Reviewerly/exHarmony huggingface dataset:
Peer Interaction in Language Learning at SMAN 1 Galis Pamekasan

This study is to finding out the ways teachers creating the peer interaction of students and the effect of the peer interaction of students on language learning at SMAN 1 Galis Pamekasan. This study facilitates the students having interaction and sharing their thought in English as well as it becomes beneficial input in language learning. This study is a qualitative research by using descriptive case study approach. This study describes in details the methods of the teachers promote student peer contact as well as the impact of student peer interaction on language acquisition. The participants of this study are the students and the teachers. Observation and interview are conducted to get the data of peer interaction and the influences of it in language learning. The results show that the way the teacher creates peer interacts with restricted English interaction and full English interaction. Peer Interaction in learning acts as an input in learning English and as a stimulus that can increase students' motivation to interact using English.
Expert system for depression detection in teenagers

Depression (major depressive disorder) is a common and serious medical illness that negatively affects how you feel, think, and act. Fortunately, it is treatable. Depression causes sadness and/or a loss of interest in activities once enjoyed. It can lead to various emotional and physical problems and decrease a person’s ability to function at work and home. Teenagers often experience this disorder because their emotions are still unstable. They also don’t have many chances to consult with a psychologist and doctor. Through this research, an expert system was created that implements knowledge from experts related to depression so that teenagers can do a self-test when needed. The expert system was developed using the Certainty Factor method for the knowledge inference engine. The system was tested iteratively and could achieve similar results with a domain expert. We hope that the system can detect early symptoms of depression among teenagers and minimize the negative impact it may cause.
Translanguaging: Perceptions of Stdudents, Teachers and School Manager Where Portuguese and Xichangana Are Spoken

Abstract: This research aims to pave the way for using translanguaging as communicative and pedagogical strategy where Portuguese and Xichangana are spoken. In order to achieve this aim, we have posed this question, as follow: how can the use of translanguaging in context where Portuguese and Xichangana are spoken impact the teaching and learning of English? This is a qualitative research based on non-structured interviews and classroom observations, analysing data collected at Xikanyanini Secondary School, which involved 3 teachers, one school manager and 36 students. The results show that the use of translanguaging makes learning and teaching process of English dynamic, flexible, participative and interactive
SISTEM INFORMASI PENJUALAN PETI MATI BERBASIS WEB DI CV. GEOJAYA NUSANTARA

Abstract—Sales is an activity that connects customers with sellers through a product or service offered to produce something that is mutually beneficial for both parties. So for that we need a system so that sales transactions can run effectively and efficiently, for example by using a sales information system. CV. Geojaya Nusantara is a company engaged in the sale of coffins. The existing sales system in CV. Currently, Geojaya Nusantara is still carried out conventionally, such as customers who want to buy their products via phone calls or also through messaging applications such as the WhatsApp application. Then the incoming sales data is still done manually, as recorded in a sales book. Therefore, with these problems, a web-based application is needed to support the sales system which aims to simplify all transaction processes, because it can be done anytime and anywhere. The research method used is by conducting direct observations and interviews with employees or shop owners. As for the software development method used is the waterfall method and the programming language used in making the website itself is PHP, HTML, CSS, and JQuery, and for the database it uses MySQL. The expected results in this web-based coffin sales information system at CV Geojaya Nusantara, are expected to be a solution to overcome the problems encountered due to the conventional system, and can also overcome errors in the sales recording input process.&#x0D; &#x0D; Keywords: coffin sales, information system, web-based
Better Class Feature Representation for Few-Shot Object Detection: Feature Aggregation and Feature Space&amp;#xA0;Redistribution

Few-shot object detection is a valuable task and is yet to achieve great progress. Most research studies generate class prototypes by support samples to guide the detection. However, there still exists some challenges with this type of approach. On the one hand, the performance is highly sensitive to the quality of class prototype encoding. But limited training data impede the procession of class prototype learning. On the other hand, similar class prototypes distribute densely in the feature space, which easily leads to misjudgment. In this paper, we propose a better class feature representation (BFR) method to obtain more representative and more discriminative class prototypes with a small size of samples. First, BFR obtains the support set feature vector with richer semantic information via different feature aggregation methods. In addition, the distance metric function is used to identify the outliers and reduce the noisy interference with dynamic weights adjustment. Finally, BFR constrains the distribution of feature prototypes through distance loss, so that different prototypes are far away from each other in the feature space to reduce misjudgment. Extensive experiments on public benchmark datasets show that our method achieves superior performance with the main components bringing an 11.3% performance improvement.
Multisensor combination algorithm based on DS evidence theory and lance distance

