Reviewerly/exHarmony huggingface dataset:
FPGA in Image Recognition System

With the rapid development of computer technology, digital image processing technology, and microelectronic technology, image processing systems with FPGA as the core have been widely used in various fields. This research is mainly based on the application of FPGA in image recognition system. Through the functional simulation of each module in the system, the received image data is processed and analyzed. Experimental data shows that the average consumption time of image recognition without FPGA array is 159.6 ms; after using FPGA, the consumption time is significantly shortened, and the average consumption time is 140 ms. It can be seen that FPGA has a significant improvement effect on image recognition and image information processing, and in terms of resource occupancy, the addition of FPGA significantly reduces the occupancy rate and shortens the recognition time.
Starting My Career

This chapter reflects on the start of the author's career. In March of 1972, the author received a bachelor's degree in economics from the University of Tokyo, and he joined the Bank of Japan on April 1. When he was considering where he would work after finishing his degree, a general aspiration to perform some public service with his economics training led him to the bank. The author spent the next thirty-nine years learning from many gifted colleagues. The author tried to give due regard to economic theory, to learn from others in the field, to focus on accomplishing the bank's mission through its operations, and to appreciate the global context and respect their relations with other central banks. Each of these lessons influenced the author when he later became the bank's governor.
IMPORTANCE OF DIGITAL COMPETENCES AND ATTITUDES TOWARD RESEARCH IN MEXICAN TEACHERS

The aim in our study was to determine the importance of digital competences and attitudes regarding research to teachers, according to various variables such as gender, age, and level of studies. A questionnaire was used to gather information from 28 teachers at the Escuela Normal de Educacion Primaria “Rodolfo Menéndez de la Peña”, in México. The questionnaire was developed based on Aldana y Joya (2011), and the GIDU-EDUTIC/IN research group from the Universidad de Alicante. The questionnaire comprises 48 questions on the importance of digital skills and 50 questions on attitudes towards research. All questions use a Likert scale with 5 answer options. Cronbach's Alpha was used to determine the reliability of the instrument. It was found that the questions related to the importance of digital competence an alpha equal to 0.912 and for the questions of attitudes towards research an alpha equal to 0.854. It was found that teachers considered important the five digital competences dimensions. It also was found that they considered that creativity and innovation as the most important dimension and the use and access of information as the less important. The participant teachers’ attitudes towards research were more neutral. It was found that the cognitive dimension was the one with the highest score, while the behavioral dimension the one with the lowest score. It is concluded that training needs are detected to improve their digital skills and their attitude towards research, the need for further research on the effect is perceived that could have for the development of research groups in this institution.
Efficient Gesture based Language Recognition using SVM and Lloyd’s Algorithm

undertaking in the field of human-computer interaction (HCI) and computer vision. 10 years prior to the undertaking appeared to be practically unsolvable with the data given by a single RGB camera. In this work, we have actualized a presumable exact strategy to perceive static gestures or image frames from a live camera or video data. As Hand Gesture Recognition is identified with two noteworthy fields of image processing and AI (machine learning), in this way, this report likewise refers to the different tools and APIs that can be utilized to implement different strategies and methods in these fields
Challenges of DeepFake Voice to Voice Forensic Identification

Deep learning; Deep fake Voice; Voice forensic identification
Effects of Subjective Memory Complaints, Depression and Activities of Daily Living on the Health-related Quality of Life in the Elder

Purpose: The purpose of this study was to investigate the effects of subjective memory complaints, depression, and activities of daily living on the health-related quality of life in the elder. Methods: A convenience sample of 183 registered elderly was obtained from a city. Data were collected using self-reported questionnaires during march 2019. Data were analyzed through the SPSS/WIN 21.0 program using descriptive statistics, t-test, ANOVA, Pearson’s correlation coefficients, and multiple regression. Results: The factors of depression(&amp;#61538;=&amp;#8722;.35, p ＜.001), and activities of daily living(&amp;#61538;=.28, p ＜.001) had the influence of health-related quality of life in the older. The total explanatory power was 48%. Conclusion: It was found that depression and activities of daily living were influencing factors in the health-related quality of life in the elder. Therefore, to improve their health-related quality of life, it is necessary to develop strategies to manage the depression and to strengthen and develop activities of daily living.
A Discussion of Data Sampling Strategies for Early Action Prediction

