Reviewerly/exHarmony huggingface dataset:
Pengaruh Struktur Organisasi Terhadap Kualitas Sistem Informasi Akuntansi Pada Pt. Kunci Inti Transindo Jakarta

Changes in an accounting information system always depend on an organizational structure, and the quality of the accounting information system will affect the success of the organizational structure. The purpose of conducting this research is to determine the extent of the influence of the Organizational Structure on the Quality of the Accounting Information System at PT. Kunci Inti Transindo Jakarta. The research results are expected to prove that the given model can be used as a solution to the quality problems of the accounting information system. In this study the population is PT.Kunci Inti Transindo located in North Jakarta with 89 employees. The sample obtained is by using a data collection technique by giving a questionnaire to the employees of PT. Kunci Inti Transindo Jakarta's core. The method used in analyzing the data is a simple linear regression analysis method and through a quantitative approach. The results prove that the Organizational Structure has a positive effect on the Quality of the Accounting Information System by 81.4%. and the remaining 18.6% is influenced by factors other than this study. This means that a quality organizational structure will result in a maximally integrated information system..&#x0D; Key words: Structure, organization, and quality, information system, accounting
THE OPTIMIZE OF ASSOCIATION RULE METHOD FOR THE BEST BOOK PLACEMENT PATTERNS IN LIBRARY: A MONTHLY TRIAL

Data mining is the process of finding interesting patterns and knowledge from large amounts of data. Sources of information service, especially in the library, include books, reference books, serials, scientific gray literature (newsletters, reports, proceedings, dissertations, theses, and others). The importance of this research being carried out in the library in this study aims to implement data mining with the association rule method to solve problems, especially in the placement of shelves based on the category of the printed version of the book collection. This research method uses a qualitative research approach. Data was collected using documentation techniques and deep analysis of existing weaknesses to identify user needs whose information was obtained through observation and interviews with key informants (admin, user, etc.). For example, the determination of the best book placement patterns can be done by looking at the results of the tendency of visitors to borrow books based on a combination of 2 item sets with 60 percent of confidence value every month or week and must be evaluated or take a calculate again.
Studying Online Multi-Agent Path Finding

Multi-agent path finding (MAPF) is the problem of planning a set of non-conflicting plans on a graph, for a set of agents. Online MAPF extends MAPF by considering a more realistic problem in which new agents may appear over time. While planning, an online solver does not know whether and which agents will join in the future. Therefore, in online problems the notion of snapshot-optimal was defined, where only current knowledge is considered. The quality of such a solution may be weaker than the quality of a solution to an equivalent offline MAPF problem (offline-optimality), where the solver is preinformed of all the agents that will appear in the future. In this paper we explore, theoretically and empirically, the quality of snapshot-optimal solutions compared to offline-optimal solutions.
Towards Making the Most of Dialogue Characteristics for Neural Chat Translation

Neural Chat Translation (NCT) aims to translate conversational text between speakers of different languages.Despite the promising performance of sentence-level and context-aware neural machine translation models, there still remain limitations in current NCT models because the inherent dialogue characteristics of chat, such as dialogue coherence and speaker personality, are neglected.In this paper, we propose to promote the chat translation by introducing the modeling of dialogue characteristics into the NCT model.To this end, we design four auxiliary tasks including monolingual response generation, cross-lingual response generation, next utterance discrimination, and speaker identification.Together with the main chat translation task, we optimize the NCT model through the training objectives of all these tasks.By this means, the NCT model can be enhanced by capturing the inherent dialogue characteristics, thus generating more coherent and speaker-relevant translations.Comprehensive experiments on four language directions (English⇔German and English⇔Chinese) verify the effectiveness and superiority of the proposed approach.
Asymmetric image encryption scheme based on Massey Omura scheme

Asymmetric image encryption schemes have shown high resistance against modern cryptanalysis. Massey Omura scheme is one of the popular asymmetric key cryptosystems based on the hard mathematical problem which is discrete logarithm problem. This system is more secure and efficient since there is no exchange of keys during the protocols of encryption and decryption. Thus, this work tried to use this fact to propose a secure asymmetric image encryption scheme. In this scheme the sender and receiver agree on public parameters, then the scheme begin deal with image using Massey Omura scheme to encrypt it by the sender and then decrypted it by the receiver. The proposed scheme tested using peak signal to noise ratio, and unified average changing intensity to prove that it is fast and has high security.
Effectively Adapting and Implementing In-Person Teacher Professional Development to a Virtual Format

