Reviewerly/exHarmony huggingface dataset:
Creating a fault map of the Central-Kamushovy meganticlinorium of the Western Sakhalin mountains by space survey data

The network of fault zones caused by vertical and horizontal tectonic displacements blocks of Earth’s crust relative to each other is clearly visible on the Earth’s surface in images obtained from satellite surveys. Many researchers distinguish linear and annular structures among the faults. Lineaments in satellite images are detected as rectilinear objects with a certain spectral brightness. The initial data for the experimental research includes images from the Landsat-8 satellite and SRTM data. The lineament analysis of satellite images and SRTM data of the Central-Kamyshovy meganticlinorium of the West Sakhalin Mountains was carried out using the functionality of the LEFA software package using the developed decryption technology. The obtained results were processed using the QGIS program tools. Statistical processing of Sakhalin lineaments was carried out on the basis of researching distribution directions of linear segments set of vector strokes data and lineaments data. The map of disjunctive disturbances of the Central-Kamyshovy meganticlinorium of Western Sakhalin Mountains on a scale 1:500 000 was compiled by basis of data obtained. The analysis of SRTM model with the help of LEFA toolkit made it possible to identify zones where discontinuous disturbances of the Earth’s crust are located. As a result of analysis, West Sakhalin fault and many other faults of a rank below 2 were identified. Fault zones are mapped on scale of 1:500 000. It was revealed that 15.3 % of all earthquakes in this area were timed to the Krasnopolsky fault, including in the zone within 1 km from the fault—70 %, 1–2 km—19 %, 2–3 km—9 %, more than 3 km—2 %. The results of work will be useful in choosing places for construction of industrial facilities, as well as for seismic zoning of territory.
Influence of Using Website-Based Learning Media (Math-Learning) on Students' Cognitive Learning Outcomes

The purpose of this study is to describe and test the implementation and influence of the use of website-based defense media on the cognitive learning outcomes of 3rd-grade students at SDN Bakalan Krajan 1, Malang City. This study uses a quasi-experimental design with a nonequivalent control group design model. Data is collected quantitatively using test instruments and analyzed using t-tests assisted by SPSS 23 software. The results showed that the implementation of learning using website-based media in class 3C got a success percentage of 90.4% with excellent criteria. Furthermore, data analysis using different tests (t-test) found that the experimental class got a value of t = 3.75 with a significance level of 0.001 (p&lt;0.05), and the control class got a value of t = 1,02 with a significance level of 0.320 (p&gt;0.05). From these results, it can be concluded that learning using website-based media influences the cognitive learning outcomes of 3C grade students at SDN Bakalan Krajan 1, Malang City. Therefore, it is expected that research related to this can be used by the department, principal, and teachers as material to be socialized and applied to the learning of elementary students.
The Abominatron

Abstract Bob prepares for Herb Deutsch’s visit. Precedents for Bob’s work are Cahill’s Telharmonium, RCA’s Mark I and II, and Harald Bode’s “System Synthesizer,” the latter being a particular inspiration to Bob, with its modular design and voltage controlled amplifier. Bode’s invention led Bob to a key stroke of insight concerning the exponential relationships in both music and engineering. From there, it was clear to Bob how to proceed: he would build a system with modular design, driven by voltage control. When Herb arrived in Trumansburg, Bob showed him his setup of two voltage controlled oscillators (VCOs), a voltage controlled amplifier (VCA), and a keyboard. During their time together, a rudimentary envelope generator was added. The two then showed the contraption at the University of Toronto Electronic Music Studio (UTEMS), which resulted in an invitation to present the invention—now dubbed “the Abominatron”—at the Audio Engineering Society.
The Cattle Rut Behavior Detection Base on AI Deep Neural Network

This paper proposes an application model of camera object detection to observe the cattle rut through its pose. This research is based on deep neural network method along with transfer learning technique. This paper employs four different deep convolutional neural network architectures 1) SSD Mobile-Net V2 2) SSD ResNet 101 V1 FPN 3) YOLOv5s and 4) Mask R-CNN. All the network mentioned above are pre-trained on COCO dataset. To observe the cattle rut behavior, the images of cattle behavior were taken in natural open environment, the data obtained are split into training and testing datasets. In this research cattle behaviors are categorized mainly in two classes, (1) normal behavior and (2) the cattle rut behavior. The result obtained after training the models shows that the YOLOv5s model obtained the highest mean average precision which is 95.5% and least training time. Thus, this paper proposes that YOLOv5s model can be applied to detect the cattle behavior for precise artificial breeding in order to increase the cattle population in farm to serve higher consumption demand in the near future.
A CUSTOMER-CENTRIC APPLICATION FOR A CINEMA HOUSE

