Reviewerly/exHarmony huggingface dataset:
Colorization of Near-Infrared Images using Generative Adversarial Networks

Near-infrared cameras can get more detail than RGB cameras even in dark environments. However, near-infrared images are black-and-white images, and RGB information is recommended when presenting information to humans. In recent years, there have been a few studies on the colorization of near-infrared images. Most of the results of previous studies are only when NIR and RGB images are paired. Therefore, in this paper, we proposed the conversion method that does not use pair images based on the cycle generative adversarial network. We performed validation experiments using two networks and evaluated by mean angle error. In addition, object detection was performed on the colorized image, and the number of detections before and after colorization was compared. As a result, it was found that it is necessary to perform the conversion without breaking the shape while maintaining the edges of the original image.
Experimental varification of autonomous movement based on selective tracking point in Pure Pursuit Algorithm and Dynamic Window Approach

The method that combines Pure Pursuit Algorithm and Dynamic Window Approach (DWA) is effective for realizing stable running of the robot. However, DWA has the problem that it is caught by the local minima when surrounded by obstacles. In this study, we examine the solution of the problem by effectively selecting the tracking point of Pure Pursuit Algorithm. The experimental results in the real environment showed that the proposed method works effectively.
Support System for Disable People

Technologies are advancing day by day at an incredible rate, but in respect of deaf and special people-related technologies advancements and new technologies are needed, such as a program that effectively translates the sign language to both text and audio. In this research paper authors have proposed a device that help in communication for deaf and dumb people and reduce the barrier of communication. Different people have trouble communicating with the person who does not know sign language, therefore, using this device they can communicate using gesture which will translate the gesture and display the text on the LCD and voice by speaker. The device is both composed of hardware and software.
The role of accounting knowledge in supporting and enhancing accounting practice in light of the internationalization of accounting education

The study aimed to identify the role of accounting knowledge in supporting and enhancing accounting practice in light of the internationalization of accounting education, in order to answer the questions and test the hypotheses of the study, the researchers relied on the descriptive-analytical approach, and to obtain the relevant data, a questionnaire was distributed after its evaluation to the study population.&#x0D; The results of the study proved that there is a role for scientific, technical and practical accounting qualification in promoting accounting practice in light of the internationalization of accounting education.&#x0D; The study recommended the necessity of taking into account the development plans in universities to provide time for faculty members in the accounting departments in Palestinian universities to develop their scientific knowledge in line with the internationalization of accounting education.
AI-based Hybrid Model for Denoising Particle Trajectories Reconstructed from Magnetic Particle Tracking Method

Magnetic particle tracking (MPT) is a recently developed method that can measure translation and orientation of a magnetic-labeled particle in an opaque environment like that of fluidized bed flows. The reconstructed trajectories often contain uncertainties due to the presence of noise in measurements of magnetic sensors. We use neural networks to denoise these trajectories. The trajectories in our experiments are obtained from a particle suspended in an upward flow. Two methodologies are used for denoising, one with a gated recurrent unit (GRU) based neural network and the other, a combination of wavelet transform (WT) and GRU. Both the methods perform well in reducing the noise and fluctuation levels in the trajectories. We also show that neural networks besides reducing noise, are able to capture sudden changes in particle trajectory which are inherent in fluidized beds.
ESTABLISHMENT OF A LIBRARY TO IMPROVE THE QUALITY OF HUMAN RESOURCES IN APUAI VILLAGE

Besides formal education such as schools and special training, education can also be obtained through libraries and other media such as the internet or television to access knowledge and information. Apuai Village, Aranio District, Banjar Regency is an underdeveloped village where people challenging to access the internet or telephone signals, and access roads to and from the village are not accessible. This condition is a significant obstacle to transferring information and knowledge from outside. To meet the community's needs in obtaining knowledge, the community service team took the initiative to establish the Apuai Village library. The hope is that the existence of this library can help the community, especially school children in the village, to have insight into creative thinking, cultivate spirituality, foster interest in reading, increase the efficiency and effectiveness of learning in the library. It is also hoped to increase entrepreneurship awareness for the readers for the local community with a low level of education. This community service activity also contains counseling to increase interest in reading. By diligently reading, people will find new knowledge to improve their ability to manage their natural and human potential. As a collection material, our library also provides books related to products and books on marketing strategies and product packaging to increase competitiveness. So far, the community can process natural products into something with better power. They also have difficulty in terms of packaging and marketing. It is because of the difficulty of access to information on attractive marketing and packaging techniques due to the problem of access to transportation, information, and telecommunications in this village.
VILLAGE GROUPING BASED ON THE NUMBER OF HEALTH FACILITIES IN WEST JAVA USING K-MEANS CLUSTERING ALGORITHM

