Reviewerly/exHarmony huggingface dataset:
Use of Electronic Resources by the Faculty Members of Government Medical College Libraries in Karnataka

Medical college libraries are aiming to provide efficient information services using both electronic and printed scholarly information resources to the medical professionals This paper study on the use of E-resources (e-books, e-journals, e-databases) subscribed by Health Science Library and Information Network, HELINET Consortium. The study sample is the faculty members of Government Medical Colleges. The study found that use of E Resources and use of Database by faculty members is not up to expectation of the provider and the investment.
Realistic Dashboard Computer For Mercedes Actros MP3

Here is the realistic dashboard computer for 2009 Actros by Schumi with EVR sounds applied. You Need To Have These Mods To Make This Mod Work: ...
Unexpected Pitfalls of Bitcoin

The Bitcoin blockchain achieves a strong tamper resistance by exploiting cryptographic technologies.
"Training and substantive resource for vocational training of future primary school teacher for inclusive education: analysis and adaptation"

Y. Fedkovych, expert of the international program for the development of inclusive communities, which is implemented
Сase-technologies in practice-oriented training of future teachers of preschool and primary general education

The article deals with the problem of convergence of fundamental pedagogical education in higher education and real pedagogical practice in preschool organizations and primary schools for the formation of children’s cognitive activity. The article presents the experience of testing pedagogical conditions for the use of case technologies in preparing future teachers for the process of forming prerequisites for cognitive activity in preschool age and cognitive universal educational actions in primary school age.
STEM: STacked Ensemble Model design for aggregation technique in Group Recommendation System

A group recommendation system is required to provide a list of recommended items to a group of users. The challenge lies in aggregating the preferences of all members in a group to provide well-suited suggestions. In this paper, we propose an aggregation technique using stacked ensemble model (STEM). STEM involves two stages. In stage 1, the k-nearest neighbour (k-NN), singular value decomposition (SVD), and a combination of user-based and item-based collaborative filtering is used as base learners. In the second stage, the decision trees predictive model is used to aggregate the outputs obtained from the base learners by prioritising the most preferred items. From the experiments, it is evident that STEM provides a better group recommendation strategy than the existing techniques.
A Nobel Approach to Detect Mysterious Action at Real-Time from Object Speed and Background Subtraction by using Incremental Tensor Subspace Learning

Abnormal action detection is a very important process for avoiding crime happening in various areas where there is no human resource. From surveillance videos abnormality like chasing, murders, races, fights, accidents, etc. should be detected automatically and intimation will be given to respective personalities. The goal of the proposed work is to recognize mysterious action detection by speed and displacement analysis in image processing. In the proposed work, authors have used a combination of motion detection along with speed and displacement measurement using various image analysis techniques implemented in MATLAB simulation environment. Motion detection is determined by Incremental and Multi-feature Tensor Subspace Learning Applied for Background Modelling and Subtraction. After Background subtraction, the procedure of moving object detection comes into the action. The threshold has been fixed for normal speed and displacement exceeding this shows mysterious action happening and the corresponding video has been popped up along by saving the frames with the action noted.
UPBRINGING ENVIRONMENT OF A PEDAGOGICAL UNIVERSITY AND SCHOOL: PRACTICE OF IMPLEMENTATION

The article presents innovative approaches to the inclusion of the upbringing component in the activities of the Shukshin Altai State University for Humanities and Pedagogy (Biysk, Altay Region). It also describes the need to create collaboration between universities and schools, which is aimed at broadcasting innovative educational practices to the pedagogical community at various levels in various forms. The future teachers’ training directions for the design and implementation of educational activities within the framework of the implementation of the general project “Architectonics of educational environment” are proposed: training a teacher as an organizer of educational activities in the educational process, in extracurricular activities and in the work of the class teacher; study and design of new educational practices; broadcasting advanced experience and innovative educational practices to the pedagogical community and educational organizations; design of objects and activities that are significant for society. The authors present innovative projects that ensure the creation of a unique university educational environment and contribute to individual school educational environments (at the example of the Biysk educational district). The article describes the main goals and objectives of such projects as “A world without borders”, “Digital humanities: a view from the XXI century”, “Classroom teacher 4.0: reboot”, “Shukshin University: talent and success”, “Center for the Study and Preservation of the Kumandin language and culture”, “Together to success”, “Modern parents PROParent”, “Foresight is the young people’s business”, “Mobile volunteers”, “Digital volunteers”, “Victory volunteers”, “Media volunteers”, “Urban environment”, “School is a rural development accelerator”, etc.
Prospects for Predicting The Most Promising Ore-Bearing Areas Based on The Classification of Potential Fields

