Reviewerly/exHarmony huggingface dataset:
PENGGUNAAN TEKNOLOGI INFORMASI DALAM PELAYANAN SIRKULASI DI PERPUSTAKAAN

Libraries are services, so there is no library without services.The service here means the user of library services. This kind of work activity is often referred to as circulation,which implies circulating library collections to users. In library science, circulation is often known as borrowing. However, the notion of circulation services actually includes all forms of recording activities related to utilization, the use of library collections quickly and timely for the benefit of users of library services. The purpose of the library to provide services to the readers is so that library materials that have been collected and processed as well as possible can reach the readers.The existence of information technology is clearly that there is a part of work that can be facilitated with help or technology. This activity is called library automation. The use of information technology can provide easy access for users and improve library services. One of them is circulation service that uses the OPAC system. OPAC is an acronym for online catalog access for the public. Users can access remotely via the web or LAN or directly through a computer that is provided specifically for online catalogs in a library.
Classifiers in Molsom

There is no work done so far on the classifiers in Molsom. This paper attempts to do so. Crosslinguistically eight classifiers are attested. Of these only the numeral classifiers are used Molsom. Numeral classifiers are used for indicating the semantic classes of concrete nouns in the context of counting. Abstract nouns do not take any classifiers as they defy quantification. The numeral classifier immediately follows the head noun in a noun phrase: [[N] CL Num]NP. A numeral classifier consists of two distinct words which must stay together. In other words, being independent words, they do not get attached to the noun within the noun phrase. Molsom has separate sets of numeral classifiers for count nouns and mass nouns. An exceptional numeral classifier called a repeater is also noticed in the language.
MD-Manifold: A Medical Distance Based Manifold Learning Approach for Heart Failure Readmission Prediction

Dimension reduction is considered as a necessary technique in Electronic Healthcare Records (EHR) data processing.However, no existing work addresses both of the two points: 1) generating low-dimensional representations for each patient visit; and 2) taking advantage of the well-organized medical concept structure as the domain knowledge.Hence, we propose a new framework to generate lowdimensional representations for medical data records by combining the concept-structure based distance with manifold learning.To demonstrate the efficacy, we generated low-dimensional representations for hospital visits of heart failure patients, which was further used for a 30-day readmission prediction.The experiments showed a great potential of the proposed representations (AUC = 60.7%) that has comparative predictive power of the state-of-the-art methods, including one hot encoding representations (AUC = 60.1%) and PCA representations (AUC = 58.3%),with much less training time (improved by 99%).The proposed framework can also be generalized to various healthcare-related prediction tasks, such as mortality prediction.
Prediksi Bayi Lahir Secara Prematur Dengan Menggunakan Metode C.45 Berbasis Particle Swarm Optimization Pada Klinik Umi

Abstract - Babies born prematurely can occur when the pregnancy has not reached the mature gestational age. Pregnancy usually lasts about 40 weeks. Some risk factors for preterm birth include having given birth to a premature baby before and becoming pregnant with twins. The complications associated with preterm birth include immature lungs, difficulty regulating body temperature, difficulty eating, and slow weight gain. Premature babies can require longer or more intense nursery care, medication, and sometimes surgery. Until now, there have been several cases of preterm labor that have no known cause. There are a number of factors and health problems that can trigger premature labor, which are unhealthy mothers, smoking, a history of pregnancy, fetal conditions, psychological conditions. For this reason, the author intends to make a study on how to predict a patient who will deliver prematurely. In this study C4.5 algorithm model and C4.5 algorithm model based on particle swarm optimization are used to get the rule in predicting premature births of babies and provide accuracy values. more accurate. After testing with two models, namely C4.5 Algorithm and C4.5 Algorithm based on particle swarm optimization, the results obtained are C4.5 Algorithm produces an accuracy value of 94.30% and AUC value of 0.986 with a diagnosis level of Excellent Classification, but after The addition is C4.5 algorithm based on particle swarm optimization, the accuracy value is 97.91% and the AUC value is 0.997 with the diagnosis level of Excellent Classification. So that both methods have different levels of accuracy which is equal to 3.61%.Keywords: gestational age, premature, C4.5 algorithm
BLOCKCHAIN AS A SOCIAL REVOLUTION: FOCUSING ON THE THREATS

The paper discusses the benefits and threats provided by the blockchain technology and focuses on those which are the flipside of its advantages. Potential threats related to creating and using digital identity, control over personal information and erosion of responsibility justify the claim that we are dealing not just with a technological but a social revolution impacting key social relationships.
PELESTARIAN BAHAN PUSTAKA DAN ARSIP (Sebuah Upaya Dalam Merawat dan Menjaga Bahan Perpustakaan)

