Reviewerly/exHarmony huggingface dataset:
LibGuides: Remote Access to Library Resources: Borrowing Books - Using "Request It!" Feature

This guide provides instructions for accessing library resources from off campus. Curbside Services provided to Law School and Public Patrons
Cataloguer Acceptance on Cataloguing Module in Open-Source Integrated Library System in Academic Library in Malaysia

This paper aims to identify the acceptance of cataloguers on cataloguing modules in the Open-Source Integrated Library System in an academic library in Malaysia. The research design adopted for this study is descriptive research surveys. This study involved cataloguers in the academic university library in Malaysia that have used Koha as their open-source software since 2013. The survey used an online questionnaire distributed via email to all cataloguers in the selected libraries. The questionnaire comprises questions related to acceptance of module features and module usability on the cataloguing module. The 5-point Likert scale is used to measure the cataloguer acceptance of the cataloguing module, and the data were analysed using SPSS. The findings conclude that the majority of the cataloguers in academic libraries in Malaysia use open-source integrated library system similar to this study, Koha, and have entirely accepted the use of cataloguing module in terms of usability and features as the majority of the data reported on agreement of the user compared to a minority of disagreement. The findings of this study will encourage other researchers to do other studies on the usability of other modules in the open-source system that might improve the acceptance of open-source software.
Use Case: Augmented Reality

How can one make efficient use of smart devices and services in smart production, smart logistics and smart governance? By eXtended Reality (XR) applications, comprising Augmented Reality (AR), Virtual Reality (VR), and Mixed/Merged Reality (MR) applications. When talking about and the join of the virtual and real worlds, we usually mean a visual join although contemporary researches also mention the possibility to include other senses like sound and smell as well.
GAs with Escape from Stagnation of Search for Multiset Iteration Permutations Problem — Consecutive Meals Planning —

In this paper, consecutive meals planning is formulated as a multiset iteration permutation problem that determines the optimal meals plan on a period consisting of consecutive days. In this problem, a meal is characterized by some characteristics such as food style, ingredient, cooking method, and so on. The evaluation function is defined by use of information entropy for measuring the appearance order of meal's characteristics on the meals plan. For optimizing this problem, Genetic Algorithms (GAs) with escape from stagnation of search are proposed. It is empirically shown that the proposed GAs with escape operation work better than the conventional permutation GA without escape operation for small and large size optimization problems.
A Sistem Informasi Akuntansi Atas Pengendalian Persediaan pada Rejeki 2 Swalayan di Omben Sampang

This study aims to determine the accounting information system for inventory control at Rejeki 2 Swalayan in Omben Sampang. The type of research used is descriptive qualitative where the aim is to describe systematically the accounting information system for controlling merchandise inventory. Data were collected by means of observation, interview, documentation. The results showed that the accounting information system for inventory control owned by Rejeki 2 supermarkets in Omben Sampang was good. However, there are also weaknesses in the system, namely not using ledgers and auxiliary books. use ledgers and subsidiary books to facilitate transactions.
A Genetic Fuzzy Approach for the Prediction of Heart Failure

Heart disease is one of the leading causes of death both the United States and around the world, responsible for the deaths of some 17 million people annually. Many of these deaths could be either prevented or treated more effectively by early detection and subsequent behavioral changes. A model which can accurately predict which patients are at high risk of heart failure would therefore prove valuable for use by healthcare professionals. This paper proposes an approach using a collection of fuzzy inference systems (FIS), arranged in a fuzzy tree to identify which patients are at the highest risk of heart failure. The structure of the fuzzy tree is assumed a priori, then the membership functions and rule base (RB) for each individual FIS in the tree are tuned using a genetic algorithm (GA). The results of the approach are quantified using accuracy, F1 score, true positive rate, and true negative rate, then compared to the results obtained by a variety of different algorithms on the same dataset.
基于联合相机路径的红外视频稳像算法

To solve the problem of infrared video image stabilization caused by parallax variation, the infrared video image stabilization algorithm based on joint camera path was proposed, which included four steps: preprocessing, joint camera path solving, multi-path optimization and motion compensation. Firstly, histogram equalization, feature point extraction, matching processing and pre-mapping were needed for infrared image. Then, each frame of image was divided into m×n grid cells, and local homography matrixs obtained from the corresponding grid in each frame were multiplied by the mapping motion representation based on the grid to obtain the joint camera path. Then, the path of the joint camera was smoothed by the strategy of ‘multi-path optimization’. Finally, the smooth path was used to stabilize the video. The experimental results show that this method can effectively deal with the nonlinear motion caused by parallax, which is better than the traditional image stabilization algorithm, and can achieve good image stabilization even when the feature points have partial occlusion.
Development of Health Systems for Home Environments with the Focus on Sleep Monitoring