Action prediction aims to predict an ongoing activity from an incomplete video, which is an important branch of human activity analysis with the important application in a number of fields, such as security surveillance, human-machine interaction, automatic driving, etc. Due to time continuity, there are a large number of redundant frames in video action sequences, which often brings challenges such as low computational efficiency and noise for action prediction. Most of the existing works levarage dense sampling or sparse sampling for processing video frames and characterize actions. On the one hand, the dense sample-based method often introduces redundant noise for predictions, easily causing confusing of the action semantics. On the other hand, although sparse sample-based method can alleviate the problem of redundant noise to a certain extent, it ignores the impact of sampling rate on action representation. In this paper, we combine the two-stream network framework and the teacher-student network framework to build an action prediction model, and discuss the influence of action representation under different sampling rates for partial or full videos. In this way, we can select more appropriate frames for video representation and thus achieve more accurate action prediction. The method proposed in this paper has achieved the current state-of-the-art performance on the standard dataset, i.e., UCF101, which verifies the effectiveness of our method.
MATHEMATICAL SKILLS OF PRIMARY SCHOOL CHILDREN IN CONTEXT OF THEIR MOTOR SKILLS

Some researchers suggest a link between motor skill levels and academic achievement.Therefore, this research focuses on assessing the effect of motor skills on children's mathematical skills.The aim of the research is to explore and analyze relationship between mathematical skills and the level of motor skills in children attending primary schools in the Czech Republic.Confirmation of mentioned relationship could lead to improved position of school physical education, higher focus on well-performed motor skills and aimed intervention.Within the research were asked following questions: Is there a relationship between mathematical skills and the level of motor skills in children attending primary education?Are there gender differences in the monitored skills (mathematical or motor)?The research group consisted of 75 children in average age 9.48 ± 0.75 years.The level of motor skills was monitored by MABC-2 test battery.The cognitive ability test (CAT) was used to determine level of mathematical skills in children.Data were assessed by correlation analysis.Gender differences data were detected by t-test.Results were obtained within the project IGA_PdF_2021_017.The research results indicate gender differences in some of motor skills subtests, but not in the overall levels of motor skills.Significant differences were found in the level of mathematical skills in children, where girls achieved better results (p ≤ 0,01).Statistical analysis also confirmed some correlations between mathematical skills and some motor skills subtests.Although the research results revealed only weak or moderate correlations between the mathematical skills and some motor skills, further research implemented on larger group of primary-aged children is necessary for better understanding of this topic.Important thing is not to neglect the role of school physical education as it may affect academic achievement in children through improved mathematical skills.
Power System Video Encryption Scheme Based on Chaotic System

A power system video encryption scheme based on chaotic systems has been developed in this paper. This scheme uses 2D sine Logistic modulation mapping to scramble pixels in video frames. Then the image is divided into three layers, and diffused by a new chaotic system. Ciphertext image is added in the diffusion to enhance the security of the algorithm. Finally, the algorithm is simulated in MATLAB. By analyzing the simulation results, it is proved that the video encryption algorithm in this paper has good encryption effect and has important application value in the information transmission of power system. Finally, the application of this algorithm in video transmission of power system is expounded.
Application of Hybrid CTC/2D-Attention End-to-End Model in Speech Recognition during the COVID-19 Pandemic

In end-to-end speech recognition task, the goal is through a network, the input ㉠ 1,…, , calculate all output tags sequence ㉠ 1,…, corresponding probability, usually ≤ , ∈ , is a finite character set, the final output is one of the biggest probability tags sequence, namely
The quagmire of open access

Global intellectual property (IP) instruments, mostly favor a strong IP enforcement regime. While this is important, this chapter raises the need for Nigeria’s IP policies to embrace access to knowledge strategies. Scholarly works by authors are generally available but not easily accessible, thereby reducing their impact. This chapter explores the concepts of availability, accessibility, and impact of scholarly works by authors in developing countries (particularly Nigeria) and how it impacts the current access to knowledge movement. It examines how the structures and mechanisms around these concepts have constituted barriers to authors and users and recommends that Nigeria’s IP policy framework should adopt open access online publication strategies in addressing the problems of availability, accessibility, and impact. Arguments are based on a social contract and utilitarian perspective which see publication as the author’s readiness to make expressions of ideas available, accessible and impactful for purposes of seeking the greatest good for the greatest number of people. The chapter aims to demystify the open access quagmire around Nigerian works and suggests ways on how to navigate through the access/impact barriers and break the walls to enable not just availability but also accessibility and impact on works from developing countries.
Bureaucratization of science is unacceptable (notes after reading the book by V.N. Protasov “Methodological problems of dissertation defense (on the example of jurisprudence)”)

