Reviewerly/exHarmony huggingface dataset:
Учёный – новатор, талантливый педагог, творческая личность (К 85-летию А. В. Соколова)

Professor Arkady Sokolov, Ph. D. (Pedagogy) is a prominent scholar. The author highlights themes and publications unique for Sokolov: the future for libraries, library science and bibliography, humanism, intelligencia and library intellectuals, social informatics, social communications, philosophy of information. In his works, prof. Sokolov gives his special attention to the library profession, librarians, library education, the libraries on the whole. “Retrospektiva…” digest are A. Sokolov’s special project. The author also reflects on Sokolov’s innovative academic social initiatives: in 1967-1984 he headed the first in the nation informatics chair In Leningrad State Institute of Culture; founded St. Peterburg library society, the first one inRussia. The Professor’s giant flock numbers 44 scientists. Sokolov’s biographical information is given; the journals where he is an editorial board member are named; disciplines in which he delivers lectures; his titles are named. Arkady Sokolov’s outstanding personality is also depicted. In conclusion, the main bibliography (56 titles) is given.
Navigation with Multi-obstacle Avoidance Composed of Stochastic Optimal Controllers

Avoiding collisions with obstacles is of fundamental importance for the safe navigation of unmanned aerial vehicles (UAVs) and mobile robots. In this paper, we approach the avoidance problem by composing a scalable navigation strategy from multiple stochastic optimal controllers. We consider a scenario with a fixed speed Dubins vehicle, which is tasked to reach a waypoint while avoiding collisions with multiple moving obstacles. Obstacle moving directions are unknown, therefore, we use a random walk stochastic process model to anticipate that uncertainty in the design of navigation feedback control. The proposed navigation is based on a composition of minimum time stochastic optimal controllers. Each optimal controller is the solution to a minimum time problem to reach either the waypoint or a safe configuration with respect to an obstacle. The composition is based on the controller value functions and is scalable, i.e., it can deal with any number of obstacles. Our results are illustrated with a numerical simulation.
An Improved Image Inpainting Method Based on Patch Matching and Texture Synthesis

Compared with the pixel based image restoration algorithm, the digital image restoration algorithm based on sample blocks is more effective for the restoration of texture and structure information in large area damaged images. The key technology is to determine the repair order. In this paper, an improved priority value calculation method is proposed. The experimental results show that the improved method can further improve the repair order of the region to be repaired and fill the missing part of the image with the matching block in the improved order on the basis of the original algorithm. The unreasonable extension phenomenon is reduced, and the texture and structure information are more accurately distinguished, which makes the inpainting effect more coherent in vision.
Implication Of Data Mining Techniques Towards Image Segmentation And Classification

Image enhancement and image segmentation are highly researched topics of Digital Image Processing (DIP).In image segmentation the image analysis is done in various steps and has important role in digital image processing.The fundamental methods and step required to segment the image for gathering information about image using image segmentation will be studied in this work.The most important method for analyzing image is segmentation.In this research work various methods for segmentation will be studied such as-edge detection method, thresholding method, region growing method, clustering method.Similarity and discontinuity are the most important properties of image segmentation algorithm.In the present time the highly growing area in the field of data mining and in the computer vision is image classification.The main purpose of the image classification is to remove space between pixels in the image.
Perancangan Aplikasi Sistem Pakar Diagnosa Kerusakan Lift Dengan Menggunakan Metode Case Based Reasoning (CBR)

The elevator requires maintenance to make it work optimally, if the elevator does not work optimally then there will be damage that can result in users who are in the elevator could be trapped due to a jammed door and not open. Elevator damage like this needs to be put on the expert system in order to shorten the analysis time by using the Case Based Reasoning method. Case Based Reasoning is a method of solving problems by utilizing previous experience. Case Based Reasoning is one method of solving problems in finding solutions for a new case to an old case solution that has the same problem. To diagnose damage to the elevator using the Case Based Reasoning method. Users will be given questions to get the similarity value with the Case Based Reasoning formula, so that the diagnostic results and the percentage of similarity values and their probability are obtained.
Fiori in S/4HANA

In early 2007, the first-generation iPhone was launched by Apple with much fanfare. Who would have thought that over the intervening years, the smartphone market would explode and we would be able to order groceries from the comfort of our homes? Whole marketplaces have moved to online and you can pretty much do business on the phone. As consumers moved toward slick UIs offered by a multitude of mobile apps at a much faster pace, enterprise applications such as monolith ERPs took much longer to adapt.
How to Achieve a Seasoned Cybersecurity Workforce