Multisensor combination with conflict characteristics is a very important task, and Jousselme distance has defects in measuring two special evidences, we propose a novel multisensor data combination algorithm based on DS evidence theory and Lance distance. Numerical simulation shows that this algorithm is effective and converges quickly in multisensor combination with conflict, and the trust degree of the identified target reaches 0.9943.
A Study on the Aspects of Children's Song Festival Winning Songs Included in Elementary School Music Textbooks

Objectives Looking back at the 100-year history of creative children's songs, the ‘Children's Song Festival’ proves to have had a great influence on the development of children songs. The first purpose of this study is to investigate all Children's Song Festival winning songs included in elementary school music textbooks according to the educational curriculum change. The second purpose is to analyze the aspects of those winning songs published in music textbooks. Methods To do so, this study conducted a combination of literature reviews and research study methods, and analyzed Children's Song Festival winning songs in music textbooks. These songs were those that were included in 3~6 grade elementary school music textbooks from the fifth curriculum period (1987~1991) until the current 2015 revised curriculum; meaning all winning songs in elementary school music textbooks since the first Children's Song Festival of 1983 were analyzed. Results First, an analysis on ‘Children's Creative Song Festival Winning Songs and Number of Songs’ shows that out of the total 96 winning songs, the majority of winning songs were from the MBC Children's Song Festival - a total of 69 songs (71.9%). Second, upon analyzing the ‘Number of Times Festival Winning Songs were Published’, it was found that the number increased as the curriculum changed and as textbooks went up to an older grade level. The textbook publisher ‘Genius Education’ had the most winning songs within their textbooks - a total of 43 times (15.8%) were winning songs published. Third, after analyzing the ‘Name and Number of Overlapping Winning Songs’, it was revealed that there were 51 overlapping songs, the song that was published multiple times in music textbooks was &lt;On a Train Ride&gt; from the 1st KBS Children's Song Festival - a total of 13 times. The songs &lt;Island Village&gt; and &lt;Walking in the Woods&gt; were published 11 &amp; 10 times respectively - both songs were from the 4th MBC Children's Song Festival. Songs that are continuously included in music textbooks are &lt;On a Train Ride&gt; and &lt;Walking in the Woods&gt;. Conclusions The act of singing creative children songs gives children hope, courage, the chance to dream, and holds an educational meaning that allows them to experience the beauty of music. Thus, continuing discovery and supply of creative children's songs are of great significance. Since Children's Song Festivals, which has played a huge role in the development of creative children's songs, are no longer as common as before, a new developing method that fits current society criteria must be sought out.
Compression of DNA Sequence Using Deep LSTM Neural Network

Compression of DNA sequence is rapidly evolving as a field of research.The researchers are persistently analysing the DNA sequences for several purposes.Hence, the DNA sequences have to be stored and transmitted for analysing the DNA sequences.However, the huge size of the DNA sequences leads to a high cost for transmission.Thus, compressing the DNA sequence data is essential to reduce the size, minimise transmission costand help in achieving efficient analysis.This study aimed to set the encoder and decoder for DNA sequence compression.This study proposed a deep LSTM Neural Network to compress the DNA sequence that leads to various merits effectively.Initially, the DNA sequence dataset is taken as input.The data is loaded, and the vectorizer technique is performed using the encoder, channel and decoder.Then, the encoder and decoder are set for compression.The compression process is performed through the proposed Deep LSTM Neural Network.The Deep LSTM Neural Network consists of the LSTM layer, dense layer and hidden layer.The trained model is taken into account to find the compression results.Thus the results are finally analysed to validate its efficiency.
Let’s Talk About Building Community

In the ALISE 2020 Strategic Planning Survey, members were asked about their participation in ALISE Special Interest Groups (SIG). The survey results highlighted some important challenges, as approximately two-thirds of membership reported not being actively involved in SIGs, citing a lack of awareness of SIGs as an impediment to participation (Hirsh 2020). The Community Building Committee was created with the goal of addressing these challenges with SIG participation as a means to strengthen the overall ALISE community. Thus far, the Community Building Committee has hosted virtual listening sessions with SIG conveners to better understand current challenges. At ALISE 2022, we propose to host an interactive poster inviting all ALISE members to contribute thoughts, suggestions, and ideas that might engage members as part of our community within the organization and across the information professions. The poster will feature prompts to foster discussion around the theme of community building, but the body of the poster will be largely blank, as ALISE members will be invited to add their own thoughts with markers and post-it notes, as well as to respond to previous responses. For much of the Works in Progress session, a member of the ALISE Community Building Committee will attend the poster to engage participants in direct discussion about the questions posed on the poster.
Artificial Intelligence Technologies in Newspaper Exclusive Topic

