Reviewerly/exHarmony huggingface dataset:
Research on current method of route planning for autonomous vehicles

With the construction of smart cities, autonomous driving is expected to provide revolutionary advancement for future road traffic systems. Among them, vehicle path optimization is a hot topic in the field of autonomous driving. Based on the related theories and methods of path planning, this paper reviews the research status of path planning algorithms, and classifies the related algorithms of global and local planning. The results show that there are few researches on dynamic obstacle avoidance in complex environment and obstacle avoidance algorithm based on driver behavior. In addition, the target of vehicle path optimization can be further expanded.
The system of work with underachievers in english lessons at the primary school level

The problem stated in the paper concerns one of the main problems of modern schools underachievement in foreign language lessons. The paper presents the main reasons for poor performance, as well as the rules that must be followed by the teacher when working with underachieving children in English lessons. The subject of the study is the system of work aimed at eliminating underachievement of primary school students in English. The aim of the research is to identify the reasons of the problem and to develop a series of classes in English to tackle underachievement in English. The theoretical significance of the study deals with generalizing of the methodological material for determining the causes of underachievement and ways to overcome it. The paper can serve as a basis for further scientific research related to the definition of the ways to improve the quality of education of schoolchildren. The practical significance of the paper lies in the possibility of using the essentials of the study in the organization of the educational process in English. The theoretical and methodological basis includes the works on the causes of underachievement (K.V. Bardin, L.S. Slavina, K.N. Meshalkina, I.V. Dubrovina); research on psychological and pedagogical problems of underachievement (P.P. Blonsky) particularly, in English (N.P. Lokalova, Z.I. Kalmykova, M.A. Kholodnaya); methodological works on the definition of difficulties and causes of underachievement (S.N. Kostromina, A.F. Anufriev, Yu.Z. Gilbukh, A.A. Budarny). The research methods are the analysis of psychological, pedagogical and methodological literature, logical argumentation, proof, generalization, logical justification, synthesis, reflection, description.
The Whale Optimization Algorithm Based on Speed-Up Robust Feature to Improve the Speed of Object Searching

Speed-Up Robust Feature (SURF) is one of the methods for extracting image features and matching. This paper proposes the object search method based on the whale optimization algorithm that inherits the previous global best value (IGP-WOA), which has the advantages of fast convergence and multiple search methods. In addition, we use integral images to find the fitness value (IGP-WOA-CII) in the target function calculation, thereby reducing the time spent on SURF extraction and matching.
Development of a Music Interactive Online Fitness System for Shoulder Press Exercise: Latest Update for Biosignal Art

Global COVID-19 pandemic limited our ability to have adequate physical activity. It is necessary to replace outdoor and gymnasium exercise with in-door and home-based fitness. However, little effort has been paid for solving the new rising problems for the new alternative fitness, such as insufficient system access, lack of exercise skill, and motivation. To make a response to these problems, we updated and published a new online fitness system: Biosignal Art (BA) for shoulder press exercise on July 1, 2020. Shoulder press motion is captured by a web camera and evaluated through an original algorithm consisted of arms initial position, forearm position, and motion rhythm. Music interactive feedback according to the shoulder press performance is also provided after the exercise and can be downloaded by the users. We collected and analyzed the access status data nine months after the first release of the new BA system. By the end of April 2021, a total of 287 visitors accessed and performed the shoulder press exercise through the new BA system. 55% of them acquired fifty shoulder press points or higher. Facing the severe COVID-19 pandemic situation, we expect the Biosignal Art system can help more people to keep inadequate physical activity.
The Effectiveness of Using Picture Word Inductive Model Strategy in Developing EFL Iraqi students’ Vocabulary Retention

&lt;p style="text-align: justify;"&gt;Vocabularies represent the basic elements of any language, thus, if there wasn’t sufficient control in using them then the result would be a difficulty in vocabulary retention when needed. The Picture Word Inductive Model Strategy (PWIM) than traditional methods. The current study aims at investigating the effectiveness of using (PWIM) Strategy in developing EFL Iraqi students' vocabulary retention. The study is conducted by using an achievement test to check the study sample. The researcher has selected a sample of (65) students in third stage in English Department in the Colleges of Education at Missan University in the Academic Year (2021-2022). The students are divided into two groups, the first group is the experimental group and the second group is the control group. In order to find out whether there are any statistically significant differences among the two groups’ achievement, the researcher applied the T-test formula for the two samples in an independent way. Based on the outcome of the study, there are statistically remarkable differences appeared in the results from the two groups. Accordingly, the study proves that using (PWIM) can increase the vocabulary retention of the students.&lt;/p&gt;
A study of DQN using VisionTransformer as an image extractor