A year of COVID-19 quarantine required educators to switch from in-person to virtual learning platforms, causing a dramatic reimagining of their daily praxis. Their experiences are likely to influence new norms for K-12 education. While virtual learning can be effective, student engagement, student retention, and student attention can be challenging. This paper discusses how we adapted a materials-heavy, hands-on, annual summer teacher professional development (PD) program from an in-person to a virtual platform in the initial months of the pandemic. We successfully maintained effective and hands-on components, giving authentic learning experiences to the participants. The 2020 virtual version of the program effectively engaged in-service teachers with high daily participation and retention rates. Nearly all participants rated the workshops as very good or excellent, and an assessment of participants' learning outcomes was comparable to that of the highly-rated in-person 2018 version of the program. Following the PD session, teachers reported feeling more prepared to facilitate their students' learning, increased inquiry-based science teaching knowledge and skills, and their enthusiasm for utilizing workshop strategies. While there are challenges to implementing virtual learning, virtual teacher PD can be widely adaptable and replicable for many institutions, especially in situations in which distance or finances deter in-person participation.
A MATHEMATICAL PROPOSED MODEL FOR PUBLIC KEY ENCRYPTION ALGORITHMS IN CYBERSECURITY

Information security is a very important science, especially after the continuous increase in cybercrime of all kinds, which caused very large financial, economic and political losses, so it was necessary to find a solution to protect the data and keep it secret. Data encryption is one of the most important solutions to preserve data and reduce cybercrime. The encryption process means converting the plain text using a private key into symbols and numbers that make this text incomprehensible to others. There are many algorithms that are used for encryption, and the public key algorithms are the strongest in the encryption process because they depend on two keys, the public key and the private key. One of the most important problems facing this type of algorithm is the lack of a clear mathematical model that facilitates understanding and how to deal with these keys. In this thesis, a mathematical model has been proposed in which two functions are defined, the public key and the function of the private key, based on the concepts and specific characteristics of the function. A general mathematical model was constructed by defining two functions, one for the public key and the other for the private key, using the properties of a function in mathematics, to produce strong keys used in the public key algorithm, to protect data and keep it secret, and this model was applied to the RSA and ELGamal algorithms. The most important result was that in the case of applying the mathematical model, it is easy to understand and deal with the public key and the private key mathematically.
Multistage BiCross encoder for multilingual access to COVID-19 health information

The Coronavirus (COVID-19) pandemic has led to a rapidly growing 'infodemic' of health information online. This has motivated the need for accurate semantic search and retrieval of reliable COVID-19 information across millions of documents, in multiple languages. To address this challenge, this paper proposes a novel high precision and high recall neural Multistage BiCross encoder approach. It is a sequential three-stage ranking pipeline which uses the Okapi BM25 retrieval algorithm and transformer-based bi-encoder and cross-encoder to effectively rank the documents with respect to the given query. We present experimental results from our participation in the Multilingual Information Access (MLIA) shared task on COVID-19 multilingual semantic search. The independently evaluated MLIA results validate our approach and demonstrate that it outperforms other state-of-the-art approaches according to nearly all evaluation metrics in cases of both monolingual and bilingual runs.
Geophysical Survey at Mount Pleasant Henge

– First complete geophysical survey coverage of the Mount Pleasant mega-henge. – Evaluation of plough damage and erosion of the henge earthworks using GPR. – Reprocessing and comparison of Clark’s original magnetic survey from 50 years ago.
Компетентностный подход в образовании: психологическое содержание основных понятий

International scientific and practical conference «Pedagogy, psychology and teaching methods: international experience» : conference proceedings, July 16–17, 2021. Riga, Latvia : «Baltija Publishing», 2021. 295 pages.
Development and Effects of a Mechanical Ventilation Education Program with Blended Learning for Nursing Students

Purpose: This study describes the development and implementation of a mechanical ventilation education program with a blended learning method for nursing students.Methods: Sixty-five nursing students were recruited either to the experimental group (n=33) or to the control group (n=32) in May 2020. This program was developed based on the analysis, design, development, implementation, and evaluation model. The analysis phase consisted of a literature review, expert consultations, and target group survey. In addition, learning objectives and a structure were designed, and an online program was developed. In the implementation phase, the program was conducted over the course of 2 weeks. The evaluation phase involved verification of the effects of the program on knowledge of mechanical ventilation, self-confidence, and ventilator nursing skills performance, as well as an assessment of satisfaction with the program.Results: The experimental group had significantly higher scores on knowledge of mechanical ventilation (t=4.29, p&lt;.001), self-confidence (t=2.31, p=.024), and ventilator nursing skills performance (t=4.65, p&lt;.001) than the control group.Conclusion: The results indicate that this mechanical ventilation education program with blended learning was effective in meeting the needs of nursing students and can be widely used in this context.
Colour, Texture, and Shape Features based Object Recognition Using Distance Measures

