Reviewerly/exHarmony huggingface dataset:
UPDATES ON MOVIE RECOMMENDATION SYSTEM

In recent years, there is a huge number of movies on the internet. Users have different desires for a movie to watch as there are different cultures, languages, and genres to choose from in a movie domain. As a result, a recommendation system approach is used to suggest the best movies to users according to their preferences. A number of different algorithms and strategies has been proposed to effectively capture users interest and provide accurate recommendation of movies. Memory Based Collaborative Filtering Recommender Systems existed for the best part of the last two decades. It is an advanced technology, implemented in various commercial applications which because of its effectiveness has been the predominantly used technique to date in recommendation system. Memory based collaborative filtering approach is popularly and extensively used in practice but yet faces some key challenges in providing high quality recommendations due to the daily increase of items and visitors of different websites. This paper presents a review of different techniques and similarity measures used in movie recommendation system and also proposed a model that can be used to build robust, accurate and scalable movie recommendation to users.
Applying Basic Encoding Rule (ITU-T X.690) on Integer Expressions using Arithmetic Circuit Homomorphic Encryption

This is an extension of an ongoing research project on Arithmetic Circuit Homomorphic encryption (ACHE) which was implemented based on Fast Fully Homomorphic Encryption over the Torus (TFHE). This paper focuses on the integration of ASN.l Basic Encoding Rule (ITU-T x.690) into ACHE with RFC7664. Tests were performed to calculate results of 3 operand integer expressions using additional, subtraction and multiplication circuits. Next, the paper will further discuss the protocol design and the method used to achieve the calculation of expressions, and the latency of the entire process.
CONDITIONS FOR EFFECTIVE DELEGATION OF POWERS BY THE MANAGER OF A HIGHER EDUCATION INSTITUTION

The article deals with the level of readiness of the manager of the Free Economic Zone to delegate his powers and summarizes the experience of such activities. During the study of the activities of vice-rectors, heads of departments, deans of faculties, directors of institutes, educational and research centers of higher education, it was found that the head (manager), as a subject of management, must be able to analyze the situation, predict strategy, plan tactics to achieve defined goals and organize operational management for their implementation. But most of the respondents approach the solution of this problem at the level of everyday consciousness, do not always understand that management is first of all the ability to organize teamwork. The effectiveness of managerial work in a higher education institution largely depends on the personal characteristics of the head, but a mandatory component of its productivity are competencies that can not be formed without special knowledge. The procedure for election and appointment does not provide for the availability of such knowledge. The manager of an educational institution can hardly influence the level of predictability of tasks that have an external nature, while the professional organization and streamlining of the structure of internal activities provides significant advantages. One of the ways to optimize the structure of the internal activities of the manager and increase its efficiency is the willingness and ability to delegate their powers. This, as part of a well-planned work, gives the manager the greatest reserve of time. Analysis of the practice of successful managers and scientific literature on this issue, allowed to formulate and test recommendations to managers for successful delegation of authority, which involves the use of certain principles of delegation, a clear understanding of the types and scope of work, work that can be delegated; understanding the procedure and procedure for setting goals and setting goals; taking into account the professional capabilities of staff. It is proved that an important condition for effective delegation is the master's mastery of the logic of formulation and the procedure of setting reasonable goals, which should provide a busy rhythm for each employee, taking into account the goals and personal and professional capabilities.
Mobile Telephone Interactions and Perspectives in the Health Sector of Rural Bengal of India

This study, conducted in Karea village (Daskalgram-Karea II) under Bolpur sub-division of Birbhum district, aimed to assess how mobile telephony is impacting delivery and availability of healthcare services. Given that the village has previously had issues with healthcare support system, it emerged as ideal ground for this study. Employing survey, focus group discussion and interviews of varied stakeholders, this study found high mobile phone ownership in the village. Smartphone use is also not uncommon. People are using mobiles for healthcare purposes, but a large number is not doing so. They are using their phones for other purposes, but not really for healthcare. This underlines opportunity for healthcare workers and officials to encourage more villagers to use mobile phones for calling health support. Notwithstanding this, phones are being used by villagers to call for ambulances and doctors and get patients admitted into hospitals. Workers and officials are also using phones to spread awareness about health issues and health-related programmes. More awareness-building initiatives about use of mobiles for availing healthcare services, need to be undertaken which can make beneficial impact on ground.
Multi-dimensional database technology based on artificial intelligence

Artificial intelligence and database technology are both important fields of computer science. The research results show that more and more industries have a growing demand for artificial intelligence and database. The combination of these two technologies will certainly bring a broader prospect to computer application. This paper mainly discusses the necessity, importance and development of multi-dimensional database technology based on artificial intelligence, introduces the combination strategy of artificial intelligence and multidimensional database and the current research field, and gives the research direction.
Bayesian Basics and the Scientific Hypothesis