There is a severe shortage of cybersecurity workers in the U.S., which puts the country’s digital privacy and infrastructure at risk. A big problem is finding qualified people to fill these jobs. This article suggests a range of options to help organiza..
Adaptive Master-Slave Cubature Kalman Filters subject to State Inequality Constraints for Wind Turbine State Estimation

The cubature Kalman filter (CKF) is well-known for a decade as a derivative-free nonlinear Kalman filter that is well-suited for high-dimensional nonlinear estimation problems. This paper further develops this classical CKF in order to cope with time-varying noise statistics as well as inequality constraints on the estimated states. The resulting adaptive filter is suggested to provide more accurate state estimates and to be more robust against filter divergence. Moreover, this contribution proposes an automated filter design based on numerical optimization which uses the normalized estimation error squared (NEES) and the normalized innovation squared (NIS) as part of the objective function. The novel adaptive CKF is applied to wind turbines in order to assess the potential improvement for state and parameter estimation. The simulation results for an illustrative acid test scenario with time-varying measurement noise show the superiority of the novel adaptive CKF since it compensates the noise robustly and thereby outperforms the classical filter.
A Study on Job Analysis for Conceptualizing of IP-R&amp;D Competencies

이 연구는 지식재산 기반의 R&D 전략 수립 업무를 수행하는 IP-R&D 직무분석을 통해 IP-R&D 능력을 개념화하고자 하였다. 연구 방법은 FGI와 전문가 협의회를 활용한 최초분석법으로 직무분석을 수행 하였고, 이를 통한 구체적인 연구 결론은 다음과 같다. 첫째, IP-R&D 직무는 “R&D 투자 성과와 조직의 성과 극대화를 위해 과제 발굴, 기획, 수행, 평가 등 R&D 전 주기에 걸쳐 가치 있는 IP 창출 활용 전략 수립을 수행하는 직무”로 정의하였다. 둘째, IP-R&D 직무는 10개 임무와 27개 작업으로 도출되었고, 중요도·난이도·빈도 현황을 분석한 결과, ‘후보기술 선정하기(AAA), 유효데이터 추출 및 요지리스트 작성하기(AAA), 핵심특허 도출하기(AAA), 침해여부 분석 및 회피 설계 전략 수립하기(AAA), 대응전략을 통해 신규 IP 만들기(AAA), 특허 분석프레임 작성하기(ABA), 특허 검색하기(ABA), 경쟁사/기술 도출하기(ABA), 기술개발방향 도출하기(AAB)’로 9개 작업이 핵심적인 업무로 분석되었다. 셋째, IP-R&D 직무의 관련 지식, 기능을 분석한 결과, R&D 방향 제시 능력, 지식재산 확보 전략 수립 능력, 지식재산 관리&#8228;활용 전략 수립 능력 3가지를 IP-R&D 능력 이라고 정의할 수 있다. 마지막으로 이 연구는 IP-R&D 능력을 개념화하고 해당 직무에 대한 표준을 확인하여 인력 양성을 위한 교육과 관련한 요구조사, 교육훈련 프로그램 개발 등 IP-R&D 인력 양성의 인프라 구축에 기초 자료를 제공했다는 점에서 그 의의가 있다.This research is to conceptualize the IP-R&D skill through the IP-R&D job analysis that realizes the work of establishing the R&D strategy based on the intellectual property. The research method analyzed the job as the first analysis method that used both FGI and conference, with the following research conclusion. First, IP-R&D job was defined as “the job that creates valuable IP and that establishes the strategy of application over the whole R&D cycle such as task excavation, planning, performance, evaluation to maximize the R&D investment performance and organizational performance”. Second, IP-R&D job was deduced with 10 duties and 27 tasks, and as a result of analyzing the importance, difficulty and frequency state, the 9 works such as ‘1)selecting the candidate technology(AAA), 2)extracting the valid data and preparing substance list(AAA), 3)deducing the core patent(AAA), 4)analyzing the possible invasion and establishing the avoidance design strategy(AAA), 5)creating new IP through the counter strategy(AAA), 6)preparing the patent analysis frame(ABA), 7)searching the patent(ABA), 8)deducing the competitor/technology(ABA), 9)deducing the technological development direction(AAB) were shown as core works. Third, as the result of analyzing the related knowledge and function of IP-R&D job, the 3 competencies including the competence of presenting the R&D direction, the competence of establishing the intellectual property assuring strategy, the competence of establishing the intellectual property management and use strategy can be defined as the IP-R&D competencies. Finally, this research has its meaning in that it had conceptualized the IP-R&D skill, confirmed the standard of the corresponding job and provided the basic data for constructing the infrastructure of forming the IP-R&D personnels such as the survey of education related needs and the development of educational training program.
Optimizing Error Function of Backpropagation Neural Network

