Reviewerly/exHarmony huggingface dataset:
Teacher-student interaction in English classroom setting

This study aimed at finding the types of teacher talk and learner talk that occur in the classroom. The research design was a descriptive qualitative method. The data source of this method was the English teachers who teach ninth-grade students of 176 Junior High School Jakarta. The data collection technique of this research was doing observation classroom and conducting an interview. The objective of this research was (1) To find out the types of teacher interaction that occur in the classroom (2) To find out the types of students interaction that occur in the classroom. This study applied observation and interviews in collecting the data. The result of the research showed the teacher-student interaction was interactive. The teacher used the teacher to talk to deliver material to the students, and students responded to the teacher. The aspect of the teacher talk employed 3 categories, and the learner employed 3 categories in the classroom interaction during the teaching-learning process. Teacher talk occurs in the classroom is lecturing, especially giving facts or opinions about content procedures and Giving their explanation. Students talk occurs in the classroom is students talk initiation specially Expressing own ideas and the interaction between teacher and students in the classroom interaction interactive they made good interaction each other.
Ensemble correction model for aspect-level sentiment classification

The aspect-level sentiment analysis is widely used in public opinion analysis. However, the problem of context information loss and distortion with the increase of the model depth is rarely considered in previous research. Few studies have attempted to combine the feature extracted from different embedding models. Based on the correction strategy, the ensemble correction (EC) model proposed in this study can correct context information loss and distortion. Based on the ensemble learning strategy and the weight sharing strategy, EC can extract features from different word embedding models and can reduce computational complexity. Experiments on the resturant14, laptop14, resturant16 and twitter datasets show that the accuracies of the EC model are 0.8848, 0.8213, 0.9301 and 0.7731, respectively. The accuracy of the EC model is higher than state-of-the-art models. Ablation studies and case studies are used to verify the model structure. The optimal number of graph convolutional network (GCN) layers is also verified.
Campus Website Security Vulnerability Analysis Using Nessus

Agencies or organizations are competing to create websites for their agencies, where this website to make work easier or disseminate information to the public in this study is a college or campus website. With this website, many people access it, so there is a possibility of security holes, which can be exploited by irresponsible people. So that data can be manipulated, retrieved or otherwise to the detriment of one-sided or several parties. For this reason, we tried to analyze the vulnerability of a website using a software called Nessus. From the results of the scan, it was found that several vulnerabilities were found from each website with different vulnerability levels. Of the 3 websites that have the most vulnerabilities, web 1 is 14. Meanwhile, the vulnerability at the medium level is on web 2, which is 22%. For the vulnerability lies in a weak DNS Server.
Face Recognition Application Based on Convolutional Neural Network for Searching Someone’s Photo on External Storage

Digital photos are often defined as personal archives collected long ago and are stored on a large enough storage media such as an external hard disk or flash disk.Problems arise when someone wants to find photos of themselves or others in tons of photo collections.Searching manually, such as opening a photo file or folder one by one, will certainly be very troublesome.Based on these problems, this study designed an application for searching certain photos based on the similarity of the inserted face photo.This application is built for computer or laptop devices, which was developed by using the Python programming language and Dlib module that applied the face recognition method through the combination of Convolutional Neural Network (CNN), FaceNet Embedding, and Triplet Loss for matching faces.The recognition scheme starts from face detection, face alignment, face encoding, and face classification stage.Our application is very handy to run in looking for particular face images on external storage compared to prior studies.We have done experimental research, demonstrating that the application can find almost all image files the user is looking for.In addition to the result in the form of an application, this study contributes to exploring the performance of the Dlib module, in terms of precision and recall rate, which could not recognize non-frontal face images well.We encourage other researchers to address this limitation in further studies.
Methodological and Contextual Foundations of Metacognitive Monitoring Training Program in Student Self-Regulated Learning

