Reviewerly/exHarmony huggingface dataset:
Perancangan Sistem Monitoring Surat Perintah Perjalanan Dinas dengan Mobile App Android untuk Biro Kepegawaian Universitas Nurul Jadid

An official travel warrant is a letter made for employee who has been assigned for an official trip to a certain area. The application process of The official travel warrant (surat perintah perjalanan dinas/SPPD) at Nurul Jadid University involves the Faculty Administration by submitting it to Head of Administration and the one who who has a right for approval, such as Representative Rector. The current process is still based on the old system and has an impact on long synchronization between employees due to lack of coordination and time-delays in the process of submitting service processes. Therefore, this study is intended to offer a system design for monitoring official travel orders with the Android Mobile App at Nurul Jadid University. The method used in this research is the waterfall method, whose stages or paths run from top to bottom. The target of this research is the monitoring of official trips which will make it easier for all parties. The results of this study are 96.9% of employees said that this system really helps the process of official travel effectively and efficiently.
The issue of variability in higher education in Russia

Abstract This paper analyzes approaches to the variability of education in Russia, the implementation of the idea of variability in the field of higher professional education. The understanding of the variability of education as a fundamental principle of the development of the modern education system is presented. The possibilities of implementing the principle of variability of education at various levels are considered. The features of the transition of the organization of the educational process to an individually oriented organization of the educational process are listed. The methodological principles of the educational development paradigm are considered in detail.
Effective technology to visualize virtual environment using 360-degree video based on cubemap projection

The paper dealt with the task of increasing the efficiency of high-quality visualization of virtual environment (VE), based on video with a 360-degree view, created using cubemap projection. Such a visualization needs VE images on cube faces to be of high resolution, which prevents a smooth change of frames. To solve this task, an effective technology to extract and visualize visible faces of the cube is proposed, which allows the amount of data sent to graphics card to be significantly reduced without any loss of visual quality. The paper proposes algorithms for extracting visible faces that take into account all possible cases of hitting / missing cube edges in the camera field of view. Based on the obtained technology and algorithms, a program complex was implemented, and it was tested on 360-video of a virtual experiment to observe the Earth from space. Testing confirmed the effectiveness of the developed technology and algorithms in solving the task. The results can be applied in various fields of scientific visualization, in the construction of virtual environment systems, video simulators, virtual laboratories, in educational applications, etc.
Training of modern specialists based on V.I. Vernadsky’s ideas of noosphere education

The article is devoted to the study of topical problems of noosphere education and noosphere pedagogy on the analysis of the development of the modern higher education system in the Russian Federation. An analysis of the reflection of the main noosphere ideas in modern education is presented. Theoretical provisions on creativity as a feature of noospheric pedagogy (corresponding to the spirit of time and the challenges of the modern globalized world) are revealed. The article reveals the importance of future educators forming humanistic-oriented personality qualities based on the implementation of new approaches to education, consistent with the natural laws of the universe, not violating the biorhythms of living systems, but taking into account the capabilities of the psyche, human nature, its age characteristics, individual pace of development. The main task of pedagogical education from the point of view of the noosphere concept is determined - the formation in a person of a holistic noosphere consciousness (holistic thinking, an ethical bioadaptable method of behavior and an ecological worldview).
Mind Mapping and Teaching Strategies of English language in High School under the Guidance of Key Competence

Under the key competence, high school English teachers shall strengthen the use of mind mappings when developing reading and teaching activities, thus making English reading, and teaching more intuitive and logical. In this way, high school students can be more interested in English, and more active and autonomous in improving their English reading ability. This article explores and analyzes the problems existing in high school English reading teaching at current stage, and puts forward an effective strategy for using mind mappings to develop high school English reading and teaching under the key competence, with the hope of facilitating the development of English reading and teaching in high school.
COMPENSATION SCHEME AND ACADEMIC STAFF PERFORMANCE IN FEDERAL POLYTECHNIC NASARAWA

This study examined the effect of compensation schemes on academic staff performance in Federal Polytechnic Nasarawa. Specifically, it investigated the effect of special allowances and part-time emoluments (independent variable) on academic staff performance (dependent variable) of the institution. The descriptive survey research design was adopted for the study. The population comprises of the 485 academic staff of the institution from where a total of seventy nine (79) samples of academic staff were selected across six (6) faculties using stratified sampling technique. Questionnaire was used to gather data from the respondent. The reliability of the questionnaire was tested using Cronbach- alpha coefficient and the test yielded the alpha coefficient of 0.85 and 0.82 for special allowances and part-time emoluments respectively.Descriptive statistics was used to present the data while multiple regression analysis was carried out to examine the extent to which the independent variable affects the dependent variable and the finding reveals thatboth special allowances and part-time emoluments have significant positive effect on academic staff performance in Federal Polytechnic Nasarawa. The researcher recommends that; the management of the institution should continue to enhance employees’ compensation schemes (both special allowances and part-time emoluments).
포스트 코로나 시대 데이터 비즈니스 생존전략