Object recognition is the recognizing process of objects into semantically expressive classes using its visual insides.Classification of objects becomes complex and challenging task because of its size, poor image quality, occlusion, scaling, geometric distortion, lightening, etc.In this paper, global descriptors that means Color, Texture, and Shape features are used to recognize object.Color histogram is used to obtain the color content, texture content is obtained using Gabor wavelet, and shape content is extracted using Hough transform.These low level or global features are used for creating feature vector.Distance measure is used to find the 1-Nearest Neighbor from the training images i.e. object with minimum distance or maximum similarity with visual contents of the query image.The class of that training image is the predicted label of the query image.We have used twelve different distance measures: some are metrics, some are non-metrics and finally, their recognition accuracy is compared.Ensemble of these distance measures is also used for object recognition in the image.We evaluate this method on a publicly available object-recognition dataset: Columbia Object Image Library (COIL-100) dataset.The experiments show that the recognized results outperform many state-of-the-art methods.
Emergence of Blockchain Technologies in Digital Healthcare—A Short Review

Blockchain Technology is a kind of encrypted record of data and it works on a distributed database which deals with the data regarding the transaction and contract.Blockchain lies on an independent record as a digital ledger and is considered as important which can be reachable in various platforms and is not confined in a particular place.Blockchain Technology or simply Blockchain is helpful in different financial activities and services.It is required in proper and healthy digital currency management i.e., bitcoin transactions.It is worthy to note that financial transaction becomes effective without the requirement of the third party and therefore it keeps the data encrypted.Additionally, here participants need not share any personal data and therefore all the data basically kept as encrypted.There are tremendous applications of Blockchain Technology in the recent past in different common and emerging areas.Among the emerging applications or sectors,the healthcare and medical sector is considered as one of the important and valuable industry sectors.This paper is conceptual and prepared with existing literature related to Blockchain Technology.Here basic aspects, viz.features, characteristics, and special basic applications of Blockchain Technology are described.However, the paper specially focused on Blockchain Technology applications in the healthcare and medical sector.
Quantum CPOs

We introduce the monoidal closed category qCPO of quantum cpos, whose objects are 'quantized' analogs of ω-complete partial orders (cpos).The category qCPO is enriched over the category CPO of cpos, and contains both CPO, and the opposite of the category FdAlg of finite-dimensional von Neumann algebras as monoidal subcategories.We use qCPO to construct a sound model for the quantum programming language Proto-Quipper-M (PQM) extended with term recursion, as well as a sound and computationally adequate model for the Linear/Non-Linear Fixpoint Calculus (LNL-FPC), which is both an extension of the Fixpoint Calculus (FPC) with linear types, and an extension of a circuit-free fragment of PQM that includes recursive types.
Pengaruh Perhatian Orangtua dalam Pembelajaran daring terhadap Motivasi Belajar Peserta Didik Madrasah Tsanawiyah

This study aims to analyze the influence of parental attention on students learning motivation in online learning during the covid-19 pandemic. The research method uses a quantitative approach. As many as 30 madrasah Tsanawiyah children aged 13-16 years were sampled in the study, they were given 20 questions related to learning motivation and parental attention. The selection of samples was conducted randomly in the pabuaran sub-district of Serang Regency, Banten Province in 2021. This study uses descriptive quantitative methods. Research instruments using questionnaires through Google Form. The data analysis method is done with the help of a computer software application program, SPSS 25 for windows. From the results of the data analysis known regression equation Y = 11.075 + 0.696. While the results of the T test obtained the results of the provisions of the Jubilee for df = 28 with an error rate of 0.05 or 5% is 1,701. While Thitung obtained from this study showed a value of 4,140. Because t hitung &gt; t table = 4,140 &gt; 1,701 ha was accepted and H0 was rejected. And the results of the calculation of determination test obtained the number R² of 0.380 or 38%. This indicates that the percentage influence of independent variables affects dependent variables by 38% while the rest by (100-38% = 62%) influenced by other variables or indicators not studied in this study. Thus, the results of the study concluded the influence of parental attention to the motivation of learning madrasah Tsanawiyah students in the district pabuaran Serang Banten Province. This study recommends parents to pay more attention to the child so that the child's learning motivation increases.
Compositional Defence of Application Privacy in Resistant to Physical and Software Attacks in Untrusted Cloud Environment

