Reviewerly/exHarmony huggingface dataset:
The impact of DFM and TheHorseCourse on domestic violence and abuse in Troubled Families.

TheHorseCourse is highly effective in reducing domestic violence and abuse, with 51% fewer DVA flags at follow up. This compares very favourably with other DVA interventions in the published research literature.
Architectures for Image Classification and Performance Analysis Using Different Convolution Neural Network and Deep Neural Networks and Different Combinations of Activation Functions

Image classification is a complex computer vision problem. Recently, there have been endeavors using convolutional and deep neural network architectures (CNNDNN). There are very deep neural networks architectures available for image classification. These networks are taking days and even weeks to learn the network. It will be time consuming if it is to be tested in various ways to find an efficient architecture. It gives rise to shallow neural networks which are having few layers. Due to this fact, such types of neural network architectures have been implemented in this research endeavor. Recently, several other improvements have been made on CNNs by way of introducing several types of convolutions and different types of activation functions. The shallow network makes it possible to test these different types of networks and finding the efficient network architecture given the less amount of time to learn in such type of network architectures. In this research five different CNN-DNN architectures have been analyzed on an image set having fifteen categories of images and their results were compared. The architectures were varied by image sizes taken, different number of filters, different sub-sampling processes and different activation functions. It is found that an architecture with a combination of Relu and Hyperbolic activation functions were performing well over other architectures and other combinations of activation functions.
Evaluating Hierarchical Medical Workflows using Feature Importance

The applicability and utility of Artificial Intelligence (AI) based solutions has been demonstrated widely in the healthcare domain via the automated analysis of medical information. However, the adoption rate of AI-based healthcare systems is inhibited due to their complicated nature. Also, the hierarchical nature of the medical settings adds a layer of complexity in understanding how a Machine Learning (ML) model functions when subjected to varying workflows. Variation in models' performance, and individual features' contribution, needs to be effectively quantified such that medical practitioners can understand the models, and validate their operation if widespread adoption is to be enabled. In this paper, a hierarchical medical workflow for understanding the operation of ML in a healthcare-based setting is proposed. Its utility is demonstrated in the context of heart disease classification. Explainable Artificial Intelligence (XAI) is incorporated in the form of Feature Importance (FI) scores and correlated with an ML model's performance metrics (Accuracy, F1-score). This provides a multi-stakeholder perspective aligned with the hierarchy as experienced in a real-world medical setting. The paper contributes a methodology for accommodating an enhanced understanding of diverse hierarchical healthcare settings that would benefit from the adoption of AI-based systems.
Properties of unique information

We study the unique information function U I(T : X \ Y ) defined by Bertschinger et al. [4] within the framework of information decompositions.In particular, we study uniqueness and support of the solutions to the convex optimization problem underlying the definition of U I. We identify sufficient conditions for non-uniqueness of solutions with full support in terms of conditional independence constraints and in terms of the cardinalities of T , X and Y .Our results are based on a reformulation of the first order conditions on the objective function as rank constraints on a matrix of conditional probabilities.These results help to speed up the computation of U I(T : X \ Y ), most notably when T is binary.Optima in the relative interior of the optimization domain are solutions of linear equations if T is binary.In the all binary case, we obtain a complete picture of where the optimizing probability distributions lie.
Current Status and Improvement Plan of Programming Education for Electronics Engineering

In the Fourth Industrial Revolution and the foundation of software and hardware technologies through ICT, the technology to analyze the principles of information processing activities is the ability to implement programming. In this study, to improve the programming academic performance of electronics majors, firstly, we presented an effective teaching method in order to promote employment in the programming field by improving problem-solving skills and logical thinking skills in the programming field that electronics majors do not prefer. Secondly, we plan to promote intelligence informatization by converging intelligence information technology into the existing electronics industry by developing software utilization skills through programming curriculum that reflects the specificity and reality of electronics. Lastly, as computer programmers, we would like to expand creative talent education by developing learners' capabilities to cultivate smart talents who have both hardware and software capabilities.
Library Guides: Issues in Society: Drugs & Alcohol

Background research resources for Senior School students. Each 'Issues in Society' eBook targets a specific social issue.
The Issues Of Financial Inclusion And Its Role In Economic Development

