Reviewerly/exHarmony huggingface dataset:
Development Of Queue Line System For Washing Machine Using Android

Nowadays, time is gold. From the observation of student life at Satra Hostel in UTeM, student have limited time to do side activities including managing their own laundry. This is because, the time required to wait for a washing machine it takes a long time. In time, students should wait until the previous washed-out clothes have to be cut off and will cause the student to take longer to wait. After researching related issues, an innovate system will be proposed “The Queue Line System using Android”. It will produce time savings for students in queuing systems for a washing machine. Student does not have to wait for too long and can-do other activities while waiting such as do their assignment, make a revision and other practical things without having regularly monitor washing machines. This project is using development of system which is the MIT App Inventor, Arduino IDE and Database using Firebase System. All of system been combined to build the application to make the user much easier. The system will be activated when the user scan the QR Code and being stated as Machine 1. The database will be reset on 12:00am. All the objective had been achieved from the analysis and testing result
INVESTIGATING THE DESCRIPTIVE WRITING MASTERY USING PASSIVE SENTENCES (A Case Study At Universitas Islam Negeri Sulthan Thaha Saifuddin Jambi In English Department)

Abstract: the issue of English teaching is always an important one and it will continue to be one of the dominant points in education problems. Through qualitative method, this study aimed to explore the investigating about students’ mastery in descriptive writing specifically in using passive sentences. The data were collected by test, observation, and in-dept interview with English lecturer and English program in Islamic state university Sulthan Thaha Saifuddin Jambi. The results of the data analysis revealed that many students are not mastery in descriptive writing in using passive sentences. The findings show that passive sentences are not discussed specifically in the classrooms. Recommendation for English subject to make a lesson plan about passive sentences and practice them in a scientific writing. Keywords:  Passive sentences, Descriptive writing, English teaching
2015 개정 초 · 중학교 영어과 교육과정의 내용 적정성에 대한 교사 인식

The purpose of this study was to explore how English teachers perceive the appropriateness of the quantity and level of content in the 2015 Revised National English Curriculum. In order to evaluate the appropriateness of the modified curriculum, a survey questionnaire was administered to English teachers at elementary and middle schools across Korea. Teachers and university professors were also consulted for guidance regarding the appropriate quantity and level of content. According to the survey results, both elementary and middle school teachers believe that the quantity and level of content are mostly appropriate for students. However, responses related to the appropriateness of achievement standards for reading and writing were less positive than those for listening and speaking for children in elementary school grades 5 and 6 and middle school grades 1 to 3. In general, methods of optimizing reading and writing content in the English curriculum are discussed.
Teaching Tolerance in the Context of Cross-Cultural Training of Future Professionals

The purpose of this study is to develop a tolerance training program for future professionals and to experimentally test its effectiveness in the process of cross-cultural preparation training.The study includes four consecutive stages: preparation, diagnosing, the experiment and evaluation of results.112 students of different nationalities were invited to participate in the study.They were split into an experimental (research) and a control group.A requirement for the control group was to participate in the survey at the beginning and at the end of the experiment.A requirement for the experimental (research) group was their cooperation throughout the experiment.Diagnosis of tolerance levels at the beginning of the experiment showed that most students had medium and low tolerance levels.The coordinators developed a discussion club program "The Impact of Society on Tolerance and Values Formation."In 8 months The control survey results were processed with the methods of mathematical statistics and compared with the results of the diagnostic experiment.Comparison and analysis of the study results showed that the number of respondents in the experimental group with medium and high levels of tolerance increased significantly.In the control group, the results remained almost unchanged.Our study has proved that the discussion club program "The Impact of Society on Tolerance and Values Formation" we developed may be implemented in different universities to foster tolerance of future professionals.
ABILITY TO WRITE SENTENCES USING ACRONYMS ON JUNIOR HIGH SCHOOL STUDENTS

A descriptive study of the ability to write using acronyms is an effort to improve and develop it as a written work using relevant and accountable scientific references. In this study, what was examined was the ability of students in writing sentences using acronyms based on a contextual approach. Frequency calculations are used by calculating the Mean, Mode, and Median and then converting the score into the final value. From the results of this study, it was obtained that the highest score of students in writing sentences using acronyms was 95 classified as excellent criteria, the lowest score in writing sentences using the acronym 75 was classified as right criteria, and the average score of students in writing sentences using acronyms was 89, 06 is classified as an excellent criterion. Then we get a median of 90 and a mode of 90.
A Comparative Study On Crypto Currency Prediction Using Modern Deep Learning Techniques