In recent years, the field of image recognition has seen rapid technological innovation, and in addition to the CNN-based models used in the past, models using transformers have also been devised. However, there are no results on the verification of DQN using the latest image recognition models in existing research. In this study, we examined the performance of DQN using VisionTransformer as an image extractor, which has become a hot topic in recent years. The performance was not stable due to problems caused by the different architecture from the resulting CNN.
Research on communication security of power system based on 5G Technology

With the concept of “Internet of Things” and the arrival of the 5G era, 5G technology as a new generation of mobile communication technology is widely used in all walks of life. The construction of smart grid and the proposal of the concepts of smart energy” and “smart manufacturing” have promoted the application of 5G technology in power system, especially in power communication system. It is undeniable that the security in the current 5G communication environment is facing risks. Physical layer security is a starting point for proposing ways to improve the security of 5G communication, and RF fingerprint technology is a representative technology of physical layer security. With the rapid development of China’s power industry, the scale of power system will gradually expand, and the future 5G communication technology will also be more widely used in power communication system. The application of 5G-based RF fingerprint technology in power communication system can reliably identify power system communication equipment, which will significantly improve the security of power system communication. This paper mainly studies the radio frequency fingerprint technology of wireless communication and verifies the feasibility of using radio frequency fingerprint technology to identify communication equipment. Firstly, the research status of power system communication security in recent years is summarized. Secondly, 5G secure communication is briefly described, and the idea of using physical layer security to improve communication security is introduced. Finally, the radio frequency fingerprint identification system is summarized, and the role of bispectrum as radio frequency fingerprint in communication equipment identification is verified by simulation of wireless transmitter.
Hibachi: A ROS compatible skid-steer vehicle

Skid-steer vehicles are one of the most popular configuration of autonomous ground vehicles (AGVs). Their mechanical simplicity provides researchers and developers with an easy to build vehicle that can perform complicated tasks either in outdoor or indoor scenarios. However, the process of building an AGV usually requires to spend a lot of time solving problems that are already solved. This work focuses on the process required to make a working AGV –the Hibachi– compatible with Robot Operating System (ROS). We mainly describe and explain the tasks of developing the required software and device drivers to implement ros_control on the existing hardware, allowing easier sensor integration and providing a standarized testbed for AGV research.
Performance Analysis of Machine Learning Algorithms and Feature Extraction Methods for Sentiment Analysis

Sentiment Analysis is the process of evaluating the document or sentence and assigning it a polarity. It has been a key area of research for the past few years. With the evolution of the World Wide Web, many platforms such as Twitter, Facebook, etc. came up where people can express their emotions related to an object, movie, or any political party. These reviews are read by many people before taking some decision, and hence it is very important for the Sentiment Analysis models to assign polarity to the reviews properly. In this paper, we will be analyzing different existing Machine Learning algorithms such as Linear Regression, Support Vector Machine, Decision Trees, Random Forest, and Maximum Entropy Model used for Sentiment Analysis, along with 2 most used methods of feature extraction, Bag-of-Words(BOW) and Term Frequency- Inverse Document Frequency (TF-IDF). The results showed that BOW used with Linear Regression models shows the best results achieving an accuracy score of 34.83% and takes minimum time for training.
Online Learning as a Tool for Developing Learner Autonomy for Future Engineers

Current university educational context is vulnerable due to challenges caused by different force majeure, which result in dramatic shift towards online education. However, not all students are willing to deal with online edtech on a regular basis as they are under severe pressure from inability to work autonomously. It is an alarming trend especially for future engineers, as they are required to solve multi-dimensional tasks, be able to find solutions promptly and autonomously. To fill in the gap between the urge for autonomous learning and lack of willingness to study independently, the authors offer the results of the research conducted among 632 future engineers. The 2-stage survey via interviews and a questionnaire was aimed at identifying major challenges and benefits that can trigger sustained autonomous learning activity of students. The findings of this study can be useful for designing and developing online courses as a tool for enhancing student autonomy.
Secure and Efficient Allocation of Virtual Machines in Cloud Data Center

Cloud computing provides a shared pool of configurable computing resources and significantly improves the utilization of computing resources, but it also introduces security threats. We focus on the virtual machine (VM) co-residency, which allows an attacker to launch cross- VM attacks against target VMs. To tackle this problem, we propose a secure and efficient VM allocation strategy to reduce the cross- VM attack threats while ensuring the efficiency of the cloud data center. First, we establish several metrics related to security and efficiency for the cloud data center. Then, we establish a constrained optimization model. Next, we allocate and migrate VMs based on typical suspicious or vulnerable VM features, and solve the optimization problem through our improved NSGA-II allocation. Finally, we implement our allocation strategy and conduct intensive experiments. The experimental results show that our allocation strategy performs better than the existing stratezies and orovides cloud vendors with tradeoff solutions.
Towards Query-efficient Black-box Adversarial Attack on Text Classification Models

