Reviewerly/exHarmony huggingface dataset:
과업 중심 언어 교수법이 특성화고 학생들의 정의적 영역에 미치는 영향

Most of the technical high schools in Korea use the same textbooks as general high schools although their goal and textbooks are different from each other. As a result, those students’ participation in class and interest in the English subject are very low. To resolve this problem, this study aims to apply the task-based language teaching (TBLT) to the technical high school classroom and verify the effects of TBLT on students’ affective domains. The participants were 57 first graders in a technical high school. They took part in 50-minute TBLT class for five weeks. Instructional materials were developed for the instruction with practical English expressions focused and participants’ English proficiency levels customized. A student survey questionnaire to measure changes in affective domains (interest, confidence, anxiety, and learning motivation) was administered before and after TBLT classes. The major findings in this study are that the three affective domains such as interest, confidence, and anxiety showed significant improvement; that is, students’ confidence and interest levels increased and anxiety decreased due to the TBLT class. However, the motivation level was not significantly improved after the instruction. It’s imperative for teachers to empower students to participate in their learning process through student-centered class activities and tasks.
Anomaly Detection and Local Outlier Factor for Credit Card Fraud Detection

Nowadays, as internet speed has increased and the prices of the mobile have decreased very much in past few years. Also the data prices too are very much affordable to most of the people. This has resulted into the digitization of most of the institutes as it is easy and convenient for the people and also for the authority to maintain the records. So it resulted in most of the banks and other institutes receiving and transferring money through credit card. But with the hackers and other cyber criminals around credit card system is very easy to perform fraud. These credit card fraud creates financial loss for customers and companies and everyday fraudsters find new technique to commit the fraud. The possibilities of the fraud transaction are very less but it is not negligible and even having one fraud transaction is unacceptable because it is crime and we can’t neglect even if amount is less as it harms. So this project aims at analyzing various classification techniques using various metrics for judging various classifiers. This model aims at improving fraud detection rather than misclassifying a genuine transaction as fraud. After using the algorithms such as Isolation Forest and Local Outlier Factor, a detailed report is given in this paper.
Implicit intention transference using eye-tracking glasses for improved safety in human-robot interaction

Eye gaze can convey information about intentions beyond what can beinferred from the trajectory and head pose of a person. We propose eye-trackingglasses as safety equipment in industrial environme ...
THE PSYCHOLOGICAL TECHNOLOGIES ACTIVATING TEACHER’S PERSONAL SELF-DEVELOPMENT IN THE CONDITIONS OF NON-FORMAL EDUCATION

The article presents the psychological technologies activating teachers’ personal self-development in non-formal education. The performed analysis of scientific literature allowed us to determine the essence and structure of teachers’ personal self-development. Teachers’ personal self-development is presented as the process that reveals teachers’ internal potential, so they can improve their personal characteristics and perform effectively their professional tasks. The technologies activating teachers’ personal self-development is based on the trans-cultural approach and implements the model for examined phenomenon activation; this model includes targeted, conceptual, substantive, organizational, and effective modules. Thanks to the described technologies, teachers’ personal properties, qualities, and competencies are developed, which are the main indicators of the effective activation of the studied phenomenon and contribute to successful professional work. The training structure is described; the training sessions enhancing teachers’ self-development are based on interactive training methods and forms, sound psychological substantiation, the principles of activation of the examined phenomenon. The program enhancing teachers’ personal self-development is laid down into the special course “Fundamentals of teachers’ personal self-development”, which contains three modules: “General characteristics of teachers’ personal self-development”, “Psychological conditions of teachers’ personal self-development”, “Psychological tools improving teachers’ personal self-development”. The first module reveals the importance of personal self-development in a teacher’s life, necessity to master knowledge on personal self-development, identify and develop motivation to self-development as a teacher. The second module provides assistance for development of the cognitive-reflective component of teachers' personal self-development. The third module is aimed at improvement of the operational-activity component of teachers’ personal self-development. &nbsp
ISIS, AN ARTIFICIAL TERRORIST ORGANISATION AND BITCOIN

Crypto currencies whose traders are not known, affect the world economy. In this case, it is possible to assert that an international terrorist organization can also trade them. In the market, Bitcoin is well-known and regarding volume is a leader crypto currency between the crypto currencies. In this article, it has been searched if there could be a strong correlation between bitcoin prices and ISIS. As methodology it has been checked ISIS attacks and Bitcoin prices relation, by graphics
A Semantic Matching Model Based on Optimal Selection Mechanism