The use of basic financial services, such as bank accounts, loans or savings, has become a necessary condition for participation in economic and social life. However, parts of the global population and firms remain excluded from the financial sector for various reasons. This paper aims to analyse the main issues of financial inclusion globally and its role in economic development. To achieve this goal, the economic and social benefits of financial inclusion are identified, as highlighted by the existing literature; further, the main factors that determine the exclusion of the population and firms from the financial system are revealed; and finally, the global trends in the evolution of the financial inclusion indicators are presented. Notwithstanding the role of financial inclusion in achieving important economic goals, our analysis highlights the existence of significant disparities internationally in the level of financial inclusion, as well as the need to address them through public policy actions.
The effectiveness of using Duolingo to improve students’ vocabulary mastery at the seventh grade of SMPN 8 Bandar Lampung

The objectives of this research are to find out whether there is any significant improvement in students’ vocabulary mastery after being taught through Duolingo and to investigate the students’ perception of it. The subject of the research was thirty students of SMP N 8 Bandar Lampung who were in seventh grade when the research was conducted. The research was conducted by using one group pretest and posttest design. The data were analyzed by using Repeated Measure T-Test in which the significance was determined by p&lt;0.05 and hypothesis testing was computed using Statistical Package for Social Science (SPSS). The students’ perception toward the implementation of Duolingo was also investigated through a close-ended questionnaire. The result of the research showed that the mean score improves from the pretest was 62,1333 and the posttest was 76,3333 in which the gain was 14,2000. The result of the t-value was 12.836 and the sig.2-tailed 0.000. It means that the hypothesis was accepted, there is a significant improvement of the students’ vocabulary mastery after being taught through Duolingo. Furthermore, it was found out that students have a positive perception of the treatment. They also stated their reasons regarding their answer to the statements in the questionnaire.
Organizing Library Intrapreneurship

Libraries occupy a special space in our society, and our minds. Today, public libraries are struggling hard to attract new users and increase footfalls that seem to be in the downtrend. Besides, Physical Libraries need innovations in their services frontier to survive stiff competition from virtual digital libraries that provide instant access to information at no cost. Librarians and library professionals as knowledge managers could help design and foster entrepreneurship models of service delivery aimed towards bringing novelty in their operations. This is for the reason that libraries must take up the challenges to survive and compete with digital libraries which would maximize user satisfaction, attract new patrons and increase their user base. To make libraries economically independent and socially competent knowledge organizations, libraries need to innovate and adopt entrepreneurship-intrapreneurship business models which would attract investments from the private sectors. To transform libraries into productive, innovative knowledge organizations, librarians must take the initiative to think out of the box.This paper addresses these issues and analyses the intrapreneurship attitude to library operations. It argues that librarians should adopt a model of knowledge entrepreneurship where librarians, besides being knowledge managers, would also act as intrapreneurs within their organization.
Scaling up Cast Face Detection in Videos at Globo

It has been recognized that a significant increase in the production and consumption of video content occurred in the last decade. Many entertainment companies, like Globo, face challenges regarding video metadata generation. The objective of this paper is to present a suitable architecture for the Globo Group to automatically identify actors that appear in each scene of a video stream, generating new metadata annotations that can be used by recommender systems and search engines among different other applications in this industry sector.
Trust Modeling and Service Level Agreement Monitoring in Federated Cloud

Communication in trusted networks is not absolute until their relation is expressed in a transitive manner. Formulizing trust relationships leads to score reputation of a party or an entity; these evaluations are measured with subjective trust measurement, where subjective trust is described in this paper. The trust between any two parties can be analyzed through their trust linking paths. The properties of evaluating trust on network can be offered as 1. Transitive trust 2. Parallel trust combination 3. Subjective logic. In modern communication of information technology and services, a familiar style being adopted for interaction procedures. The phenomenal growth in business-to-business forum offers people with distributed application sets that are really sensitive for processing and delivering tasks. As a result computer networks fail to meet these uncertain challenges and it degrades quality of services (QOS). Business processing through e-commerce is the recent trend that offers viable applications to customers for fulfilling their business needs. Likewise, people are influenced to use distributed e-commerce application in an enormous way without considering the risk of security as a primary challenge. Cloud computing is a considerable security path, offering services to its users by meeting minimal security needs. Cloud must offer better trusted service to their consumers by building its reputation scores. In this paper assessing of trust becomes a major objective to achieve QoS and better decision-making system in cloud computing. The entities of cloud are CSP’s, which delivers the services to consumers, provided by cloud infrastructure provider (CIP). Assessing of trust with respect to CSP and CIP can be accessed on the basis of CSP positive belief on CIP.
Career Success, Career Commitment and Organizational Support: Empirical Evidence from the Banking Sector