Cryptocurrencies are now well-established and widely accepted as a form of alternative trading money. Because they have invaded nearly all accounting operations, cryptocurrency trading is often regarded as popular and propitious sorts of successful investments. A reliable forecasting and prediction model is essential for predicting the high volatility caused by the increase in financial market. This current work summarises various optimisation techniques by shedding light on the volatility factors like internal competition, market pressure, financial problems, social and political conflicts, etc. A comprehensive study is presented on how to predict the volatility of cryptocurrency and formulate their inter-connections with the parent Cryptocurrencies using various deep learning frameworks. Further, this work focuses on utilising sophisticated models to improve the forecasting performance of cryptocurrency. We are hopeful that this work will provide broader insights in the future research of cryptocurrency.
CNN-based Off-board Computation for Real-time Object Detection and Tracking Using a Drone : Sophan Wahyudi Nawawi, Ahmed Ashraf Mohamed Ahmed Abdou, Nur Azlina Abd Aziz*

Object detection and tracking have become one of the most important applications for UAVs, especially in surveillance applications. Single object tracking using a drone is an active field for research due to its importance in surveillance. In this paper, a real-time human and cars detection and tracking approach are proposed using a CNN-based technique by combining the state-of-the-art object detection algorithm YOLOv4 with the state-of-the-art multi objects tracking algorithm DeepSORT using video streaming from a drone for the purpose of surveillance. Furthermore, an algorithm was developed to enhance the observation ability by choosing a single object to be tracked. The algorithm was implemented using Tello drone with a developed navigation algorithm based on the vision analysis.Keywords: Object detection, Single object tracking, drone, CNN, UAV
LOW-COST FIELD PROGRAMMABLE GATE ARRAY ACCELERATES DEEP Q-LEARNING

Abstract. Due to recent advances in digital technologies, deep reinforcement learning has emerged, and has demonstrated its ability and effectiveness in solving complex learning problems not possible before. In particular, convolution neural networks (CNNs) have been demonstrated their effectiveness in reinforcement learning. However, they require intensive CPU operations and memory bandwidth that make general CPUs fail to achieve desired performance levels. In this paper, we used some low-cost field programming gates array (FPGA) designed a parallel Deep Qlearning accelerator to solve this problem. And the system has high efficient and flexibility.
Design and simulation of video monitoring structure over TCP/IP system using MATLAB

Video monitoring systems are undergoing an evolution from conventional analog to digital clarification to provide better rate and security over internet protocols. In addition, analog surveillance becomes insufficient to face enormous demand of security of system contains more than hundreds of camera often deployed in hotels environments far away from room control. This paper presents the design and simulation of a video monitoring scheme in excess of a Transmission Control Protocol/Internet Protocol (TCP/IP) system using MATLAB. Sophisticated cameras could record directly high definition digital videos based on digital technology which simply communicate the control room relaying on ordinary internet protocol infrastructure networks. This technology provides a flexible network interface over a wide variety of heterogeneous technology networks. Though, the acceptance of IP designed for video monitoring pretense severe difficulties in terms of power processing, system dependability, required bandwidth, and security of networks. The advantage of IP based video monitoring system has been investigated over conventional analog systems and the challenges of the method are described. The open research issues are still requiring a final solution to permits complete abandon against conventional technology of analog methods. In conclusion, the method to tackle the purpose of video monitoring in actual operation is proposed and verified properly by means of model simulation.
Data Segmentation Methods for Activity Recognition in Ambient Assisted Living

The segmentation of sensor data plays an important role in the Recognition of the activities of daily living. In this paper, we summarize the state of the art of data stream segmentation in the past five years and divide them into four categories, i.e., change point detection based method, semantics based method, window based method, and deep learning-based methods. The summary shows that there are relatively few studies on segmentation using deep learning methods. Besides, there is a lack of a general platform, which can be used in comparing different methods.
THE ROLE OF QUALITY EDUCATION AND THE IMPORTANCE OF LEADERSHIP AND ADAPTABILITY IN THE NEW CHALLENGING TIMES OF COVID-19 OR HOW TO EDUCATE NEW GENERATION OF LEADERS IN DIGITAL EDUCATION ERA

THE ROLE OF QUALITY EDUCATION AND THE IMPORTANCE OF LEADERSHIP AND ADAPTABILITY IN THE NEW CHALLENGING TIMES OF COVID-19 OR HOW TO EDUCATE NEW GENERATION OF LEADERS IN DIGITAL EDUCATION ERA
The bridge - Part 3