Imagine a cinema with different branches and because of diverse regions, there may be a need to have different services for such regions. Uniformity is needed for systems like this. In this research, we developed a customer-centric online booking system for a cinema house called FLOW Inc. We used Hypertext Mark-Up Language, Cascading Style Sheet and JavaScript for the front end and MySQL database as the back end; and PHP as the scripting language. The system was implemented using the XAMPP package and Apache as the server. It was successfully tested on a computer system with a 4GB RAM and a CORE i5 processor with a processor speed of 2.16GHz.
BENCHMARKING METODE RANCANG BANGUN WATERFALL DAN PEMODELAN BERBASIS OBJEK

This research is a research Benchmarking Waterfall Design Method and Object-Based Modeling. Software development has many models, software methodologies have evolved from time to time, including the Waterfall approach and the UML (Unified Modeling Language) approach. Waterfall is a software development model that is carried out sequentially and very systematically. Meanwhile, UML is a visual modeling method that serves as a means of designing object-oriented systems. The difference between the two models is that Waterfall is a structured method, while UML is a system analysis method, a representation of the programming method. This study aims to perform a comparison or benchmarking of each of these software models, which can assist in determining the most suitable model for the current software development process. The method used in this research is descriptive quantitative method, which analyzes data by describing or describing the data that has been collected as it is. From the results of this study, it can be concluded that the UML method is most suitable for software development, because UML in terms of development, is a method that has undergone evolution from previous methods, so this method can follow the use of users in designing projects on a medium to large scale. That are relevant to the current developments
Micro calcification detection in digital mammograms using deep learning approaches

Breast Cancer is one of the normal and causing passing among ladies and least essential in men; Micro calcification, an abnormality that leads to breast cancer and is detected by various imaging such as X-ray, Computerized tomography (C.T.), etc. Detection of breast carcinoma is a challenging task since the micro calcifications are buried under the background of mammography. Numbers of studies have shown the early diagnosis is a more effective method to cure breast carcinoma. In this paper, Micro calcification was distinguished by the techniques for profound learning and by numerical figuring. The capabilities of deep learning futures and mathematically calculated features are combined on the characteristic of a deep learning filter. The filtered deep learning feature provides better experimental results compare with the mathematically calculated feature. We obtained 86.6% of overall precision level and sensitivity level by applying the deep learning features filtered and providing better performance with all the features.
Knowledge Creation and Performance of Private Health Facilities in Kisii County, Kenya

Well performing private health facilities afford countries access to quality healthcare and support services, easing the disease burden in public health facilities. Being a knowledge-driven industry, the field of medicine keeps advancing, highlighted by new discoveries in treatments from continuing research. As such, desirable performance among private health facilities would ideally necessitate that healthcare providers adequately share knowledge. By so doing, when one that bears knowledge that is specialized exists the facility, other staffs may continue accessing the knowledge, thus decreasing the probability of committing errors as a result of misinformation. Whereas extant studies attempt to link knowledge sharing and organizational performance, their focus has been on industries other than private healthcare. The present research thus set out to assess the effect of knowledge sharing on the performance of private health facilities in Kisii County, Kenya. The study was grounded on both knowledge-based view, and upper echelon theories. The research adopted both descriptive and explanatory research designs, with the target population comprising 135 staff drawn from all 43 private health entities in Kisii County. The research used a census survey with one top cadre staff from each facility forming the unit of observation. The research involved the gathering of data that is primary by utilizing a questionnaire that is semi-structured. Inferential and descriptive calculations were then computed in data analysis. Findings reveal a statistically significant relationship between knowledge sharing (β = .221, Sig.=.008&lt;.05) and performance. It is thus concluded that knowledge sharing significantly influences performance among private health facilities in Kisii County, Kenya. The study recommends that in order to realize improved and superior performance, private health facilities in the country ought to invest in knowledge sharing.
Classification of scholarship applicants using multilayer perceptron neural network