Abstract: The professionalism of a librarian and the challenges in the era of the industrial revolution 4.0, which in this era really demands the skills of a librarian in utilizing the sophistication of existing technology. Also, being able to minimize risks and face the challenges posed by this era of the industrial revolution 4.0 - so that the functions and objectives of the library can be achieved. Keyword: Librarian Professionalism, Industrial Revolution Era 4.0 Abstrak: Profesionalitas seorang pustakawan dan tantangannya pada era revolusi industri 4.0 yang mana era ini sangat menuntut kemahiran seorang pustakawan dalam memanfaatkan kecanggihan teknologi yang ada. Serta, mampu meminimalisir resiko dan menghadapi tantangan yang dimunculkan oleh era revolusi industri 4.0 ini—sehingga fungsi dan tujuan perpustakaan dapat tercapai. Kata Kunci : Profesionalitas Pustakawan, Era Revolusi Industri 4.0
Anonymity – Print/e-Book Bundle

"Anonymity – Print/e-Book Bundle." Journal of Electronic Resources in Medical Libraries, 18(1), pp. 74–75
BiDETS: Binary Differential Evolutionary based Text Summarization

In extraction-based automatic text summarization (ATS) applications, feature scoring is the cornerstone of the summarization process since it is used for selecting the candidate summary sentences.Handling all features equally leads to generating disqualified summaries.Feature Weighting (FW) is an important approach used to weight the scores of the features based on their presence importance in the current context.Therefore, some of the ATS researchers have proposed evolutionary-based machine learning methods, such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), to extract superior weights to their assigned features.Then the extracted weights are used to tune the scored-features in order to generate a high qualified summary.In this paper, the Differential Evolution (DE) algorithm was proposed to act as a feature weighting machine learning method for extraction-based ATS problems.In addition to enabling the DE to represent and control the assigned features in binary dimension space, it was modulated into a binary coded format.Simple mathematical calculation features have been selected from various literature and employed in this study.The sentences in the documents are first clustered according to a multi-objective clustering concept.DE approach simultaneously optimizes two objective functions, which are compactness measuring and separating the sentence clusters based on these objectives.In order to automatically detect a number of sentence clusters contained in a document, representative sentences from various clusters are chosen with certain sentence scoring features to produce the summary.The method was tested and trained using DUC2002 dataset to learn the weight of each feature.To create comparative and competitive findings, the proposed DE method was compared with evolutionary methods: PSO and GA.The DE was also compared against the best and worst systems benchmark in DUC 2002.The performance of the BiDETS model is scored with 49% similar to human performance (52%) in ROUGE-1; 26% which is over the human performance (23%) using ROUGE-2; and lastly 45% similar to human performance (48%) using ROUGE-L.These results showed that the proposed method outperformed all other methods in terms of F-measure using the ROUGE evaluation tool.
The Effect of Online Game Addiction on Adjustment Social in Adolescents

Technology is currently developing rapidly, one of which is online games. Excessive online game play can give teens a lot of trouble. The purpose of this study was to determine the effect of online game addiction on social adjustment. The populations in this study were adolescents in Kampung Dalam. The technique used is purposive so that the research sample is obtained as many as 23 adolescents in the inner village. The data collection method uses a questionnaire which will later be analyzed by SPSS. The results showed the value of r = 0.586 with a significance of 0.03 (p <0.05), which means that there is a negative influence between online game addiction and adolescent social adjustment. Keywords:  online game addiction, social adjustment, adolescents
Perancangan Aplikasi Sistem Informasi Akuntansi Persediaan Barang Menggunakan Microsoft Access 2016 (Studi Kasus Toko Villi Bandung)

Toko Villi is a trading business unit engaged in the food sector with snacks as their main product. The Villi shop sells snacks with dozens of types, and each type has a very large number from tens to hundreds of units. However, in its business activities, Toko Villi does not keep records of the goods they have. The Villi shop does not perform data processing and only relies on documents such as sales and purchase invoices as the basis for the entry and exit of goods. Based on the problems faced by these companies, the authors designed an inventory accounting information system application that will assist the company in running its business. This research is a qualitative research with a case study and development approach. The data analysis tool used in designing this application is the waterfall model SDLC (Software Development Life Cycle). This inventory application is designed using Microsoft Access 2016 and is tailored to the needs and desires of the company. This design is expected to meet the company's needs for information such as stock of goods, transaction reports of incoming and outgoing goods and reports of out of stock goods.
Цифровые иммерсивные среды в искусстве: новый антропологический регистр