The focus of the study is on how newspapers have covered artificial intelligence (AI) in newspaper exclusive topic.decades.In addition to the typical suspects like war and politics, it's not uncommon for news organizations to cover education, health, the environment, fashion, and the arts, as well as sports and other out-of-the-ordinary happenings.A government announcement about a royal ceremony, a new legislation or levy or a warning about public health or criminals has been referred to as news from ancient times.For the most part journalists have utilized various framing strategies, such as lexical compounds and argumentation patterns, to portray AI as a strong and value-laden subject.
Digital Forensic Analysis on Mobile-based MiChat Services using National Institute of Standard Technology Method

The development of technology is increasing, mobile phones have now developed into smartphones.Smartphones can make it easier for users to communicate, do learning and many things with the support of the internet.The internet has a good impact on its users but of course, there are also bad effects because anyone can access it.This research was conducted based on real cases that have occurred, to collect digital data on smartphones.Digital data is very important in helping to uncover cybercrimes but digital data that has been deleted from the device cannot be recovered in its entirety.This study will simulate cases of online prostitution using MiChat services.This research was conducted to find out how digital data from mobile-based MiChat services can be obtained.This research uses the National Institute of Standard Technology (NIST) method.This method has four stages, namely the stages of collection, examination, analysis, and reporting.The tool to be examined is a rooted cell phone used in online prostitution transactions.This study shows the data found from the MiChat application which can be obtained using the MOBILedit Forensic Express, Autopsy and DB Browser for SQLite tools.The data that can be found from the tool used is a message in the form of a photo of the user's profile, proof of a transaction, a voice message, user data of the linked MiChat account, and the time the transaction occurred.
Security and Performance Analysis of Chaos-based Image Encryption Schemes

The widespread of images and their massive daily transmission in cyber society have created excess demand for encryption of image assets to guarantee confidentiality, integrity, and availability.Many researchers have applied chaotic encryption methods due to image cryptography's high efficiency and quality.This paper is an in-depth performance analysis and comparative study on three recent chaos-based image encryption schemes.The three schemes implement the multiple chaotification method, hybrid chaotification method, and hyper chaotification method, with a single-round design to improve the random behaviors.This research evaluates the schemes' strengths, weaknesses, vulnerabilities, performance, and robustness.In addition, it assesses the schemes' performance using a common analytical standard to measure their security.It also explores that choosing the appropriate chaotification method with high security and reasonable computational cost in encryption schemes is insufficient to ensure the security and efficiency of encryption schemes.However, the general structure of the scheme is an essential complement and plays a crucial role in the security and efficiency of the encryption system.Finally, this research explores that several statistical tests are insufficient metrics for security analysis measures for detecting weaknesses even though they pass all tests.Statistical tests can only provide a necessary but not sufficient condition, and cryptanalysis is the only proof of cryptographic schemes' security.These facts highlight the need for principles for designing robust chaotic ciphers.
Gaining trust by tracing security protocols

In this article, a novel form of white-box testing is used to test an implementation of the Noise Cryptographic Protocol Framework, which is used as an integral component in a commercial blockchain. Our approach extends the normal interoperability testing, where the noise implementation under test, written in the Erlang programming language, is tested against an implementation of the Noise protocol framework written in the C programming language. Testing typically performs a noise protocol handshake between the two implementations. If successful, then both implementations are considered compatible. However, such testing does not, for example, detect whether the Erlang implementation incorrectly reuse session keys that should have been newly generated. In this article, such interoperability testing is extended to also check that keys and information transmitted in protocol handshakes is correctly constructed, e.g., that session keys are freshly generated by calling the correct low-level cryptographic libraries. Such extended, white-box testing, begins by tracing the Erlang Noise implementation during protocol handshakes with the C programming protocol implementation. The resulting protocol trace is refactored, obtaining as the end result a symbolic description (a functional term) of how key protocol values are constructed using cryptographic operations and keys. Thereafter, this symbolic term is compared, using term rewriting, with another symbolic term representing the ideal symbolic execution of the tested Noise protocol handshake, i.e., the “semantics” of the handshake. The semantic symbolic term is obtained by executing a symbolic implementation of the noise protocol that we have developed, which very closely follows the semi-formal authoritative description of the Noise protocol framework.
Detection of Breast Cancer in Mammography Using Deep Learning Models

Due to the growing need for specialized care in communities that do not have a local radiology service, and the long response times of diagnostic departments, there is a need to provide technologies that help medical diagnosis. In this project, we implement convolutional neural network models for the identification of mammography’s with data suggestive of breast cancer, considering the BI-RADS scale system in a binary classification based on its scales. We considered BI-RADS scales from 1–3 as benign and from 4–5 as malign, binary interpretation for both models (VGG16 and ResNet50) obtained results of 0.87 in accuracy.
Roadmap for continuous professional development of STEM lecturers