In this viewpoint paper, we overlook the potential of the data industry and the strategies needed in order to survive in this new socio-economic order brought by COVID-19. The social distancing culture is leading to the expansion and centralization of data. The government established the development plan of the data industry ecosystem and the capital flow is following this stream, so this is an opportunity for those in the data business. To survive and grow in the data industry ecosystem, we need to identify quality characteristics that have a comparative advantage over competitors based on high data quality and need to determine the target business segmentation to avoid wasting resources and make efficient investments.
Pest Diagnosis Expert System On Chili Plants Using Forward Chaining Method In The Department Of Agriculture In Pagar Alam City

This study aims to produce an expert system for diagnosing pests in chilies using the Forward Chaining method.Chili is one of the basic needs of the community as a flavoring or flavor, but farmers often experience failure to harvest due to pest attacks on chili plants.The system development method used by Waterfall consists of four stages, namely Analysis, Design, Coding and Testing.Therefore, the researcher created an expert system for diagnosing pests in chilies using the Onlane Forward Chaining method.the benefits of this expert system for the city of Pagar Alam, especially for farmers, make it easy to find out the types of pests that attack and provide solutions to prevent pests from being planted in chilies like an expe
DESAIN PERENCANAAN MASTER PLAN PADA UPT. PERPUSTAKAAN UNIVERSITAS SERAMBI MEKKAH ACEH

The library of Serambi-Mekkah University is one of the main libraries at the Aceh College which serves all academic communities. In facilitating library service activities, it is necessary to use good information technology with strategic planning as outlined in a Master Plan in a form. Preparing the Master Plan aims to provide long-term guidelines to be aligned by aspects of the library field and provide tangible benefits to the library in achieving its vision and mision from the design of information system. The research method used in developing information systems at the Serambi Mekkah University Library Aceh uses needs analysis and designing library software. The library of Serambi-Mekkah University Aceh uses a diagram model (use case) which is a complete description of the interactions between actors with designing and creating information systems.
Analysis of Newspaper Articles about Food Stockpile

Objective: Every disaster had drawn attention to food stockpiles. There is a possibility that its quality and quantity have changed through disaster experiences. In order to help to consider future strategies, we clarified the countermeasures that had not been progressed while they had been acknowledged as a problem for long time and the areas moved ahead from the events and newspaper articles in the past 30 years.
Readiness Of Future Lecturers For Educational Activities: Motivational And Value Component

Socio-economic changes, changes in the meaning of life orientations of young people lead to an increase in the importance of the educational component of the educational system. The role of education is particularly important for the system of secondary vocational education, which is often associated with a complex contingent of students. Methodology. The methodological basis of the research is based on systematic and axiological, contextual, nuclear and personality-oriented approaches; structural approach to the study of S. L. Rubinstein's personality. The basic part. In Western scientific sources, readiness for educational activity is associated with the acquisition of new repertoires of pedagogical behavior, general and internal regulation of lecturer behavior, a flexible combination of theoretical and practical readiness for the studied activity. The motivational and value component of the future lecturer's readiness for educational activities in secondary vocational education organizations, analyzed in the framework of this study, includes: as stable components: stable motivation to carry out pedagogical activities and acceptance of its values, as flexible components: self-motivation, integration of personal professional values and meaningsю We see further prospects for this research in the development of a system for preparing future lecturers for educational activities in organizations of secondary vocational education, which results in readiness for it, including: motivational-value, conative-activity and emotional components.
A Robust Solution to Variational Importance Sampling of Minimum Variance

Importance sampling is a Monte Carlo method where samples are obtained from an alternative proposal distribution. This can be used to focus the sampling process in the relevant parts of space, thus reducing the variance. Selecting the proposal that leads to the minimum variance can be formulated as an optimization problem and solved, for instance, by the use of a variational approach. Variational inference selects, from a given family, the distribution which minimizes the divergence to the distribution of interest. The Rényi projection of order 2 leads to the importance sampling estimator of minimum variance, but its computation is very costly. In this study with discrete distributions that factorize over probabilistic graphical models, we propose and evaluate an approximate projection method onto fully factored distributions. As a result of our evaluation it becomes apparent that a proposal distribution mixing the information projection with the approximate Rényi projection of order 2 could be interesting from a practical perspective.
Land Rover fails to defend 3D shape mark oppositions