Cloud computing facilities have become an increasing rise in demand for presenting computing sources. Various programs like monetary transactions, fitness care systems, video streaming, IoT programs want on-call for provisioning of cloud sources to guarantee timeliness and excessive availability. A shared culture for data interchange has evolved as a result of the fast progress of networking technology. The data security has become a difficult issue as a result of the vast volume of data that is exchanged via the internet. Thus there is a requirement for security to protect data that is transmitted across an insecure connection. In our proposed work, privacy, confidentiality, availability, integrity, and accountability that contribute to the security of information are ensured by cryptographic technique. This paper also describes an exhaustive study on the usage of hybrid algorithms i.e. the combination of Advanced Encryption Standards (AES) and Elliptical Curve Cryptography (ECC) to protect data leakage and protect the privacy of end-users and SHA256 algorithm to ensure data integrity. This type of hybrid encryption will help not only in concentrating software as well as physical attacks but also provide the model to deal with and prevent the application from these types of attacks; thus making the cloud application system more secure. The implemented web application can be used as a defence system for privacy and security in organizations as well as institutions where members of the organization can share the file or confidential data to other team members or colleagues without data leakage thus providing data privacy and security.
Investigation of measurement data of low-coherence interferometry at tilted surfaces in the 3D spatial frequency domain

Abstract The 3D transfer characteristics of interference microscopes and their effect on the interference signals occurring at surface slopes are studied. The interference image stacks acquired during a depth scan are 3D Fourier transformed. This allows a comprehensive frequency domain analysis of the interferograms. The double foil model introduced in a previous publication enables the interpretation of the signal spectra and the underlying transfer behavior of the interferometer using the concept of the Ewald sphere, which is limited by the numerical aperture (NA) of the imaging system. Analysis in the 3D spatial frequency domain directly discloses that the lateral dimensions of the transfer function depend on the axial spatial frequency. In this contribution we investigate measuring objects produced by Nanoimprint-Lithography. The corresponding signal spectra bear information that can be utilized to optimize the subsequent signal processing algorithms. These include envelope and phase evaluation procedures of the interference signals. A narrow bandpass filter is used to actively select certain frequency components in order to improve the robustness of the estimation of the envelope position. Although the shape and width of the envelope are affected, this procedure increases the reliability of the evaluation process and improves the accuracy of the measured topography especially at steeper surface slopes.
A Study on the Usage Intention of Japanese Learning Mobile Applications

Mobile applications change living habits and social style and provide an alternative learning channel for foreign languages. The use of applications overcomes limitations of time and space, thus enhancing the effectiveness of foreign language learning. In Taiwan, from the university students learning a foreign language, most part is learning English, followed by Japanese. Many scholars have conducted studies on issues related to English learning applications, but few have studied Japanese learning applications. Therefore, the main purpose of this study is to investigate the factors that influence learners to use Japanese learning applications. An online questionnaire survey was conducted from February 21 to March 2, 2021, in the Japanese language group of the Department of Applied Foreign Languages at a university in northern Taiwan. From the 127 valid forms collected, 40 respondents indicated they have not used Japanese learning applications. Thus, the remaining 87 answers were analyzed using the statistical software IBM SPSS Statistics 20. The results showed that among all variables, the mean score of “perceived ease of use” was the highest and that of “behavioral intention” was the lowest. Empirical analysis revealed that “perceived usefulness,” “facilitating conditions,” and “social influence” were the key factors that influenced the “behavioral intention” of learners. The findings can provide design guidelines for Japanese learning application developers and serve as a reference for educators to promote the use of Japanese learning applications.
An Empirical Study of Partial Deduction for miniKanren

We study conjunctive partial deduction, an advanced specialization technique aimed at improving the performance of logic programs, in the context of relational programming language MINIKANREN.We identify a number of issues, caused by MINIKANREN peculiarities, and describe a novel approach to specialization based on partial deduction and supercompilation.The results of the evaluation demonstrate successful specialization of relational interpreters.Although the project is at an early stage, we consider it as the first step towards an efficient optimization framework for MINIKANREN.
The TRANSFER OF CODES AND MIXED CODES IN INDONESIAN MOLEBRITIES INSTAGRAM

This study tries to analyze the code and code mix in Indonesian celebrity Instagram accounts. The research method used is descriptive. Is this research. Then, the source of this research data is uploading on celebrity Instagram accounts from May to June 2020. Meanwhile, the data in this study are the status information uploaded by Indonesian celebrities. Furthermore, collecting data in this study was carried out by making screenshots of uploaded photos or videos accompanied by information and data sourced from Indonesian celebrity Instagram accounts. Then, all the collected text will be categorized by the type of code switching and mixed code. Based on the analysis of research results can be seen as follows. (1) code switching found in the Indonesian celebrity Instagram account caption upload caption over internal code and external code transfer, (2) mixed code found in the Indonesian celebrity idiom Instagram Instagram account caption, and clauses.