Reviewerly/exHarmony huggingface dataset:
Starategi Dalam Pengolahan Bahan Koleksi Anak di Taman Bacaan Kampung Nelayan Kota Medan

&#x0D; A community reading garden is a place dedicated to the community and is usually run by the community itself and the government. The presence of a community reading garden around the house is meant to spark an interest in reading. Taman Bacaan Masyarakat itself is a kind of public library. The existence of a community reading garden in the midst of the community is intended to increase public interest in reading in general and is used as an informal means of education. This study aims to apply the strategy of developing children's reading interest through the reading collection of Kampung Nelayan Reading Center. This research method uses qualitative research method based on the collected information. The results of this study indicate that the book collection of the floating library in the fishing village has a total of 400 books donated by the Padang city government and donors. The collection is a collection provided by the director of Kampung Nelayan Reading Center. Introducing children to a love of reading is not easy, especially when children don't learn to read from birth.&#x0D; Keywords: Children's Reading Collection Material, Community Reading Gardens
Implementasi Jaringan Informasi, Sarana Bantu serta Kendala yang Dihadapi Perpustakaan

&#x0D; This research was conducted to determine the implementation of the information network. Its implementation is seen from several locations such as IPDN and Bukit Tinggi. Both places are referred to from sources in the form of journals to complement this scientific work. The method that the researcher uses is qualitative research using descriptions and conducting literature studies so as to help the author understand some of the problems by looking at some references. It was found that to implement the information network, it is necessary to make improvements first, such as the procurement of facilities and infrastructure, selecting the right location and several other indicators described in the results and discussion section of the study.&#x0D; Keywords: jaringan, OPAC, perpustakaan.
Jaringan Kerjasama Perpustakaan Lapangan

&#x0D; &#x0D; According to UNESCO, one out of every 1000 Indonesians is interested in reading. This study shows that a lack of interest in reading can be an indication of a lack of awareness of Indonesian culture. According to the Central Bureau of Statistics, 4-5 hours a week is the same as the time for collecting and submitting collections of achievements for making collections of printed and recorded works in 2022 of 2,939,008 copies, which are in the National Library and libraries in the regions. It signifies that we will fulfill the demands of our desire to collect small reading books; You could say 1:90, or one book for every 90 people, right? This has contributed to the low literacy rate in Indonesia.&#x0D; Keywords Collaboration , Library , Field Network , Cooperation Network , Library Cooperation .
Innovation and Collaboration in Organizations: A Bibliometric Research

Purpose - This article is a bibliometric study of innovation research and internal collaboration in organizations at three levels (i.e., individual, work team, and organization).&#x0D; Design/methodology/approach - This research was conducted using Publish or Perish software and VOS Viewer to analyze 6,356 academic articles from 2000 to 2022 in four aspects: temporal distribution of published papers, the scientific community (country/region/authors cited), intellectual structure (journals) cited/references cited), and research centers.&#x0D; Findings and Discussion – The results show that the number and growth rate of publications at the organizational level is much higher than the other two levels (individual and teamwork). This is based on innovation which is often related to collaboration within the organization. The publications with top three countries for the most publications are the United States, China, and the United Kingdom. The top five most cited authors were identified and listed from the individual, work team, and organizational levels&#x0D; Originality - The author combines innovation and collaboration as an interesting subject because not many have made a review of this material. These findings provide a snapshot and comparison of innovation research in management at three levels namely, individual, work team, and organizational levels, which are useful for researchers and students to understand and explore innovative behavior in organizations from a multilevel perspective.
Low-Energy Convolutional Neural Networks (CNNs) using Hadamard Method

The growing demand for the internet of things (IoT) makes it necessary to implement computer vision tasks such as object recognition in low-power devices. Convolutional neural networks (CNNs) are a potential approach for object recognition and detection. However, the convolutional layer in CNN consumes significant e nergy c ompared t o t he f ully c onnected l ayers. To mitigate this problem, a new approach based on the Hadamard transformation as an alternative to the convolution operation is demonstrated using two fundamental datasets, MNIST and CIFAR10. The mathematical expression of the Hadamard method shows the clear potential to save energy consumption compared to convolutional layers, which are helpful with BigData applications. In addition, to the test accuracy of the MNIST dataset, the Hadamard method performs similarly to the convolution method. In contrast, with the CIFAR10 dataset, test data accuracy is dropped (due to complex data and multiple channels) compared to the convolution method. Finally, the demonstrated method is helpful for other computer vision tasks when the kernel size is smaller than the input image size.
Comparing Association Rules and Deep Neural Networks for Heart Disease Prediction