Health is very important for the welfare and development of the Indonesian nation because as a capital for the implementation of national development, it is essentially the development of all Indonesian people and the development of all Indonesian people. Due to the outbreak of the Covid-19 virus, many health facilities must be provided for patients. Of course, the government must pay attention to the health facilities that can be used in every district/city in West Java in the future. Therefore, to determine the level of availability of sanitation facilities in each district/city in West Java, we need a technology that can classify data correctly. One method of data processing in data mining is clustering. The application of clustering to this problem can use the K-Means algorithm method to group the most frequently used data. The purpose of this study is to classify sanitation data on the highest sanitation facilities, medium sanitation facilities, and low sanitation facilities, so that areas/cities that are included in the low cluster will receive more attention from the government to improve/provide sanitation facilities.
Multi-UAV scalable platform for heavy load transportation

In transporting a heavy load, instead of utilizing a conventional unmanned aerial vehicle (UAV), this research introduces the new scalable UAV design for lifting and transporting applications. The main concept focuses on reconfigurable control layers with multiple UAVs arranged in hierarchical order. Data transmission across layers is responsible for sending desired actuator outputs to the mixer located in the low-layer UAV units. Moreover, in this scalable UAV platform, each layer has different control methods for each unique controlling task. With several small propeller configurations, it gains flight safety, stability and mobility while achieving high thrust for heavy load lifting application.
Evolution of the "Screen-on-Screen" Motif in the Cinema

The motif of a screen as an element of the figurative matter of film is analyzed in the article. The author focuses on the period of silent cinema, when the main models of the use of "screen-on-screen" are formed. This motif can have different interpretations. The diegetic screen plays the role of the magical level of reality. It is also shown as a part of technical devices, fantastic and real. But the most significant and dramatic type of diegetic screen is precisely the screen in the cinema, the screen reality of cinema. The article examines the evolution of the attitude to screen reality: from a dismissive attitude, understanding it as a strange attraction to the perception of screen reality as the highest, ideal reality, getting into which becomes a dream for the characters.
Target-Driven Navigation Based on Transformer

This paper presents a target-driven visual navigation technique that can exploit long-term history for navigating an agent to a given target image. In particular we use Transformer architecture that has been developed in the natural language field and can handle long-term temporal dependencies. Experimental results showed that the use of Transformer improves the navigation performance to new target images by utilizing long-term history and also improves the data efficiency, especially in large-scale environments. We also conducted an ablation study to show how the number of training frames affects the navigation performance. This results in the accuracy of the proposed method improving while the baseline decreases as the number of training frames increases.
Image Captioning using Deep Learning for the Visually Impaired

Describing the content of an image has been a fundamental problem of Machine learning that connects computer vision and natural language processing. In recent years, the task of object recognition has advanced at an exceptional rate which in turn has made image captioning that much better and easier. In this paper, we have discussed the usage of image captioning using deep learning for the visually impaired. We have used Convolutional Neural Networks along with Long Short-Term Memory to train and generate captions for images along with a text-to-speech engine which makes the experience of visually impaired users who are browsing the internet much smoother. We discuss how the model was implemented, its different components and modules along with a result analysis conducted on a set of outputs peer reviewed by our colleagues, friends and professors.
Study on the impression given by walking motion in a 6-legged walking robot

In this study, we evaluated the impression given by walking of a 6-legged walking robot. As a result of creating 6 types of walking simulations and conducting evaluation experiments on about 30 subjects, it was found that the impression is improved by considering regular walking and interlocking of how to put out the legs.
Convolution and Related Theorems

A concise introduction to geophysical data processing - many of the techniques associated with the general field of time series analysis - for advanced students, researchers, and professionals. The textbook begins with calculus before transitioning to discrete time series via the sampling theorem, aliasing, use of complex sinusoids, development of the discrete Fourier transform from the Fourier series, and an overview of linear digital filter types and descriptions. Aimed at senior undergraduate and graduate students in geophysics, environmental science, and engineering with no previous background in linear algebra, probability, or statistics, this textbook draws scenarios and datasets from across the world of geophysics, and shows how data processing techniques can be applied to real-world problems using detailed examples, illustrations, and exercises (using MATLAB or similar computing environment). Online supplementary resources include datasets for students, and a solutions manual and all the figures from the book as PowerPoints for course instructors.
Internal Mechanics of Neural Network Processing