Bidikmisi scholarships are tuition assistance for prospective students who are economically disadvantaged but have the good academic potential to study at State Universities in Indonesia . With the amount Bidikmisi applicants, there is a need to use a system that can speed up the selection process and avoid human errors. The purpose of this study is to develop a classification system for Bidikmisi scholarship applicants at Universities in Indonesia. This study uses a multilayer perceptron (MLP) neural network to build a classification model. Because MLP has some hidden layers, MLP has advantages to predict or analyze complex problems. The methodology in this study is data collection, data preprocessing, data encoding, data modeling, and evaluation. The results of the classification of bidikmisi scholarship applicants are divided into two classes, namely accepted and rejected. The multilayer perceptron method generates an accuracy value of 72.81%. The Multilayer perceptron is compared with other classification methods, namely Naïve Bayes and K-Nearest Neighbors (KNN). The results of the classification using the Naïve Bayes method obtained an accuracy value of 79.47%, while the accuracy value using KNN was 78.33%. Evaluation using MLP resulted in precision, recall, and F1-measure values of 68.36%, 72.81%, and 66.33%. the results of the evaluation using Naïve Bayes were 75.58%, 79.47%, and 71.24%, while the KNN values were 71.90%, 78.33%, and 72.53%. In order to the conclusion in this research is the MLP method can generate good performance for the classification of bidikmisi scholarship applicants. However, Naïve Bayes’ performance is better than MLP for the classification of bidikmisi scholarship applicants.
Assembly Training, Software Installation and Computer Troubleshooting at Karang Putih Community Learning Activity Center

This service activity will be focused on everything related to assembly, software installation and computer troubleshooting for participants in the Karang Putih Community Learning Center (PKBM). The activity steps are carried out in several stages, starting from field surveys, literature studies, discussions, to the implementation of training activities that use an approach between theory and practice. Indicators of the success of this activity are the Assembly Training, Software Installation and Computer Troubleshooting. This training is used by partners, by seeing that this training has been in accordance with the needs of the community in the partner environment; This training can help the educational process and skills in practice quickly; and this training can be conducted by other Community Learning Activity Centers (PKBM). The attention of the participants in this activity was quite large, almost all of them were active in the discussions and practices that were carried out. From this discussion and training it was revealed that about 75% of the participants had understood the material as a whole.
High Simulation Reconstruction of Crowd Animation Based on Optical Flow Constraint Equation

Abstract The amount of information available in modern life is very high. And people's knowledge about what kind of genre they like or prefer, the richness of content and the frequency of use will affect the quality of their animation works and their style. Therefore, how to make animation reach a higher level of simulation has become one of the topics of social concern nowadays; with the advent of mobile Internet era, more and more people like this social platform, and in this environment, we need to personalize ourselves and integrate into it faster through various technical means. In this paper, researchers focus on the reconstruction of crowd movement trajectory based on the optical flow constraint equation (SDH) after modification. Since lasers, cameras and other devices have high-intensity pixel resolution characteristics as well as better directional characteristics, we can use these features to design and build the function; then we can complete the relevant actions according to the prototype model under certain conditions, realize the simulation of the scene according to its requirements, and finally complete the required functions of the whole system. Finally, the feasibility and effectiveness of the optical flow constraint equation and the optimized action model in practical applications are verified through experiments; at the same time, this also provides reference values for relevant staff.
PENGARUH KEHADIRAN OJEK ONLINE TERHADAP KEPUASAN PELANGGAN ONLINE DAN DAYA SERAP PENGANGGURAN DI MASYARAKAT BANYUMAS

The presence of ojek-online in Banyumas Regency turned out to be able to provide satisfaction for its customers, especially in Banyumas Regency. many as ojek-online in the Banyumas Regency and surrounding areas so that very many unemployed and already working residents are now working as ojek-online because in addition to the benefits achieved, it also has its own charm. Although it has received criticism from both the government and conventional ojek, slowly the existence of ojek-online can now be received positively by the wider community in Indonesia, especially in Banyumas Regency, because in addition to the easy ordering method, it also saves time, costs and energy.&#x0D; The presence of ojek-online turns out to be very helpful for public transportation, especially in certain rural areas where no transportation is available or transportation is available but time is limited, so the presence of ojek-online brings fresh air and bright hope in increasing population mobility in remote areas that are difficult and expensive to transport.&#x0D;
Perspective of Virtual Exhibition during the COVID-19 pandemic

Virtual exhibitions are growing driven by physical restrictions during the COVID-19 pandemic. The exhibition of works that were previously more physical in nature, can be visited physically is slowly turning into an exhibition that is visited virtually. This change is uncomfortable for the community. For this reason, a study is needed on the impact of virtual exhibition visits on the community during the COVID-19 restrictions. This study aims to answer these problems and at the same time evaluate the progress of virtual exhibitions in the early days of the pandemic. Collecting data using an online questionnaire on 49 architecture students. The results of the questionnaire were analyzed using distribution and content analysis for open-ended questions. Exhibition content is the main focus. in a virtual exhibition. Other aspects to consider are virtual quality, exhibition perception, and execution. Restrictions cause boredom and stress. Virtual exhibitions can help overcome these feelings. Virtual exhibitions are not a substitute for physical exhibitions because people do not feel the need to refrain from visiting virtual exhibitions. Professionals feel motivated to visit any exhibition whether physical or virtual. So virtual exhibitions function like physical exhibitions, the only difference is the impression and experience that visitors get
The Best Techniques to Deal with Unbalanced Sequential Text Data in Deep Learning