Health monitoring in a home environment can have broader use since it may provide continuous control of health parameters with relatively minor intrusiveness into regular life. This work aims to verify if it is possible to replace the typical in some sleep medicine areas subjective questioning by an objective measurement using electronic devices. For this purpose, a study was conducted with ten subjects, in which objective and subjective measurement of relevant sleep parameters took place. The results of both measurement methods were evaluated and analyzed. The results showed that while for some measures, such as Total Time in Bed, there is a high agreement between objective and subjective measurements, for others, such as sleep quality, there are significant differences. For this reason, currently, a combination of both measurement methods may be beneficial and provide the most detailed results, while a partial replacement can already reduce the number of questions at the subjective measurement by measurement through electronic devices.
Hide and seek with quantum resources: new and modified protocols for quantum steganography

Steganography is the science of hiding and communicating a secret message by embedding it in an innocent looking text such that the eavesdropper is unaware of its existence. Previously, attempts were made to establish steganography using quantum key distribution (QKD). Recently, it has been shown that such protocols are vulnerable to a certain steganalysis attack that can detect the presence of the hidden message and suppress the entire communication. In this work, we elaborate on the vulnerabilities of the original protocol which make it insecure against this detection attack. Further, we propose a novel steganography protocol using discrete modulation continuous variable QKD that eliminates the threat of this detection-based attack. Deriving from the properties of our protocol, we also propose modifications in the original protocol to dispose of its vulnerabilities and make it insusceptible to steganalysis.
Information Control System for Educational Processing Case Study of College of Management Mahidol University

A research and development of an Educational Processing Control Information System have been developed from faculty members’ work that submitting their final grade on a paper form. Then, staff use the package software to process results and submit the results to be verified and approved. This research aims to develop the Educational Processing Control Information System for the academic units of College of Management, Mahidol University as the educational technology tool for faculty and staff members. This Educational Processing Control Information System includes the research methods of studying the system requirements with interview and existing documents, analyzing demands, designing and developing the system, implementing the system and then, evaluating user satisfaction. The results of the user satisfaction surveys showed that a total of 21 system users consisting of the faculty and academic staff members, the authorizers who verify and approve the results, etc. were satisfied with the system usage at an average score of 4.20, the system efficiency at the average score of 4.00 and the overall satisfaction at the average score of 4.14. Therefore, the overall results indicated that the Educational Processing Control Information System: A case study of College of Management, Mahidol University can be used and achieved the desired objectives.
FEATURES OF TEACHING HUMANITIES IN A CREATIVE UNIVERSITY

Introduction. This paper seeks to address specific features of teaching humanities in a creative university. The novelty of the research lies in the analysis of features of the educational process, students enrolled and the conditions for conducting classes in creative universities. The presented results can be used in teaching a cycle of humanities in universities that train specialists in creative disciplines. Materials and methods. The study identifies the features of methods and forms of control that need to be adapted to improve their effectiveness. Examples of intermediate and final control forms and ways to maintain and enhance motivation in students of different forms of education are given. The material relies on the author’s teaching experience in the Federal State Budgetary Educational Institution of Higher Education “Russian Institute of Theater Arts.” Research results. The rationale behind the choice of teaching methods is supplemented with examples of practical tasks and ways to increase and maintain a high level of student motivation. The need to use imitation games and non-game teaching methods and to individualize the forms of control is emphasized. Conclusions. The paper reflects the features of teaching humanities in creative universities, which are conditioned by the educational environment, students enrolled, specific features of the educational process, and curricula. Keywords: humanities, creative university, students, educational process, motivation, methods, forms of control.
Machine Learning Methods for Ordinal Classification with Additional Relative Information.