Career success plays a significant role in the progress of any employee's career. The current study attempted to investigate how organizational support and career commitment can influence career success. Through using the quantitative approach, data were collected from 415 employees in the Islamic banking sector of Bahrain. The structural equation modeling results using Smart PLS 2.0 reported a significant relationship between organizational support and career success. Accordingly, the study also reported a significant correlation between career commitment and career success. The findings highlight how career success is essential, and the role of organizational support and career commitment towards harnessing it. The paper presents implications for theory and practice, followed by the scope for future studies.
Ultra-Lightweight Block Cipher in Medical Internet of Things for Secure Machine-to-Machine Communication Using FPGA

With the swift growth of internet applications with the Internet of Things (IoT), medical sensors and online medical service has become mandatory part of every use case in the recent years. The health care system has become more connected with the increasing use of IoT devices, and these medical devices introduce vulnerabilities into health care organizations. Recently, there are significant cyber-threats against the medical IoT and some resisting elements of cryptosystem that cloud help to combat these threats. Hence, in medical IoT, security and privacy of patients are among the major areas of concern. However, such methods are very complex to implement in Field Programmable Gate Array (FPGA) platforms. This paper proposes an ultra-lightweight block ciphers (ULBC) for medical IoT applications. The first contribution of ULBC algorithm is to propose the chaotic Whale optimization (CWO) algorithm for key management, which improves the security and reduce hardware cost by reducing the number of iteration rounds. The second contribution is to introduce the flexible design of modified ULBC algorithm that provides an area, power and delay efficient design with attack free feature. The flexible design avoids the reconfigurable runtime, power; and it is surely different from existing block ciphers. Finally, the ULBC algorithm is synthesized in Xilinx tool with different FPGA families and the performance is compared with existing lightweight ciphers in terms of maximum clock frequency, power consumption and hardware utilization.
The Effect Of Management Information System On The Work Effectiveness Of ASN At BPKAD, Bengkulu City

This study aims to determine the effect of management information systems on the work effectiveness of ASN at BPKAD Bengkulu City. The results showed that there was an influence of management information systems on the work effectiveness of ASN BPKAD Bengkulu City, with the test results obtained t count > t table (12.837 > 2.002) with The regression equation Y = 16.84 + 0.53X means that for every 1 unit increase in the value of the management information system variable, the ASN work effectiveness variable will increase by 0.53 at the Bengkulu City BPKAD. The value of the correlation coefficient (r) of 0.63 indicates that there is a strong influence between the management information system on the work effectiveness of ASN BPKAD Bengkulu City because it is in the interval 0.60-0.799. The Coefficient of Determination (KD) value of 40.1% means that the contribution of management information systems to the work effectiveness of ASN BPKAD Bengkulu City is 40.1% and 59.9% is influenced by other variables not examined.
Hybrid quantum genetic algorithm based on spin and its performance analysis

Quantum computing is a new interdisciplinary science combining information science and quantum mechanics. This paper presents a hybrid quantum genetic algorithm based on spin, which implements quantum crossover on quantum individuals, which is beneficial to retain relatively good gene segments. The strategy of updating quantum gate and adaptively adjusting search grid by using quantum bit phase method; In this paper, the critical properties of quantum Heisenberg model with mixed spins on simple cubic lattice are studied by using the mean field approximation of two spin groups, and the hybrid quantum genetic algorithm based on spins is applied to solve knapsack problem. At present, many problems in the fields of industry and financial investment can be transformed into backpack problems to solve. The effectiveness of spin-based hybrid quantum genetic algorithm in solving knapsack problem has been proved by several groups of experiments.
LibGuides: Digital Primary and Secondary Sources: Newspapers and Periodicals

This guide contains links to dozens of 100% online primary and secondary resources aimed at students conducting historical research without any access to physical archives or libraries. While most can be freely accessed, some may require a CofC account
Researching anxiety of pre-service teachers in teaching science and mathematics program

This study purposed to investigate researching anxiety of pre-service teachers that might want to explain why they are able to learn successfully in the context of difference in program of study. There were 15 pre-service teachers in M.Ed. program of teaching science and mathematics voluntary participated. Learning Anxiety Questionnaire (LAQ) was employed their anxiety towards learning through Google Form. The study revealed that pre-service teachers had anxiety at medium level. However, some of item present they had different level of anxiety. The effective learning for decreasing level anxiety needs to be more discussed.
A Novel Framework for credit card fraud detection

