Reviewerly/exHarmony huggingface dataset:
Teaching Methodology for Designing Smart Products

This paper aims to explain the teaching methodology used for the course “New Product Development” at the Faculty of Mechanical Engineering in Skopje, Republic of North Macedonia, as a method that promotes project-based learning and design exploration as the most effective learning tools for designers and engineers. The main steps and the learning path strategy of the smart product development process, as practiced with the Industrial Design students, are provided and several project examples are elaborated in order to illustrate the advantage of the applied teaching methodology. The paper also includes an explanation of the state-of-the-art smart products from an aspect of their development for users’ acceptance, which is what the methodology is based on. The goal of this paper is to provide an overview of the external and internal learning sources used as a part of the methodology, as well as the special topics thought to support the project development process, in order to inspire other designers, professors and students to apply similar tools for smart product development. Such tools help increase their, as well as target users’ understanding of the technological aspect of smart items, and in addition, grow the general willingness to use such products, removing the skepticism and unfamiliarity barriers.
On the issue of the formation of professional competence of a teacher, taking into account the requirements of Worldskills standards

WorldSkills Championships set high standards of professional excellence, foster pride in their specialization, make them see the smallest details of problems, and optimize the student's path to a high level of professional activity. During the competition, it becomes possible to assess the level of formation of professional competencies of future graduates, to make suggestions and draw conclusions about the quality of professional and pedagogical training of students. The article presents the current trends in the development of secondary vocational education in the context of the transition to a new digital economy. International movement WorldSkills as a resource for the development of the teaching profession. The prospects and problems of training teachers in accordance with WorldSkills standards are described. Approaches to the assessment of professional pedagogical activity: the place of WorldSkills assessment tools and technology in the implementation of the educational process. The conclusion about the professional readiness of future IT specialists is a complex of personal skills, the development of which is the result of a targeted professional impact by means of specialized resources that allow for effective preparation for successful professional activity.
Intelligent Control Application of Unity + Playmaker Based on Physical Simulation Trolley Experiment

Physical simulation is also called physical simulation. The general simulation process is based on physical properties and geometry similarity, and other properties remain unchanged.Physical simulation in the field of education experiment through computer experimental equipment, teaching content, teacher guidance and students operation organic integration, through the simulation of experimental environment, strengthen the students’ understanding of physical ideas and methods, the structure and principle of instrument, can achieve difficult practical experiment, realize the practical ability, learning experimental skills, the purpose of deepening physical knowledge.Moreover, in experiments in other fields, physical simulation can reduce the experimental cost and increase the experimental volume, so as to obtain more physical data.As a game engine, Unity’s performance and its own strong physical simulation performance makes Unity a powerful physical simulation platform.This paper is based on the physical properties of the Unity itself and the visual programming plugin Playmaker, without code, and this method is also applicable to digital media related majors such as game production.It greatly reduces the threshold of interactive programming, simplifies the realization difficulty of small car control in physical simulation, and truly achieves the combination of art and technology.
Topical Problems of Education System Adaptation to Actual Social Changes Conditions

The purpose of this study is to analyze the training models of contemporary Russian organizations. As a hypothesis, it was suggested that despite the general understanding of the need to activate the processes of education and development of human capital in Russia at the macro level, models that consider labor resources as an exclusively social factor prevail at the micro level, there is no understanding of its economic efficiency, which prevents effective hyper-cybersocialization. To test this hypothesis, we studied the training models used in a number of organizations in Moscow and the Moscow region. The methodological basis of the research was the approaches outlined in the concept of “Industry 4.0”, the theory of human capital and resource theory. In order to overcome the identified problems, a systematic approach is needed that combines efforts of the state, business, trade unions and public organizations.
Systematic Evaluation of Research Progress on Technology-Enhanced Language Learning: Content Analysis and Knowledge Mapping