Optimal features selection is essential for sentence similarity recognition. In this paper, a semantic matching model based on optimal selection mechanism is designed. Compared with other models that without using an optimal feature selection mechanism, the model uses optimal features that are closest to the original semantics to match, resulting in higher matching. This paper proposes an improved semantic information selection mechanism. This mechanism selects a candidate feature that is as close as possible to the semantics of the original text by calculating the probability of distribution of semantic information in the sentence. Furthermore, a new attention focus mechanism is designed, which iteratively updates the information weight to obtain another candidate feature that may affect the matching accuracy. Then, an optimal feature selection algorithm is designed by using the context vector and two candidate features. The coefficients are selected, and the optimal features are further selected from the candidate features for semantic matching. The experimental results show that the accuracy of sentence matching is greatly improved on Quora benchmark and a self-defined Chinese dataset, this indicates that the proposed model outperforms existing matching models.
Encoding Context in Task-Oriented Dialogue Systems Using Intent, Dialogue Acts, and Slots

Extracting context from natural language conversations has been the focus of applications which communicate with humans. Understanding the meaning and the intent of the user input, and formulating responses based on a contextual analysis mimicking that of an actual person is at the heart of modern-day chatbots and conversational agents. For this purpose, dialogue systems often use context from previous dialogue history. Thus, present-day dialogue systems typically parse over user utterances and sort them into semantic frames. In this paper, a bidirectional RNN with LSTM and a CRF layer on top is used to classify each utterance into its resultant dialogue act. Furthermore, there is a separate bidirectional RNN with LSTM and attention for the purpose of slot tagging. Slot annotations use the inside-outside-beginning (IOB) scheme. Softmax regression is used to determine the intent of the entire conversation. The approach is demonstrated on data from three different domains.
Teaching Cybersecurity in CSP (or Any CS Class)

Cybersecurity is vital to a technology-driven society. Daily headlines about data breaches and ransomware attacks demonstrate that we cannot ignore the security risks inherent to our highly networked lives. Cybersecurity is a growing job field -- and even for students who don't go on to pursue cybersecurity careers, it is crucial to have some level of security awareness. But until very recently, the intrigue and opportunity of cybersecurity was usually not introduced until advanced undergraduate CS courses. However, the real world implications and applied nature of the topic lends itself well to catching the interest of a diverse group of students in CS at a younger age. The Teaching Security lessons (at teachingsecurity.org) introduce the broad idea of cybersecurity through threat modeling and the human-centered nature of authentication. They were prepared by subject-matter experts with research backgrounds in the technical workings and social implications of cybersecurity. Our lessons were designed to meet the cybersecurity learning objectives in the AP Computer Science Principles framework, but they are appropriate for any high school computer science class or program. This will be an interactive workshop for CS educators at all levels; no previous cybersecurity experience required. (Laptops also optional.) Participants will learn how to begin developing the "security mindset" by teaching students a simplified version of threat modeling (mostly via "unplugged" activities). We will also preview lessons on authentication and social engineering. The workshop will also provide opportunities for attendees who teach cybersecurity to share their own strategies.
Learning Application in Supporting Teaching and Learning Activities at Higher Education in Banjarmasin

Technology is very important in our lives today and it is very good if the technology that is available today is used as well as possible to develop education. In this study, researchers wanted to find out what applications were used by several lecturers at universities located in Banjarmasin. In accordance with the kinds, application here will be grouped so that it can be additional information for readers. If the education sector does not keep up with the modern era that is developing as it is now which almost all sectors have used technology well, it will be increasingly left behind and will not advance the education system in Indonesia, especially in BanjarmasinIn this study, researchers used qualitative research as a research method using several theories from previous experts to support this research until it was completed. Through interviews with several English language lecturers from UIN Antasari Banjarmasin to the University of Muhammadiyah Banjarmasin, researchers asked several things related to the type and use of applications that have been and are being used by lecturers today to support their teaching and learning activities inside and outside the classroom.With this study, researchers obtained interviews with lecturers who had been asked about the applications they had used while teaching. And as a result, the lecturers use the applications they choose according to what they need in their teaching and learning activities related to the course they are studying. Each lecturer has their benchmarks based on the ease and features they use in each application. And the researcher get kinds of learning applications from the lecturers that have been asked as follows; Learning Management System (LMS) it has: Edmodo, Schoology, Google Classroom, Canvas, and Moodle. In Mobile Learning Applications has: Kahoot, Google Forms, Rubistar, and Quizstar. And in Social Media, it just has Instagram.
Yale University Library Research Guides: Collection Development & Acquisitions: Home

Process, guidelines, and contact information for ordering both electronic and tangible materials.
Development of a multi-item scale for measuring Blue Ocean leadership