The article argues that a dynamic systems theory approach can be helpful in understanding intrapersonal psychological behaviour changes. In terms of control and coordination, different movement systems - walk, trot, canter - are incomparable. This is also the case with psychological phase transitions. Person 1 can be nice in an mundane state and become life-threatening in an angry or furious state, while Person 2 can be relatively impatient and easily annoyed in the mundane state, but on the other hand relatively controlled in an angry state. Person 1 will then probably rarely go into the angry state, while Person 2 can easily switch between the two mentioned states. Some attractor regimes are rarely achieved under normal circumstances (a killer sleeps in all of us). Psychology often focuses on individual states rather than transitions between states.
"Characterization and Classification of Castoff Spatter from Kitchen Knives"

Blood spatter is defined as a distribution of bloodstains that indicate, through a specific arrangement, how the pattern was created [1]. Interpretation of blood spatter and its different patterns plays a crucial role in crime scene reconstruction. For example, the ratio of width to length of a drop can indicate the angle at which the blood drop fell
An Evaluation of State-of-the-Art Approaches to Relation Extraction for Usage on Domain-Specific Corpora

The task of relation extraction aims at classifying the semantic relations between entities in a text. When coupled with named-entity recognition these can be used as the building blocks for an information extraction procedure that results in the construction of a Knowledge Graph. While many NLP libraries support named-entity recognition, there is no off-the-shelf solution for relation extraction. In this paper, we evaluate and compare several state-of-the-art approaches on a subset of the FewRel data set as well as a manually annotated corpus. The custom corpus contains six relations from the area of market research and is available for public use. Our approach provides guidance for the selection of models and training data for relation extraction in realworld projects.
Methodologies and Strategies for a Mixed Reality Mobile Learning

Mixed reality mobile learning (MRML) is intended as a continuous advancement and expansion of mobile learning. The main feature of M-leaming is that it enables a situated learning experience mediated by a particular technology. As mobile learning has its roots in e-learning and moves from it, bringing a change of paradigm, likewise the shift from M-learning to MRML brings novelties, such as new tools and new characteristics. In the transition from e-learning to M-learning the peoples moved from attributes, such as personalized, media-rich, usable, hyper-linked, accessible, and connected to spontaneous, situated, portable, informal, and personal. Teachers need to encourage the instances of meaningful learning, providing students with conceptual means of judging their MRML experiences within the prospect of self-regulated learning and lifelong learning. Observation of institutional and educational contexts highlights that the most practised teaching method is the ‘traditional’ one, i.e., lecturing.
Ethics-Based Auditing of Automated Decision-Making Systems: Nature, Scope, and Limitations

Important decisions that impact humans lives, livelihoods, and the natural environment are increasingly being automated. Delegating tasks to so-called automated decision-making systems (ADMS) can improve efficiency and enable new solutions. However, these benefits are coupled with ethical challenges. For example, ADMS may produce discriminatory outcomes, violate individual privacy, and undermine human self-determination. New governance mechanisms are thus needed that help organisations design and deploy ADMS in ways that are ethical, while enabling society to reap the full economic and social benefits of automation. In this article, we consider the feasibility and efficacy of ethics-based auditing (EBA) as a governance mechanism that allows organisations to validate claims made about their ADMS. Building on previous work, we define EBA as a structured process whereby an entity’s present or past behaviour is assessed for consistency with relevant principles or norms. We then offer three contributions to the existing literature. First, we provide a theoretical explanation of how EBA can contribute to good governance by promoting procedural regularity and transparency. Second, we propose seven criteria for how to design and implement EBA procedures successfully. Third, we identify and discuss the conceptual, technical, social, economic, organisational, and institutional constraints associated with EBA. We conclude that EBA should be considered an integral component of multifaced approaches to managing the ethical risks posed by ADMS.
명대(明代) 일용유서(日用類書)를 통해 본 사민(士民) 여성의 일상과 교육

This paper is intended to analyze the daily lives and educational situations of various women in the Ming Dynasty through Encyclopedias for Daily Use. Encyclopedias for Daily Use have explanations of food, clothing, and very trivial things. The content of Encyclopedias for Daily Use is so popular that it has a device that even people who don’t know the letters can read it. It is poetry and illustration. Poetry is short and can be memorized quickly if you follow the rhythm, and Illustrations have an educational effect that allows you to know the content just by looking at the picture.Inside Encyclopedias for Daily Use, there are poems and illustrations, which allow female readers to understand life-related knowledge. By analyzing how Encyclopedias for Daily Use deliver food, pregnancy, childbirth, and childcare to female readers, one can understand the daily lives and cultures of various female readers in the Ming Dynasty.
Balanced (Almost) Binary Sequence Pairs of Period Q ≡ 1(mod 4) with Optimal Autocorrelation and Cross-Correlation