This article is the author&amp;apos;s reflections caused by the work of V.N. Protasov “Methodological problems of dissertation defense (on the example of jurisprudence)”. The monograph examines the general problems of bureaucratic management of science, education and the process of defending dissertations in modern Russia. According to the author of the article, V.N. Protasov highlighted a layer of problems that cannot be passed by.
Establishment of Path Planning Method Suitable for Earthmoving Work of Large-scale Dump Trucks

There is an urgent need to automate earthmoving works for large-scale six-wheeled dump trucks. At actual sites, a dump truck stops at a loading position, informed by the backhoe's backet, with its bed facing the backhoe. Therefore, it is necessary to plan a path including a turning back and rapidly replan according to the goal position change. However, there is no suitable path-planning method for earthmoving works of a large-scale six-wheeled dump truck. Here we propose a path-planning method that moves the dump truck forward and then backward to the working position. According to the goal position change, it also rapidly generates a path from the turning position to the new goal position. We confirmed the proposed path resembled the trajectory of human-operated dump trucks, and the time required for replanning was shortened. We also confirmed the autonomous dump truck could do earthmoving works in cooperation with a human-operated backhoe.
Latent Factor-based Rating Feedback Learning for Restaurants Recommendation

Nowadays, when people go out to eat, their choice of restaurant depends not only on taste, but also on many other factors.Therefore, mining what factors of the restaurant the users care about is a key problem for restaurant recommendation.This paper is engaged to mining the latent theme factors of restaurant the users care about and applying the result to restaurant recommendation.In this paper, we used LDA model to extract the latent theme features of the restaurants, calculated the similarity based on latent factors and rating feedbacks to make rating prediction and restaurants recommendation.This paper conducted an experiment with the review data from Yelp dataset, exploring the performance of the algorithm and the optimal theme number K. The results of the experiment showed that the algorithm achieved some improvement in rating prediction.To some content, applying the latent theme distribution to the problem of restaurant recommendation can solve the problem of data sparsity, decrease the computational dimension and raise the accuracy of rating prediction.
Research on A Joint Attribute Based Neural Network Model for Multi-class Voltage Violation

Abstract Electronic engineering technology is a symbol of modern technology, and a large number of electronic devices have been produced. This paved the way for the development of the Internet. This article analyzes the characteristics of the application of computer electronic engineering technology, and it analyzes the measures to strengthen the application of electronic engineering technology and the measures to promote the development of electronic engineering technology. In addition, this article also studies the teaching system design of electronic engineering technology.
Pioneering Document Delivery

The provision of materials through document delivery has become a critical issue for all libraries as the costs for materials skyrocket. This workshop described examples of pioneering document delivery from Maryland and Canada. The presenters provided examples of a public and a commercial document delivery system. [Article copies available for a fèe from The Haworth Document Delivery Service: 1-800-342-9678. E-mail address: getinfo@haworth.com]
Integration of Information Technology in the Public Music Curriculum of Secondary Vocational Schools under the Background of Information 2.0

With the continuous development of information technology, the development and reform of education informatization are imminent.Exploring the application of public music teaching methods in secondary vocational schools under the new model will play a specific role in improving teaching efficiency, improving students' music literacy, and improving teachers' information technology capabilities.Therefore, this article uses the secondary vocational public music course to explore the integration and feasibility of information technology in teaching.
Intrusion Detection Protocol Using Independent Outlier Ensembles

Numerous anomaly detection algorithms are used for detection of malicious networks’. Yet, a protocol to segregate suspicious and attacker networks is an essential enhancement in this domain. Therefore, this paper tries to generate a rule to differentiate suspicious, attacker networks and trusted networks. We used independent outlier ensemble algorithm for performing this segregation with random forest, AdaBoost, XGBoost and K nearest neighbours as the components of the independent ensemble design. When a user has to take caution about the network, the detection foot print is high. In such cases, logical OR operator helps to identify all the suspicious outlier points. However, for attacking scenarios, the detection foot print is low and AND operator detect only those points which are highly dangerous and action has to be taken by the user. We did evaluation of our algorithm with the help of CIDDS-001 dataset which an emulated dataset. Experiments show that our algorithm can successfully sort networks into suspicious, malicious and trusted ones. User can take caution for suspicious networks and can take action for malicious ones. Thus, this paper brings a new idea for classification of networks which is not addressed till now.
Flooding

