Reviewerly/exHarmony huggingface dataset:
SIJAPIN Atasi Kebosanan PJJ Matematika Kelas VII A SMP Negeri 12 Semarang

Distance learning using information and communication technology brings some problems for some teachers in Indonesia, including the writer. Students learn independently without explanation from the teacher. This condition causes learning boredom for some students. SiJaPin (Sinau bareng Jateng Pintar) or Learning with Smart Central Java is an effort to overcome students boredom of Mathematics distance learning in Class VIIA SMP Negeri 12 Semarang . The implementation of SiJaPin is 1) Design and preparation stage 2) Implementation stage. The results of SiJaPin implementation are results of learning final evaluation, on the first day of learning, class VIIA students get an average score of 71.75 and 83.25 on the second day. Questionnaire of students' reflection on distance learning with SiJaPin: 18 students stated that they felt happy, 21 said they could overcome their boredom, and 10 said that they were motivated to learn. Supporting factors for the implementation of SiJaPin are the support from fellow teachers and principal, the enthusiasm of students, adequate facilities by the provided rooms, laptops, handphones and internet. Inhibiting factors for the implementation of SiJaPin 1) limitation of the teacher in monitoring internet signal, that makes students cannot hear teacher’s voice when starting the lessons, 2) the teacher is less careful that makes typing errors on the PPT slides, 3) lack of coordination on the previous days, 4) next lesson plan by video conference using attractive PPT.
Implementasi Algoritma Arithmetic Coding dan Sannon-Fano Pada Kompresi Citra PNG

The rapid development of technology plays an important role in the rapid exchange of information. In sending information in the form of images, there are still problems, including because of the large size of the image so that the solution to this problem is to perform compression. In this thesis, we will implement and compare the performance of the Arithmetic Coding and Shannon-Fano algorithms by calculating the compression ratio, compressed file size, compression and decompression process speed. Based on all test results, that the Arithmetic Coding algorithm produces an average compression ratio of 62.88% and a Shannon-Fano compression ratio of 61.73%, then Arithmetic Coding the average speed in image compression is 0.072449 seconds and Shannon-Fano 0.077838 second. Then the Shannon-Fano algorithm has an average speed for decompression of 0.028946 seconds and the Arithmetic Coding algorithm 0.034169 seconds. The decompressed image on the Arithmetic Coding and Shannon-Fano algorithm is in accordance with the original image. It can be concluded from the test results that the Arithmetic Coding algorithm is more efficient in compressing *.png images than the Shannon-Fano algorithm, although in terms of decompression Shannon-Fanose is a little faster compared to Arithmetic Coding.
ANALYSIS OF UNDERGRADUATE STUDENTS’ FORMAL ESSAY WRITING PERFORMANCE BASED ON HALLIDAY’ SYSTEMIC FUNCTIONAL LINGUISTICS THEORY

This study aims to analyze undergraduate students’ formal essay writing performance using Systemic Functional Linguistics theory. This study employed a qualitative research design, embracing the characteristics of a case study. The data were obtained from the collection of samples of students’ formal essay writing. The finding revealed that there were 192 clauses found in six undergraduate students’ formal essay writing and those clauses were analyzed in the three sections. They were transitivity process, mood, and theme. there was six transitivity process found in undergraduate students’ formal essay text. There were material prprocessesmental processes, relational processes, behavioral processes, verbal processes, and existential processes. The material process was used dominant by the students. There were three mood types found in the undergraduate students’ formal essay texts. The first was indicative declarative, the second was interrogative, and the last one was imperative. Drawing from the findings of mood, the declarative mood was the most dominant among the other two moods.
EFFECTIVENESS OF MINDLY IN TEACHING READING COMPREHENSION

Coronavirus has forced schools to teach online, where learning uses a variety of applications, one of which is Mindly. Therefore, the writer is interested in conducting research to find out the effectiveness of Mindly in teaching reading comprehension. Grounded in quasi-experiment method with the design pre-test and post-test, this research is conducted on the 26 students from 2 class at SMPN 1 LOHBENER. The result of the pre-test students score in control class showed that the average was 42,77 and the pre-test students score in experiment class showed the average was 47,08. The post-test total scores in control class showed the average was 60,62. And the result of post-test the total scores in experiment class showed the average was 59,08. Then, the statistical analysis showed that the value tobs was 0,9999 while the value of ttable 0,6 which means that the value of tob higher than ttable 0,9999 &gt; 0,6 (tobs &gt; ttable). From the result of statistical analysis, it can be concluded that tobs was higher than ttable (tobs &gt; ttable) it means that Alternative Hypothesis (Ha) was accepted while Null Hypothesis (Ho) was rejected. It means that using Mindly does not give positive effect to students’ reading comprehension
System of professional-digital competencies of a teacher ofahigher pedagogical educational institution