In this letter, the almost binary sequence (sequence with a single zero element) is considered as a special class of binary sequence. Four new bounds on the cross-correlation of balanced (almost) binary sequences with period Q ≡ 1(mod 4) under the precondition of out-of-phase autocorrelation values {-1} or {1, -3} are firstly presented. Then, seven new pairs of balanced (almost) binary sequences of period Q with ideal or optimal autocorrelation values and meeting the lower cross-correlation bounds are proposed by using cyclotomic classes of order 4. These new bounds of (almost) binary sequences with period Q achieve smaller maximum out-of-phase autocorrelation values and cross-correlation values.
Technological and legal challenges for adoption of blockchain in land registry system

The application of blockchain technology in land registry domain has gained momentum because of the availability of consortium-based blockchain, smart contracts and distributed ledger with no single failure and inclusion of trust. The relationship between the property, rights and legal validity is complex. This complex relationship needs to be preserved by the authentic transactions and transaction timestamp and immutability of the transaction. The transactions should be tamper-proof and should be legally valid and adapt to the present and future scope of the enhanced regulatory acts of a country. This article describes the transactions that need to be preserved for land records data, geospatial data and land registry domain. The various blockchain systems, technical and legal requirements, mechanisms and implementation details that need to be addressed in adaptation of blockchain system are discussed in this article.
Research and Practice on the Cultivation and Evaluation of Students' Autonomous Learning Ability in the Network Environment

Autonomous learning means that students can learn without being pushed by external forces, rely on their own subjective wishes, and can completely control their own learning process.  In the current online teaching, the passive learning problem of students is a prominent problem that affects the quality of teaching.  In this regard, this article studies the methods of cultivating students’ autonomous learning ability and the evaluation system under the network environment.
Εξόρυξη κειμένου στην ανασκόπηση βιβλιογραφίας και την τεκμηριωμένη ιατρική

Evidence-based medicine in practice requires the continuous education of medical personnel according to the best up to date medical practices, an increasingly difficult task due to the growing volume of new published research. This thesis explores the implementation of text mining practices under the scope of literature reviews. For this purpose, a large corpus was acquired through programmatical access to scientific publication repositories. Subsequently, two different searching techniques were implemented to retrieve texts concerning text mining and evidence-based medicine. The first method utilized PostgreSQL full-text search to carry out keyword and phrase searches. The second method implemented was Latent Semantic Analysis – LSA, a mathematical technique that relies on Singular Value Decomposition – SVD to project the data in a reduced dimension semantic space. Results were evaluated after manual labelling of records as relevant or non-relevant, with promising results.
Perancangan Aplikasi Pengenalan Objek 3D Komponen Komputer Menggunakan Augmented Reality Berbasis Android

Weak knowledge of computer scholars about the components of the preparation of computers often become a joke in the world of work. There are not many programmers and designers who do not know computer components, even though their interactions at the computer are above the average normal use. Augmented reality is a way to combine virtual worlds (virtual environment) into the real world (reality environment) by utilizing the camera in real time. This technique can help display the shape of objects in three-dimensional computer components into the real world. Text Recognition is a detection of writing into a computer system. The application of text recognition to the Augmented Reality technique can detect text as well as project objects of 3 dimensional components of computer components. This certainly makes it easier for users to find out computer components just by using text.
A Multi-Pedestrian Tracking Algorithm Based on Center Point Detection and Person Re-identification

Objectives  In video-based multiple object tracking, the object detection and re-identification have a strong correlation. The existing methods generally train the object detection and re-identification networks separately, which makes the tracking speed fail to meet the real-time requirements. In this paper, we integrate the detection and re-identification into one network to accelerate the tracking process, and also solve the problems of identity switching and failure tracking. Methods  This paper develops a pedestrian motion model and obtains the optimal state estimation of pedestrians using center point detection. The person re-identification model with deep layer features uses the Mahalanobis distance and cosine distance to enhance the ability of person identification. And the Hungary algorithm is used for data online association, where the state estimation results become more accurate using Kalman filtering, and the unrelated lost objects are predicted by motion. Results  Experiments are conducted on MOT15, MOT16 and MOT17 datasets using the proposed algorithm and other multi-pedestrian tracking algorithms, and the multiple object tracking accuracy of tracking results using our proposed algorithm is 63.5, 72.4 and 70.9, respectively, and the identity F1-measure is optimal, with the real-time rate. Conclusions  The proposed algorithm can accelerate the tracking speed by network parameter sharing, and improve the recognition accuracy by person re-identification training.