Reviewerly/exHarmony huggingface dataset:
THE EFFECT OF LIFE-STORY-RETELLING TECHNIQUE ON STUDENTS’ SPEAKING FLUENCY

Second or foreign language learners often get difficulty in speaking fluency, which can be called as disfluency. Disfluency can be caused by some problems such as difficult task and lack of practice. Retelling a life story is one of the activities in teaching speaking which can be used by teachers in the EFL classroom. This study aims to find out the effectiveness of using Students’ Life Story by retelling technique in improving speaking fluency. The research design used in this study was Pre-Experimental Research with a quantitative approach. This study was conducted in three meetings. As the instruments, the researcher used the test which was pre-test and post-test. The subjects of this study were 36 students of X Science 6 class at Senior High School 3 Lumajang. The result of this research showed that life-story-retelling technique can help the students in improving their speaking fluency. This study was considered successful when there was a significant result between students’ score in pre-test and post-test. Thus, it can be concluded that life-story-retelling technique successfully improved the students’ speaking fluency. Keywords: Speaking Fluency, Students’ Life Story, Retelling Technique
Detection of Credit Card Fraud in a Brazilian database using Autoencoder Neural Network

The increasing number of credit-card transactions made over the internet in recent years has lead to a rise in the same proportion in the amount of fraud. Due to the large volume of web-based transactions that should be carried out daily, it is necessary to have a robust system to predict such crime to reduce loss and increase the confidence of banks and issuers. Deep Learning techniques emerge as a way to automate this process, training classifiers with data from past transactions to try to predict future frauds. In this paper, we build an Autoencoder model and perform a threshold tuning to predict fraudulent transactions. A proprietary Brazilian credit-card transaction database was used for training and performance evaluation of the model, containing almost 40 million transactions and challenging frauds, which were not previously detected by the organization's current fraud detection systems. The results of the experiments presented satisfactory results in a real-world dataset. The Autoencoder metrics show a good performance in fraud classification, reaching a positive Matthews Correlation Coefficient value and an AUC of 0.81, which are not affected by the database imbalance.
Evaluation of Thermal Deformation of Fastening Structure of Carbon Fiber Reinforced Plastic and Aluminum Using Stereo Image Correlation

This paper describes the evaluation of thermal deformation of the CFRP-aluminum fastening structure using stereo DIC (stereo digital image correlation). This structure is used at the FOB (Fixed Optical Bench) of the astronomical satellite “ASTRO-H.” The fastening structure is heated up with a self-made thermostat, and the in-plane displacements on the three-dimensional surface of it are measured using stereo DIC. Then, the strains are evaluated and the results are compared with those obtained by FEM. By comparing experimental results with those of finite element analysis, the finite element model is improved, then analysis of thermal deformation of the fastening structure is made more accurate and easily.
The effect of the use of information and communication technology (ICT) learning media on the student’s learning activity in class V SD Negeri Pannara Makassar City

This study uses a quantitative approach with the type of research True-Experimental Design with Pretest-Posttest Control Group Design. The purpose of this study was to determine the effect and description of student learning activity before and after the use of information and communication technology (ICT) learning media in Pannara Makassar Elementary School. Data collection techniques used observation sheets (observations), questionnaires (questionnaires), and documentation. The population is all fifth grade students of SD Negeri Pannara Makassar. The sampling technique used is the total sampling technique. The data analysis technique used is descriptive analysis and inferential analysis. The results showed that the use of Information and Communication Technology (ICT) learning media was well implemented. Based on the results and implementation. Student learning activity in learning before using Information and Communication Technology (ICT) learning media (freetest) in the experimental group in the low category 24.00%, the medium category 20.00%, the high category 56.00% and in the very high category 24.00% and the control group in the low category was 32.00%, the medium category was 40.00%, the high category was 28.00%, and the very high category was 24.00%. After being treated with the use of Information and Communication Technology (ICT) learning media, there was an increase in student learning activity in the experimental group with low 0.00%, medium 12.00%, high 32.00%, and very high 56.00% categories. While the control group is in the low category of 0.00%, moderate 20.00%, high 56.00%, and very high 24.00%. From these acquisitions, the use of Information and Communication Technology (ICT) learning media has an effect on the learning activities of Pannara Makassar Elementary School students.
Students’ Attendance Management in Higher Institutions Using Azure Cognitive Service and Opencv Face Detection &amp; Recognition Attendance System