Aim. This manuscript aims to present the theoretical and contextual characteristics of the developed training program focused on identifying the components of students’ self-regulated learning activities with the use of metacognitive monitoring as well as improving the effectiveness of the students’ learning activities at the individual-personal, motivational-volitional, cognitive and metacognitive levels.&#x0D; To do this, we sought to analyze these phenomena in scientific literature and develop a training program aimed to develop students’ reflexivity, internal learning motivation, and metacognitive skills; to inform students about the features of metacognitive monitoring and metacognitive control of self-regulated learning activities, their awareness of the characteristics of their own processes of understanding, evaluating and reproducing information; to form comprehension and task analysis skills, as well as understanding of the specifics of performed tasks.&#x0D; Methods. A system of general scientific methods was used: analysis and synthesis of the main characteristics of the concepts of self-regulated learning and metacognitive monitoring as a complex multidimensional formation, comprehension of the psychological foundations of self-regulated learning, systematization and generalization of scientific provisions of metacognitive monitoring in student self-regulated learning. This study focused on the design and development of the training program for increasing the efficiency of metacognitive monitoring in student self-regulated learning.&#x0D; Results. The presented manuscript has analyzed the theoretical aspects of the concepts of metacognitive monitoring and self-regulated learning of HEI students. The theoretical essence of the methodological and contextual characteristics of the above mentioned phenomena has been studied. The role and importance of metacognitive monitoring and its components in the learning efficiency and academic self-regulation of HEI students have been described. It has been determined that metacognitive monitoring as a metacognitive characteristic of personality determines not only the organization of mental and behavioral processes, but also relates to the academic success of the subject of learning activity, namely the student. The training program for increasing the efficiency of metacognitive monitoring in student self-regulated learning has been developed and presented.&#x0D; Conclusions. The program was designed to help students consciously approach the independent planning and setting of learning goals, control intellectual and metacognitive activities, and use cognitive and metacognitive strategies in learning, monitoring, controlling and correcting their learning activities. Since these processes provide students with cognitive understanding of their own cognitive processes, the use of this type of training program will help students optimize their learning outcomes through metacognitive monitoring in the process of self-regulated learning activities.
Proposals on Reform of Test Questions of Senior High School Entrance Examination and National College Entrance Examination Based on Educational Measurement

Question setting technology of senior high school entrance examination and national college entrance examination awaits some reform. on the basis of educational measurement principles.Following are seven proposals on such reform. for respective question types in the two examinations,for the reference of question originators.Firstly,the number of the correct choice(s) for choice questions can be made uncertain, disturbance options can be added,and point assigning can be conducted in accordance with different ratings.Secondly,multiple answers can be provided for certain blank-filling questions.Thirdly,redundant known conditions can be given for calculating questions,and points may be made respectively for different solutions.Fourthly,experiment questions shall attach greater importance to examining students’ abilities of assimilating and applying experimental methods,of questioning and detecting,and of exploring and innovating, as well as the rigorousness of their scientific attitude.Fifthly,some unnecessary,useless and even false information can be offered for question-and-answer questions.Sixth,self-selected topics can be set for composition writing,and assessing technology shall be optimized.Seventh,integrated interdisciplinary questions can be taken into the test.Eighth,audio questions can be added to test students’ hearing and observing abilities.
Agro-Chain: Blockchain Powered Micro-Financial Assistance for Farmers

Agriculture acts as the fixed sector for all economics over a millennium which constitutes a critical indeed major part of the developing country’s GDP and extends as a massive part of rural household monetary income. As the majority of farmers mainly depend on the government schemes for financial support where agriculture banking plays a significant role in the modernization of agricultural activities, but the majority of the farmers/peas-ants are excluded from such banking systems and do not have access rights. It is explored with the farmers’ concern that the traditional rural financial paradigm was supported by public authorities that desire to facilitate access to the financial service. However, such banking systems were costly and unsustainable due to poor repayment. They ultimately did not have a great effect on agriculture production and, in turn, led to the shutting down of state-owned banks and finally gave rise to the concept of microfinance. Over time, technological advancement from the plow to fertilizers and biotechnology has revolutionized the industry. Blockchain is the advancement of new technology aspiring to upgrade agricultural activities related to farmers’ financing. This chapter adopts distributed ledger technology (DLT) that allows the recorded data in the system to fan-out amongst the farmers, consumers, and all the actors involved in the system. Blockchain-based micro-financial assistance makes the transactional data more transparent and immutable task. It reduces the intervention of the middleman in the 462transaction who expects some percentage of commission from farmers for selling their food grains in the market. The work extends to allow the farmers to establish a digital identity and supports them to access various monetary offers. The system makes a significant difference in helping to reduce the rate of interest and also ensures efficient repayment of loans by making it more accessible through smart contracts (SCs). Every farmer/consumer can keep track of the transactions carried out by them in selling/buying the products through the platform. Further, update the data collected from these transactions to the credit history of the farmers that give them the aid of availing the credits. The system makes a significant difference in helping to reduce the rate of interest and also ensures efficient repayment of loans by making it more accessible through SCs.
Improving Security Using Cryptography Based on Smartphone User Locations