Jaguar Land Rover Limited v Ineos Industries Holdings Limited, High Court of Justice of England and Wales [2020] EWHC 2130 (Ch), 3 August 2020 The High Court of England and Wales has rejected Jaguar Land Rover’s UK trade mark applications covering the shapes of its Land Rover Defender motor vehicles, in particular, due to a lack of acquired distinctiveness. In a judgment by Her Honour Judge Melissa Clarke, the High Court of Justice has rejected Jaguar Land Rover’s (JLR) applications to register UK trade marks for 3D shapes, on appeal from the UK Intellectual Property Office’s Trade Marks Registry (UKIPO). JLR failed to overturn the UKIPO’s findings that the signs in issue lacked inherent distinctiveness (section 3(1)(b) of the Trade Marks Act 1994) and had not acquired distinctiveness (within the meaning of section 3(1)). The signs which JLR sought to protect via the applications were the shapes of...
The problem of digital transformation of Russian universities

There are numerous disputes and discussions about the need to introduce online learning technologies into the educational process of the university. However, the welcoming examples of individual educational institutions should not give rise to the illusion of complete and widespread prosperity. In many Russian universities, the situation with the introduction of new teaching aids is, to put it mildly, difficult both in terms of the availability of an organizational strategy and in terms of cultural changes. The article attempts to characterize the situation with online education in universities based on an analysis of the expectations of students who seem ready to move to digital, and the decisions of the Bologna process, requiring the introduction of online components in the educational process of universities. In addition, the authors of the article provide an overview of the initial attempts to introduce online learning into the educational process of universities in a particular region, taking into account the systematic and psychological difficulties that have arisen. As the best option, the authors propose a combination of online education with a research component in order to preserve the university’s status as a center of science and education.
Invariant Feature Learning for Sensor-based Human Activity Recognition

Wearable sensor-based human activity recognition (HAR) has been a research focus in the field of ubiquitous and mobile computing for years. In recent years, many deep models have been applied to HAR problems. However, deep learning methods typically require a large amount of data for models to generalize well. Significant variances caused by different participants or diverse sensor devices limit the direct application of a pre-trained model to a subject or device that has not been seen before. To address these problems, we present an invariant feature learning framework (IFLF) that extracts common information shared across subjects and devices. IFLF incorporates two learning paradigms: 1) meta-learning to capture robust features across seen domains and adapt to an unseen one with similarity-based data selection; 2) multi-task learning to deal with data shortage and enhance overall performance via knowledge sharing among different subjects. Experiments demonstrated that IFLF is effective in handling both subject and device diversion across popular open datasets and an in-house dataset. It outperforms a baseline model of up to 40% in test accuracy.
Comparison of Result Clustering Study Case Posyandu With The Scalable K Means ++ Clustering Method

Application of data grouping aims to group data unsupervised, in this study comparing the results of the grouping with the K mean clustering method, K Means ++ clustering method and the Scalable K Means ++ clustering method. Based on the test results by analyzing the iteration error value, the results of the analysis show that the K Means ++ clustering and Scalable K Means ++ clustering method will produce less error values when compared to the K Means Clustering method. The data used as the basis of analysis in this study is based on data from Posyandu Rajawali Singosari in Malang. The initial initialization value of the centroid can be determined or randomly and is very influential for the data grouping process. Calculation analysis program used scilab programming and the error results with the graph of the minimum value. Result in test data, error value test data 1 get Scalable K Means ++ clustering error minimum 0,07, test data 2 get error value minimum K Means ++ Clustering 0,15, test data 3 get error value minimum 0,005 at metode Scalable K Means Clustering, test data 4 get error value minimum 0,15 at K Means ++ Clustering.
Adaptive Neural Layer for Global Filtering in Computer Vision

This study is motivated by typical images taken during ultrasonic examinations in the clinic. Their grainy appearance, low resolution, and poor contrast demand an eye of a very qualified expert to discern patterns and to spot pathologies. Automating any computer vision task on such data always involves excessive pre-processing and batch filtering, with an accumulation of the error emerging due to the annotation uncertainty, the digital post-filtering artifacts, and the amplified noise. Each patient case generally requires an individually tuned frequency filter to obtain optimal image contrast and to yield the desired outcome in a given computer vision problem. Thus, we aspired to invent a universal adaptive neural layer to learn optimal frequency filter for each image together with the weights of the network itself. The proposed approach takes the source image in the spatial domain, automatically selects the necessary frequencies from the frequency domain, and transmits the inverse-transform image to the main convolutional neural network. Remarkably, such a simple add-on layer can dramatically improve the performance of the main neural network regardless of its architecture. We observe that the light networks gain a noticeable boost in the performance metrics; whereas, the training of the heavy ones starts to converge faster when our adaptive layer is allowed to 'learn' alongside the main architecture. We validate the idea in four classical computer vision tasks: classification, segmentation, denoising, and erasing, considering popular natural and medical datasets.
Application of Computer Technology in Ocean Ecosystems Plankton Classification