Owing to the recent advances in information and communications technologies, technology-enhanced language learning (TELL) research has resulted in diverse theories and empirical evidence, showing the complex and dynamic nature of TELL. The retrospective amount of TELL research literature is ever-growing, making it difficult to produce a comprehensive overview. However, knowledge mapping and clustering technologies are capable of visualizing and structuring research literature on a large scale. Therefore, based on 1,295 SCI/SSCI peer-reviewed TELL research articles from 1995 to 2019, we aim to systematically investigate and map the TELL literature to generate implications and insights into future research. Results identify recent major TELL research issues like technology-assisted vocabulary/word learning, computer-facilitated communication, language learning driven by applying computers, virtual reality, mobiles, and digital games, as well as a focus on learners and the use of experimental design. Additionally, scholars are advised to pay attention to issues like robots-assisted language learning, multimodal strategies for language learning, synchronous technologies for language learning, anxiety towards TELL, and artificial intelligence in TELL.
Automatic Searching of Deep Neural Networks for Medical Imaging Diagnostic

Medical imaging diagnosis is the most assisted method to help physicians diagnose patient diseases using different imaging test modalities. But Imbalanced data is one of the biggest challenges in the field of medical imaging. To advance this field, this work proposes a framework that can be used to find the optimal DNN architectures for a database with the challenge of imbalanced datasets. In our paper, we present a framework for automatic deep neural network search for medical imaging diagnosis.
Image Registration with Conditional Adversarial Networks

In image process, as an example, once combining the data content of image, we tend to have an interest within the relationship between 2 or a lot of pictures. Registration may be an elementary task in image process wont to match 2 or a lot of photos taken, as an example. CAN are investigated as a general-purpose answer for image version problems. Such systems were not just taking in the mapping from input picture to yield picture, yet additionally, gain proficiency with a misfortune capacity to mentor this mapping. Such things make it possible to use a similar kind of generic approach to traditional types of problems which requires very less or different loss formulations. We also show that the approach used here is very effective for image synthesizing from the label maps, and also we reconstruct the objects from edge maps, and colorizing pictures, among different errands. To be sure. Further showing its wide materialness and simple selection without the requirement for parameter tweaking. As a network, it's never again a hand engineer for our mapping capacities and with the assistance of this we can accomplish powerful result without hand-designing our misfortune work.
Survey Paper on Touchify: Smart Solution to Convert Any Surface into Touchscreen.

The project is to create affordable and easy to set up touch interface on any flat surface. The project mostly uses commonly available items that most people should have access to. Main part of this project is "runtime" application that uses two neural networks: vision based and sound based. Vision based neural network is used to track pointer on the screen. Sound network is used to detect events such as knocking on screen that will be recognized as mouse click and scratching that will be recognized as moving cursor with left mouse button pressed. Considering that the overall cost of this project is abysmal compared to commercially available touch boards, I think that it can be used for educational purposes in poorer or developing countries. We have used Open CV, Qtcreator, TensorFlow. It also can be used to digitize content of traditional "analog" blackboard.
Research on Accurate Prediction of Operating Energy Consumption of Green Buildings Based on Improved Machine Learning

Aiming at the problem that the current prediction model constructed by the current accurate prediction method of green building operation energy consumption is relatively backward, resulting in large errors in the prediction results, an accurate prediction method of green building operation energy consumption based on improved machine learning is designed. Box plots and data-driven systems were used to complete data collection and preprocessing of energy consumption for green building operations. The gray correlation function is used to analyze the parameters of building energy consumption. Improve machine learning algorithms and build energy consumption prediction models. To date, the design of an accurate prediction of green building operation energy consumption based on improved machine learning has been completed. Experiments have confirmed that the method in this paper can accurately predict the energy consumption of green buildings and improve the efficiency of prediction.
Summing Up

The work presented in this book is based on copy-move forgery detection (CMFD) in digital images. We find that CMFD is a popular research area due to increase or development in the image handling software technology, and the requirement of this can be seen by the rapid publications in the last 5 years.
Memory hot-zone and its application to accelerate the convergence of KSM for VM consolidation

Memory deduplication, which detects and removes redundant memory pages, can efficiently increase the efficiency of memory usage. It is often used with virtualization technologies, such as virtual machines (VMs), to improve their memory utilization. However, current memory deduplication systems, such as KSM (Kernel Samepage Merging), suffer the problem of either slow convergence or high CPU usage. In this paper, we proposed an algorithm, called hotscan, to accelerate the convergence of KSM for VM consolidation. We have observed that the pages have higher chance to be merged among different VMs are clustered in certain memory regions, called memory hot-zone. Based on this observation, hot-scan changes the scanning rule of KSM to check the pages in hot-zones of all VMs first. A novel data structure, called transpose list, is proposed to efficiently carry out the new scanning pattern. Experiments show that our method can accelerate the speed of deduplication 20% to 30% faster than the vanilla KSM without consuming too much additional CPU resource.
Online training of students in a modern university