This chapter covers the basics of Bayesian statistics, emphasizing the conceptual framework for Bayes’ Theorem. It works through several iterations of the theorem to demonstrate how the same equation is applied in different circumstances, from constructing and updating models to parameter evaluation, to try to establish an intuitive feel for it. The chapter also covers the philosophical underpinnings of Bayesianism and compares them with the frequentist perspective described in Chapter 5. It addresses the question of whether Bayesians are inductivists. Finally, the chapter shows how the Bayesian procedures of model selection and comparison can be pressed into service to allow Bayesian methods to be used in hypothesis testing in essentially the same way that various p-tests are used in the frequentist hypothesis testing framework.
The Church Renewal Movement’s History and Evangelism

When the Korean church has lost public trust and the possibility of evangelism decreases, there are lessons to be learned from the church renewal movement's history such as Believers’ Church, Protestant Monasticism, and Radical Christian Community. They pursued life not by living on tradition and doctrine but by faith. Through various challenges such as the monastic movement’s spirituality, the reinterpretation of the sacrament, and laymen’s preaching, they continued to agonize and sometimes struggle to practice a faithfully biblical life. In a world where individualism prevails, we must regain our identity as Christ’s body church and spirituality to guide seekers to the Gospel. “The reformed church must always be reformed” is currently valid for the Korean churches.
Reinforcement Learning based Evolutionary Metric Filtering for High Dimensional Problems

Metric learning algorithms create distance metrics to capture the important relationships among features. These algorithms have been successful in low dimensional data. However, it is a challenge to handle high dimensional problems in real-world applications. This paper applies in high dimensional clustering problems a Reinforcement Learning (RL) based metric filtering approach in Evolutionary Distance Metric Learning (EDML), which relies on an evolutionary approach to optimize its distance metric. The proposed framework called High Dimensional Reinforced (HDR)-EDML has two novelties. The first is using a function approximation RL method called Least-Squares Policy Iteration (LSPI) to create a feature selection control strategy in high-dimensional input space to filter the metric. The second is adopting a two-way information exchange approach between LSPI and EDML Evolutionary Algorithm (EA) in metric learning. In the first way, LSPI will learn and send feedback that will affect the EDML metric creation. In the second way, the evolutionary feature prioritizing of EDML is utilized by LSPI in its learning process. These two novelties aim to reduce the number of selected features while maintaining the clustering performance. HDR-EDML is compared to conventional K-means, Information-Theoretic Metric Learning (ITML), normal EDML, and EDML with l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> norm regularization for feature selection as baselines. Moreover, 3 different HDR-EDML approaches are examined to explore different ways of information exchange. Results show a significant decrease in the number of features while maintaining accuracy as well as reduced computational time and memory compared to another RL-based filtering method.
KONTRIBUSI PENGUASAAN KALIMAT EFEKTIF TERHADAP KETERAMPILAN MENULIS TEKS EKSPOSISI SISWA KELAS X SMK NEGERI 2 PADANG

ABSTRACT The purpose of this study was categorized into three. First, to describe the effective sentence mastery of the first year students at SMK Negeri 2 Padang. Second, to describe the writing skills of a exposition of the first year students at SMK Negeri 2 Padang. Third, to describe the contribution of the effective sentence mastery into the writing skills of a exposition text made by the first year students at SMK Negeri 2 Padang. The design of this research was quantitative with a descriptive method. Then, this study also was a correlational design. The population of this study was the first year students at SMK Negeri 2 Padang for about 498 students. The sample of this study was taken by using a proportional random sampling technique (15%), which was 70 students. The data of this study were the results of effective sentence mastery and the results of the writing skill of a exposition text. The instrument of this study was an objective test to measure effective sentence mastery and performance tests to measure expositon text. There were several results of this study. First, the effective sentence mastery of the first year students at SMK Negeri 2 Padang was in Good qualifications (B). Second, the writing skills of a exposition of the first year students at SMK Negeri 2 Padang was in a Good qualification (B). Third, describe the effective sentence mastery contributed 82,00% to the exposition text writing skills of the first year students of SMK Negeri 2 Padang. Kata Kunci: kontribusi, penguasaan kalimat efektif, keterampilan menulis teks eksposisi
Comparative analysis of Soviet and Russian school education