Despite the ongoing systematic integration under the Bologna Agreement, higher education systems in Europe are still different in different countries and have different focus areas in the professional development of lecturers.At many European universities, professional development is often organised from a pedagogical point of view and the lecturers are left alone to apply the acquired pedagogical knowledge in their own teaching practice.In the Erasmus+ project STEM-CPD@EUni, five European universities and the European Chemistry Thematic Network (ECTN) are collaborating to enable continuous professional development (CPD) in a local university STEM teaching practice.A new concept in CPD is introduced, the CPD ambassador.Three dimensions characterize the activities of the CPD ambassadors in their local context: (1) STEM educational competences, (2) teaching attitudes, and (3) CPD activities.To define the needs for the CPD in these dimensions, a survey was developed with 66 statements evaluated from two different perspectives: their general importance for the quality of teaching and learning and their use in teaching practice.420 lecturers from 80 universities from 26 countries and 46 education managers from 31 universities from 11 countries in Europe completed the survey from the end of November 2020 to the end of January 2021.The results show similarities and also some differences between the European countries and indicate in which directions the CPD is needed.The survey also showed that the priority list of needs for CPD should not be blindly followed but used in an evidence-based way.It is recommended to repeat the survey after some time.Based on the results of this research, a roadmap for STEM-CPD with guidelines and recommendations was developed in the STEM-CPD@EUni project.
Model stealing attack based on sampling and weighting

模型窃取攻击旨在获得一个和目标受害模型功能相似的替代模型.现有的方法主要采用数据生成或数据选择方法和交叉熵损失函数去获得一个较好的攻击效果.在本文中,我们探讨了攻击过程中这两个极为重要的模块:数据采样和损失函数.据此我们提出了一个名为S&W的新颖方法,包含了一种采样策略和一个精心设计的加权损失函数.我们设计的采样策略更加关注有助于从受害者模型获得更多信息的重要样本,并且加入了k-Center算法来保证所选择样本的多样性.之后,受到focal损失函数的启发,我们设计了一种加权损失函数.这个损失函数主要关注于受害者模型和替代模型对于相同输入所给出的输出之间的差异,从而促使替代模型模拟受害者模型.在四个常用的数据集上进行的实验证明了我们方法的有效性.相比于之前最好的方法,我们的方法最高有5.03%的性能提升.
Utilization of Sludge from Textile Wastewater Treatment Plants as Raw Material for Iron Coagulant

Treatment of liquid waste using iron coagulant produces a by-product in the form of sludge which requires large handling costs. To reduce environmental pollution and sludge treatment costs, the sludge will be used as raw material for the manufacture of iron coagulant. This study aims to determine whether the sludge from textile WWTP can be used as raw material for iron coagulant. To determine the effectiveness of coagulants made from sludge, this study will compare the results of the coagulation-flocculation process using commercial iron coagulants and iron coagulants made from sludge as well as mixed coagulants with ratios of commercial iron coagulants to iron coagulants made from sludge of 70%, 60%, 50%, 40%, and 30%. The water quality resulting from the coagulation-flocculation process was indicated by pH, color turbidity, Total Dissolved Solid (TDS) and Total Suspended Solid (TSS). The results showed that the water quality of the coagulation-flocculation process was worse when mixed coagulant was used with a smaller ratio of commercial iron coagulant to iron coagulant made from sludge. A mixture of commercial iron coagulant and iron coagulant made from sludge that meets the quality standard for the TSS parameter is a mixed coagulant with a v/v ratio of 70%, while those less than 70% do not meet the quality standard.&#x0D;
FORMATION OF LOCAL STUDIES COMPETENCE OF THE FUTURE GEOGRAPHY TEACHER USING METHODOLOGICAL APPROACHES

The article describes the methodological approaches to the formation of the local linguistic competence of the future geography teacher in the course of local history tourism.Methodological approaches to the formation of the local linguistic competence of the future geography teacher in the process of local and tourist work, such as activity, system, personal, technological, are determined.Generally, methodological approaches to the formation of local lore play a role to the development of students' positive motivation in professional activity, cognitive abilities, ability to quickly and easily enrich their knowledge through the conscious use of information flows related to current issues and knowledge in the orientation of the educational process.Formation of local lore should be aimed at mastering students' personal traits that ensure personality-oriented and harmonious development.It is noted that fundamentally new approaches to the political, economic and social progress of the state, insufficient development of local lore and tourism as an effective means of personality formation, acquaintance with the natural and urban environment make the necessity of significant changes in the future geography teachers' professional training.All this actualizes new approaches to vocational training, and in particular, the future geography teacher in the field of tourism.In the course of the conducted research, we have concluded that methodological approaches of formation of local lore competence in the process of future geography teacher's training are one of the main components for scientific substantiation of effective vocational training.The theoretical principles of determining methodological approaches to the formation of the professional and regional competence of the future geography teacher are described.