This research aimed at studying the current methods of attendance used at higher institutions of learning in Uganda and the feasibility of using facial biometrics as a new method of capturing attendance. Facial biometrics is distinct from other biometrics because it can be carried out without the consent of the person involved. As a result, the researcher developed a face recognition attendance system using OpenCV and Microsoft Azure CS. Questionnaires, interviews, and observations were used to capture data for the research. The data were analyzed using SPSS to get the requirements and systems functionalities. Object-Oriented Design tools were used to model the architecture of the system. Data Flow Diagram, Use-Case Diagram, Activity Diagram, and Flow Chart were used for processing whereas Entity Relation Diagram was used for data modeling. The system was designed to facilitate attendance management of a large number of attendees with ease. Efficiency and reliability were essential features of the system. Data visualization was provided to help management make informed and timely decisions on management matters that are related to attendance. The system was developed using python Tkinter, OpenCV, and Azure CS as mentioned above. The data (images) used by the system were stored in the cloud for accessibility by multiple users. The system was tested thoroughly using various testing types to uncover and fix errors and to minimize the severity of failures.
Peningkatan Partisipasi Relawan dan Pelaku Pariwisata dalam Pengelolaan Risiko Bencana di Kompleks Candi Borobudur

Disaster Risk Management Plan in cultural heritage areas such as the Borobudur Temple Complex, should be the joint responsibility of all stakeholders. In fact, disaster management at the Borobudur Temple Complex, especially the preservation of the site against disasters, is only the responsibility of the Borobudur Conservation Center. Therefore, in September-November 2021 through the research activities funded by UNESCO, UAJY and BKB have formulated a draft Disaster Risk Management Plan in the form of the borobudur-drr.id digital platform. However, due to the limited implementation time, this platform has not been fully socialized by all stakeholders. Based on the stakeholder meeting, it is known that there are differences in understanding among stakeholders in understanding the comprehensive approach contained in the Disaster Risk Management Plan Action Plan for the Borobudur Temple Complex. The diversity of educational backgrounds, experiences and exposure of stakeholders to disasters and their management requires a forum for equalizing perceptions that supports the synergy of stakeholders in supporting, supervising and implementing the action plans that have been prepared. Conservationists, volunteers and tourism actors are three of the fifty-three stakeholders that have been mapped in the Borobudur Temple Compounds Disaster Risk Management Plan, which has a vital role in realizing the action plan in the Borobudur Temple Area.
A tighter proof for CCA secure inner product functional encryption: Genericity meets efficiency

Inner product functional encryption (IPFE) is a primitive which produces, from a master secret key, decryption keys skk associated to vectors k over some specified base ring. Decrypting an encryption of vector m with skk only reveals 〈k,m〉. Benhamouda et al. [7] provided a generic construction for CCA-secure IPFE from projective hash functions (PHFs), unfortunately their security reduction suffers an exponential loss. Their only instantiation capable of decrypting inner products of large sizes, which relies on the decisional composite residuosity (DCR) assumption, is impractical due to the large size of ciphertexts, decryption keys, and the prohibitive speed of the scheme. Our core contribution is a new approach to proving CCA security. Our constructions maintain the genericity of [7], while our security proof relaxes the requirements on the underlying PHFs and gains in reduction tightness. We instantiate these constructions from the DCR assumption, an assumption in class groups (HSMCL) and the decision Diffie Hellman (DDH) assumption. Our CCA-secure constructions from DCR and HSMCL are the first such schemes to efficiently decrypt inner products of large size, improving by multiple orders of magnitude upon the work of [7]. A single-core C implementation of these schemes shows that, for a 112 bit security, and 100-dimensional vectors, their DCR-based scheme takes 1 h 20 min to encrypt, and over 5 min to decrypt, whereas our slowest scheme takes 5.2 s to encrypt and 0.5 s to decrypt. Similarly a ciphertext for their scheme is of 283 MB; those of our HSMCL-based scheme are of 30 kB.
Graph Algorithms

The graph is represented in the form of vertices and edges. The association between entities shown using graph requires suitable graph algorithm to apply for the application. The different standard graph algorithms are discussed in this chapter.
Studying the squeezing effect and phase-space distribution of a single-photon-added coherent state using a postselected von Neumann measurement

In this paper, ordinary and amplitude-squared squeezing as well as Wigner functions of single-photon-added coherent state after postselected von Neumann measurements are investigated. The analytical results show that the von Neumann type measurement which is characterized by post-selection and weak value can significantly change the squeezing feature of single-photon-added coherent state. It is also found that the postselected measurement can increase the nonclassicality of the original state in strong measurement regimes. It is anticipated that this work could may provide an alternate and effective methods to solve state optimization problems based on the postselected von Neumann measurement technique.
Implementasi Keamanan Citra Menggunakan Algoritma AES-128 Dengan Aplikasi Client-Server