Summary This article is aimed at studying new ways of forming predictive and prospecting models for the localization of ore objects. For this purpose, the text discusses the possibility of applying the classification technique of potential fields together with the transformation of the initial geophysical data, for further identification of the most interesting anomalous structures. Based on the results of studying the a priori information, the following transformations are performed: the division of the source maps into regional and local components, the calculation of the transformants of potential fields. Based on the identified identical features, the fields are classified using the Coscad 3D program, both for each field individually and for the combined model. As a result, a comprehensive analysis of the original and converted geoinformation is performed. The authors substantiate the patterns of distribution of the most interesting structures, draw conclusions about the prospects for the development of the method of classification of potential fields, when solving problems of interpretation of geophysical data.
A Defense Framework for Privacy Risks in Remote Machine Learning Service

In recent years, machine learning approaches have been widely adopted for many applications, including classification. Machine learning models deal with collective sensitive data usually trained in a remote public cloud server, for instance, machine learning as a service (MLaaS) system. In this scene, users upload their local data and utilize the computation capability to train models, or users directly access models trained by MLaaS. Unfortunately, recent works reveal that the curious server (that trains the model with users’ sensitive local data and is curious to know the information about individuals) and the malicious MLaaS user (who abused to query from the MLaaS system) will cause privacy risks. The adversarial method as one of typical mitigation has been studied by several recent works. However, most of them focus on the privacy-preserving against the malicious user; in other words, they commonly consider the data owner and the model provider as one role. Under this assumption, the privacy leakage risks from the curious server are neglected. Differential privacy methods can defend against privacy threats from both the curious sever and the malicious MLaaS user by directly adding noise to the training data. Nonetheless, the differential privacy method will decrease the classification accuracy of the target model heavily. In this work, we propose a generic privacy-preserving framework based on the adversarial method to defend both the curious server and the malicious MLaaS user. The framework can adapt with several adversarial algorithms to generate adversarial examples directly with data owners’ original data. By doing so, sensitive information about the original data is hidden. Then, we explore the constraint conditions of this framework which help us to find the balance between privacy protection and the model utility. The experiments’ results show that our defense framework with the AdvGAN method is effective against MIA and our defense framework with the FGSM method can protect the sensitive data from direct content exposed attacks. In addition, our method can achieve better privacy and utility balance compared to the existing method.
Analisis Perbandingan Algoritma Klasifikasi MLP dan CNN pada Dataset American Sign Language

People who have hearing loss (deafness) or speech impairment (hearing impairment) usually use sign language to communicate. One of the most basic and flexible sign languages ​​is the Alphabet Sign Language to spell out the words you want to pronounce. Sign language uses hand, finger, and face movements to speak the user's thoughts. However, for alphabetical sign language, facial expressions are not used but only gestures or symbols formed using fingers and hands. In fact, there are still many people who don't understand the meaning of sign language. The use of image classification can help people more easily learn and translate sign language. Image classification accuracy is the main problem in this case. This research conducted a comparison of image classification algorithms, namely Convolutional Neural Network (CNN) and Multilayer Perceptron (MLP) to recognize American Sign Language (ASL) except the letters "J" and "Z" because movement is required for both. This is done to see the effect of the convolution and pooling stages on CNN on the resulting accuracy value and F1 Score in the ASL dataset. Based on the comparison, the use of CNN which begins with Gaussian Low Pass Filtering preprocessing gets the best accuracy of 96.93% and F1 Score 96.97%
Panel Discussion on the Future of Performance Analysis and Engineering

In this panel, a team of four experts in performance analysis, parallel computing, and distributed systems discuss the future of performance analysis. A particular emphasis will be placed on how the growth of GPUs and cloud computing are changing the landscape of tools and techniques we are currently using. This panel will discuss the limitations of today's technology, the barriers to progress, the research which may help us overcome these barriers and provide insight into what future tools may look like. The panel is in the format of question & answer session given by the moderator combined with interactive communication with the audience.
INVESTIGATION OF THE EFFECTIVENESS OF USING QR CODE SUPPORTED BOOKS

