Reviewerly/exHarmony huggingface dataset:
Peningkatan Hasil Belajar Perbankan Melalui Penerapan Kartu UNO pada Siswa Kelas X Akuntansi di SMK Muhammadiyah Delanggu Tahun Ajaran 2019/2020

This study aims to improve banking learning achievement by applying UNO cards to accounting grade X students at SMK Muhammadiyah Delanggu in the 2019/2020 school year. This type of research is classroom action research (CAR) method which carried out total of II cycles, with two times of meetings in every cycle. The type of data in this study uses descriptive quantitative data. Subjects were teachers (actor) an a class X Accounting SMK Muhammadiyah Delanggu totaling 16 students (recipients of the action). The object of this research is to increase student learning outcomes through the application of UNO cards. Data collection techniques used include interview, observations, tests, field notes, and documentation. The results of the study using the UNO card showed that the banking learning result of Grade X Accounting students have increased, it can be seen from students who score more than the Minimum Mastery Criteria (MMC). Before taking action, banking learning result of 25% or 4 students who tuned, in the first cycle banking learning result increased to 62,55% or 10 students pas the MMC score, and in cycle II student’s banking learning result to 87,5% or 14 students pas the MMC score.Based on these results it can be concluded that the application of UNO cards can improve student learning result in banking subjects in class X Accounting at SMK Muhammadiyah Delanggu in the 2019/2020 school year.
Row-Level Security

At some point, you may come across a requirement to create a report that needs to deliver results specific to the currently logged in user who looks at the report. One scenario is when different team members need a report that shows low-level detail about items they are individually responsible for, but prevents them from seeing the same level of detail for other members in the same team. Another scenario might be to provide a report to multiple groups external to your organization, making sure the person accessing the report only sees the information they are supposed to.
Dr(Hc) “Impact of Consumer Shopping Experience through Virtual Reality”

Abstract: Background- The most obvious reason why virtual reality work so well with retail business is that of its ability to solve major problems with customer experience. A wave of virtual reality content is hitting the market this year and consumer adoption could quickly follow, bringing with it growing demand for shopping experiences using the technology.Objective- Retailers need to be watching very closely because when VR hits the market adoption tipping point it’s going to go fast and shoppers will be expecting to be able to shop from home with a VR experience. Our objectives are to understand what constitutes customer experience in retail and to study various factor influencing positive customer shopping experience.Method- with Exploratory research method & Sampling unit: Brand factory Major findings of the project is that 52 (52%) of respondents at brand factory are unmarried according to marital status & 62 (62%) of respondents says responsiveness from store staff is excellent & 58 (58%) of respondents says that professionalism at brand factory shopping mall is good. & 52 (52%) of respondents agree that virtual reality shopping mall results in better customer satisfaction when it compared to ordinary shopping mall.Conclusion- Participants were likely to spend more time in the virtual reality environment than in the online catalog. However, the delay was not significant. From the results of the interview, we found that participants remembered and remembered more elements in the virtual reality environment
HisArc-RDF: prototyping an operating chain, related to the Linked Open Data, on structurally and semantically heterogeneous archaeological data sets

HisArc-RDF project aims to share and reuse archaeological data, by articulating their description on semantic web repositories and standards. The project will test four data sets, samples of which will be determined to cover different archaeological themes, both in terms of vocabulary and data modelling: hydraulic structure, epigraphic data, ceramic and building structures. To achieve that, we want to reduce veracity concerns on descriptive vocabularies (from artefacts description to period names and limits) so that different datasets can be addressed and compared through concepts (instead of words) at a data level. For that purpose, we will create micro-thesauri (at sub-disciplinary level), then vocabulary and data model will be aligned in parallel with the semantic web repositories and CIDOC CRM to build a structured description of database fields as well as database variables. To address this, the project plans to interconnect Opentheso (thesaurus management tool), OntoME (ontology management environment) and IdRef (database for authority records). Finally, the project plans to bring together, through workshops, a large network of actors in order to disseminate good practices experienced by LOD implementation.
Estimating GSR by Empirical models: Case Study for İskenderun, Turkey

In this study, the predictability of Global Solar Radiation (GSR) data is investigated for Iskenderun region, which has a rich source of solar energy. Four different models were used to estimate GSR using current data. Linear, quadratic and exponential relationships were preferred among the parameters for absolute and stable results of these models. The empirical coefficients a, b and c of the models were calculated to estimate the average solar radiation of the region. The correlations between the obtained values from models and the current meteorological values were found to be consistent. As a result, a stable and reasonable approach was obtained for the estimation of GSR coming to the horizontal plane for the region.
Guide to Streaming Video Acquisitions, an ALCTS Monograph