Credit card fraud is the challenge of predicting fraudulent transactions based on specific rules. In this paper, Various classification algorithms are implemented on an imbalanced dataset concerning the performance analysis to detect fraud in the credit card. In this study, the dataset is sourced from Kaggle. There are 284,807 transactions, out of which 17% of transactions are fraudulent. Various classifiers that are logistic regression, naive Bayes, AdaBoost, and voting classifiers that are combinations of all mentioned above algorithms are refined. The AI model needs significant historical data to prepare the model. For this, a huge amount of information is given to the model as Training data, While dealing with a lot of information, the model's execution time is expanded, which influences execution. In this study, the voting classifier is applied for the expectation analysis which is a mix of different AI calculations.This voting based classifier increases the complexity of the prediction analysis and also increases execution time. In the future, a hybrid classification model will be designed to detect credit card scams.
Chapter 13 of Holistic Education in South America, Bhutan, and The Asia Pacific Network in Holistic Education by John Miller

This is a chapter from a memoir that describes the journey of John (Jack) Miller.  The book explores how his personal journey is related to the work he has done in holistic education, contemplative education, and spirituality in education. In holistic education the personal and professional are connected.  Professor Miller’s journey includes events, books, teachers, and the many factors in his life that  have contributed to his work, which includes more than 20 books and extensive travel around the world. An example of the relationship between the personal and the professional is that Jack began meditating in 1974 and this practice has provided the foundation for much of his teaching and writing.Keywords: holistic education, contemplative education,  spirituality in education,  mindfulness,  embodied learning
LibGuides: Permalinks: EBSCO

Learn how to create permanent URLs for the library's electronic resources: databases, journals, articles, ebooks, etc
Remote Sensing Journalism in the Omnimedia Era

Objectives  As an extension of human perception in space and time, remote sensing is a new medium that conforms to the concept of omnimedia. Methods  Based on the analysis of the current situation at home and abroad, this paper proposes the interdisciplinary direction of remote sensing journalism. The combination of remote sensing and journalism has advantages in breaking through the limitations of human vision in time, space, and spectrum, realizing multi-scale revealing laws and ensuring authenticity. Results  This paper explains that the scientific problems of remote sensing journalism are to build a news mission-driven remote sensing chain service model and to create a narrative mechanism and lens language system. And it also explains that the essential technical problems of remote sensing journalism are the quality assurance, the realization and the expressiveness of remote sensing data. Conclusions  Combined with the technical applications of Xinhua News Agency in the production of remote sensing news, this paper reveals the outstanding performances including efficient image acquisition, convenient and intuitive forensics, time-series image extraction, and lens language innovation in current remote sensing news dissemination.
TEACHING ENGLISH GRAMMAR THROUGH TRUE OR FALSE QUIZ BY MACRO FEATURE IN MICROSOFT POWERPOINT FOR EFL STUDENTS

Nowadays, the improvement of strategy to teach grammar as a difficult subject matter brings educators to engage with technology. The closest technology or multimedia used by teachers is Microsoft Power Point. It is quite common for modern teacher to present a teaching material using Microsoft Power Point. However, the frequent use of Power Point makes the students bored. They need something more attractive than conventional presentations. Therefore, English teachers can use macro feature in Microsoft Power Point to make a quiz in order to enhance students’ interest in learning. This paper presents two strategies of teaching grammar using interactive Microsoft Power Point with macro features that enable them to make interactive yet efficient true or false quiz for EFL students followed by its benefits in every aspect of the quiz.
Case Study : Air Terjun Laundry / Ainun Najiha Ridzuan

Air Terjun Laundry is a business that provide facility of self-service to wash and dry the clothes without much personalized professional help. It is a well-known self-service laundry at Lembah Sireh since it is the biggest laundry shop at Kota Bharu and has been operating for 6 years. The facilities offered by Air Terjun Laundry including user-friendly coin-operated washing machines, dryers and Wi-Fi. There is also a vending machine for the customers to buy drinks
Technology and Crafts in Archaeology Critical review over “Archaeological Approaches to Technology”

Introduction and Aim: “Archaeological Approaches to Technology” by Heather Margaret-Louise Miller, professor at University of Toronto is truly an update survey over technology and crafts in archaeology that witnesses the hard efforts of the author. . Method: To do this critical review, the author of this paper first read the whole book in precise way and then made some notes over those part of the book that was necessary in terms of contents or in editorial aspects. Then to correct some shortage it was necessary to compare the Persian translation with the original texts and finally some suggestion have been made for improving the translation.Conclusion: one of the most notable aspect of the book is its wide references over different area of studies in each seasons. This could be very useful for graduated students who seek to work on crafts and technology in archaeology. . From technical point of view the book is printed and edited in professional way, which its combination with its simple translation would probably satisfy the readers. The biggest shortage of the translation is that translator stick too much to the main texts and its structure in a way that in some parts of the book the grammar is more like to original language than to Persian.