Digital immersive environments are a kind of a new anthropological register in contemporary visual culture. Artists seek to move away from the traditional formats of presenting artistic content referring to the divided channels of influence designed only for sight and hearing. Immersive practices actively develop the creation of a total immersion environment. Artists work with the body and the psychoemotional state of the recipient forming a multi-sensory artistic environment.Visual and auditive impressions are supported by tactile, kinaesthetic experience, creating a new anthropological register of total inclusion in the perception of a work of art. In itself, the creation of immersive environments is not new. At all stages of the development of the artistic language, attempts were made to develop an instrument for a comprehensive impact on all the senses of a man.This can be seen in ancient mysteries, theatrical cultic rituals, carnival culture, temple architecture, and art.The most obvious break with such syntheses is observed in the era of rationalism, when each of the arts seeks and acquires its own independent language responsible for a certain channel of perception. Active attempts to return to the total synthesis of the impact on all senses have been undertaken again with the emergence of modernism, they can be found in the era of modernity, avant-garde, and, not least, in the synesthesia practices of the German expressionists and the French theatre of cruelty. In the neo-avant-garde era, these experiments begin to be widely conducted in happening, performance and total installation. The novelty of the present moment is the emergence of digital technologies as an artistic resource and a basis for creating immersive environments. In modern art, the effect of immersion is increasingly achieved not through architectural solutions or sound and light discoveries of temple synthesis, not at the expense of the physical creation of total media as it was in the “large installations” of the 90s‑2000s, but due to a digital illusion submerging man in the ghost world of a digital biosensor environment. Immersion is achieved through digital architecture affecting all senses and actively involving the body of the viewer in the process of experiencing an artistic event. In full, these experiments are manifested in the activities of “team Lab” and “imaginarium studios UK”.
Social Distance Detection

Social distancing is a recommended solution by the World Health Organisation (WHO) to minimise the spread of COVID-19 in public places. The majority of governments and national health authorities have set the 2-m physical distancing as a mandatory safety measure in shopping centres, schools and other covered areas. In this research, we develop a hybrid Computer Vision and YOLOv4-based Deep Neural Network (DNN) model for automated people detection in the crowd in indoor and outdoor environments using common CCTV security cameras.
Civilizational Pedagogical Systems - Intellectualization Of Educational Content As A Didactic Basis

This article considers the development of an organizational-structural model for the formation of civilized pedagogical systems. This article will be used by those who are concerned with improving future teacher training.
The Role of Extracurricular Activities in an Educational Process

This article will take into consideration the role and importance of extracurricular activities in methodical points of view giving reliable types and examples of such extra works.
Analisis Penerapan Algoritma C4.5 Dalam Mengukur Tingkat Kepuasan Pelanggan Indihome Pada Kota Pematangsiantar

The purpose of this study was to study the level of customer satisfaction with Indihome services in Pematangsiantar City by using the C4.5 Algorithm. The source of the data used in the study is to conduct observations and interviews by distributing questionnaires to Indihome customers in Pematangsiantar City. The results of this study are expected to be able to determine Indihome customer satisfaction so that service levels are in accordance with the provisions of the indicator.
The Proyeksi Permintaan Suplai Energi Listrik Tahun 2018-2038 di Provinsi Papua:

In the modern era, it will be very difficult for humans to carry out activities without the presence of electrical energy. This is due to the fact that most of the current human needs are based on the use of electronic instruments and machines that require electrical power as their main source of energy. In addition, the availability of electricity is one of the important parameters for the progress, growth and development of an area in the economic, industrial, public service, commercial sectors and even improve the quality of life of it’s people. So that electrical energy planning is needed to overcome and provide solutions to electrical energy problems. This research uses LEAP (Long-Range Energy Alternative Planning Systems) software with the DKL 3.2 approach model to calculate the projected electricity supply needs in Papua province in 2018-2038. From the calculation results of the projection using the DKL 3.2 method for the needs and customers of electricity in 2018-2038, the demand for electricity in the household, industrial, business, and public sectors grew by 12.66%, 16.43%, 5.87 % and 9.78%. As for the projected number of electricity customers in the same sector, customer growth was 6.42%, 4.50%, 3.40% and 6.42%. The results of this study indicate an increase in energy demand in all customer sectors.Keywords : projection, electrical energy, DKL 3.2 metdod, LEAP
국내 대학 특허가 기술사업화 연구 생산성에 미치는 영향에 관한 연구