The ability to learn an accurate classification process is often limited by the amount of labeled data. Incorporating additional information into the learning process for overcoming this limitation has been a popular research topic. In this work, we focus on ordinal classification problems that are provided with limited absolute information and additional relative information. We modify some classical machine learning methods to combine both types of information. Moreover, we propose a new distance metric learning method to exploit both types of information for learning a suitable distance metric that can be incorporated into the augmented method of k nearest neighbors for ordinal classification. The experimental results show that our method is competitive with other modified machine learning methods and considering additional relative information leads to a better performance.
Intention Enhanced Dual Heterogeneous Graph Attention Network for Sequential Recommendation

Sequential recommendation plays a vital role in many web applications, aiming to predict users’ next actions based on their historical sequential behaviors. Efficiently learning the features of items and understanding user’s intentions are pivotal for sequential recommendation. However, due to the diversity of items and the sparseness of user’s interaction with items, it’s challenging to accurately learn the features of items through sparse interaction data. In addition, users usually have shifting intentions when interacting with items, which makes it difficult to understand users’ intentions. To this end, we propose a novel intention enhanced dual heterogeneous graph attention network (IE-DHGAT) for sequential recommendation. Specifically, we construct an extensible heterogeneous graph, which contains items and items’ various attributes, and we design a dual graph attention network to learn the features of items via explicitly incorporating item’s various attribute information into item embeddings. Further, we propose an intention enhanced attention layer to efficiently capture users’ shifting intentions through computing the correlation between items and discriminating different intention areas in users’ interaction sequences. We conduct extensive experiments on three real-world datasets and the results demonstrate that our proposed approach achieves better performance than the state-of-the-art methods.
Logical Majorana Fermions for Fault-Tolerant Quantum Simulation.

We show how to absorb fermionic quantum simulation's expensive fermion-to-qubit mapping overhead into the overhead already incurred by surface-code-based fault-tolerant quantum computing. The key idea is to process information in surface-code twist defects, which behave like logical Majorana fermions. Our approach implements a universal set of fault-tolerant gates on these logical Majorana fermions by effecting encoded measurement-based topological quantum computing with them. A critical feature of our approach is the use of code deformations between logical tetron and logical hexon surface-code-patch encodings, which enables one to move beyond the limitations of a wholly square-patch tetronic surface-code approach. To motivate near-term implementations, we also show how one could realize each of a universal set of logical Majorana gates on a small-scale testbed using noisy intermediate scale quantum (NISQ) technology on as few as 13 qubits.
PENGARUH BIMBINGAN BELAJAR TERHADAP HASILBELAJAR MAHASISWA PADA MATAKULIAH KALKULUS DIFERENSIAL

This study aims to investigate the effect of tutoring on student learning outcomes. This study employed a descriptive and quantitative approach. The population of this research was the first year students of the Mathematics Education Study Program for the 2019/2020 academic year. The research sample was 50 students, selected by purposive sampling from four classes of students. Data collection was conducted using the test instrument for student learning outcomes before and after the tutoring. The data were analyzed using the t-test. The results showed that there was a significant effect of tutoring on student learning outcomes in the differential calculus course. Tutoring activities outside of lecture activities need to be continued in other courses in future lectures.
TopoDetect: Framework for topological features detection in graph embeddings

TopoDetect is a Python package that allows the user to investigate if important topological features, such as the Degree of the nodes, their Triangle Count, or their Local Clustering Score, are preserved in the embeddings of graph representation models. Additionally, the framework enables the visualization of the embeddings according to the distribution of the topological features among the nodes. Moreover, TopoDetect enables us to study the effect of the preservation of these features by evaluating the performance of the embeddings on downstream learning tasks such as clustering and classification.
Transdisciplinary integration and its implementation in primary education through two STEAM projects

