano. Mediante la implementacion de metodos de componentes principales funcionales, analisis de datos y agrupacion jerarquica, fue posible describir el sistema e identificar patrones de movilidad humana. EnglishThis doctoral dissertation proposed several statistical approaches to analyse urban dynamics with aiming to provide tools for decision making processes and urban studies. It assumed that human activity and human mobility compose urban dynamics. Initially, it studied geolocated social media data and considered them as a proxy for where and when people carry out what it is defined as the human activity. It employed techniques associated with generalised linear models, functional data analysis, hierarchical clustering, and epidemic data, to explain the spatio-temporal distribution of the places where people interact with their social networks. Afterwards, to understand the mobility in urban environments, data coming from an underground railway system were used. The information was considered repeated daily measurements to capture the regularity of human behaviour. By implementing methods from functional principal components data analysis and hierarchical clustering, it was possible to describe the system and identify human mobility patterns.
Acute Stress Shapes Creative Cognition in Trait Anxiety

This study examined the cognitive mechanism underlying acute stress in creative cognition among individuals with high and low trait anxiety. Specifically, cognitive inhibition was assessed using the flanker task during acute stress. Fifty-two participants (26 with high trait anxiety, 26 with low trait anxiety, with a mean age of 18.94 years) underwent stress induction via the Trier Social Stress Test (TSST). They all completed the Alternative Uses Test (AUT) and the Remote Associates Test (RAT) before and after the TSST. Biochemical markers (salivary cortisol and salivary alpha amylase) were recorded at regular intervals. The results showed that cognitive inhibition was influenced by trait anxiety and acute stress. In low-trait anxious individuals after experiencing acute stress, there was a lack of cognitive inhibition and they performed better in AUT (fluency), compared to before experiencing acute stress, whereas high-trait anxious individuals showed a decreased interference effect and reduced performance in AUT (fluency, flexibility, and originality). In the RAT, there were shorter response times and increased accuracy after acute stress in both high- and low-trait anxiety groups. Thus, we suggest that cognitive control, which modulates changes in acute stress, influences creative cognition. These findings provide evidence that inhibition control mediates the effect of stress on the creativity of individuals with different trait anxiety.
Improvement Strategy of Localization Algorithm in Sensor Network

Localization technology in sensor network is an important problem for researchers.In this paper,a node deployment strategy is proposed to reduce the localization error of DV-Hop algorithm in the network where nodes are uniformly distributed.And a distance correction strategy is also presented to improve the localization accuracy of the node since the average hop distance has different influence on the distance computation between hops.Through the above procedure,the average hop distance could be estimated more accurately.The experiment results indicate that the proposed algorithm could increase the location accuracy and improve the stability of localization error.
Robots for Research

The fruits of these collaborations are proving to be highly symbiotic. Developmental psychologists are able to build and test new theories simply by manipulating the neural pathways of robots; meanwhile, roboticists are tapping into child development research to create robots that can learn and make decisions. The result is the field of developmental robotics, also referred to as epigenetic robotics.
Usages of Social Networking Websites among Undergraduate Students

Today in India mostly among the Indian undergrads the use of Social Networking Sites (SNS) has significantly expanded and has unquestionably had broad effects on the scholarly and different exercises of the understudies’ students. These effects are widespread to the point that they grabbed the eye of social researchers around the world. Be that as it may, the scope of studies led to managing the impact of SNS among college students is irrelevant in India. Hence, this study is set in this context, aims in presenting the relationship between the usages of social network education of undergraduate students. For the said reason a survey has been directed among 400-students in various colleges and universities including governments and private’s institutions throughout Mysore and Bangalore cities. The findings of the study recognized the strong relationship between the Usages of Social Network Education and college students in India, and especially in the last decade of 21 century.
Experiment on Robofish Aided Underwater Archaeology

This paper briefly analyzes the requirements of underwater archaeology for underwater vehicles, and explains the feasibility of SPC-II robofish to perform underwater task from the point of view of its velocity, maneuverability, comparison with UUV(Unmanned Underwater Vehicle), etc. A scheme for underwater archaeology assisted by SPC-II and based on hovering dive is presented. Experiments validate this scheme. The scheme resolves the problem of SPC-IIs lack of dynamic positioning and supplies reference to future research.
Independent research project with web-derived corpora for language learning

Recent studies have indicated the enormous potential of the web as a source of linguistic data for language learning in the classroom . However, there are comparatively fewer reports on the successful application of corpora compiled from the web as a tool for EFL students to raise their awareness of various lexical phrases . The purpose of this paper is to investigate Japanese students’ perceptions of inductive approaches to understanding word combinations and lexical limitations by using their own web-derived corpora and an online concordancer . By explaining the benefits and problems that the students experienced during the corpusbased analyses, this study also determined how the use of corpora can be applied to teaching English effectively .
Exploring the Concerns of Online K-12 Teachers