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Performance Evaluation of MOA vs KNN Classification Schemes Case Study of Major Cities in the World

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
HOW EFFECTIVE IS SIMULATION-BASED EDUCATION FOR IMPROVING THE NURSES’ KNOWLEDGE ON PEDIATRIC IV INSERTION: A SYNTHESIS FROM AWAL BROS HOSPITAL GROUP IN INDONESIA

Background: Simulation-based nursing education has been growing rapidly and becomes one of the most popular teaching methods for improving patient safety and patient care. One of the difficult Nursing skills to achieve is IV insertion. Due to the high complaints in the number of IV insertion attempts in the paediatric patients, the Nursing Corporate of Awal Bros Hospital Group organized an educational program emphasizing the team training, clinical decision- making and communication skills. These were the first internal education sessions using live rabbits and mannequins. This study aimed to evaluate the attitude of the participants, the self- confidence level and their change in the knowledge on clinical performance in Paediatric IV Insertion after attending the educational program. Methods: The training and education sessions were conducted at Awal Bros Hospitals in Bekasi Barat and Tangerang during March and April 2019. The participants included a total of 52 Nurses. Pre- and Post-tests consisting of 20 multiple choice questions were administered to the participant before and after the 3-day simulation-based training workshop in Bekasi Barat and after the 2-day simulation- based training workshop in Tangerang. The workshop also utilized rabbits for the participants to practice their hands-on skills. Results: A total of 52 Nurses working in different Nursing units were enrolled. The mean pre-test and post-test scores were 43.81 and 87.52 respectively. In the Statistics Test table, the value of Asymp. Sig (2-tailed) was 0,000. Because the value of sig 0,000 < 0.05 was according to the statistical tests we used, then there are significant differences between before training and after training. Conclusions: Participants had positive attitude toward this new training program. They stated that this techni que was more exciting and effective compared to the “traditional” techniques such as lecture, power point presentations or Q&A that they attended. Significant improvement of the knowledge on clinical performance in Nurses participating in these training and education session was observed after the participation in this simulation-based educational program. Many expressed their higher self- confidence in doing IV insertion to the future patients, especially babies and children. More simulation- based education using pre- and post-tests are recommended.
Trust-Driven Privacy in Human-Robot Interactions

In this paper we present a trust-driven differential privacy implementation for private trajectory sharing in human-robot interactions. While differential privacy implementations depend on a privacy parameter that is typically set before runtime, there are a number of applications in which human users may not have any information about their robot interaction partners a priori, making it difficult to determine a reasonable privacy level for information sharing. To enable collaboration in scenarios with unfamiliar robots, we dynamically adapt a human user's privacy level when sending information to a robot by using a quantitative measure of trust. We develop a trust model that reflects a robot's level of cooperation over time and captures key features of trust from both the psychological and human-robot interaction communities. To characterize our framework and its performance, we quantify the amount of information a robot can gain as a function of its cooperation, and we present bounds on the level of cooperation needed to attain a desired level of trust (and therefore privacy) over time. Simulation results are provided to illustrate this trust-driven private information sharing scheme.
A Data Correlation Algorithm Based on Resnet for Unsteady Data

A data correlation algorithm based on Resnet for unsteady data was designed in this paper. Traditional data correlation algorithms, such as joint probabilistic data association algorithm (JPDA) and k-nearest neighbor correlation algorithm (KNN), require to satisfy the conditions that data error distribution is approximately stable or stable, and have a significant performance degradation under unsteady data conditions. Resnet was used to extract multi-level and heterogeneous features to solve the optimal decision function in correlation algorithm problem. First, the global correlation problem was decomposed into the basic correlation problem with fixed problem space size. Then, the deep network was designed to extract the invariant features of the unsteady data and find the classification model of the solution of the basic correlation problem. In this way, the correlation robustness and accuracy can be improved when the error distribution changes and the parameters cannot be accurately estimated. The simulation results show that the algorithm designed in this paper is effective. When the error distribution changes within a certain range and under unknown conditions, it is better than JPDA and k-nearest neighbor algorithm.
EVALUASI USER INTERFACE PADA APLIKASI E-COMMERCE (STUDI KASUS INFORMA DAN IKEA)

