Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Chaotic Map for Secure Transmission

The secure communication through synchronization between two identic chaotic systems have recently gained a lot of interest. To implement a robust secure system based on synchronization, there is always a need to generate new discrete dynamical systems and investigate their performances in terms of amount of randomness they have and the ability to achieve synchronization smoothly. In this work, a new chaotic system, named Nahrain, is proposed and tested for the possible use in secure transmission via chaos synchronization as well as in cryptography applications. The performance of the proposed chaotic system is tested using 0-1 test, while NIST suite tests are used to check the randomness statistical properties. The nonlinear control laws are used to verify the synchronization of master-slave parts of the proposed system. The simulation results show that Nahrain system has chaotic behavior and synchronizable, while the equivalent binary sequence of the system has excellent randomness statistical properties. The numerical results obtained using MATLAB for 0-1 test was 0.9864, and for frequency test was 0.4202, while for frequency test within a block was 0.4311. As a result, the new proposed system can be used to develop efficient encryption and synchronization algorithms for multimedia secure transmission applications.
The Effect of the Dr. LEE Jong‐wook—Seoul Project  on Medical Student Academic Performance in Laos

The Dr. LEE Jong-wook—Seoul Project (DLSP) in the Lao People’s Democratic Republic (PDR) is a long-term development cooperation initiative aimed at upgrading the medical education capacity at the University of Health Sciences (UHS) in the Lao PDR. Under the project, eight faculty members from UHS were trained at the Seoul National University College of Medicine for a 12-month period during 2010–2011. Using a training-of-trainers model, we estimated the effect of DLSP on the learning outcomes of students, which was measured using the standard test scores of the students. The questionnaire developed by the Medical Education Assessment Consortium in Korea was given to the students and both the percent-correct and standardized scores were examined. The evaluation strategy was to compare the learning outcomes of the students taught by the trainees with those that were not and to compare the medical topics taught by the trainees with other topics. It was found that the first group of trainees in the DLSP was associated with an increase of 1.5 in the percent-correct test scores for basic medicine. While the interpretation requires caution, it is consistent with the view that a training program for faculty members could be effective in improving the teaching capacity of medical schools in developing countries.
Effects of Whatsapp and Facebook on academic, professional and social lives of medical students and resident doctors of North India

Background: Whatsapp and Facebook are the communication apps which facilitate the exchange of instant messages, pictures, videos and thus help in connecting the people with each other. Although it has brought many benefits, these benefits have come at a price. People spend more than usual hours on social networking and find it difficult to concentrate on their work and studies. This study was planned to assess the effects of Whatsapp and Facebook on academic, professional and social lives of medical students and resident doctors.Methods: The study was conducted on 480 medical students and 275 resident doctors. The data were collected with the help of a questionnaire designed for gathering the effects of Whatsapp and Facebook on academic, professional and social lives of medical students and resident doctors.Results: Majority of the participants (98.3%) used both Whatsapp and Facebook and spent 1-2 hours per day on Whatsapp and Facebook. Nearly 45% participants said that usage of Whatsapp and/ Facebook had a positive impact on their study performance. More than half of the participants (54.6%) agreed that Whatsapp and Facebook use affected their mood and reduces their interpersonal interaction with family and friends.Conclusions: Study concludes that Whatsapp and Facebook have positive impact in academic and professional lives of medical students and doctors. However, excessive use of social networking sites for recreational purposes has negative impact on their mental and social health.
Incorporation of external information into clinical prediction models

In this thesis statistical methods are developed to incorporate external information into existing risk prediction tools. Statistical concepts motivated by practical applications are introduced, which update the Prostate Cancer Prevention Trial Risk Calculator by two genetic markers, detailed family history and single nucleotide polymorphisms. Both updates are available online for physician and patient use as well as for research and validation purposes. In addition, several methods in this updating context are compared by extensive synthetic and data-based simulations.
Methods and principles of using a priori knowledge in recognition tasks

a priori knowledge about recognizable objects is used in some form. The using of such knowledge can significantly raise the quality of the recognition systems. Often the proper use of a priori knowledge allows bringing the quality of recognition algorithm to the level of practical application. Despite this correct use of a priori knowledge is an open question in the modern theory of pattern recognition. For the object detection task, several basic approaches to the use of knowledge were developed: Deformable Part Models, Mixture-of-Parts, Implicit Shape Model, Stacking . Each of these approaches has its own advantages, disadvantages, scope of applicability and ways to improve. In most tasks of pattern recognition, there are similar methods of using a priori information can be applied. The using of a priori knowledge is an important part of the development of pattern recognition systems. Often the proper use of a priori knowledge allows bring quality of recognition algorithm to the level of practical usage. The main advantage of using a priori knowledge is that the classification algorithms are prone to errors, whereas a priori statements are always true. In the article will be show how to improve the quality of recognition system using a priori knowledge. The evolution of approaches to the use of knowledge considered by the example of the task of object detection, the advantages and disadvantages of these approaches analyzed. The basic principles of using a priori knowledge in recognition algorithms formulated.
YENİ FİZİK ÖĞRETİM PROGRAMINA VE UYGULANMASINA YÖNELİK ÖĞRETMEN GÖRÜŞLERİ