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 58, Issue 4 p. 23401B-23401C Policy and Practice Flooding First published: 12 June 2021 https://doi.org/10.1111/j.1467-6346.2021.10013.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume58, Issue4June 2021Pages 23401B-23401C RelatedInformation
Investigation of the hydrogeochemical processes affecting the Nubian sandstone horizons: West El Mouhoub, Western Desert, Egypt

The Nubian Sandstone Aquifer System (NSAS) is the world's largest known fossil water aquifer system.It is located underground in the Eastern end of the Sahara Desert and spans the political boundaries of four countries in north-eastern Africa.NSAS covers a land area spanning just over two million km 2 , including north-western Sudan, north-eastern Chad, south-eastern Libya, and most of Egypt.Containing billions of cubic meters of groundwater, the significance of the NSAS as a potential water resource for future development programs in these countries is extraordinary.Therefore, understanding of the hydrogeochemical processes and continuous monitoring of its groundwater regionally and locally is so vital.The present study has been conducted to investigate these processes in a pilot area of Western Desert of Egypt (West El Mouhoub).To accomplish this objective, surface water and groundwater samples were collected and analyzed to estimate the chemical properties of these water samples.The ion ratios, water type, facies, hypothetical salts, geochemical diagrams were integrated with geostatistical analyses [factor analysis (FA) and correlation analysis (CA)] to characterize the hydrogeochemical processes that are controlling the Nubia sandstone aquifer system (NSAS).The obtained results revealed that, the Sabaya and Six Hills Formations represent the main aquifer horizons where the groundwater exists under confined conditions.The groundwater within these aquifer units is mainly fresh and the salinity increases from southeast to northwest direction in the Sabaya Formation groundwater.Both the hypothetical salts assemblages and the groundwater genesis confirm that there is a connection between the Sabaya and Six Hills Formations in the investigated area.The results show a chemical development from the groundwater that dominated by bicarbonate salts to that dominated by chloride salts.The main process controlling the groundwater is the rock-water interactions.
Analysis of the Effects of Control Parameters Variation of ABC Algorithm Used in Filter Bank Design on the Performance

In this work, Cosine Modulated Filter Bank (CMFB) is designed using Artificial Bee Colony (ABC) Algorithm. In heuristic algorithms, one of the important factors affecting the performance of the algorithm is to determine the control parameters of the algorithm. The performance of the designed filter bank is investigated according to the change in the control parameters of the ABC Algorithm. The effects on the filter bank performance parameters of the change in the control parameters are detailed.
TELECOMMUNICATIONS: Ethiopia

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 58, Issue 5 p. 23454A-23455C Communications and Transport TELECOMMUNICATIONS: Ethiopia First published: 04 July 2021 https://doi.org/10.1111/j.1467-6346.2021.10082.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume58, Issue5July 2021Pages 23454A-23455C RelatedInformation
1.5-THz-Bandwidth Digital Photonic Quantum Memory

Quantum optical memories are a key component of quantum information applications. Here we develop a system with multiplexed free-space storage cavities, able to efficiently store single photons for up to 12.5 µ s over several nanometers of bandwidth.
On Scientific and Technological Paradigms Competitions in Ideological Control in Science Conditions

Modern science is, as Thomas Kuhn pointed out in his fundamental work The Structure of Scientific Revolutions, a science that develops in stages: “scientific revolution” – “nor­mal science” – “scientific revolution”. During periods of normal functioning of science, the rules of testing and testing show established and perceived without reflection para­digms, but in the case of technical disciplines, this rule does not work, since technical paradigms do not change according to the same rules as other scientific paradigms. To change technical paradigms, you only need to accept them by the expert community – you also need to accept them by technical consumers. The article discusses the difficul­ties of defining the concepts of “technology” and “technical knowledge” as knowledge about artifacts, their use and the consequences of their use (Bernhard Irrgang). On two examples of the control of technical paradigms in two totalitarian regimes of the twenti­eth century (Lysenkoism, or Lysenkovshchina and “Aryan physics”), the role of para­digms in the situation of ideological control is presented. In these cases, we used at­tempts to “correct” genetics and quantum physics (more precisely, to completely abandon it), respectively. Of course, this control brought biology in the Soviet Union and physics in Nazi Germany to the brink of disaster. In this article, with the help of Gisle Solbu's theory of epi-knowing (knowledge at the general educational level), we propose solutions to the problem of purposeful ideological interference in the scientific and ideo­logical adjustments of not only scientific paradigms, but also scientific paradigms.