This chapter discusses the inner workings of neural network processing. It shows how a network is built, trained, and tested.
Fusion of MCL and End-to-End Localization Equipped with Monte Carlo Dropout

This paper presents a hybrid localization method using model- and learning-based methods. Monte Carlo localization (MCL) is used as a model-based method. End-to-end (E2E) learning is used to implement a learning-based localization method. Monte Carlo dropout is applied to the E2E localization and its output is treated as a probabilistic distribution. This distribution is then used as a proposal distribution and the E2E localization estimate is fused with MCL via importance sampling. Experimental results show that both the advantages are simultaneously leveraged while mitigating their disadvantages.
A Study on the Knowledge, Attitude, Perceived Risk, and Preventative Behavior of COVID-19, Among Clinical Laboratory Science Students in Some Regions of South Korea

This study aims to investigate the knowledge, attitude toward and perceived risk of COVID-19 in clinical laboratory science students. This study also attempts to identify the factors influencing the performance of infection prevention behavior. From October 1st to October 30th, 2021, a face-to-face survey was conducted on the students in the Department of Clinical Laboratory Science. A total of 150 students participated in this study. There was a higher percentage of female students (86.7%) than male students (13.3%). For data analysis, independent t-test, one-way ANOVA analysis, Pearson’s correlation analysis, and multiple regression analysis were used. The percentage of correct answers in relation to knowledge about COVID-19 was 88.5%. In response to the questions about attitude towards COVID-19, the result was 73.8 points (mean). As for the questions about risk perception the result was 35 points (mean). When it came to the question about prevention behavior the result was 80.7%. It was confirmed that the preventative behavior for COVID-19 did not significantly correlate with knowledge of COVID-19 (r=0.040, p=0.629) and had a significant net correlation with attitude toward and perceived risk of COVID-19 (r=0.291, p<0.001). A stepwise multiple regression analysis was conducted by adding attitude toward and perceived risk of COVID-19 to the correlation analysis, where factors such as current year of study, living status, and college life satisfaction were first encountered. It was concluded that living status (β=0.25, p=0.003), current year of study (β=0.17 and p=0.037), and attitude toward and perceived risk of COVID-19 (β=0.19, p=0.019) were significant. The results of this study can be used as data for future clinical laboratory science students as well as the prevention of COVID-19 infection. These results can also be used for education on new infectious diseases and the development of COVID-19 infection prevention programs.
Securing and Protecting AI Environments

Once upon a time, IT and information security were simple. IT security specialists deployed malware agents and set up a firewall – and the organization was safe. Today, information security is much more exciting and complex, requiring everyone’s contribution. Even data scientists in AI organizations must be aware and contribute to security – and AI managers might suddenly get accountable and responsible for proper security measures for their organizations’ AI infrastructure. The pressure is ubiquitous, but not the necessary know-how – especially not in AI organizations. To complicate matters, many senior IT security and risk professionals do not have an in-depth understanding of AI methodologies and techniques they assess. A dilemma for which this chapter provides the solution by addressing four topics:
On tendencies of the Russian academic neography development in the XXI century

The report characterizes present-day condition of the modern academic neography and focuses on the set of changes of principles and approaches in compiling of the dictionary of new words. Furthermore it covers the work of searchable database ‘Russian Academic Neography’.
Concluding Remarks

This Chapter concludes the book. We present a synopsis of the topics, followed by few interesting problems that could be useful for future research.
Towards Synthetically Trained Convolutional Neural Networks for Induced Earthquake Detection and Localization

Summary The seismic hazard associated to induced seismicity becomes increasingly important as the sites for the exploitation of natural resources, geothermal energy and CO2 injections move closer to urban areas. Successful, reliable and fast detection and earthquake localization methods are a necessity for optimal safety and productivity. The many advances in artificial intelligence in various fields and their capability to apply their learned features to new data in real time is intriguing. We propose to use synthetic earthquake response data modelled using the velocity model and same receiver configuration as in the field to train a convolutional neural network to classify the source to its corresponding 3-D cluster. Once training is completed the network is applied to the corresponding field data. The results show promise that this is indeed feasible as 4 out of 5 events were correctly classified and the missed event was only missed by a little. This method returns a possible cluster inside which the exact hypocenter is located. Therefore, this approach can be used in combination with grid-search type hypocenter location methods to speed up the search by limiting the possible search space.
Hubungan Keceradasan Emosional dengan Kemampuan Beradaptasi Dalam Pembelajaran Daring di SMPN 1 Kota Bogor