Two decades ago, the most popular data mining technique were association rules (ARs). Nowadays deep neural networks (DNNs) are the most popular mechanism for building predictive models. On the other hand, medical data sets, despite being generally small in size (low volume), they are challenging for predictive models due to diverse attribute content (high variety) and variables with low redundancy (high variability). In this work we compare these two analytic techniques to identify effective models to predict heart disease, a multi-target prediction problem. Both techniques require expertise, manual tuning, and iterative experimentation to determine optimal parameters. Our goal is to build a DNN model that is at least as good as the best ARs. There exist two Big Data challenges: risks factors combined with imaging attributes produce a large number of hidden patterns and the number of association rules reaches millions, without using search constraints at low support (frequency) values. Preliminary experiments on a real data set show discovered rules have high predictive accuracy and they provide a highly accurate, but highly specific, profile of sick patients. Despite careful data pre-processing and hyper-parameter tuning DNNs are slightly more accurate than association rules, but more generalizable. Therefore, both techniques can complement each other.
In-DBMS K-means Clustering for Binary Streams

Clustering data streams is an important problem in big data analytics to detect and monitor activity in fast-evolving environments. We thereby present efficient variants of the K-Means algorithm for finding quality clusters in one-pass, suitable for stream processing in a DBMS. Our main variants are Online K-means, Incremental K-means, and Sliding Window K-means, which can consider or ignore time decay. We then explain how to integrate our algorithms with a DBMS using a combination of SQL queries and UDFs. Acceleration is achieved through a careful combination of optimizations, including sufficient statistics (data summarization), sparse distance computation (Jaccard and Euclidean), multithreaded processing (for multi-core CPUs), and sparse matrix operations. We present benchmark experiments comparing the quality of results and speed. We show that Incremental K-Means achieves similar or even better results than the Standard K-Means algorithm. On the other hand, we show that the sliding window K-Means algorithm captures the evolution of data streams through time.
The Use of Picture Series Technique to Improve Students’ Writing Skills on Recount Text to the Eighth Grade Students at SMP N 6 Tabanan

This research aims to improve students' writing skills in recount text using the picture series technique. The subjects were the eighth grade students at SMP N 6 Tabanan in the academic year 2021/2022. Consisting of 29 eighth students. This research was categorized as Classroom Action Research (CAR). Data were collected by conducting observations, documentation and tests. The research was conducted in two cycles in which each cycle consists of planning, action, observation, and reflection. The result of this research after the implementation of the picture series technique showed that students seemed more confident when writing and began to generate ideas for writing texts. It can be proven by comparing the average value of each score from pre-test to post-test. In the pre-test the average score obtained by students was 47.06%. After the application of the picture series in cycle I the average value was 65.52%. Meanwhile, the results of the post-test of students in cycle II reached 80.86%. With these results, it can be concluded that the picture series technique can improve students’ learning outcomes and can be applied in the teaching and learning process, especially for writing.
A survey on E commerce recommendation system using SPSS statistics

Ecommerce recommendation system.Recommender frameworks plan to foresee clients' inclinations and prescribe results important to them.They are among the most impressive AI frameworks executed by online retailers to increment deals.Information expected for proposal frameworks is gotten from unequivocal client evaluations subsequent to watching a film or paying attention to a tune, understood web search tool questions and buy chronicles or other information about clients/things.Recommender frameworks are broadly used to give suggestions in light of clients' inclinations.With the rising measure of data on the web, proposal frameworks are a valuable instrument to manage data over-burden.The utility of recommender frameworks couldn't possibly be more significant, given its expected impact to address some high-decision challenges.There are many sorts of proposal frameworks with various techniques and ideas.Different applications have taken on suggestion frameworks, including web based business, medical care, transportation, farming, and media.IBM SPSS Estimations is a cloud-based data examination engine that helps individuals and relationship by giving verifiable information to additionally foster execution across the business.Expected for associations of all sizes, it offers game plans including coercion help; risk the chiefs and undertaking data offloading.IBM SPSS Estimations improves enlisting processes through immense data and man-made intelligence computations.Weighted, Switching, Mixed, Feature Combination, Cascade, Feature Augmentation, Meta-Level.The Cronbach's Alpha Reliability result.The overall Cronbach's Alpha value for the model is .482which indicates 48.2% reliability.From the literature review, the above 31.5 % Cronbach's Alpha value model can be considered for analysis.The outcome of Cronbach's Alpha Reliability.The model's total Cronbach's Alpha score is .482,which denotes a 48.2% dependability level.The 31.5 % Cronbach's Alpha value model mentioned above from the literature review may be used for analysis.
Solution for XOR Problem with Neural Networks Using Google Colab and MATLAB / Simulink