Smartphones have become widely employed in a range of fields as a result of substantial developments in communication technology, distribution, and the development of numerous types of smart mobile devices.The goal of this research is to secure information sent over mobile phone networks.In this paper, we propose using cryptography to create a more secure application for transmitting confidential information, using encryption to improve security, and depending on the location of the mobile phone user's coordinates, obtained via GPS, to increase security.The XOR process was used between coordinates, the idea was new, the application was implemented, and good results were obtained.The process of converting text into unreadable text is known as ciphering, and in order to achieve it in this paper the Twofish algorithm was used to encrypt confidential information.When sending the coordinates, the RSA algorithm was used to encrypt them as for the Twofish algorithm, the coordinates serve as a key.We conclude that the proposed system used in this study achieved a high level of security.
Adversity Quotient pada Siswa Tunanetra dalam Meningkatkan Literasi

Obstacles in visionary function in blind student impacts on limitedlearning process, mainly in literacy activities such as reading, writing, andcounting. In preventing such obstacles, they need adversity quotient forenhancing literacy skill at school. Adversity quotient is very important sothat they could get through the difficulties in the process, not depend ontheir parent and teacher to counter society’s stigma on the issues, likesnormal student. The objective of research is to explore the meaning ofadversity quotient on blind student in improving their literacy.This studyused a qualitative method with phenomenological approach. Four blindstudents who study in Special Needs School of Prof. Sri Soedewi Jambibecame the subject of this study. Data collecting was carried out throughin-depth semi-structured interviews. An interpretative phenomenologicalanalysis was used as the data analysis technique. Study results indicate thatthe adversity quotients of blind students in improving literacy skillsencompass origin and ownership, motivation, perseverance, independence,and control. Factors affecting adversity quotients include parentalencouragement, social support, facilities, and future orientation.Abstrak. Hambatan fungsi penglihatan pada siswa tunanetra berdampakpada keterbatasan dalam proses pembelajaran, terutama pada aktivitasliterasi seperti membaca, menulis, dan berhitung. Dalam mengatasihambatan tersebut mereka membutuhkan kecerdasan daya juang (adversityquotinet) untuk meningkatkan kemampuan literasi di sekolah. Daya juangsangat penting agar mereka mampu mengatasi berbagai kesulitan dalammembaca, tidak bergantung pada orang tua dan guru, serta mengubahstigma masyarakat bahwa mereka tidak mampu belajar di sekolah sepertisiswa normal. Tujuan penelitian ini untuk menggali makna adversityquotient pada siswa tunantera dalam meningkatkan kemampuan literasi.Penelitian ini menggunakan metode kualitatif dengan pendekatanfenomenologi, subjek penelitian ini adalah siswa tunanetra yang menuntutilmu di Sekolah Luar Biasa (SLB) Prof. Sri Soedewi Jambi sebanyakempat orang, pengumpulan data dilakukan dengan wawancara semistruktursecara mendalam. Teknik analisis data menggunakan interpretativephenomenological analysis. Hasil penelitian menunjukkan bahwa adversityquotient siswa tunanetra dalam meningkatkan kemampuan literasi berupamengatasi kesulitan, motivasi, ketekunan, kemandirian, dan kontrol.Adapun faktor yang memengaruhi adversity quetiont yaitu dorongan orangtua, dukungan sosial, fasilitas, dan orientasi masa depan.
VALIDITY OF 3D PAGEFLIP POCKET BOOK CONTAINING POACEAE SPECIES IN GALAM VEGETATED SWAMP, BATI-BATI DISTRICT

Species of Poaceae may be used as mastering objects, based on local potential, as learning resources, thats in accordance with technological developments, making it into 3D pageflip based pocket book. A valid pocket book, as learning resources, can be defined if it has been validated by experts in field. Validation role to assess the prototype, and eligible for more developmental phases. The aim of this research is to determine the validity of the pocket book, which contains material about Poaceae species in galam vegetated swamps. This pocket book is in the form of a 3D pageflip. This development uses Tessmer's formative evaluation model. The value of validity is determined by 2 experts. The results of the study confirm that the product that has been developed is very valid, especially for expert consequences of 93.42%.
A Comparison of Convolutional Neural Networks and Traditional Feature-Based Classification Applied to Leukaemia Image Analysis