Digital images that are private and confidential are very vulnerable to eavesdropping by irresponsible parties. Especially when distributed over the internet, such as chat-based applications such as Facebook, WhatsApp and e-mail media. Image sent via the internet. Because digital images are still recognizable images and can be used by eavesdroppers for personal gain, to the detriment of those who have access to image data. The act of tapping the image data can be minimized by the application of cryptographic encryption techniques. This research will secure digital images with 128 bit AES method for encryption and decryption of digital images in client-server based applications. The results of the AES algorithm encryption produce a cipherimage with pixel values that are much different from the plainimage pixel values.
Preface

The fifth International Conference on Data Mining, Communications and Information Technology (DMCIT 2021) was held in Hangzhou, China from April 16 to 18, 2021, which is organized by Asia Pacific Institute of Science and Engineering (APISE), and media supported by MDPI-Mathematics. The conference strives to offer plenty of networking opportunities to meet and interact with the world-leading scientists, engineers and researchers as well as industrial partners in Data Mining, Communication Engineering and Information Technology Applications. DMCIT has been held for four years since 2017 after four successful conferences in Phuket, Shanghai, Beijing, and Virtually (2020), attracting a large number of researchers, scholars and students from almost all over the world. DMCIT 2021 is the fifth event and we continue to provide a unique and excellent forum to exchange research methodologies, explore practical applications, and foster innovative ideas, in Data Mining, Communication Engineering and Information Technology Applications. The conference was originally scheduled in Hangzhou from April 16 to 18, 2021. Due to the outbreak of COVID-19, we follow most current conferences and organize it as a hybrid conference, participants who cannot attend offline can also join online. The proceedings of this year’s edition consists of 5 main categories: 1, Intelligent Processing based on Reasoning and Models; 2, Machine Learning Research and Appllications; 3, Classification Methods and Applications; 4, Mathamatical Modeling and Optimization; 5, Simulation and Implementation of Data Centric Approaches. The research tracks attracted 105 submissions from about 11 countries, among which 46 were accepted. All the submissions were rigorously reviewed by the conference Program Committee (PC). We have also selected 2 best oral presenter award and 1 best poster award. Four keynote speakers were invited to share their latest and insightful research ideas in the conference. We would like to take this opportunity to thank all the authors for submitting their papers to our conference. We also extend our appreciation to the invited speakers, PC members, supporting staff, as well as all the Organizing Committee members for their hard work, which eventually makes DMCIT 2021 a successful and fruitful event! Yucong Duan, Hainan University, China Conference Committee Chair, DMCIT 2021
Internet of Things in Enhancing Competitive Capabilities: An Exploratory Study

As a result of intensifying competition between transportation companies and an attempt to reduce costs, deliver on time, maintain products quality and maintain high flexibility in transportation, it has become imperative for transportation companies to go toward using modern technology, including the Internet of things that may ensure achieving competitive capabilities of companies and continue to remain in the market. The study aims to determine the role of the Internet of things in achieving the competitive capabilities (cost, quality, time, flexibility) and priorities of transportation companies and highlighting the importance of the Internet of things because the transport activity is considered as one of the important logistical activities that have a large share in the cost of products. The theoretical part has been written based on previous literature review, whereas, the practical part has been conducted by using a checklist which is distributed to 31 commodity land transportation companies operating at Ibrahim Al-Khalil International Crossing in Iraq by using the Likert triple scale and arranging the scores on the scale; (Agree, somewhat agree, disagree) with weights (2, 1, and 0) respectively. The most important conclusion reached by the current study is that the Internet of things has a significant role in achieving the competitive capabilities of transportation companies which is proved by the result of the total agreement rate up to 71%. The research presented a set of recommendations which are: The necessity of conducting more research on this topic to enrich the current study and benefit from the current study idea to improve transportation companies’ performance in general.
APuML: An Efficient Approach To Detect Mobile Phishing Webpages Using Machine Learning

Abstract Nowadays, the growth of mobile phones users has gained a significant increase because of the features offered by them in abundant amounts. These devices are being used rapidly for accessing the web and many online services. However, the security mechanisms that are available in smartphones are not yet mature. Therefore, smartphones are vulnerable to various types of attacks, such as phishing. The browsers on smartphones are very trivial and the smartphones security abilities have been lessened, to match the smartphone's capabilities. Therefore, detection of the malicious website is different from the previously known technique, which is used on the desktop. Many anti-phishing techniques for mobile devices have been developed but still, there is a lack of a full-fledged solution. Therefore, this paper presents an efficient approach to detect malicious mobile webpages. The proposed approach APuML (Anti Phishing using Machine Learning) extracts all the static and site popularity features from the given URL to create a feature vector. An appropriate machine learning classification algorithm is then applied on the feature set to obtain the result and update the database accordingly. In our approach, the Random Forest classifier outperforms over other classifiers and achieved detection accuracy of 93.85 %. We have also created an endpoint application for the users to interact with our system using his/her mobile devices. Moreover, the proposed approach can identify drive-by downloads attack, zero-day attack and clickjacking attack with high accuracy.
Optimizing digital controller of continuous object automatic control system