To find solution for XOR problem we are considering two widely used software that is being relied on by many software developers for their work. The first software is Google Colab tool which can be used to implement ANN programs by coding the neural network using python. This tool is reliable since it supports python language for its implementation. The other major reason is that we can use GPU and TPU processors for the computation process of the neural network. The major advantage of this is that for complex Neural Networks instead of using CPU present in the user’s system we can use those two processors through online mode without purchasing such processors for our computation. The next software that can be used for implementing ANN is Matlab Simulink. This software is used for highly calculative and computational tasks such as Control System, Deep Learning, Machine Learning, Digital Signal Processing and many more. Matlab is highly efficient and easy to code and use when compared to any other software. This is because Matlab stores data in the form of matrices and computes them in this fashion. Matlab in collaboration with Simulink can be used to manually model the Neural Network without the need of any code or knowledge of any coding language. Since Simulink is integrated with Matlab we can also code the Neural Network in Matlab and obtain its mathematically equivalent model in Simulink. Also, Matlab has a dedicated tool in its library to implement neural network called NN tool. Using this tool, we can directly add the data for input, desired output, or target. After inserting the required data, we can train the network with the given dataset and receive appropriate graph’s which will be helpful in analyzing the data. Once the Neural Network is trained, we can test the network through this tool and verify the obtained results.
A Chaotic System and Count Tracking Mechanism-based Dynamic S-Box and Secret Key Generation

In cryptography, Block ciphers use S-Boxes to perform substitution and permutation operations on a data block. S-Boxes provide non-linearity and confusion of bits to the cryptographic algorithms. In addition, secret keys are critical security aspects for encrypting and decrypting messages. The uncertainty and randomness of the secret key and S-boxes used in the algorithm determine the extent of security against any cryptanalysis attack. This paper proposes a new mechanism to dynamically generate a secret key and S-Box each time while sending and receiving the message. These dynamically generated S-Boxes and keys depend on mutually decided security parameters and message transfer history. Furthermore, a new counter-based mechanism is introduced in this paper. These enhancement techniques are applied to the serpent cipher algorithm, and a data transfer simulation is performed to validate the efficacy of the proposed method. We observe that the dynamically generated S-box follows the strict avalanche criteria. We further validate that the encrypted message shows higher sensitivity to the S-box and the secret key in enhanced serpent cipher than the original version. However, to validate our proposed method, we test and analyze the improvements in the Serpent Cipher Algorithm.
“A chiare lettere – Confronti” • Il sonno dell’argomentazione genera mostri (giuridici)

SOMMARIO: 1. Sempre a proposito dell’art. 7 d.p.r. n. 285 del 1990 - 2. Un recente caso locale - 3. Una nuova frontiera del “classico”? Citare un testo che non esiste - 4. Qualche precisazione in materia di circolari - 5. Conclusione.&#x0D; The sleep of argumentation produces (legal) monsters&#x0D; ABSTRACT: This writing is intended to reply to certain allegations concerning the burial of aborted foetuses in the absence of the mother’s consent. A recent local news case is also reported. In addition, some theoretical and practical aspects of the legal instrument of the circular are clarified.
Pengaruh Literasi Digital Terhadap Keterampilan Penulisan Surat dalam Pembelajaran Bahasa Indonesia Mahasiswa STIE SAK Tahun 2022

This study aims to determine: 1) STIE-SAK students' digital literacy skills, 2) STIE-SAK students' letter writing skills, 3) The effect of digital literacy skills on STIE-SAK students' letter writing skills. This type of research is ex-post facto. The population in this study were all STIE-SAK students. The total population in this study were 350 students. While the sample in this study were 75 students. The sampling technique used in this study was purposive sampling, namely random sampling without regard to strata in the population. This research instrument uses a questionnaire, tests and documentation. The collected data was processed using descriptive statistical analysis and inferential statistical analysis. Based on the results of the descriptive analysis, students' digital literacy skills are included in the medium category with a percentage of 70% and narrative writing skills are included in the medium category with a percentage of 72.6. Based on the results of inferential statistics by testing the hypothesis, the calculation results are obtained, namely tcount = 0.176 while ttable = 1.995 for a significance level of 5%. Because tcount is smaller than ttable, it can be concluded that H0 is accepted and HI is rejected. This means that there is no positive and significant effect of digital literacy skills on STIE-SAK students' letter writing skills.
The Students’ Listening Problems For Senior High School in Pematangsiantar