This study aims to develop and validate a scale to measure Blue Ocean leadership within five-star hotels in Jordan. A quantitative approach through a questionnaire-based survey of all the employees working within five-star hotels in Amman is used. A sample of 207 employees within the three administrative levels in hotels under study is selected. A structural equation modelling is conducted through both exploratory and confirmatory factor analyses to assess construct validity and reliability. Findings confirm validity and reliability of the developed scale consisting of four Blue Ocean leadership dimensions. This paper develops a multi-item measurement instrument for current multi-dimensional construct, and offers professionals and practitioners at all management levels a valid and reliable tool for evaluating and implementing this construct within their organisations, which will affect positively all stakeholders and allow organisations to achieve higher performance and manage organisational change with less effort and time.
Петрогеохимия и условия формирования мезозойских вулканоплутонических образований Балейского рудного узла

Research subject. In this research, volcanoplutonic formations (VPF) in the Baleisky ore node (BON) consisting of intrusions of the Amudzhikan-Shakhtama complex (J2-3) and comagmatic effusions of the Shadaron series (J2-3) were investigated. Methods. Investigations were carried out in the analytical center of the SB RAS Geological (Ulan-Ude). Silicate analysis was performed by the conventional method. Ore and rare elements were determined by the RFA method. Rare earth elements were detected using the ASP-AES method. Results. It was determined that VPF in the BON has a zonal structure. In the central parts of the BON, granite rods of the Amudzhikan-Shakhtama complex (J2-3) are located. Further, moving from the central BON parts towards its periphery, a belt of small intrusions of the Amudzhikan-Shakhtama complex (stocks of monzonite diorites, granodiorites, dikes of diorite porphyrites, lamprophyres) is located. The majority of gold deposits and ore occurrences are confined to this zone. The peripheral parts of the BON feature volcanogenic sedimentary deposits of the Shadaron series (J2-3). In composition, these deposits correspond to island-arc and post-col-lisional formations. It is shown that the intrusions of the Amudzhikan-Shakhtama complex correspond to high-potassium calc-alkaline series. Conclusions. It was found that the magmatic melts of the Mesozoic ore-bearing intrusions located in the Baleisky deposit area are more differentiated and located at lower depths compared to the rocks of similar composition in other BON parts.
Tag-based Video Retrieval with Social Tag Relevance Learning

High-quality tags play an important role in many applications such as multimedia information retrieval. This paper proposes a social tag relevance learning method using a data-driven approach to improving tag-based video retrieval performance. The tag relevance means how a tag is relevant to multimedia content. To learn the tag relevance, we apply a well-known tag neighbor voting algorithm, which accumulates votes from visual neighbors. However, an imbalance in the number of tags among the datasets causes a loss in the accuracy of tag voting. Therefore, in the proposed method, we examine a formula for calculating the tag relevance score considering the tag occurrence frequency imbalance. We conduct experiments on the YouTube-8M dataset, and the results show that our approach is effective and efficient.
Towards Efficient and Real-Time Human Activity Recognition Using Wearable Sensors: A Shapelet-Based Pattern Matching Approach

With the advent and proliferation of wearable sensors, Human Activity Recognition (HAR) has received considerable research attention in recent years. Most existing HAR systems operate in a batch-processing (offline) mode, and they rely upon complex features from accelerometer readings for activity recognition. On the other hand, many applications such as continuous patient monitoring and elder fall detection demand real-time human activity recognition, and existing offline systems are inadequate for these applications. In this paper, we investigate challenges of real-time human activity recognition and present an effective framework based on a waveform pattern matching approach. We introduce the concept of A-Shapelets (activity shapelets), which is a representative pattern for each activity. Our framework incorporates several novel aspects; first, we present a scheme for computing the most distinctive A-Shapelet for each activity. Our scheme extracts repetitive patterns from wave forms. Second, our framework builds decision tree models using a personalized library of A-Shapelets. Third, we present a low-overhead matching algorithm for classifying incoming accelerometer data stream in real-time. This paper reports a series of experiments to evaluate the proposed framework. Our experiments demonstrate that the performance of our scheme is very good and the accuracy is comparable to offline HAR systems.
RETAINING WORKFORCE: A NEW CHALLENGE

Getting pay without delay definitely give satisfaction at early stage but it is not all about it above it there should be a feeling of happiness while coming to job it can be achieved if employees are motivated by their boss and it could be colleague as well support, recognition, clean environment and many more things. Major 6 elements are physical environment: comfort, reinforcement, team spirit, respect, self-development and taking care. . In today's environment, in order to survive every organization has to develop competitive edge over competitors in the industry. It can be achieved by effectively managing the human resources as well as by providing better workforce environment. Workplace environment is the environment where employees are supposed to work. Work environment plays a vital role in the life of employee as well as business organization. Research is conducted to study the impact of workplace environment on the human resources with respect to their retention in the organization, to study the major elements of workplace environment and to examine the workplace environment of major business organizations. Work environment plays a vital role in retaining employees. Therefore in the study it is concluded that work environment is foremost factor which the employee must consider while deciding either to stay in organisation as loyal employee or to switch
Art Therapy as a Means of Psycho-Correction and Correction-Educational Support to Persons with Limited Health Opportunities