Her ulkede, ogretim programlarinin zaman icerisinde ihtiyaclar dogrultusunda yenilendigi bilinmektedir. Ulkemizde de, ogrenme zorluklari, ogrencilerin ilgisizligi, basarisizligi ve diger ulkelerdeki degisim ve gelisimler gozonunde bulundurularak fizik ogretim programi yenilenip uygulanmaya baslanmistir. Bu uygulama ile amaclanan hedeflerin gerceklestirilebilmesi icin, oncelikli olarak ogretmenlerin yeni programi istenen duzeyde algilamalari gerekmektedir. Bu calismada, fizik ogretim programinin yapisinin, fizik ogretmenlerinin bu programi algilama duzeylerinin ve programi uygulamaya yonelikgoruslerinin incelenmesi amaclanmakta olup, elde edilen sonuclar tartisilmis vebir kisim onerilerde bulunulmustur
Technology Acceptance Factors and Student Retention in Online Courses

This study aimed to evaluate the relationship between factors of technology acceptance and retention of students in online courses. They included, the expectation of performance, hedonic motivation, self-efficacy, social influence, system quality, information quality and intention to continue, belonging to the Unified Theory of Acceptance and Use of Technology and the Information Systems Success Factors. We studied 231 students of free courses offered online by a public educational institution. The results show that there is a definite and statistically significant relationship between student retention and expectation factors, hedonic motivation and information quality. The factors self-efficacy, social influence and quality of the system did not present significant relationship with retention, contrasting with the assumptions advocated in some of the empirical studies. The results contribute to the understanding that the retention of students in online courses can be obtained mainly from investments in the quality of content made available to students.
Innovation in Work Teams

Researchers and practitioners have recognized the importance of team innovation for organizational effectiveness. This chapter provides an overview of the factors that influence team innovation using an input–process–output structure. It identifies factors relating to the team and organizational context as inputs for various team processes that translate into innovative outputs. It further suggests that leadership acts as a contingency factor that facilitates the transition of input factors into team processes. Highlighting the often-overlooked difference between idea generation and idea implementation as part of team innovation, it discusses which input factors and processes are more likely to exert more influence over idea generation and/or idea implementation. It concludes by emphasizing the importance of implementing creative ideas for achieving innovation success.
Learning Management System versus Social Networking Sites

Purpose - The motive of this study was the notice of the constant movement of the students in The University of Jordan (UJ) from official communities to creating groups on SNSs. The purpose of this paper is to illustrate an analysis about students’ usage of E-learning and Facebook, and identifies the major functions that are missing in the e-learning system. This paper firstly, compared students’ usage for Learning Management Systems (LMSs) vs. Social Networking Sites (SNSs), and secondly, investigated the students’ perceptions towards educational value of integrating social networking features in the LMS through Mobile Learning (m-learning). Design/methodology/approach – Data were collected from students from multiple sources: observation, interviews, and survey. The obtained results formed students perceptions toward currently used LMS in the university and SNSs, which lead to extracting their requirements to enhance the LMS used. Findings – The results of this research emphasize the importance of SNSs as a communication tool and the development of e-learning systems to move beyond LMS and engage students in an active use of the system as a resource of their information and collaborative activities . Originality/value – This study contributes to examining UJ students’ perceptions toward embedding the characteristics of the smart learning and the social network services into an e-learning system. In contrast to previous studies in enhancing LMS by just integrating features of SNSs into LMS without utilizing smart learning.
Implementing Digital Tools to Support Student Questioning Abilities: A Collaborative Action Research Report

This collaborative action research project was conducted in a second-grade classroom to determine the impact that digital web-based tools would have in helping a school media coordinator scaffold her students’ understanding of productive versus nonproductive questions. The digital tools Kahoot, Quizizz, and Socrative were used by the students to help them recognize the difference between productive and nonproductive questions, as well as support them in the ability to generate their own productive questions. While results related to student learning outcomes showed minimal increases, the iterative and reflective nature of the action research cycle enabled the media coordinator and researcher to refine their original choices of digital technology, based on formative assessment in the action research cycle, to select the digital tools that best fit the context of this specific learning environment. These findings offer further support for the use of collaborative action research as a means to assist educators in choosing the right digital tools to meet their students’ learning needs.
Measuring Responses to Negative Peer Pressure Using Virtual Reality