The accuracy of smear test image classification is a fundamental aspect in differentiating the type of leukaemia and determining the right treatment to improve the patient's chances of survival and recovery. Image Classification has lately become a very effective tool in detecting and analysing the right type of leukaemia as each type of the disease looks differently when evaluated under microscope. This paper is evaluating and comparing the efficiency and performance of feature extraction techniques (colour descriptors and Haralick texture descriptors) and a CNN (Convolutional Neural Network) built and trained by using the TensorFlow packages for classifying leukaemia images. Extracting texture and colour features from a given set of leukaemia images through computation was successful in detecting the type of disease and the results analysed with Weka Classifiers were giving the highest accuracy of 93.58%. TensorFlow tested with Cross-Validation proves efficient in training and customising the system, but the accuracy was median 56% and was not greatly improved by addressing the class imbalance issue from the data set with SMOTE. Further studies will investigate increasing the number of images by using a segmentation and image manipulation/augmentation techniques and increasing the accuracy of CNN through the addition of the investigated traditional features.
Workshop Internet of Things (IoT)

SMK Negeri 7 Samarinda aspires to be a world-class information and communication technology school. It is important for students to understand about technology advancements in order to become employable human resources in the workplace. Teachers' roles in schools are critical in helping students learn this, hence vocational school teachers should have Internet of Things (IoT) training. The workshop will take place entirely online, utilizing Google Meet. Following the training, it can be inferred that partners will have a simple understanding of the IoT technology work system, particularly when the pilot is deployed. Partners can learn and grasp the notion of blended learning models with IoT through workshops and facilities.
Developing a Cybersecurity Educational Community Using Discord During the COVID-19 Pandemic

The COVID-19 pandemic has been a hectic time for faculty at the higher education and K-12 levels. With many institutions having to switch to remote learning, faculty had to find tools and resources that could be used to create virtual educational communities. In this milieu of remote learning, the technology tools must foster a thriving educational environment and facilitate communications. In the undergraduate Cybersecurity and Network Management (CNM) program at Murray State University (MSU), the faculty adopted Discord for teaching classes, lab work, and for social events. Discord has been used by the CNM faculty for over a year now and has shown positive results. Students like using Discord for streamlining the communication process and for having the ability to establish real time communication with faculty. In this paper, the authors present their approach to developing and managing the use of Discord in the CNM program at MSU.
NFTs in the electronic market and its impact on digital art

This article aims to clearly conceptualize NFTs in electronic commerce and identify what their impacts are on digital art. Therefore, it was posed as a research question: What are NFTs in e-commerce and what are their impacts on digital art? This purpose was achieved with the review of technological publications in databases such as Google Scholar and Redalyc. According to the analysis carried out, it is concluded that the NFTs are a cryptographic certification that gives a digital work the ability to be unique and unrepeatable and therefore its monetization and commercialization. As a financial impact, NFTs allow the sale of digital assets for large sums of money through decentralized finance (DeFi); As an impact on authenticity, the NFTs guarantee the attribution of the work as its uniqueness and origin from those who can legitimately dispose of it; and finally, as an impact on security, the NFTs make a work traceable and whose property can be transferred in a private and secure way thanks to the records based on Blockchain.
Large Neural Networks

This chapter covers large neural networks with random weights, in both feed-forward and recurrent settings. While being rather different from modern deep neural networks, these preliminary results shed new light on the interplay between data, network structure, and nonlinear neurons, leading to the somewhat surprising double descent phenomenon. The impact of gradient-based optimization method on the resulting network and more advanced consideration of deep networks are also discussed.
Assessing Internal Consistency of HAIS-Q: A Survey Conducted in Greek Hospitals

Despite the prevailing perception that powerful software and hardware are adequate solutions to minimize information systems’ security breaches, privacy remains at stake. Human factors play an important role in maintaining information security as it is evident that non secure practices applied by employees may increase the vulnerability of the systems and lead to privacy issues. Non secure practices found in literature are related to the use of Internet, the use of emails, password management, information handling and incidence reporting. For this purpose a survey was designed to be conducted in seven hospitals in Greece in order to record non secure practices applied by nursing staff and identify correlation factors. This paper presents the reliability test of the HAIS-Q tool which was applied in order to conduct the survey entitled: Examining the Nurses’ non secure IT practices in Greek Hospitals as well as the preliminary results of the study.
Risk identification of power transaction based on PCA-BP neural network

GPS technology has the characteristics of high precision, high sampling, real-time, and simultaneous determination of three-dimensional coordinates of points, which can not be compared with other monitoring technologies. It plays a very important role in deformation monitoring. Starting from the composition of GPS positioning system, this paper expounds the three components of GPS positioning system, as well as the association and coordination between each component of the work; then the GPS deformation monitoring mode and several error sources in the monitoring process are introduced. The advantages and disadvantages of GPS technique in deformation monitoring are analyzed and its application trend is predicted. GPS positioning technology is applied in all aspects of our life, creating a lot of social and economic value for us.