The investigation is dedicated to the possibilities of art therapy as one of the methods for implementing psychological and pedagogical support to persons with disabilities of various ages (primarily childhood) in conditions of inclusive education. The results of approbation of art therapy technologies and its corrective influence in the process of working with children with intellectual and emotional-volitional systems are presented in the investigation. The scientifically grounded methodology of organization and usage of art-therapeutic technologies and methods in the organization of psychological and pedagogical support to persons with limited health possibilities are described.
LibGuides: Frequently Asked Questions: Circulation & Operations

FAQ for Kirk Library patrons. The how-to's, why's, and how-long's of the library circulation desk.
gopherserver coming soon

Looks like Adam Curry spoke about Internet Gopher on the Rogan Podcast, so I had to dig this out of the email archives from September
التخطيط الاستراتيجي المبني على النتائج ودوره في تطوير السياسات العامة تجاه الاستقرار المالي في جامعة القدس

The research aims to identify the results-based strategic planning and its role in the development of public policies towards financial stability at Al-Quds University. The researcher used the analytical descriptive method for this purpose and the questionnaire as a main tool for data collection since (2015 to2017) the community of the study included 34; only 26were obtained. The researcher used the comprehensive inventory method for data collection, andused the statistical analysis program (SPSS) as a statistical package for data processing and hypothesis testing.
Representing Basic Physical Fields by Quaternionic Fields

Basic physical fields are dynamic fields like our universe and the fields that are raised by electric charges. These fields are dynamic continuums. Most physical theories treat these fields by applying gravitational theories or by Maxwell equations. Mathematically these fields can be represented by quaternionic fields. Dedicated normal operators in quaternionic non-separable Hilbert spaces can represent these quaternionic fields in their continuum eigenspaces. Quaternionic functions can describe these fields. Quaternionic differential and integral calculus can describe the behavior of these fields and the interaction of these fields with countable sets of quaternions. All quaternionic fields obey the same quaternionic differential equations. The basic fields differ in their start and boundary conditions. The paper introduces the concept of the Hilbert repository. It is part of a hierarchy of structures that mark increasingly complicated realizations of a purely mathematical model that describes and explains most features of observable physical reality. That model is the Hilbert Book Model. The paper treats the mathematical and experimental underpinning of the Hilbert Book Model.
IMPROVING STUDENTS’ VOCABULARY ACHIEVEMENT THROUGH PEGWORD STRATEGY FOR THE YEAR-2 STUDENTS AT SMPN 9 KENDARI

The objective of this study is to improve students’ vocabulary achievement at class VIII-6 of SMPN 9 Kendari through Pegword Strategy. The researcher finds some problems faced by students at VIII-6 class of SMPN 9 Kendari on learning vocabulary. Those problems are find offer the researcher do preliminary research through direct observation, interviewing some students and the English teacher, and giving diagnostic test. The problems of the students difficulty to determine the word class of vocabulary, do not know synonym and antonym of vocabularies, do not know vocabulary use, easy to forget the vocabularies which they have learned, rare to apply new vocabularies which they get, and do not have a good way to learn vocabulary. The subject of this study is VIII-6 class of SMPN 9 Kendari in academic year 2017/2018. The total subjects are 35 students. The design of this study is classroom action research. This study is conducted in two cycles which applied some instruments. They are vocabulary tests in form of objective test, observation sheet, and note taking. The target vocabulary of this study are verb, noun, and adjective (contents word). In this research, qualitative and quantitative data are collected and analyzed by describing data into words and by using descriptive statistics. As the result of this study, the writer finds that in diagnostic test, the mean score is 51.7. In the first cycle, the mean score of the vocabulary test is 75.30 with the average of target improvement is 68.57 %. While for the cycle two, the mean score of the vocabulary test is 82.98 with the average of target improvement is 94.28 %. In other words, it could be said that there is an improvement about 7.68 in the cycle two compared to the mean score of vocabulary test in the cycle one and about 25.71 % improvement of the target of study. This result indicates that the Pegword Strategy can improve students’ vocabulary achievement class VIII-6 of SMPN 9 Kendari.
LibGuides: Government Documents: International Resources

The Government Documents Department supports the Libraries' objectives by providing federal and state resources, instruction and other services for Columbus State University and the local community.