This study aims to describe the relationship between emotional intelligence and adaptability in online learning in class VII at SMPN 1 Bogor City. The method used in this research is a quantitative method with a correlation approach. The sample in this study was 25% of the total population of 288 (72 respondents) using simple random sampling technique. This data collection technique uses a questionnaire (questionnaire). Emotional intelligence using a questionnaire with the results of the validity test of 15 statement items, there are 14 statements that are proven valid and the reliability test results of the coefficient of 0.750 are declared reliable. While the ability to adapt in online learning using a questionnaire with the results of a valid test of 15 statements proved valid and a reliability test result of 0.762 was declared reliable. Prerequisite test is done by normality test and linearity test. Data analysis used the analyze correlate-bivariate technique on SPSS 26 with a significance level of 5%. The results showed that there was a positive and significant relationship between emotional intelligence and adaptability in online learning as indicated by the r-count value of 0.623 which means it has a strong correlation. And r-count is greater than r-table (0.623 &gt; 0.232), then Ho is rejected and Ha is accepted. And the two variables also have a significant relationship because the significant value (p-value) is 0.000 &lt;0.05, then Ho is rejected and Ha is accepted.&#x0D; Keyword: Emotional Intelligence, Adaptability, Online Learning
THEORETICAL AND METHODOLOGICAL FUNDAMENTALS OF FORMATION OF SOCIAL AND CULTURAL COMPETENCE OF STUDENTS

Мақолада ижтимоий-маданий компетентликни шакллантиришнинг назарий-методологик асослари ёритилган. Шунингдек олий таълим муассасаси талабаларида ижтимоий-маданий компетентликни шакллантиришда муомала маданиятининг ўрни ва зарурий томонлари тахлил қилинган.
An Aggregate Signature with Pre-communication in the Plain Public Key Model

Aggregate signatures without the bilinear map is a challenging and important problem in aspects of practical and theoretical cryptology. There exists only one aggregate signature which does not use the bilinear map, however, the scheme requires a non-standard cryptographic assumption in the security proof. In ProvSec 2020, Takemure et al. proposed a new variant of aggregate signatures, the aggregate signature with the pre-communication (ASwPC), to realize the security proof from a standard assumption. The ASwPC requires signers to interact with each other to share a temporary randomness before deciding their messages to be signed. After the pre-communication, each signer can start the signing process individually. They gave an instantiation of ASwPC based on the discrete logarithm (DL) assumption, and its security is proven in the random oracle and the knowledge of secret key (KOSK) model.Although the previous construction achieved the provable security from the standard assumption, it requires a slightly stronger security model, the KOSK model. Thus we aim to construct a new ASwPC scheme whose security is proven in the plain public key (PPK) model which is the standard security notion of the aggregate signature. We employ the DDH assumption rather than the DL assumption and the property of the decisional assumption helps us to apply the lossy key technique to construct a security proof in the PPK model.
Developing General Cultural Competencies As A Condition For Future Successful Professional Activity

The paper considers the problem of training effective and successful specialists. The success of a specialist's professional activity depends on the development of general cultural competencies that ensure the specialist's ability to transmit, understand and analyze information. The necessity of developing the integrative trait of the specialist's personality (operational competence) as the basis for the successful implementation of professional functions, the ability to avoid professional risks and situations of uncertainty is proved. The components of operational competence are defined: cognitive, control and evaluation, and communicative. The paper describes the means of forming operational competence on the example of training guides-interpreters in the framework of additional education. The article proves the necessity of modular construction of the content for the development of the communication skills use. The need for a creative process in the preparation of guides-interpreters is proved and implemented in the context of the use of interactive learning methods, namely: discussion; heuristic method; case method; role-playing game; brainstorming. The article describes the results of an experiment on the operational competence development, as the basis for future successful professional activity.
Real-time Prediction of 3D Motion of Person with RGB-D Camera

The paper describes a method for predicting 3D pose of a person in real-time with RGB-D camera. Three dimensional pose of a person is measured by extracted 2D skeleton on the image and corresponding depth. Motion predictor of RNN is trained by measured 3D pose of a person. 3D pose of a person after several frames is predicted in real-time by inputting time-sequential 3D pose of a person to RNN. Predicted error is evaluated in the experiment.
Integration Function of HRM – A Case Study

This study gives us an notion about the integration function of human resource management without which the concept of engaging the employees in the organization to make them to work with bonding becomes a question mark.The concept of integration function generates the plan to reconsider organization goals to manage the employees within the organization in a effective way so that the employee's loyalty and performance will increase to a greater extent.In this case we can identify the possibility of attrition is due to improper integration of employees and no new changes have been adopted to make the employees to hold citizenship towards the organization.