Adolescent susceptibility to negative peer pressure consistently relates to maladaptive adolescent adjustment. However, measurement of this construct typically involves a mono-method, self-report approach. The current study uses virtual reality to create an observational assessment procedure for measuring adolescent responses to negative peer pressure. Participants ( n = 264) completed a lab assessment, including self-reports of susceptibility to peer pressure, antisocial behavior, dating violence perpetration, and depressive symptoms. Participants also engaged in 9 virtual reality simulations (4 involving peer pressure), which were coded for resistance to peer pressure. Control participants repeated the virtual reality simulations at a 2-month follow-up. Resistance scores evidenced item-level convergent validity with each other and discriminant validity with bystander behavior, coded from 5 separate virtual reality simulations. When peer pressure scores were summed and treated as a scale, they evidenced acceptable internal consistency, stability over a 2-month period, convergent validity with self-reports of susceptibility to peer pressure, and criterion validity with self-reports of antisocial behavior and dating violence perpetration. The latter two associations held after accounting for self-reports of susceptibility to peer pressure and participant sex. Results provide initial evidence for the utility of a virtual reality procedure for assessing adolescent resistance to negative peer pressure. validity in assessment
SELF-EFFICACY ANALYSIS OF SIXTH GRADE MATHEMATICS LEARNING OUTCOMES IN SD N 7 KEBUMEN

The essence of mathematics is aimed at solving everyday problems. However, so far mathematics still a subject that is considered difficult. One factor that influences learning success is self-efficacy. This study aims to analyze the level of self-efficacy of sixth grade students on the results of mathematics learning. The sample in this study were all sixth grade students of SD Negeri 7 Kebumen as many as 20 students. This research is a qualitative descriptive study. Data collection techniques use: (1) Questionnaire; and (2) interviews (3) observations and (4) documentation. The analysis used is descriptive qualitative. The results showed that: Students in sixth grade SDN 7 Kebumen had varying levels of self-efficacy. Students who have a high level of self-efficacy get high mathematics learning outcomes, because they have confidence or self-efficacy and are more persistent in facing difficulties. Students who have low levels of efficacy get less satisfying learning outcomes.
Robust real-time hands-and-face detection for human robot interaction

With recent advances, robots have become more affordable and intelligent, which expands their application domain and number of consumers. Having robots around us in our daily lives creates a demand for an interaction system for communicating humans’ intentions and commands to robots. We are interested in interactions that are easy, intuitive, and do not require the human to use any additional equipment. We present a robust real-time system for visual detection of hands and faces in RGB and gray-scale images based on a Deep Convolutional Neural Network. This system is designed to meet the requirements of a hands-free interface to UAVs described below that could be used for communicating to other robots equipped with a monocular camera using only hands and face gestures without any extra instruments. This work is accompanied by a novel hands-and-faces detection dataset gathered and labelled from a wide variety of sources including our own Human-UAV interaction videos, and several third-party datasets. By training our model on all these data, we obtain qualitatively good detection results in terms of both accuracy and speed on a commodity GPU. The same detector gives state-of-the-art accuracy and speed in a hand-detection benchmark and competitive results in a face detection benchmark. To demonstrate its effectiveness for Human-Robot Interaction we describe its use as the input to a novel, simple but practical gestural Human-UAV interface for static gesture detection based on hand position relative to the face. A small vocabulary of hand gestures is used to demonstrate our end-to-end pipeline for un-instrumented human-UAV interaction useful for entertainment or industrial applications. All software, training and test data produced for this thesis is released as an Open Source contribution.
Download time and intent to use a web page: Working paper series--02-09

The World-Wide Web (WWW) has grown, and continues to grow, at an epic rate. Unlike applications software, which provides a structured navigation schema, the web encourages users to move frequently from page to page. In most cases, a web site has only one chance to make a favorable first impression. If a web page takes more than a few seconds to present this first impression, the user may decide to abandon or "bail out" from the current site and move to another site. The result of failure to deliver information to the user in a "reasonable" amount of time to a commercial web site is the loss of business--possibly forever. This research indicates that web page download time has both direct and antecedent effects on a user's behavioral intent to use a web page. In addition, this research indicates that traditional models used to assess behavioral intent and subsequent usage of applications software may not be useful in evaluating a user's intent to use a web page and that alternative predictive models should be evaluated.
Thermal-Aware Modeling and Analysis for a Power Distribution Network Including Through-Silicon-Vias in 3-D ICs