Hui, Z.; Wei, R.; Feng, Y.; Zang, Y.; Gao, F.; Liu, M., and Li, Y., 2020. Application of computer technology in ocean ecosystems plankton classification. In: Liu, X. and Zhao, L. (eds.), Today's Modern Coastal Society: Technical and Sociological Aspects of Coastal Research. Journal of Coastal Research, Special Issue No. 111, pp. 352–355. Coconut Creek (Florida), ISSN 0749-0208.Plankton marine biology is a biological term that refers to the living species in the ocean, including marine animals, marine plants, microorganisms, and viruses, among which marine animals include invertebrates and vertebrates. According to the research of on-site data, we could apply algorithms on marine biology. First, perform factor analysis on the multispectral reflectance data of the South Yellow Sea to solve the characteristic problem of the reflectance covariance matrix, solve the eigenvalues and corresponding eigenvectors, find the main factors, and then establish the multivariate linearity of the chlorophyll a concentration versus the main factors regression equation, and return and forecast test of the algorithm. The calculation results show that the algorithm has high accuracy, and it also shows that weather conditions have a greater impact on the estimation accuracy.
ANALISIS KESALAHAN PENULISAN汉字 (HANZI) DALAM PEMBELAJARAN BAHASA MANDARIN SISWA KELAS VIII SMP ISLAM ATHIRAH II MAKASSAR

Abstract. This research aims to classify the types of errors made by the 8th grade students of Athirah Islamic Middle School II Makassar in writing 汉字 (Hànzì) of Mandarin language. The type of this research is descriptive quantitative which collecting the data by doing a writing in汉字 (Hànzì) tests and questionnaires. The analysis method used is the error analysis method by Tarigan (2013). The population of this research is all the students of 8th grade in Athirah Islamic Middle School II Makassar who chose Mandarin as an optional subject totaling 15 of students which is as the total sample. The results of data analysis showed that the writing error of 汉字 (Hànzì) was at the frequency of 96 or 64% and 13 or 13.57% as the highest errors for the character 年 (nián) which means "year" with at the frequency of 1 or 1.04% as the lowest error for the character 三 (sān) which means “three” and 人 (rén) which means “person”, also at the frequency of 0% as no writing errors were found for the character 二 (èr) which means "two". In filling out the questionnaire, there were 7 students or 46.67% which stated that it was difficult to learn Mandarin and 11 or 73.33% which stated that they rarely learn 壁画 (Bǐhuà) 笔顺 (Bǐshùn) in writing 汉字 (Hànzì).
Environmental impact of alum shale mining and oil and uranium production in Kvarntorp, Sweden, based on historical archives and environmental monitoring data

Oil production (1942Oil production ( -1966) ) and uranium extraction (1953)(1954)(1955)(1956)(1957)(1958)(1959)(1960)(1961) from the Alum Shale Formation in Kvarntorp, Sweden has had a great environmental impact on the area.Other industrial activities have also contributed to pollution.This study combines archive research with monitoring data and new sampling in order to assess the extent of the impact.During the production period, process water containing oil, phenols, sulfur compounds and high concentrations of iron reached the stream resulting in low water quality downstream.Also the landscape was reshaped, resulting in water filled pit lakes and a 100-meter-high shale waste deposit.Today, past alum shale activities still have an impact on the environment.Sulfate concentrations in the pit lakes are significantly higher than background values and downstream water also shows higher concentrations of elements such as nickel and uranium.The waste deposit still has a hot interior and an important question is the cooling rate and possible future leaching scenarios.Remaining hydrocarbons show today only a local impact while trace elements are transported downstream and affect a larger area.
Joint Optimization of an Autoencoder for Clustering and Embedding

Deep embedded clustering has become a dominating approach to unsupervised categorization of objects with deep neural networks. The optimization of the most popular methods alternates between the training of a deep autoencoder and a k-means clustering of the autoencoder's embedding. The diachronic setting, however, prevents the former to benefit from valuable information acquired by the latter. In this paper, we present an alternative where the autoencoder and the clustering are learned simultaneously. This is achieved by providing novel theoretical insight, where we show that the objective function of a certain class of Gaussian mixture models (GMMs) can naturally be rephrased as the loss function of a one-hidden layer autoencoder thus inheriting the built-in clustering capabilities of the GMM. That simple neural network, referred to as the clustering module, can be integrated into a deep autoencoder resulting in a deep clustering model able to jointly learn a clustering and an embedding. Experiments confirm the equivalence between the clustering module and Gaussian mixture models. Further evaluations affirm the empirical relevance of our deep architecture as it outperforms related baselines on several data sets.