"Guide to Streaming Video Acquisitions, an ALCTS Monograph." Journal of Access Services, 17(2), p. 96
Application of Engineering Quality Control and Management Based on BIM and 3D Laser Scanning

3D laser scanning is a novel technological breakthrough in engineering measurement and management field.In this paper, a new engineering quality control and management method has been adopted, which is focusing on engineering quality pre-management and process management, by the combination virtual and real method.It has been verified by practice that BIm and 3D laser scanning technology is suitable for precise quality control and management especially for the projects with complex structures and environment.
Characterizing Leveraged Stack Overflow Posts

Stack Overflow is the most popular question and answer website on computer programming with more than 2.5M users, 16M questions, and a new answer posted, on average, every five seconds. This wide availability of data led researchers to develop techniques to mine Stack Overflow posts. The aim is to find and recommend posts with information to developers. However, and not surprisingly, not every Stack Overflow post is from a developer's perspective. We empirically investigate what the characteristics of useful Stack Overflow posts are. The underlying assumption of our study is that posts that were used (referenced in the source code) in the past by developers are likely to be useful. We refer to these posts as leveraged posts. We study the characteristics of leveraged posts as opposed to the non-leveraged ones, focusing on community aspects (e.g., the reputation of the user who authored the post), the quality of the included code snippets (e.g., complexity), and the quality of the post's textual (e.g., readability). Then, we use these features to build a prediction model to automatically identify posts that are likely to be leveraged by developers. Results of the study indicate that post meta-data (e.g., the number of comments received by the answer) is particularly to predict whether it has been leveraged or not, whereas code readability appears to be less useful. A classifier can classify leveraged posts with a precision of 65% and recall of 49% and non-leveraged ones with a precision of 95% and recall of 97%. This opens the road towards an automatic identification of high-quality content in Stack Overflow.
Efficient cryptographic building blocks for processing private measurements in e-healthcare

In order to achieve practical e-healthcare systems, five requirements should be addressed, namely 1) availability, 2) integrity, 3) accuracy, 4) confidentiality, and 5) efficiency. Using remote computer storage and processing services satisfies availability, integrity, and efficiency. However, it introduces privacy concerns regarding the leakage of private medical data to unauthorized parties, which violates GDPR. Data encryption is one of the widely used techniques to address those privacy concerns in e-healthcare systems. Although data encryption provides data confidentiality, while the accuracy and integrity of the data are preserved, it introduces computation and communication overheads that downgrade the efficiency of the e-healthcare systems. To precisely find the bottlenecks in achieving privacy-preserving e-healthcare systems, we design three real-life e-healthcare scenarios. The scenarios are different in terms of the number of parties used in the system, the way that data are stored (centralized or distributed), and encryption key setting (single-key or multiple-key). Then, we identify the challenges and required cryptographic protocols for each scenario. Afterward, we investigate the performance of several applications that are using the same identified cryptographic protocols. We show that the existing cryptographic protocols, which are required for our scenarios, are dominating the computation and communication costs of the applications. To address the challenges in the single-key setting, we improve the existing core building blocks, comparison, and equality testing, and develop new protocols to mitigate the overall costs of e-healthcare systems. We show that data filtering and retrieval protocols are still highly resource demanding, even though efficient building blocks are used. Thus, we develop a new secure indexing protocol that reduces the data filtering cost significantly. Moreover, we develop a novel data packing technique to achieve an efficient data retrieval protocol by using our indexing protocol. For themultiple-key setting, we introduce a homomorphic proxy re-encryption scheme. Our encryption scheme has several properties such as an unlimited number of re-encryption, supporting homomorphism after each re-encryption, one-direction re-encryption, and non-interactive re-encryption key generation. Afterward, we use our encryption scheme for data filtering in the multiple-key setting and evaluate its performance. The results of the performance analysis of our protocols show that improving core building blocks can significantly decrease both computation and communication costs of the cryptographic applications. Moreover, we show that developing techniques such as data packing and indexing can limit the number of homomorphic operations considerably, and consequently, mitigate the overall computation and communication costs of the cryptographic applications.
Mastery Learning in the Modern Context

This paper analyses whether mastery learning can be effectively introduced into the education system, with a specific focus on India.By presenting successful data studies on the experimental implementation of Mastery Learning, it discusses the significance of the findings and highlights the potential drawbacks of the widespread implementation of the learning philosophy and its feasibility into the real world.
Face Reconstruction from Profile to Frontal Evaluation of Face Recognition