R&D investments in Korea amounted to 87.1 trillion won as of 2018, while government funded R&D investments continued to grow and reach 18.3 trillion won, about 21.4% of the total R&D budget in 2018, 20.5 trillion won in 2019, 24.1 trillion won and a sustained increase on a yearly basis. The ratio of R&D to gross domestic product (GDP) is 4.81%, ranking first in the world. As of 2018, a total of 6.1 trillion won, an increase of 14.2% compared to 2014 with an option of 5.4 trillion won, which is 88.7%, invested in science and technology.On the other hand, despite such a large amount of R&D investment, the success rate of commercialization in terms of performance was 20%, lower than 70.7% in the United Kingdom, 69.3% in the United States, and 54.1% in Japan. In terms of aspect, the situation is still low, and the issue of efficiency improvement for domestic public sector R&D investment has been continuously raised.In the related research, there were mainly researches that analyzed research productivity in terms of university input variables and patent-based research models, but among the main factors constituting the primary result of R&D patents, patents Few studies have analyzed the factors affecting strength and correlated with research productivity through technology commercialization, which is a R&D result and performance.According to this research, Hypothesis 1''s increase in R&D research cost has a positive effect on technology transfer income. However, the hypothesis that an increase in R&D research costs would have a direct impact on university R&D productivity was rejected. For this reason, it is analyzed that universities in Korea still treat papers as important research achievements rather than technology transfer. Hypothesis 2 is an analysis on whether the increase in university R&D expenses is related to patents, which are qualitative results of research. As a result of hypothesis verification, it was found that an increase in R&D research expenses in universities affects the quality of patents. Hypothesis 3 analyzes the effect of the quality of university patents on research productivity. As a result of the analysis, it was analyzed that the high level of quality of university patents did not increase the research productivity. As mentioned above, it is analyzed that papers is still recognized as a more important research output than patents or technology transfer for Korean universities.Therefore, this study empirically analyzes the correlation between cumulative R&D expenses and primary and secondary outcomes from a technology commercialization performance perspective through cross-sectional analysis, big data analysis tools, and statistical methods to analyze research expenses, patent characteristics, and technology transfer fees at a specific point in time. By doing so, there will be significance as a theoretical and policy research to improve the research productivity of R&D and the efficiency of government R&D investment.
Developing a Framework for the Implementation of Evidence Collection System: Focusing on the Evaluation of Information Security Management in South Korea

Recently, as evaluation of information security (IS) management become more diverse and complicated, the contents and procedure of the evidence to prepare for actual assessment are rapidly increasing. As a result, the actual assessment is a burden for both evaluation agencies and institutions receiving assessments. However, most of them reflect the evaluation system used by foreign government agencies, standard organizations, and commercial companies. It is necessary to consider the evaluation system suitable for the domestic environment instead of reflecting the overseas evaluation system as it is. The purpose of this study is as follows. First, we will present the problems of the existing information security assessment system and the improvement direction of the information security assessment system through analysis of existing information security assessment system. Second, it analyzes the technical guidance for information security testing and assessment and the evaluation of information security management in the Special Publication 800-115 'Technical Guide to Information Security Testing and Assessment' of the National Institute of Standards and Technology (NIST). Third, we will build a framework to implement the evidence collection system and present a system implementation method for the ‘6. Information System Security’ of ‘information security management actual condition evaluation index’. The implications of the framework development through this study are as follows. It can be expected that the security status of the enterprises will be improved by constructing the evidence collection system that can collect the collected evidence from the existing situation assessment. In addition, it is possible to systematically assess the actual status of information security through the establishment of the evidence collection system and to improve the efficiency of the evaluation. Therefore, the management system for evaluating the actual situation can reduce the work burden and improve the efficiency of evaluation.
Transferable Unsupervised Robust Representation Learning

Robustness is an important, and yet, under-explored aspect of unsupervised representation learning, which has seen a lot of recent developments. In this work, we address this gap by developing a novel framework: Unsupervised Robust Representation Learning (URRL), which combines unsupervised representation learning's pretext task and robust supervised learning (e.g., AugMix). Moreover, it is commonly assumed that there needs to be a trade-off between natural accuracy (on clean data) and robust accuracy (on corrupted data). We upend this view and show that URRL improves both the natural accuracy of unsupervised representation learning and its robustness to corruptions and adversarial noise. A further challenge is that the robustness of a representation might not be preserved in the transfer learning process after fine-tuning on downstream tasks. We develop transferable robustness by proposing a task-agnostic similarity regularization during the fine-tuning process. We show that this improves the robustness of the resulting model without the need for any adversarial training or further data augmentation during fine-tuning.