The aim of this study is to examine the effect of course book supported by QR code applications on students' academic achievement and self-learning with technology. Within the scope of the study, printed course book was directed to digital materials. In the other group, the same materials (course book and digital materials) were processed by the teacher. In the 2018-2019 academic years, a 4-week application was carried out within the scope of the research conducted with 98 students in a secondary school. An achievement test and a scale were used as data collection tools. As a result of the research, no difference was found between the academic achievements of the experimental group in which the lessons were taught with qrcode and the control group. However, it was observed that the experimental group students showed a higher development in terms of self-learning with technology. It was concluded that the use of qrcode contributed to the development of students in self-learning with technology. Article visualizations:
TORS: A train unit shunting and servicing simulator

When trains are finished with their transportation tasks during the day, they are moved to a shunting yard where they are routed, parked, cleaned, subject to regular maintenance checks and repaired during the night. The resulting Train Unit Shunting and Servicing problem motivates advanced research in planning and scheduling in general since it integrates several known individually hard problems while incorporating many real-life details. We developed an event-based simulator called TORS (Dutch acronym for Train Shunting and Servicing Simulator), that provides the user with a state and all feasible actions. After an action is picked, TORS calculates the result and the process repeats. This simulator facilitates research into a realistic application of multi-agent path finding.
Soundtrack in Modern Cinema

The purpose of the research is to analyze popular examples of modern cinema music to determine the features of its interaction with various elements of screen text, taking into account the applied nature and applying various relevant approaches to the study of soundtracks. The research methodology consists in the application of a set of methods for theoretical analysis of film music, their interaction with internal and external factors of influence on the formation of the viewer’s image-emotional sphere in conditions of purposeful perception of the storyline of modern cinema. The scientific novelty lies in the fact that for the first time the peculiarities of the music functioning in modern cinema were analyzed, the main trends in the development of film music in the socio-cultural conditions of our time were revealed, and film music from the perspective of the viewer as a “non-ideal” evaluator of soundtracks in modern cinema was also considered. Conclusions. The article, using various methodological approaches, has proved that film music in the framework of interaction with screen text manifests itself as a significant tool, expanding the artistic space of the film. Film music can go beyond direct acoustic information, reflecting the narrative and conceptual components of the work of art as a whole. A practical example of the manifestation of modern film music is the use of timbral colours as an instrument for revealing the context of events, time, and the image of a hero; leitmotif; experiments with the technical side of sound through the expansion of the imaginary space of the screen. The main trends in the development of film music in the socio-cultural conditions of our time are due to the release of soundtracks beyond the boundaries of a practical film instrument. The modern soundtrack occupies a significant part of the cultural space of music and culture in general. This position is facilitated by the composer’s conceptual approach, the style integrity of the work and the relative independence of the soundtrack in the general cultural space. The rating of soundtracks is given by the audience and depends on their aesthetic preferences and the level of musical “experience”. Soundtracks must meet the requirements of modern cinema and common cultural space, which contributes to the success of the film.
IMAGE COMPRESSION USING LOCAL MAP VIEW TECHNIQUE

Image compression has gained importance in many medical treatments and diagnostic processes.Image compression aims at correctly separating different tissues, organs, or pathologies in volumetric image data.Most of the existing algorithms for Image compression have a "scattered" cluster problem (disconnected clusters) happened in many clustering techniques (agglomerative, k-means, Dbscan) above algorithms not taken into account of both quality value and connectivity of points and region varying shapes.This proposed technique LMV (Local Map View) concentrates on determination of local quality for each point in all instances of the region in the comparative similarity view by applying the initial cluster technique.This view allows the user to choose instances for detailed analysis and filter the outlier instances from the input, next specific feature selection process identifies regions with systematic characteristics across the images.Then the process continues showing threshold marked of the regions and displays the Image compression quality across selected instances for standard image values as resultant dataset.This proposed technique shown the better results in case Image compression constraints (multi-level threshold, MSE, FRR) by the existing techniques.
Cultural participation during the spring lockdown of 2020 in France