Abstract: This article describes the English listening problems faced by students in senior high school in Pematangsiantar. Specifically, it reveals (1) students' English listening skills, (2) problems they face in listening to English, and (3) how the teacher solves the problem. This article uses a qualitative descriptive method and is carried out in high school in Pematangsiantar, North Sumatra. the subject of this article through the purposive sampling technique. The data was obtained through a series of English listening tests using recordings with native and non-native speakers, observation, and interviews. The findings show (1) the problems they face in listening to English deal with speaking speed, limited vocabulary, level of concentration, and established language habits, and (3) To overcome this problem, the teacher applies the practice of the right way technique. by giving students several ways to practice listening to English. Thus, it can be concluded that the teacher's efforts are relevant to listening problems faced by students.
Ethical Aspects of Health Sensing Applications in E-Textiles

The role of e-textiles has been discussed widely for health sensing applications. However, the ethical aspects of health sensing e-textiles have received less attention in the literature. In this contribution, we aim to identify the ethical concerns that emerge from the collection and use of health data from e-textiles. To identify these concerns, we draw upon the literature on health wearables and m-health applications. We propose that four ethical concerns need to be accounted for in the design of e-textiles that collect health data. These are privacy, discrimination, autonomy, and harm. We discuss the need to address these ethical concerns during the design process.
Economics keyword lists: A comparative corpus study for ESP

English-medium instruction (EMI) and English for specific purposes (ESP) go hand in hand in higher education, and the demand for those has risen significantly over the last two decades.Studying in an EMI economics program requires a certain level of language proficiency.In most cases, students in these programs are provided with additional language support in the form of an ESP program.Mastering in an EMI economics program challenges students with a number of new and often technical words.Corpus linguistics is, therefore, one of the great tools to answer the vocabulary needs of ESP students.While Coxhead's (2000) Academic Word List (AWL) has been a satisfactory source for academic programs, its being too limited for diverse academic fields has also been criticized.In the current corpus-based study, two separate field-specific keyword lists -(1) Economics Textbook Keyword List (ETWL) and ( 2) the Economist Magazine Keyword List (EMWL) -were created and the coverage of the AWL in these lists was measured.The correspondence ratio between the ETWL and the EMWL was also measured and reported by percentages.In the light of the results, it is argued that the AWL on its own may not be a sufficient source for students of economics and language given in non-academic authentic materials should also be placed in corpus and curriculum design.Thus, for the vocabulary needs of ESP students in an EMI Economics program, it is substantially important that a keyword list covering both academic and non-academic contexts be provided.
Intellectual rent as a tool for assessing the formation of an innovative educational environment in the region

В статье рассмотрены существующие авторские подходы к интерпретации категории «инновационная образовательная среда». Раскрыты условия формирования, функционирования и развития инновационной образовательной среды. Проанализированы существующие подходы к оценке инновационной среды, основанных на наборе оценочных показателей, среди которых наибольшее аналитическое значение имеют показатели инновационного: потенциала, инновационной активности и инновационного климата. The article considers the existing author's approaches to the interpretation of the category "innovative educational environment". The conditions for the formation, functioning and development of an innovative educational environment are disclosed. The existing approaches to assessing the innovation environment based on a set of assessment indicators are analyzed, among which the indicators of innovation potential, innovation activity and innovation climate have the greatest analytical value. The category of intellectual rent is presented as a form of income in connection with the use of human capital, which arises in an innovative educational environment, the innovative competence of which allows generating innovations and designing innovations.
S SISTEM INFORMASI AKUNTANSI KEUANGAN UNTUK MENGANALISA KESEHATAN PERUSAHAAN BERBASIS WEB

The use of sophisticated technology is very much needed by the company as a support for the success and success of a plan that the company wants. The financial report is an information medium that records, summarizes a company's activities and is used to report the company's state and position to interested parties, especially creditors, investors and the company's management itself. Financial ratio analysis helps determine whether the company's financial performance is good or not. Financial ratio analysis can be classified into various types, some of which are liquidity, solvency, activity, and profitability ratios. The financial management system at the food market eat and eat Paragon Mall still uses a simple and less effective system (Microsoft Excel) because it still uses excel formulas and logic if using the formula incorrectly will result in errors in recording financial statements. The method used really takes a long time so that it is often not timely and the way to analyze it is only with profit and loss and the profits are written in the table. The financial ratio method is the main tool for conducting financial analysis and has several uses. Financial ratios show a systematic relationship in the form of comparisons between estimates (posts) of financial statements. With the existence of a financial reporting system to analyze the health of the company, it can help determine the profit for each period, so that the structure of the company's financial health can provide clearer information.&#x0D; &#x0D; Keywords: Financial Statements, Financial Ratios, Performance&#x0D;