The article is devoted to the problem of substantiation of the integral target orientation of preparation of future teachers of institutions of higher pedagogical education for professional activity in the conditions of digitalization of society: systems of their professional-digital competences. The main conceptual idea is put forward: professional-digital competencies of a teacher of a higher pedagogical educational institution are in isomorphic dependence on his/her professional functions and form a holistic system - a reference model of the target landmark of the digitalized educational process in graduate and postgraduate studies. The integral-functional dimension describes the procedure for establishing a holistic set of updated teacher functions in the digital educational environment ofa pedagogical university. The set of the following criteria for their search is outlined: 1) the specifics of thefunctional content of the types of teaching activities, taking into account the process of digitization of higher education; 2) the subject of the teacher's relations with future teachers and public life; 3) the nature of the relevant links. According to all criteria in their unity, three core professionally defined functions are defined: heuristic-digital, managerial-digital and self-development-digital. To these are added purely instrumental general professional - executive-digital, technical-digital and the function of compliance with digital security.&#x0D; The differences between the concepts of "professional-digital" and "digital" competence are emphasized. The concept of the system of professional-digital competencies of a teacher of a higher pedagogical educational institution as a holistic and interconnected set of their components, adequate to his/her certain professional functions in the digital environment, is formulated. The following relevant system of competencies is defined: heuristic-digital aspect (competencies in the areas of pedagogical innovations, digital content of personal and professional development, in particular, worldview and existential orientation, etc.); managerial and digital aspect (competence of the teacher of diagnostic and prognostic, motivational, design, organizational, stimulating and control functional and managerial nature); self-development-digital aspect (important for personal, professional and professional-cultural development of the teacher's competence); aspect of digital culture (digital competencies, highlighted in the literature, important for information retrieval, reception, processing and output, use of basic and application software, solving technical problems, personal data protection, copyright, etc.)
Referring Expressions with Rational Speech Act Framework: A Probabilistic Approach

This paper focuses on a referring expression generation (REG) task in which the aim is to pick out an object in a complex visual scene. One common theoretical approach to this problem is to model the task as a two-agent cooperative scheme in which a ‘speaker’ agent would generate the expression that best describes a targeted area and a ‘listener’ agent would identify the target. Several recent REG systems have used deep learning approaches to represent the speaker/listener agents. The Rational Speech Act framework (RSA), a Bayesian approach to pragmatics that can predict human linguistic behavior quite accurately, has been shown to generate high quality and explainable expressions on toy datasets involving simple visual scenes. Its application to large scale problems, however, remains largely unexplored. This paper applies a combination of the probabilistic RSA framework and deep learning approaches to larger datasets involving complex visual scenes in a multi-step process with the aim of generating better-explained expressions. We carry out experiments on the RefCOCO and RefCOCO+ datasets and compare our approach with other endto-end deep learning approaches as well as a variation of RSA to highlight our key contribution. Experimental results show that while achieving lower accuracy than SOTA deep learning methods, our approach outperforms similar RSA approach in human comprehension and has an advantage over end-to-end deep learning under limited data scenario. Lastly, we provide a detailed analysis on the expression generation process with concrete examples, thus providing a systematic view on error types and deficiencies in the generation process and identifying possible areas for future improvements.
Efficient and Effective Similarity Search over Bipartite Graphs

Similarity search over a bipartite graph aims to retrieve from the graph the nodes that are similar to each other, which finds applications in various fields such as online advertising, recommender systems etc. Existing similarity measures either (i) overlook the unique properties of bipartite graphs, or (ii) fail to capture high-order information between nodes accurately, leading to suboptimal result quality. Recently, Hidden Personalized PageRank (HPP) is applied to this problem and found to be more effective compared with prior similarity measures. However, existing solutions for HPP computation incur significant computational costs, rendering it inefficient especially on large graphs.
Incorrect Trial Registration Identifier

Thomas G. H. Kempen, MPharm; Maria Bertilsson, MSc; Nermin Hadziosmanovic, MSc; Karl-Johan Lindner, MPharm, PhD; Håkan Melhus, MD, PhD; Elisabet I. Nielsen, MPharm, PhD; Johanna Sulku, MPharm; Ulrika Gillespie, MPharm, PhD
Adopting Literature Circle to Guide Work Undergraduate Students in Extensive Reading Program: Lessons Learned from Initial Teacher Education