One of the main challenges in face recognition is handling extreme variation of poses which may be faced for images collected in labs and in the wild. Recognizing faces in profile view has been shown to perform poorly compared to using frontal view of faces. Indeed, previous approaches failed to capture distinct features of a profile face compared to a frontal one. Approaches to enhance face recognition on profile faces have been recently proposed following two different trends. One trend depends on training a neural network model with big multi-view face datasets to learn features of faces by handling all poses. The second trend generates a frontal face image (face reconstruction) from any given face pose and applies feature extraction and face recognition on the generated face instead of profile faces. Recent methods for face reconstruction use generative adversarial networks (GAN) learning model to train two competing neural networks to generate authentic frontal view of any pose preserving person’s identity. For the work described in this paper, we trained a feature extraction neural network model to learn representation of any face pose which is then compared with each other using Euclidean distance. We also used two recent face reconstruction techniques to generate frontal faces. We evaluated the performance of using the generated frontal faces against the posed counterparts. In the conducted experiments, we used three face datasets that contain several challenges for face recognition having faces in a variety of poses and in the wild.
PLANNING OUR EVERYDAY USING TOOLS AND TECHNIQUES OF PROJECT MANAGEMENT

Planning our daily lives may not be a custom for individuals to have and see how important it is. Therefore, the objective of this paper is to present the most used Project management methodologies, tools and techniques used by project managers, which can be applied in our day by day, such as Project Management Body of Knowledge guide (PMBOK), Work Breakdown Structure (WBS), MS Project, Project Canvas and the methodology agile with the Scrum framework. In the research, it was found that using the concepts; it is possible that people can plan, even if they are not able to acquire software licenses due to their high cost. However, despite that, there are alternatives that can be used.
A Linear Regression Application of Comprehensive Knowledge with Attitudes Towards HIV / AIDS Sufferers in Indonesia Based on 2018 Riskesdas Data

Public understanding of early detection of HIV disease that is lacking should be a major concern because this will trigger the emergence of infectious disease transmission will be wider. The purpose of this study is to model comprehensive knowledge with attitudes towards HIV / AIDS sufferers in Indonesia.This type of research in this study is quantitative using secondary data from Riskesdas 2018. The method in this study uses linear regression is useful for modeling the relationship between knowledge and attitudes towards people with HIV / AIDS. The linear regression assumption is that the error follows the normal distribution, there is no problem with heteroscedasticity, and there is no autocorrelation problem. After the assumptions are met overall testing and partial testing are done.Assumption test results for normally distributed errors are met based on the Kolmogorov Smirnov test with a significance value of .400. Assumption test there is no problem with heteroscedasticity fulfilled based on the results of scatterplot that is not forming a certain pattern and is confirmed using the Spearman rho's test with a significance value of 0.245. The assumption test that there is no autocorrelation problem is also fulfilled based on the Run test with a significance value of 0.117. The results of testing the whole model using the F Test obtained fit model with a significance value of 0.001. The results of individual testing (partial) using the t-test found that knowledge has a significant influence on the attitudes of people with HIV / AIDS with a significance value of 0.001.The conclusion from this study obtained a linear regression model that is formed is attitude = -219,804 + 4,555 * knowledge means that attitude will increase by 4,555 each increase in knowledge by 1 unit.
PENGUKURAN KEAKTIFAN DOSEN DALAM PEMBELAJARAN BERBASIS SMARTLECTURER MENGGUNAKAN FUZZY MAMDANI DAN SUGENO

The success of learning in a classroom that uses supporting media demands lecturer activity.  The level of activity of lecturers in class and using learning media such as Smartlecturer can be measured using a fuzzy logic approach. This study aims to measure the level of active lecturers using the approach, namely: Mamdani and Sugeno method. Stages of lecturer activity measurement by forming a fuzzy set, composition rules as many as 24 rules and the defuzzification process using the centroid method that produces the level of activity of each is low, medium and high. Based on 173 lecturer activity data, the results of the mamdani method low 66%, medium 31%, and high 3%. While the Sugeno method produces a level of activity low 75%, moderate 17%, and high 8%. Therefore, Mamdani method is more suitable for the calculation because the spread of results is relatively evenly distributed at each level. Key words: Lecturer, Fuzzy, Activeness, Mamdani, Sugeno
Forensic detective control using hardware steganography for IP core protection