The article gives the analysis of optimizing the digital controller of the automatic control system (ACS) of a continuous object. The procedure for replacing a continuous controller with a discrete controller has been analyzed. The original continuous optimized ACS has been illustrated. It has been stated that the continuous ACS and its elements (all or particular) can be modeled by discrete models described by the difference equations, and not the differential ones, as is done in the case of continuous models. The specification of the sampling period of the PI controller model equal to 0.001 s has been given, the coefficients of the Z-transfer function of the digital PI controller, which is equivalent to a continuous controller, are considered. Of practical importance in the control theory is the representation of a discrete model of a controller, which helps obtain a digital transformation algorithm carried out by a controller over a control error, organize a discrete-digital control of a continuous object using a digital processor. The model with a continuous and discrete controller is illustrated. A formula for calculating the values of the lattice function of the output signal of a discrete controller is obtained. It has been found that sampling and quantization of the error signal, as well as restoring the control signal, should be carried out with the proper accuracy, which should provide the required control accuracy. There are considered the models of discrete-digital control with the correct selection of the parameters of discrete PI controllers, a model with a finite time of the transient process and a structure of its contour, given a fifth-order discrete function with a five-step transition to the steady state. It has been inferred that reducing the sampling period and quantization step significantly increases the processor speed requirements.
Some approaches to solving the problems of teaching the disciplines of the natural science cycle and computer science in rural small schools

The article deals with the problems and peculiarities of teaching science and IT in small rural schools. Moreover, it looks upon incomplete classes and forming shared classes filled with student of different levels of education. To underline the importance of the given problem the authors of the article pro-vide the readers with statistics of the percentage of rural schools and of num-ber of students studying there. The article also contains various solutions of the objective problem of teaching science and IT in such schools.
Music Recommendation System using Machine Learning Algorithms

Music рlаys аn imроrtаnt rоle in humаn lifestyles. Humans рrefers tо hear tо musiс/songs mоre оften thаn аbig apple оther pursuit. With internet teсhnоlоgies, large quantity оf musiс соntent hold musiс оf several genres hаs beсоme’s eаsily аccessible tо milliоns оf user аrоund whole wоrld. Musiс group sinсe deсаde аnd соmрgrowing оf many genres оf musiс is accessible. The mаjоr diffiсulties thаt customer fасe is tо choose аррrорriаte song/musiс frоm suсh big collection of music. The objective оf our рrоjeсt wаs tо reсоmmend sоngs tо customers built exclusively оn their listening habits, with nо knowledge аbоut the musiс. Musiс аррliсаtiоns аre аttemрting tо imрrоve their reсоmmendаtiоn structures in оrder tо оffer their customers the quality роssible listening exрerienсe аnd keeр them оn their рlаtfоrm. For better reсоmmendаtiоns, view аnаlysis will be рerfоrm оn the lyriсs оf sоng and the use of rаndоm-fоrest аlgоrithm will be use fоr сlаssified the song lines intо vаriоus саtegоry (hаррy, sаd).
CREATING EVALUATION-STANDARD OF ABILITY TO ORGANIZE EXPERIENTIAL LEARNING ACTIVITIES FOR PRIMARY EDUCATION STUDENTS

Capacity can be seen not only as target and conditions but also a result of every activity. Evaluating capacity is fundamental for each person to recognize advantages and disadvantages in order to self-improve and develop to obtain activities’ quality and effectiveness. Capacity of organizing experiential activities is one of the output standards for students of primary education to serve the aims of Vietnam’s popular education program of 2018, especially in the subject of Experiential Activities and Experiential and Vocational Guidance. This article, therefore, tries to introduce standards to evaluate capacities of performing experiential activities of Primary Education students. In order to complete the research, we apply methodologies of analyzing documents, pedagogical observing, investigating with questionnaire, and interviewing professional experts.
SemEAGAT: A Novel Approach by Incorporating Semantic Dependency Graph in Event Detection

Abstract Event detection (ED) is a task that requires capturing deep semantic information in text to correctly identify specific types of events. Semantic dependency graph aims to recover sentence-internal predicate-argument relationships. However, recent ED researches often use syntactic dependency tree in GNNs, while we believe that the semantic dependency graph can further improve the ED task’s effectiveness since it has already been used in many other NLP tasks such as relation extraction, machine translation and abstractive summarization to provide effective semantic information, which is exactly required for event detection. In this paper, we propose a novel semantic dependency edges aware graph attention network (SemEAGAT). It incorporates the semantic dependency graph with an additional multi-head attention in an edge-aware way. Experiments on ACE2005 show our proposed method can achieve better effectiveness by comparing with the state-of-the-art methods.