Albeit many works provide insight into EFL's extensive reading programs, relatively few studies investigate adopting literature circles in the extensive program. To fill this void, this phenomenological case study reports on the adoption of literature circle as the instructional procedure in an extensive program in Indonesian teacher education. Thirty-one undergraduate students in the cohort, four students, were recruited as participants voluntarily. Data are derived from classroom observation, focus group discussion, and interviews. Findings revealed that the literature circle enables students to engage in online discussion actively. Pedagogically, this study implied that the literature circle could be adopted as instructional scaffolding in an extensive reading program situated in an EFL classroom. This study implies the teacher educator to provide fruitful feedback to motivate students after discussing it. Practically, undergraduate students are encouraged to practice navigating skills in exploring a wide range of texts for extensive practice in EFL text.
Grasshopper Optimization Algorithm-Generative Adversarial Network for Lung Cancer Detection and Classification

Lung cancer is one of the most dangerous deadly diseases for individuals worldwide.Thus, the survival rate is low due to the difficulty in detecting lung cancer at advanced stages like symptoms; thus, prominence for early diagnosis is important.The detection and treatment of lung cancer is having great importance for early diagnosis.The existing Convolution Neural Network (CNN) based deep learning methods showed tuning was the problem of choosing a set of hyperparameters for the learning algorithm and included outliers that affect the classification result.Therefore, the present research work aims to utilize Grasshopper Optimization Algorithm (GOA) effectively to solve global unconstrained and constrained optimization issues.Additionally, performing training using the Generative Adversarial Network (GAN) model that controlled the behavior of the classifier during training showed a significant impact.The results showed that the proposed method gives better results in terms of accuracy of 98.89% when compared to the existing models such as KNG-CNN of 87.3%, mask region-based CNN of 97.68%, Transferable Texture CNN of 96.69%, Fuzzy Particle Swarm Optimization (FPSO) CNN of 95.62% and E-CNN method of 97%.
Pengembangan Daftar Arsip Inaktif untuk Simplikasi Monitoring Penyusutan Arsip di Departemen Manajemen FEM IPB

Depreciation of archives is the activity of reducing the number of archives by transferring inactive archives from processing to archiving unit, destruction of archives that have no useful value, and submission of static archives to archiving institutions (UU Nomor 43 tahun 2009). At each stage an archive list is required. At the stage when it has become an inactive archive, a list of inactive archives must be made with a column referring to article 44 of PP No. 28, 2012. This study aimed to describe the efficiency, ease of archive search, and monitoring archive depreciation with the development of existing inactive archive lists through the addition columns as needed for archival depreciation. Data were obtained through observations, interviews, and questionnaires. The development of inactive archive lists included archive management and availability of archiving human resources, implementation of archiving regulations, arrangement of inactive archives and services, development of inactive archive lists, implementation and services. The constraint of existing inactive archives list is unable to monitor the depletion of the next stage of the archives. The development of new inactive archives list can be retrieving archives as well as monitoring the depletion of archives, increasing the effectiveness and efficiency of work.
Secure File Storage on Cloud Computing Using Cryptographic Algorithm

Abstract: Cloud computing is one among today’s hottest research areas thanks to its ability to scale back costs related to computing while increasing scalability and adaptability for computing services. Cloud computing is Internet based computing thanks to shared resources, software and knowledge are provided to consumers on demand dynamically. Cloud computing is one among the fastest growing technology of the IT trade for business. Since cloud computing share disseminated resources via the network in the open environment, hence it makes security problems vital for us to develop the cloud computing applications. Cloud computing security has become the leading explanation for hampering its development. Cloud computing security has become a hot topic in industry and academic research. This system will explore data security of cloud in cloud computing by creating unique key and encryption by using that key. Keywords: cloud computing, cloud security, data security, encryption, elliptic curve cryptography, AES.
The Effect of Skimming on Educational Reading Texts

The present study investigated the effect of skimming on the learners’ educational reading comprehension skills. In order to answer research questions, the researcher used both qualitative and quantitative methods. The researcher used observation and questionnaires as instruments to collect the data. The participants were 28 students in the common first year at Al-jouf university for the academic year 2020/2021. The study lasted for four weeks. The instruments of the study included observation and a questionnaire. They were approved by a panel of jury. The result of the study showed that most of the students positively responded that the skimming technique was an effective way to understand educational reading texts and helped them to answer the questions attached to the texts easily and quickly. As such, it was concluded that skimming had a positive effect on developing EFL university learners’ reading comprehension skills.
Hyperledger Fabric Implementation for a Transparent Food Product Supply Chain