Currently, the Russian Federation is implementing the national project «Education», the key goals of which are to ensure the global competitiveness of Russian education and to become one of the top 10 countries in the world in terms of quality of education. The article presents a comparative analysis of the principles of the educational systems of the Soviet and Russian schools. The article describes the key advantages and disadvantages of education in the Soviet era, which was based on ZUN (knowledge, skills). The article reveals the advantages and disadvantages of modern Russian education, the fundamental core of which is UUD (universal educational actions). The article emphasizes that, despite the introduction of the second-generation Federal state educational standards and the introduction of innovative technologies, the level of quality of education in the USSR (the Union of Soviet Socialist Republics) was higher than at present.
COVID-19 유행시대의 사회적 거리두기에 따른 노인의 신체활동과 가정기반 운동의 중요성

Isolation at home due to social distancing measures can promote an unintended reduction of daily physical activities outside the home (e.g. work, market, leisure activities, walking) and increase the sedentary time (e.g. sitting and lying). The purpose of this study was to review the importance of home based exercise and physical activity of the elderly according to social distancing during the COVID-19 pandemic. Formal measures to limit people''s movement in a COVID-19 crisis do not necessarily mean that they should not limit physical activity or exercise. Exercise has clear health benefits for healthy people and patients. As an example of a home based exercise, the application of GOSTEP exercise, which was recently developed based on scientific evidence to prevent falls and improve cognitive function, can obtain psychological effects including functional performance improvement as a multi-task exercise program. Therefore, regular physical activity and exercise in home based exercise are important strategies for healthy living during the COVID-19 pandemic.
A Survey on Consortium Blockchain Consensus Mechanisms

Blockchain is a distributed ledger that is decentralized, immutable, and transparent, which maintains a continuously growing list of transaction records ordered into blocks. As the core of blockchain, the consensus algorithm is an agreement to validate the correctness of blockchain transactions. For example, Bitcoin is a public blockchain where each node in Bitcoin uses the Proof of Work (PoW) algorithm to reach a consensus by competing to solve a puzzle. Unlike a public blockchain, a consortium blockchain is an enterprise-level blockchain that does not contend with the issues of creating a resource-saving global consensus protocol. This paper highilights several state-of-the art solutions in consensus algorithms for enterprise blockchain. For example, the HyperLedger by Linux Foundation includes implementing Practical Byzantine Fault Tolerance (PBFT) as the consensus algorithm. PBFT can tolerate a range of malicious nodes and reach consensus with quadratic complexity. Another consensus algorithm, HotStuff, implemented by Facebook Libra project, has achieved linear complexity of the authenticator. This paper presents the operational mechanisms of these and other consensus protocols, and analyzes and compares their advantages and drawbacks.
A Reinforced Dynamic Multi-keyword Ranked Search with Forward Privacy

Searchable symmetric encryption performs satisfactorily in protecting the privacy of outsourced data in cloud storage scenarios because it encrypts data and provides a secure way of searching on the ciphertext. Dynamic searchable symmetric encryption is designed to support insertion and deletion of outsourced data. However, insertion may cause information leakage of updated keywords. Thus, forward privacy is proposed to limit the leakage of insertion, and it has become an important security attribute for dynamic schemes. The existing dynamic searchable symmetric encryption schemes with forward privacy are mainly based on two approaches, re-build index with fresh key and token with state information. However, both approaches have their constraint and advantages. In this paper, we first proposed a new highly versatile reinforcement approach. The proposed approach is easy to implement. Besides, we minimized the loss of efficiency by setting a small threshold value. In order to demonstrate that the proposed approach is effective, we utilize our approaches to improve EDMRS scheme. Security and performance analysis show that the improved scheme with the proposed approach is still satisfy the forward privacy without a significant loss of performance.
Finding suitable algorithm for Text Analysis the basic concept of Big Data

Data analytics plays a major role in each and every field of text analysis .It is one of the basic methods in data analytics. It helps in feedback analysis, customer behavior analysis, movie and product reviews. The behavior and sentiment is resulted as emotions of a person that is decided by the words used by the individuals. To brief it if a WhatsApp chat if a person is analyzed, they must have used mixed word that depicts both positive and negative words. If there are maximum numbers of positive words it is concluded that the person is happy or else it is concluded that the person is in a problematic situation. Sentiment analysis algorithm is dealing with the classification of those positive, negative and neutral words. Text analysis is done by some deep learning algorithms such as Support Vector Machine (SVM), Naive Basie (NB), K Nearest Neighbor (KNN),K* and DT-J48.This Proposed research paper is based on the idea to find a suitable algorithm for text analysis .Based on the best results, comparison of each results is performed. It can analyze Structured, Unstructured and Semi Structured data. The data set for this analysis is a simple whatsapp chat combination of both text and emojis and results the emotion of an individual by counting Positive, Negative and Neutral words using Sentiment Analysis and this proposed idea is to fix the best algorithm for text analysis.Keywords – SVM, NB, KNN, K – MEANS, DT-J48, feedback analysis and customer behavior analysis
Semi-Supervised Learning with Meta-Gradient