Datasets with a balanced distribution of data are often difficult to find in real life.Although various methods have been developed and proven successful using shallow learning algorithms, handling unbalanced classes using a deep learning approach is still limited.Most of these studies only focus on image data using the Convolution Neural Network (CNN) architecture.In this study, we tried to apply several class handling techniques to three datasets of unbalanced text data.Both use a data-level approach with resampling techniques on word vectors and algorithm-level using Weighted Cross-Entropy Loss (WCEL) to handle cases of imbalanced text classification.With Bidirectional Long-Short Term Memory (BiLSTM) architecture.We tested each method using three datasets with different characteristics and levels of imbalance.Based on the experiments that have been carried out, each technique applied has a different performance on each dataset.
The Role of Tacit Knowledge in Improving Audit Quality: An Applied Study in the Audit and Control Departments of the Colleges of the University of Al-Qadisiyah.

The current research aims to study the role of the Tacit knowledge of auditor in their dimensions (thinking, experience, skill), In improving the quality of the audit in its dimensions (guidance and supervision, distribution of tasks, skill and efficiency, professional requirements, In the departments of auditing and internal control of the faculties of Qadissiyah University, The research included two hypotheses, the first for correlation and the second for the relationship of influence, A sample of 54 employees was selected, By adopting the questionnaire which included (29) paragraphs, and the results were extracted using the statistical program SPSS, A number of results were reached, the most important of which was a statistically significant correlation between the implicit knowledge dimensions of the auditor and the quality of the audit, And formulated a set of recommendations, most important of which is the need for the organization's interest in the research sample to meet the requirements of the professional by establishing policies and procedures that confirm and oblige the auditor to abide by the principles of independence, objectivity and integrity.
Bakti Sosial Peduli Korban Kebakaran Sape Oleh Civitas Akademika Sekolah Tinggi Ilmu Ekonomi (STIE) Bima

The Community Service Team of the Bima College of Economics (STIE) is a collection of the academic community consisting of leaders, lecturers, staff and campus security who care about the condition of the community. STIE Bima cares about the Sape Naru fire as a place to channel ideas and contributions, wants to contribute in the form of social service that is felt directly by the community. Social service is an alternative solution to the problems of today's society. The social service activity was carried out in the fire area in Naru Hamlet, Sape District, Bima Regency, NTB. The stages of service activities include preliminary studies, preparation, distribution, and activity reports. The purpose of social service, apart from being a community activity, is also to raise awareness for sharing which needs to be further improved so that care for the surrounding environment is maintained. All donations in the form of mats, proper clothes, medicines, basic necessities and cooking needs were recorded by type and amount. The distribution of aid is divided into three points, namely, the main post which is directly adjacent to the refugee camp, the post near the main road and the post in the Sape sub-district. In the distribution stage or distribution of basic food packages, lecturers and staff use a participatory approach. Based on community service in the form of distributing basic necessities at the fire site, Naru Hamlet, Sape District, Bima Regency, it showed a positive impact on fire victims.
KRATAK OSVRT NA PREDLOG UREDBE O ODGOVORNOSTI ZA UPOTREBU SISTEMA VEŠTAČKE INTELIGENCIJE OD 20. OKTOBRA 2020. GODINE

In this paper author shortly reviews key provisions of Proposal for a Regulation on Liability for the Operation of Artificial Intelligence which was adopted on 20 October 2020 by European Parliament. The attention is given to the provisions which provide the definition of AI systems and their operators and regulate civil liability regimes for operators (strict liability for high-risk AI systems and fault-based liability for other AI systems), amount and extent of compensation, limitation period as well as the relationship between the proposed Regulation, on one side, and other EU legal acts (especially Product Liability Directive 85/374/EEC) and national laws of Member States, on the other side.
The Importance of Ethics in Socio-Educational Robotics

Socio-educational robotics can be defined as investigating teaching-learning processes involving robots capable of bonding, learning and communicating. These robots are used as a didactic tool for their ability to interact with people, and they are designed to meet their objectives and benefit the human beings involved in the process. Therefore, it is essential to recognize the social and educational purpose of the intervention itself that will be carried out with them. However, the deontological code of the pedagogy profession does not include social robotics since it is a relatively new phenomenon in education. All the didactic interventions using robots must be designed to be compatible with the ideals of human dignity, rights, freedoms and cultural diversity.