ABSTRACT Increasingly complex human needs cause changes in the community environment. This is indicated by the increasingly rapid development of information technology, especially information technology related to online shopping applications through e-commerce applications. The development of technology that is currently being talked about and is the subject of discussion is to develop technology towards modern business by using mobile-based e-commerce applications. Anywhere and anytime quickly and in real time, people can easily make purchases of any product related to the needs of the house they are looking for. The results of this study were to determine the magnitude of the heuristic value of the quality of the mobile e-commerce application user interface Informa and Ikea according to users using the Nielsen 10 principle method. It is expected that the results of this study can be used as input for e-commerce mobile application developers Informa and Ikea to be better, and can be proposed to improve the user interface for e-commerce applications Informa and Ikea. Keywords: E-Commerce, User Interface, 10 Nielsen Principles.
NCHLT Setswana Auxiliary Speech Corpus

The corpus contains orthographically transcribed broadband speech in each of South Africa's eleven official languages. Transcriptions are provided in XML format.
Proposed Algorithm for Creation of Misuse Case Modeling Tree During Security Requirements Elicitation Phase to Quantify Security

Gathering secure measurement is the first step toward the developed of comprehensive secured software. Security is an intangible measure also considered as a non-functional attribute which needs to be quantified in some manner using tools and techniques during the preliminary phases, i.e., the requirements engineering stage of software development process. Studies carried out so far have shown and suggested that among the available techniques of security measurement, misuse use case modeling which is a form of unified modeling approach is very easy to implement during the requirements engineering (RE) phase of SDLC. This research work proposes an algorithm for creation of misuse case modeling tree during the security requirements elicitation phase. This algorithm can be customized according to the specific software application and is supported and synchronized with industry accepted standards like Common Vulnerability Scoring System (CVSS) and Common Vulnerability Enumeration (CVE). The work proposed is an extension of Misuse Case Oriented Quality Requirements (MCOQR) Framework and metrics and includes software application-specific database. The proposed work also showcases the areas where future work can be carried out to further fortify the entire system during the software development process, thereby contributing to the enhancement of various measures of performance.
The Effect of Extrinsic Motivation and Instrinsic Motivation Against Learning Achievements of Food and Beverage Service Student Ak. Mapindo, Academic Year 2018/2019

This study aims to determine the effect of extrinsic motivation and instrinsic motivation on learning achievement students in the Food & Beverage Service Program Study, Akademi Komunitas Manajemen Perhotelan Indonesia academic year 2018/2019. The questionnaire distributed to 57 respondents was all members of the population. This study, using regression analysis techniques by testing hypotheses using t test and F test. The t-test results show that extrinsic motivation has a positive and significant effect on student achievement in the Food & Beverage Service Program Study, Akademi Komunitas Manajemen Perhotelan Indonesia academic year 2018/2019. This is seen from the results of the regression coefficient X1(b1) thitung = 6.977 > ttable (0.05: 54) = 1.6736 and sig t = 0,000 (p ttable (0.05: 54) = 1.6736 and sig t = 0,000 (p F table = 3.17 with sig F = 0,000 (p < 0.05). Other information obtained from the results of the above analysis that extrinsic motivation has a more dominant influence on learning achievement when compared with intrinsic motivationKeywords: Extrinsic Motivation, Intrinsic Motivation, Learning Achievement
Review of Machine Learning Method for Resolving Issues of Big Data Analytics

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
ESTUDIO DE LA LIXIVIACIÓN ÁCIDA A PRESIÓN DE LAS CONCRECIONES FERROMANGANOSAS CON EL USO DE PIRITA COMO REDUCTOR

The present work has as objective to study the acid leaching to pressure of a sample of the Ferro-manganese concretions, using pyre as laboratory scale reducer, establishing the possibility to extract Ni, Co, Cu and Mn. The kinetics of breakup of the metals, the influence of the partial pressure of oxygen and the acid- mineral relationship in the extraction of metals were study. Under the studied conditions the kinetics of breakup of the metals is relatively quick, reaching a high extraction to 60 minutes. An increase of the leaching time up to 120 minutes doesn't produce a significant change in the extraction of the metals. In pyre presence the partial pressure of oxygen influences in the breakup of the metals. Efficiency is reached of: 93% Ni, 90% of Cu, 95% for the Co and Mn to the pressure of 5 bars It was established the possibility of extracting Ni, Co, Cu and Mn of the sample of marine nodules with a high efficiency by means of the acid leaching to pressure, in pyre presence like reducer agent, using the following parameters: Under these conditions are obtained extractions of 93-98% of Ni; and 96-98% of Co, Mn and 90-93% of Cu. The studies of the leached pulp indicated that the same one didn't deposit well, for what additional studies are required to improve the rheological properties of the pulp.