In this work, we propose a simple yet effective meta-learning algorithm in semi-supervised learning. We notice that most existing consistency-based approaches suffer from overfitting and limited model generalization ability, especially when training with only a small number of labeled data. To alleviate this issue, we propose a learn-to-generalize regularization term by utilizing the label information and optimize the problem in a meta-learning fashion. Specifically, we seek the pseudo labels of the unlabeled data so that the model can generalize well on the labeled data, which is formulated as a nested optimization problem. We address this problem using the meta-gradient that bridges between the pseudo label and the regularization term. In addition, we introduce a simple first-order approximation to avoid computing higher-order derivatives and provide theoretic convergence analysis. Extensive evaluations on the SVHN, CIFAR, and ImageNet datasets demonstrate that the proposed algorithm performs favorably against state-of-the-art methods.
AUDIT SISTEM INFORMASI PERSEDIAAN BARANG PADA PT HARAPAN BARU MOTORINDO DENGAN MENGGUNAKAN METODE FRAMEWORK COBIT

PT Harapan Baru Motorindo is a spare parts sales company in Batam that uses an information system to manage data. However, there are problems with the system, such as the occurrence of errors about one to two times a month so that the data management process is done manually and the company has never conducted an information system audit. The purpose of this research is to measure the level of maturity and to find the source of problems in the system and to provide recommendations to companies to improve IT governance. The study was conducted with the COBIT 4.1 framework with a focus on the PO1, PO8, AI2, AI3, DS10 and ME4 sub domains. The results of the analysis of the maturity level show that the company is at level 3 with a defined process status, which means that the company has carried out IT strategic planning (PO1), IT quality management system (PO8), made design, security and system control according to business needs (AI2), already has procedures for implementing and updating IT infrastructure (AI3), has built procedures for managing data (DS10) and has conducted training and communication to employees regarding standard IT procedures and responsibilities (ME4).
PORTFOLIO AS A TOOL FOR EVALUATING INTELLECTUAL CAPITAL

The competitiveness of an organization (including an educational organization) is determined by a combination of various factors, including: the presence of highly qualified personnel in its staff, the implementation of research activities, the use and implementation of innovations, and others. The real pace of life and scientific and technical development has its own requirements for employees of organizations – it is necessary to be a highly qualified specialist. And one of the tasks of the employer is the task of finding such a specialist. A well-designed electronic portfolio, which is considered one of the tools for assessing the intellectual capital of an employee or future specialist (student), can help in this.
Quantitative Analysis of Watersheds Partitioned from Cartosat Dem of Lower Indus Sub-Basin Via Multifractal Spectra

This paper provides watershed-specific information dimensions computed through construction of binomial multiplicative process based multifractal spectra. Information dimension of watersheds provides clues on the distribution of terrestrial elevations spread across all the spatial positions within the watershed. This information dimension could be related to the responses of watersheds to the perturbation caused due to cascade of endogenic and exogenic forces. Higher the information dimension, lesser is the response to the cascade of endogenic and exogenic forces. Based on the information dimension computed through multifractal spectra for thirty one watersheds partitioned from the Cartosat DEM of the Lower Indus subbasin, we inferred that the watersheds are within the range of highly heterogeneous to highly homogeneous categories. It would be interesting to adopt this approach to study watersheds belonging to physiographically distinct regions.
Simulasi Terbaik Dalam Persediaan Komponen Darah Menggunakan Metode Monte Carlo

The supply of blood components requires care that must be considered. Especially at the Red Cross Indonesian Blood Donation Unit (UDD). In fulfilling the demands of every hospital that requires blood, it often experiences a vacuum in the supply of blood components. This happened because of the difficulty in predicting the demand and supply of blood components in UDD PMI. The purpose of this study is to assist in predicting the processing of blood component inventory data so that blood components are always available to meet blood demand. The method used is the Monte Carlo method. With Monte Carlo simulations it can be calculated using random numbers (random) as one of the input values so as to produce an output value which is a value which approaches the prediction of real data. Furthermore, the data managed are the blood component inventory data from 2016 to 2018. The results of the simulation calculation using the Monte Carlo method become predictions in producing blood component supplies in the future. So that the accuracy value in the prediction truth will be obtained. With an average accuracy rate of 93.1%. Then the system in predicting the supply of blood components can be used in UDD PMI. The results of the simulation of blood component inventory using the Monte Carlo method can meet the demand for blood components in the future. So that there is no shortage of blood components in UDD PMI.