This chapter discusses forensic detective control using hardware steganography for intellectual property (IP) cores or integrated circuits. The chapter is organized as follows: Section 2.1 introduces the utility or applications of hardware steganography; Section 2.2 discusses the threat model for which hardware steganography is applicable; Section 2.3 presents comparative study on contemporary approaches; Section 2.4 explains the IP core steganography model; Section 2.5 discusses forensic detective control using hardware steganography for digital signal processing (DSP) cores; Section 2.6 presents the design process of the hardware steganography process for DSP cores; Section 2.7 analyses security properties of hardware steganography; Section 2.8 presents an analysis and comparison of hardware steganography with watermarking for different DSP IP cores; finally, Section 2.9 concludes the chapter.
Quantum color image encryption technology based on hyper-chaotic systems

In order to improve the security of traditional encryption systems, hyper-chaotic systems are introduced into the field of quantum image encryption. Firstly, the image is bitwise XOR by He fractional order hyper-chaotic Rabinovich system, and then the color image is represented as a quantum superposition state. The quantum image is scrambled by the unitary matrix generated by Logistic hyper-chaotic sequence, and then a hyper-chaotic sequence is generated to randomly replace the red, green and blue primary colors of each pixel to achieve the purpose of quantum image encryption. Finally, numerical simulation experiments are carried out on a computer. The experimental results show that the histogram of the encrypted image is flatter and even, the pixels are evenly distributed between 0 and 255, the correlation between adjacent pixels of the image is low. The average correlation coefficients of the red, green, and blue pixels of the encrypted image are 0.0012, 0.0025, and 0.0018. The system has high key sensitivity and can effectively resist statistical analysis attacks. The algorithm has good security and robustness.
Development of the Face Recognition Application Using Neural Networks Technology

Recognition and classification are the main tasks of machine learning with a wide range of applications: determining handwritten numbers, identifying objects in video recordings, diagnostics using MRI scanning, and much more. Currently, one of the most common applications of neural network technology is face recognition in photographs or in video. For example, corporations such as Facebook are currently using neural network technologies to identify a user's friends by their faces in general photos. The paper discusses the development of face recognition applications using neural network technologies. The developed system has a relatively small size and works with a sufficiently high accuracy.
ANALISIS DAN PERANCANGAN SISTEM INFORMASI PROMOSI BERBASIS WEB PADA BETACAM STUDIO PHOTOGRAFHY

Betacam Studio Photografhy is a studio engaged in photografhy and videografhy, where in general thebusiness process is product production, product promotion, and product sales. The problem experiencedby Betacam Studio Photografhy was that there were still very few people who knew Betacam StudioPhotografhy because its promotion activities were still carried out by distributing brochures and mouthto-mouth promotions so that it was only known around the neighborhood and there was no significantincrease every month. This study aims to analyze and design a promotional information system in theBetacam Studio Photografhy with the prototype method. The solution made by the author is to analyze theold system and design the system offered to be developed using UML. Where researchers combine thefields of marketing science, especially promotion mix with information technology by designingdigitization of product catalogs and promotional brochures with websites as media. This researchproduces a prototype that can be implemented to reach a wider consumer not only limited to theenvironment around Betacam Studio Photografy. This result is expected to be developed into a PromotionInformation System application on Betacam Studio Photografhy.
Cuando la innovación es la conquista de lo viejo

This paper includes the intervention made in the Research and Innovation in Scientific Education conversation group that took place at the X Ibero-American Congress of Scientific Education on the 25th of March, 2019, in Montevideo. The information provided by the research about the impact of teacher educators' practices on future teachers is taken up and it is noted that it has not been considered seriously in the training process in Uruguay. It is concluded that an urgent change in the practices of teacher educators is required and that this, although it is a matter well known by the members of the community, continues to be a current challenge for teacher training in this country.
Importance of Modern Educational Technologies in Russian Districts

Modern educational online technologies are the most important in distinct districts of Russia. Thus, in Moscow, Saint-Petersburg, Perm, Novosibirsk, Ekaterinburg and other large cities there are many educational opportunities in higher and secondary education. Whereas in small cities and towns there is lack of opportunities. Therefore scholars and students from these areas have no possibilities to get proper education without online technologies. The paper is based on statistical data about education in Russia. The result of the research is that online education cannot just explore ordinary education in distinct regions, but also can substitute it.
HUMANITARIAN STRATEGIES IN REGIONAL UNIVERSITIES OF RUSSIA

1 Udmurt State University (RUSSIAN FEDERATION)2 Kazan National Research Technical University named after A.N. Tupolev (RUSSIAN FEDERATION)