The lockdown due to the out-break of Covid-19 has changed the everyday life, modifying timetables, working patterns and schooling at the same time. For a while people have been deprived of ‘in-real-life’ cultural experiences: it was indeed impossible to visit a museum, or to go to a cinema as many premisses dedicated to culture, as well as many shops selling cultural goods, were temporarily closed. Spending more time at home meant one could allocate more time using digital resources on the other hand.The current study shows what cultural participation looked like during these weeks of lockdown in spring 2020 in France. It was carried out thanks to a special wave of a recurrent survey led by Credoc that coincided precisely with this moment in time in 2020 (the French institution Credoc – Centre de recherche pour l’etude et l’observation des conditions de vie – collects data on living conditions every quarter of the year from a sample of circa 3000 individuals aged 15 and above). The data from the 2018 survey on cultural participation have also been included in the analysis in order to put the 2020 lockdown situation in perspective with a recent and more usual situation.It appears that people seized the opportunity to stay at home to develop their own creativity and self expression playing music, drawing, painting, writing a diary or a novel for instance and those who did were younger and from less privileged social backgrounds than usual. On average, cultural participation kept steady and even became more prevalent in social groups which were previoulsy less accustomed to cultural experiences. This latter statement is particularly noticeable for playing videogames and watching online videos, but not for reading books nor for reading the newspapers. Social networks became more popular, especially among older people (people aged 60 and above). The environment in which people were living at that time also had an influence on their cultural behaviour.All in all, it seems that in spite of a tough economic situation which led to widening the gap between social groups in terms of social inequalities, the outcome is slightly different when it comes to cultural participation. The time spent home enable to somehow bridge the gap in terms of cultural participation and cultural habits between the young and the elderly and between social classes.
DESIGN INFORMATION SYSTEMS OF PRODUCTION RESULTS IN THE RAJAWALI BROMO CONVECTION INDUSTRY, MAKASSAR

The development of the era where everything is instantaneous and fast as it is today must be supported by the development of increasingly sophisticated information technology. One of the functions of this technological development is to obtain accurate and fast information. But in fact, there are still companies / organizations that have not used computer technology as a work aid, such as the Bromo Rajawali Convection which still uses the manual method of writing employee data, namely data storage still using books. Therefore, the design of an employee data management information system is carried out that can help companies control the production data of each tailor employee. The method used in this research is the Waterfall method. It is called a waterfall because the steps that are passed must wait for the completion of the previous stage and run sequentially, for example the design stage must wait for the completion of the previous stage, namely the requirements stage [1]. The Waterfall method consists of 5 stages, namely Analysis, Design, Coding, Testing and Maintenance. The purpose of this study is to design an information system that can make it easier for companies to write down employee production data accurately. From the design results, there are two factors that support the running of the system, namely administration and production data, the input form available on the system that has been designed, namely the login input form and the employee data input form, while the output form contains complete data related to employee personal data and employee production data. With the creation of a management information system in writing data on employee production, the Rajawali Bromo Convection can accelerate the search for more accurate data in the future, and applications made later by the company can be used properly as one of the employee production data systems
Efficiency of singularity and PCA mapping of mineralization-related geochemical anomalies: a comparative study using BLEG and &lt;180μm stream sediment geochemical data

In gold (Au) exploration, the analysis of both bulk leach extractable gold (BLEG) and acid-extractable Au in the <180μm stream sediment fraction are the two most common approaches. The Eskişehir- Sivrihisar region in Western Türkiye hosts several orogenic type mineral deposits. The purpose of this study is to delineate geochemical anomalies of ore-related elements and track their dispersion, which may lead to discovery of unknown ore deposits. This research also compares the capability of conventional statistical and principal component analysis (PCA), with concentration area (CA) and number-size/concentration (N-S/C) fractal methods as well as singularity index method to differentiate anomalous and background Au distributions. Known Au mineralization in the region of interest is strongly reflected in stream sediment BLEG Au patterns, which have robust singularity indices with C-A and N-S multifractal modeling and PCA. A hundred % of the Au deposits were detected using either BLEG Au and Ag singularity index mapping with C-A fractal analysis whereas the factor analysis of which revealed 85% efficiency. Several strong Au-Ag anomalies defined by the singularity index and factor analysis in this study requires further follow up for the discovery of new deposits.