The high-power dissipation and the low-heat conduction between stacked chips in 3-D structures lead to a high temperature, which has become a critical design constraint for high-performance 3-D integrated circuits (ICs). Naturally, a power distribution network (PDN) in 3-D ICs consists of good heat conductor, but many existing methods do not fully show its thermal removal capability, and the thermal models of a 3-D PDN are imperfect. In this paper, compact and accurate physically based models to compute effective thermal conductivities of a 3-D PDN are proposed. By combining the equivalent thermal conductivity and the proposed complete thermal models for a 3-D PDN, a fast temperature analysis procedure can be expediently applied using the finite volume method. Finite element method (FEM) tools are used to verify the accuracy of the proposed models, and the errors in the temperature responses of our proposed method are within 3% compared with the results from the FEM. In addition, our method also improves the computational efficiency.
SAMPTA'09, International Conference on SAMPling Theory and Applications

SAMPTA'09 was the 8th international conference on Sampling Theory and Applications. The previous conferences were held in Riga (Latvia) in 1995, Aveiro (Portugal) in 1997, Loen (Norway) in 1999, Orlando (USA) in 2001, Salzburg (Austria) in 2003, Samsun (Turkey) in 2005 and Thessaloniki (Greece) in 2007. The next SAMPTA conference will be held in Singapore, in May 2011. The purpose of SAMPTA's is to bring together mathematicians and engineers interested in sampling theory and its applications to related fields (such as signal and image processing, coding theory, control theory, complex analysis, harmonic analysis, differential equations) to exchange recent advances and to discuss open problems. SAMPTA09 has been organized around plenary lectures, general sessions on sampling and applications, and special sessions on selected topics. Ample time was left for discussions. The topics of the special sessions were the following:Compensation of channel mismatch errors in time-interleaved analog-to-digital converters, Compressed sensing, Mathematical aspects of compressed sensing, Frame theory and oversampling, Geometric multiscale analysis, Sampling and quantization, Sampling and communication, Sampling and painting, Sampling and industrial applications, Sampling using finite rate of innovation principles, Sparse approximation and high-dimensional geometry.
The Development of a Detaché Rhythm Hierarchy for String Sight-Reading

The purpose of this study was to determine the rhythm sight-reading ability of high school string players, establish a hierarchy for detaché rhythm skills in string sight-reading, and discover any effects of key or bow direction. Twenty-six rhythm skills, grouped into seven categories were embedded into four 8-measure melodies, which appeared in three different keys and with occasional designated bowings. Participants (N = 82) obtained a mean score of 19.1 (73%), with success rates ranging from 20% to 94% for individual rhythm skills. While significant differences were found between skills appearing in the major keys of D and E-flat, no significant differences were found by bow direction. Future researchers may explore whether these rhythm skills hold their relative difficulty level with less accomplished players, investigate the effects of various bowing practices, and identify any effects of anxiety levels for sight-reading when the consequences of performance quality varies.
Multi-Task Learning for Argumentation Mining

Multi-task learning has recently become a very active field in deep learning research. In contrast to learning a single task in isolation, multiple tasks are learned at the same time, thereby utilizing the training signal of related tasks to improve the performance on the respective machine learning tasks. Related work shows various successes in different domains when applying this paradigm and this thesis extends the existing empirical results by evaluating multi-task learning in four different scenarios: argumentation mining, epistemic segmentation, argumentation component segmentation, and grapheme-to-phoneme conversion. We show that multi-task learning can, indeed, improve the performance compared to single-task learning in all these scenarios, but may also hurt the performance. Therefore, we investigate the reasons for successful and less successful applications of this paradigm and find that dataset properties such as entropy or the size of the label inventory are good indicators for a potential multi-task learning success and that multi-task learning is particularly useful if the task at hand suffers from data sparsity, i.e. a lack of training data. Moreover, multi-task learning is particularly effective for long input sequences in our experiments. We have observed this trend in all evaluated scenarios. Finally, we develop a highly configurable and extensible sequence tagging framework which supports multi-task learning to conduct our empirical experiments and to aid future research regarding the multi-task learning paradigm and natural language processing.
T1-B: Bulldog Bytes: Engaging Elementary Girls with Computer Science and Cybersecurity

Responsive to broadening participation challenges, Mississippi State University (MSU) established the Bulldog Bytes Outreach Program in 2013 with a residential summer camp for middle school girls funded through the National Center for Women in Information Technology (NCWIT). Since then the program has grown to provide co-curricular activities to K12 students throughout the state. Following a pilot offering of an elementary camp in 2016, the Bulldog Bytes program delivered two of these camps in small towns during 2017, supporting a strategy of engaging under-resourced students with computing in their home communities. This paper will detail our project-based approach to learning and share experiences from the elementary camps.