The presented article reveals the peculiarities of foreigners in a modern university, and pedagogical successes and means of training foreign students in the conditions of a modern university with online learning. The idea is emphasized that politics, economics, education, medicine, culture have been filled with new content and technology of implementation in the event of global competition between different countries, trends in world development of the importance of a person’s intellectual resource. Innovative changes in the educational sphere in the context of globalization, the impact of the pandemic on this process are considered. The formation of a new paradigm of the educational process in universities, including changes in both the content and technological components of the process of teaching students in modern universities, is proposed. The importance of introducing innovations into the educational process, including in the training of foreign students, is shown. The experience of professional training at the Saratov Agrarian University named after N.I. Vavilov is analyzed. The forms of international cooperation in the conditions of this university with various countries are revealed. The stages, forms and means of online education of foreign students are considered. The relevance of the problems of this article is to consider such an innovation as online student education. The theoretical significance of this article lies in the disclosure of the content and technological features of on-line teaching of foreign students in university conditions to various disciplines. The practical significance lies in the substantiation of the methodology of teaching students.
Petrogenetic Studies of the Basement Rocks in Jimgbe and Environs, Northcentral Nigeria

Geochemical and petrographic studies of Basement rock outcropped at southeastern Jimgbe have been carried out with the aim of characterizing and delineating the petrogenesis of the basement rocks. Field results with Facies analyses of the basement rocks in the study area revealed four (4) dominant rock units: Porphyritic granite, Migmatitic gneiss, Granite gneiss and Biotite gneiss. The minor rocks include quartzo-feldspartic intrusion and quartz vein. The area has different structures such as fold, fracture and foliation which trends NW-SE and NE-SW direction, this is allotted to the Pan-African Orogeny imprints. Fourteen (14) analyzed for petrographic method and twenty-four (24) samples were analyzed for major elements using XRF geochemical method. The petrographic analysis result showed that the four rock types are granitic in origin due to their high quartz and feldspar contents. The major mineral compositions are quartz, plagioclase, microcline and biotite. Results of geochemical studies shows that the average oxide percentages are; SiO2 (69.25%), Al2O3 (12.41%), CaO (5.72%), Na2O (3.25%), K2O (3.76%), MgO (2.76%), Fe2O3 (1.79%), TiO2 (0.28%), MnO (0.33%) and P2O5 (0.47%). These results showed that the rocks are calcic, and are also of high K-Calc alkaline in nature, the rocks majorly plot in the eugeosynclinal field except for sample T4 which plots in the sedimentary field. They are mostly S-type peraluminous rocks except for T11 which is an I-type peraluminous rock and all plot in the Granodioritic field.
Privacy Preserving Consensus Scheme for Dishonest Nodes in System

Average consensus algorithm is widely used in distributed systems, but it has privacy leakage problems. Although the existing consensus schemes provide privacy guarantee for nodes, most schemes rely on the assumption that participating nodes follow the consistency rules and there are no dishonest nodes in the system. When there are dishonest nodes, the consistency process is easily contaminated. Aiming at the system with dishonest nodes, this paper designs a privacy protection consistency scheme. This scheme uses homomorphic encryption to encrypt the state and then performs ciphertext operations to ensure node privacy. At the same time, it uses a dishonest node detection mechanism to limit the improper behavior of nodes through initial state detection and consistency process detection. Reduce the pollution of dishonest nodes and ensure bounded errors when there are undetectable dishonest nodes. Experiments have verified the effectiveness of this scheme, and it has better convergence in the face of dishonest nodes.
UAV remote sensing image Rural homestead detection based on deep learning

With the implementation of the rural revitalization strategy, the revitalization of rural homestead utilization is extremely important, master the regional location, quantity, size and distribution of rural homestead is a necessary prerequisite for the revitalization of rural homestead utilization. To detect rural homestead in UAV remote sensing image, it is necessary to seek a method that can automatically learn image features from a large number of samples and obtain the most effective feature information in the image, Deep learning is an algorithm that can automatically learn effective features from a large amount of data. In this paper, the SSD_MobileNet deep learning model is trained using massive UAV remote sensing data to realize intelligent detection of rural homestead. The experimental results show that the accuracy of the model is more than 90%, which can meet the needs of rural homestead detection in practical work.
PENGUJIAN API WEBSITE UNTUK PERBAIKAN PERFORMANSI APLIKASI DITENUN