espanolLa integracion curricular desde una perspectiva STEAM transdisciplinar representa un profundo desafio. Este estudio profundiza en una comprension transdisciplinar de la Educacion Primaria y el rol del arte en dos proyectos STEAM a traves del concepto de gran idea. Han participado 111 estudiantes de ocho grupos (11–12 anos) de un programa para alumnado con altas capacidades, junto con cinco profesores y cuatro profesionales externos. Desde el rol de profesores e investigadores, se ha empleado la observacion participante y no participante, grabaciones de video, entrevistas individuales y grupales, diarios de clase y cuestionarios, triangulados y codificados a traves de la Teoria de la Actividad mediante el software Atlas.ti8 y el analisis estadistico. Los resultados evidencian la significatividad del aprendizaje y la construccion de experiencias significativas, relacionadas con un grado elevado de motivacion y de satisfaccion, asi como a la integracion de diversas areas en un proceso participativo, en el que el arte ha jugado un rol disciplinar e integrador. Se presenta una aproximacion STEAM Transcisciplinar que podria resultar paradigmatica para el ambito de la Educcion Primaria. EnglishCurriculum integration from a STEAM transdisciplinary perspective represents a profound challenge. This study delves into a transdisciplinary approach to primary education and the role of the arts through two STEAM projects in a programme for gifted students in Madrid (Spain). Participants include 111 students from eight groups (11–12 years old), five teachers and four external professionals. The teachers fulfill the dual role of both teacher and researcher, using participant and non-participant observation, video recordings, interviews and classroom journals and questionnaires. All the findings have been triangulated and coded by means of Activity Theory, using Atlas.ti8 software and statistical analysis. The results show the significance of learning and the creation of meaningful experiences as being related to a high degree of motivation and satisfaction, and to the integration of diverse areas in a participatory process in which the arts play a disciplinary and integrating role. A transdisciplinary STEAM approach is presented that could be paradigmatic for the field of primary education.
A Traffic Video Completion Model Based on Generative Adversarial Networks

Aiming at the problem of missing traffic video frames, this paper proposes a complementary model of generative adversarial networks. The model uses the Feature Pyramid Network (FPN) to obtain feature maps of multiple scales on the input video frame. By fusing feature maps of different scales, it can better integrate the semantic information on the frame. The local patch discriminator added to the discriminator model effectively ensures the accuracy and continuity of the completed frame. Experimental results on Caltech pedestrian dataset and KITTI dataset show the good performance of the proposed model.
Development of the creative potential of students studying in the field of training "Musical Variety Art"

This article is devoted to musical pedagogy in the broadest sense of this concept. The teaching of the performing arts is very specific. In our country, there is a system of training musicians, which, as a rule, consists of the initial, secondary professional and higher stages of ascent to mastery. Such a professional school has evolved over several centuries. It received its consolidation in practice in the 19th and 20th centuries. The performing art of Russian musicians and singers is recognized all over the world. The arts education system continues to improve. The author of this article offers her analysis of the professional training of students at the Department of Art at the higher educational institution. The materials of the article will be of interest to our colleagues, especially in the part related to the comprehension of the educational standard in the musical variety art.
Blind classification for linear and non-linear modulations based on the fusion of multiple features

Blind identification for modulations is an important issue in signal processing and wireless communications. The role of modulation identification is to find out which type of modulations for the signals received. To investigate the classification for both linear and non-linear modulations, the fusion of multiple features is studied in terms of the cumulants, approximate entropy and kurtosis. The features are combined as the input vector of back propagation neural network, which is designed to discriminate multiple modulations. Training and test are verified via simulations finally.
Colour, texture, and luminance: Textile design methods for printing with electroluminescent inks

Smart materials for textile printing present an exploratory design space where the traditional textile methodology of working with colours and print design needs to be revisited to exploit their ex ...
Pengabdian Masyarakat di Tiban Indah 2 Dengan Pembuatan Rajutan Benang Dan Plastik

Knitting is making cloth, clothing or fashion equipment from knitting yarn with two needles, knitting activities can also be used as high-value and attractive goods in the eyes of foreign tourists. This knitting not only produces items such as clothes but can also produce items for accessories such as key chains that can be shaped according to taste, knitting can be done by hand or machine. Basic techniques in knitting are the upper and lower stitches, the knitted material is not only obtained from yarn but can also be obtained from used plastic that can be recycled and is also environmentally friendly. The purpose of this study is to introduce to local residents that knitting activities that can provide income or income for the business and also provide experiences that can be shared with many people. The location of the place of knitting is in the area of ​​Tiban Indah 2 coinciding in the Sun Beach Housing Rt 002 / Rw 010. In this knitting activity also often involves the mothers around the housing by dividing their respective tasks.
LibGuides: Engaging in Science, Engineering, and Math (SEM) PD 126: Find Articles

Research information for students enrolled in PD 126: Engaging in Science, Engineering, and Math
Oil Depot Detection via CNN Semantic Segmentation

Neural network methods are nowadays used for a wide variety of tasks, in particular in computer vision. Among those tasks, semantic segmentation aims at labeling every pixel in an image, giving a good understanding of the scene. In this paper, we propose to use two neural network architectures designed for semantic segmentation to detect oil tank depots in Sentinel-2 images. We compare the methods to an unsupervised algorithm designed to solve the same problem.