Abstract: Blockchain technology came into existence because of bitcoin and has seen an extensive set of applications in recent times. In the last few years, numerous projects have been taken up to make use of the efficient features provided by this technology. The main focus of the blockchain is to maintain trust among the users. Farmers of the country are facing huge issues because of the corruption in the supply chain involved due to which they are not getting the proper market price for the goods produced. With the help of the Blockchain we can make the contract transparent and make the payment systems automatic which in return will help the economic situation of the farmers and reduce corruption in the system. Keywords: blockchain, supply chain, Hyperledger, agricultural, transparency
Construction of Higher Education Management Data Analysis Model Based on Association Rules

This paper adopts the analytical method of intelligent programming to conduct in-depth research and analysis on university education management and designs a corresponding university education management model to be applied in actual teaching. Based on the basic theories and methods of big data distributed data mining and machine learning, automated machine learning, and big data programming computational methods, this paper combines the importance and technical challenges of the algorithms themselves and the background of the practical application needs of the industry and firstly selects a series of data mining and machine learning algorithms that are commonly used based on high complexity, outstanding computational efficiency problems, and difficult to design distributed algorithms. The research on efficient large-scale distributed parallelized data mining and machine learning methods and algorithms is carried out. As an innovative teaching model, the experiential teaching model focuses on the cultivation of individual students’ independent learning ability and subjective initiative, which not only can effectively activate the classroom atmosphere and improve the teaching effect but also meet the requirements of classroom teaching for the development of the times. The empirical evidence of the experiential teaching model proposed in this paper is carried out, and the implementation process of the experiential teaching model of high school physics is further improved. In terms of the overall implementation effect, the experiential teaching model proposed in the paper can deepen students’ understanding of concepts and physical laws, thus enabling them to solve physics problems better, and has a positive and active effect on enhancing students’ learning interests and attitudes. In the case of system security, the average comprehensive index of each unit is 61.11, 22 are higher than the average index, accounting for 61.11%, 14 are lower than the average index, accounting for 38.89%, and 23 management departments’ management systems passed the safety monitoring, accounting for 63.89%. At the same time, the proposed model also provides educational practitioners with a more reliable framework for instructional design, which has realistic reference value and significance.
Correlation of Attitudes and Perceptions in Intermediate Reading Class Students, University of Muhammadiyah Palembang

The enthusiasm toward reading happens as a result of good reading attitude is known as the attitude of reading. Students' reading attitudes are strongly related to their ability to be achieved by practice. The purpose of this study was to find out the correlations between students’ attitude and perception of reading in intermediate reading class. The participants were twenty-three students in the second semester of English study program, University of Muhammadiyah Palembang. The sample was taken by using purposive sampling of the even semester class in the Faculty of Teacher Training and Education. Coefficient correlation was adopted in this study. It is also intended to see if there any significant correlation between reading habits and reading perception of intermediate reading class students. The data was acquired through the use of Elementary Reading Attitude Survey (ERAS) that was established by McKenna and Kear (1990) in order to measure students’ reading attitude. An informal interview was also conducted by the researcher to acquire additional information about students' perceptions to reading. The results of this study revealed that there is moderate correlation between students' attitudes and perceptions of reading with the correlation value are 0.48. Thus, students must keep practicing and improving reading comprehension.
Forensic Face Sketch Construction and Recognition

Abstract: In forensic science, it is seen that hand-drawn face sketches are still very limited and time consuming when it comes to using them with the latest technologies used for recognition and identification of criminals. In this paper, we present a standalone application which would allow users to create composites face sketch of the suspect without the help of forensic artists using drag and drop feature in the application and can automatically match the drawn composite face sketch with the police database much faster and efficiently using deep learning and cloud infrastructure. Keywords: Forensic Face Sketch, Face Sketch Construction, Face Recognition, Criminal Identification, Deep Learning, Machine Locking, Two Step Verification.
Improving the Digital Security of Smart Energy Systems with Smart Contracts

Smart grids are evolving towards intelligent electricity grid where the operation of systems is distributed and automatised. Technical solutions to achieve these future needs are proposed using blockchain with smart contracts in many studies, where smart contracts enhance automation. Fundamentally smart contracts will increase security because of their distributed nature and since it inherits the security of blockchain. However, smart contracts are software components, which have special features like the unstoppable nature of applications and may use special languages like Solidity. Our aim in this paper is to get a holistic review in the smart contract life cycle, what potential new vulnerabilities and threats will they introduce and how can they be prevented, and what smart contract specific issues programmers should focus on. We also propose a future direction to achieve more secure smart contracts in smart energy systems.