In this interpretative phenomenological analysis (IPA) study, we found that the experiences of online teachers are highly complex and individualized, and that the development of their concerns as teachers is largely unaffected by years of teaching experience. Because of the dramatic increase in online K-12 education, there is a need for additional research to understand evidence-based practices in online teaching. Few studies have attempted to capture the rich experience of online teachers through a careful analysis of their teaching concerns. In this study, educators from a large online K-12 institution were contacted via email and invited to participate. Final study participants were purposely selected to represent both new and experienced educators in order to understand the possible impact of teaching experience on the development of concerns. In total, seven educators were chosen to participate in two online video interviews and bimonthly journaling entries over a four-month period of time. These educators revealed numerous teachingrelated concerns hereafter categorized by personal, instructional, and relational themes, along with categories found at the intersection of these three themes. The findings presented here encourage greater dialogue between teachers and organizational leaders to understand and mitigate the negative impact of these concerns.
Toolkits for 21st century teaching: Practical implications for the 4th industry skills development

What are the super skills for the 21st Century? Can the skills be taught deliberately in classrooms? How will the teachers deliver their lessons effectively for the present generation? Toolkits For The 21st Century Learning: Practical Implications For the 4th Industry Skills Development is a comprehensive book and reference guide for teachers who wish to equip their students with the 10 super skills in order to survive the current and future challenges. The book is ideal for all educators, teachers, lecturers and practitioners who are engaged in improving and preparing their students for the 4th Industrial Revolution. The result of an innovative and collaborative work, this book provides the perfect combination of theoretical discourse, pedagogical recommendations and practical solutions that helps teachers, practitioners, lecturers and educators derive maximum benefit from its content. Each chapter is organized in four central sections; an introduction of the skill, the underlying theories behind it, several recommendations on how to position the skill in education and two lesson plans as an added value. The reader can use the lesson plan simply by following the steps provided or adapt them to suit the needs of their learners. This book is a commendable effort from twenty lecturers from various higher learning institutions all over Malaysia. The pioneers of UiTM/ UKM TESL degree holders draw on more than two decades of teaching experience with their talent in academic writing to produce this reference book as a torch for a clear explanation and effective teaching. This book is an invaluable reading for those who wish to strategize their teaching using integrated methods that can enhance student engagement and improve learning outcomes.
GPU‐accelerated finite‐difference time‐domain method for dielectric media based on CUDA

The simulation of electromagnetic (EM) waves propagation in the dielectric media is presented using Compute Unified Device Architecture (CUDA) implementation of finite‐difference time‐domain (FDTD) method on graphic processing unit (GPU). The FDTD formulation in the dielectric media is derived in detail, and GPU‐accelerated FDTD method based on CUDA programming model is described in the flowchart. The accuracy and speedup of the presented CUDA‐implemented FDTD method are validated by the numerical simulation of the EM waves propagating into the lossless and lossy dielectric media from the free space on GPU, by comparison with the original FDTD method on CPU. The comparison of the numerical results of CUDA‐implemented FDTD method on GPU and original FDTD method on CPU demonstrates that the CUDA‐implemented FDTD method on GPU can obtain better application speedup performance with reasonable accuracy. © 2016 Wiley Periodicals, Inc. Int J RF and Microwave CAE 26:512–518, 2016.
Application of data mining in medicine research

It is the most important to know the pharmacody and the side-effect in studying a new medicine.This paper,by applying data mining to analyze the experiment data of eomecon chinanthe alkaloids against oncomelania,gives a new analysing method of multi-factors model,unveils the regular pattern of every factor of the new medicine against oncomelania,and opens out the optimal solution for application.It supplys the theory basis in using eomecon chinanthe alkaloids against oncomelania in reason.
Foreign language practice in simulation video games: An analysis of game‐based FL use dynamics

Video/digital games have grown into a mainstream language‐mediated activity that attracts millions of foreign language (FL) learners worldwide. While empirical studies have demonstrated that digital game‐based interactions offer valuable opportunities for FL practice and learning (e.g., Sundqvist & Wikstrom, 2015), little is known about the specific dynamics of FL use that facilitate FL learning. The present exploratory case study examined three Arabic learners’ game‐based FL use when playing the Arabic simulation‐management video game Baalty. The study was framed by an ecological approach to FL learning, and data were collected through gaming journals, interviews, observations, and think‐aloud protocol. Findings revealed that a number of specific dynamics including engagement, active FL use, and embodied meaning motivated, promoted, and scaffolded FL practice in the course of gameplay. Pedagogical and research implications are discussed.
Neurobiological Aspects of Violent and Criminal Behaviour: Deficits in Frontal Lobe Function and Neurotransmitters 1

Many neurobiological abnormalities have been reported in patients with violent and criminal behaviour. Strong associations exist between aggressive/violent behaviour and brain dysfunction. Also, many studies support an association between frontal lobe dysfunction and increased aggressive or antisocial behaviour. The focal orbitofrontal brain injury is specifically associated with increased aggression. Deficits in frontal lobe executive functions may increase the likelihood of future aggression, but as of now, studies have reliably demonstrated a characteristic pattern of frontal network dysfunction predictive of violent crime. The evidence is strongest for an association between focal prefrontal damage and an impulsive subtype of aggressive behaviour. This paper covers dysfunctions in these regions contributing to severe aggressive and violent behaviour, as well as neurotransmitters implicated in the same. ________________________________________________________________________