The DiTenun application is an intelligent device for producing Indonesian weaving motifs which was built in 2016 entitled "Intelligent Device for Producing Indonesian Weaving Motifs". Seeing the existence of problems in the DiTenun application where performance becomes less good when the number of users increases, it is carried out to perform performance testing with Load Test levels in virtual user numbers. The server used in the DiTenun application is a server from the DEL Institute of Technology, so that the development of the DiTenun application comes from the IT DEL server. For now, the DiTenun application uses the application of the API as a means and process of development and development carried out by the developer. Therefore, in this study, API testing will be carried out on the DiTenun application by measuring the level of performance usingJMeter to do the Performance test and measuring the level of the number of virtual users interacting with the system simultaneously using the Load Test. The researcher will also measure the baseline of the DiTenun application web service from the API response time based on the data load being called. After the analysis, based on the performance testing performed on the API using the Load Testing method, it was found that the performance of most of the APIs decreased with the increase in the number of users accessing, although no errors were found in the tests carried out. As for the results of the baseline web service measurement, the researcher obtained the results of the response time which can be used as a reference for an API that will be run in a system on the server that has been used by the researcher. The result could be used by DiTenun to improve the performance of DiTenun.
Authenticated Encryption to Prevent Cyber-Attacks in Images

The increased usage and availability of multimedia-based applications have led authentication and encryption to gain considerable importance. Cryptography plays an important role in protecting images from theft and alteration. Digital images are used in a large number of applications such as education, defense, medicine, space and industry. This chapter aims at providing a secure authenticated encryption algorithm for the storage and transmission of digital images to avoid cyber threats and attacks. The designed algorithm makes use of the deep convolutional generative adversarial network to test if the image is a fake image originated by the intruder. If found fake exclusive OR operations are performed with the random matrices to confuse the intruder. If the image is not fake, then encryption operations are directly performed on the image. The image is split into two four-bit images and a permutation operation using a logistic map is performed and finally the split images are merged together. Finally, exclusive OR operations are performed on the merged image using the convolution- based round keys generated to generate the concealed image. In addition, authentication is also achieved by calculating the mean of the actual image. The performance analysis shows that the designed technique offers excellent security and also helps in testing the authenticity of the stored images.
Later Applied Mark Found to Infringe Regardless of Declaration of Invalidity

Data Factory; with case note by Il Ho Lee
Traditional and Soft Computing Techniques for Image Enhancement

Now-a-days, there is a growing demand for image processing. The target of image enhancement is to find details present in images having low luminance for better image quality. Enhancement is required to improve the picture quality. In this process, we can enhance an image, by applying the suitable technique. In enhancement, there is a conversion in image contrast, quality, color vision, brightness, clarity etc. So we need image enhancement. A comparative survey is carried out in this paper, explaining traditional and soft computing techniques. This paper clarifies a study of traditional such as edge detection of an image and fuzzy logic based soft computing for improvement of an image. In the result section output of image is shown as edges using traditional as well as fuzzy. A small description is also study for picture improvement using different soft computing and optimization techniques such as Neural network, Convolution Neural Network, Ant Bee Colony, Particle Swarm Optimization etc. in literature survey and in comparative table. It is concluded that Image enhancement can be done by traditional method, soft computing and optimization method. Image enhancement has found various vision applications that have the ability to enhance the visibility of images. To enhance an image it is very important that image should be clear, so before using the enhancement techniques we should need to learn about the enhancement. So this paper described a survey of image enhancement with different techniques. In future scope of this paper we can find out different type of parameters like PSNR, MSE and execution time, also we can use optimization technique. We are also showing a comparison table of image enhancement based on traditional, soft computing and optimization techniques with its open scope.
Research on Face Pose Estimation Method for Virtual Try-on System

This paper proposes a 3D face pose estimation algorithm based on feature points, which realizes the angle estimation of human faces in any pose. It can accurately estimate within 30 degrees on 6 degrees of freedom, and provides the algorithm basis for a subsequent real 3D try-on.