Recent work has demonstrated that modern text classifiers trained on Deep Neural Networks are vulnerable to adversarial attacks. There is not sufficient study on text data in comparison to the image domain. The lack of investigation originates from the challenges that authors confront in the NLP domain. Despite being extremely prosperous, most adversarial attacks in the text domain ignore the overhead they induced on the victim model. In this paper, we propose a Query-efficient Black-box Adversarial Attack on text data that tries to attack a textual deep neural network by considering the amount of overhead that it may produce. We show that the proposed attack is as powerful as the state-of-the-art adversarial attacks while requiring fewer queries to the victim model. The evaluation of our method proves the promising results.
Kannada Language Based Hybrid Cryptographic Scheme for Protecting Human Rights for Privacy

In this era of digitalization, data security plays a key role in maintaining any firms or people's personal information securely. Privacy and integrity of data becomes the main factor that cannot be compromised on. Therefore, to ensure a highly secured data transmission, we are already familiar with a large number of encryption techniques but they have their own limitations. Where our priority becomes to secure the data from any form of data breach such as cryptanalysis or brute-force attack and this is where the efficiency of an algorithm can be tested. In this paper we propose a Kannada Language Based Hybrid Cryptographic scheme for Protecting Human Rights for Privacy (KHCS-HRP) which uses kannada language for an efficient way of encryption by double proofing the data. In addition to this we will be using a hybrid encryption technique by combining Elliptical curve cryptography, Advanced encryption standard and XOR- DUAL RSA algorithm to overcome the drawbacks of key size in symmetric encryption and low security level when it comes to asymmetric encryption. Furthermore, MD5 hash Algorithm is used to check authentication and integrity of data transfer by using a multilayered hash technique for fast generation of hash code. The performance evaluation of the proposed scheme showed effective results in the efficiency compared to other schemes.
Homomorphic Filtering and MAD Filtering Based Speckle Removal in Ultrasound Images

The economy of medical ultrasound images comes at the expense of image quality that is usually affected by speckle noise. In this paper, a method for 2D ultrasound medical image despeckling is presented, which combines homomorphic filtering and MAD (Median Anisotropic Diffusion) filtering that the improved Anisotropic Diffusion filter. First, the preprocessed image after dilution of speckle-noise is obtained by homomorphic transformation of the ultrasound image with Gaussian high-pass filtering and median filtering. Then the speckle is removed with the MAD filtering, and finally, the contrast is enhanced. Experimental results demonstrate that the algorithm can effectively reduce the speckle noise and maintain high image quality. The algorithm in this paper helps remove speckle in 2D static ultrasound images, which is potentially valuable for improving the quality of medical ultrasound images.
Development of WebGIS of the Level of Community Participation in Flood Mitigation and Preparedness

As the components affected by the hazard, mitigation and community preparedness are essential in minimizing the flood hazard. This study is aimed at mapping the community participation in flood mitigation and preparedness in South Tangerang to be then developed to be a mapping system of South Tangerang through WebGIS. The approach of this study aimed at mapping the level of community participation in flood preparedness and mitigation through WebGIS is using Waterfall method as the system development method. The study shows that WebGIS used to map the level of community participation in flood preparedness and mitigation in South Tangerang has passed a system test that shows the strengths of the developed system where it can be used to find some information related to the physical and social data of the sub-districts in the city that can be accessed whenever and wherever as long as the internet access is available. The developed WebGIS can be used by the community, but can also be a consideration for the government in designing programs to overcome flood problems in South Tangerang.
Empirical Analysis of Foreign Direct Investment on Economic Growth: Evidence from the East African Community

This paper empirically examines the impact of foreign direct investment on economic growth in the East Africa Community throughout 1970-2017. The study used Pedroni test of cointegration for testing long-run relationship and VECM to inspect the long- run and short-run Granger causality between FDI and economic growth. The paper confirmed the integration of order one among the variables at the first difference. The results from Pedroni cointegration and VECM found that FDI is statistically significant and positively associated to economic growth in East Africa Community country members. The gross capital formation also is affirmative and statistically noteworthy connected to economic progress in the region, while inflation and Population growth were found as statistically significant and negatively correlated with economic, and thus, government final consumption expenditure and trade respectively are negatively and positively statistically insignificant. The VECM Granger causality exploration discovered the bi-directional Granger causality between GDP per capita and population growth rate; FDI and population growth rate, and gross capital formation and population growth. As well, unidirectional Granger causality was found among some variables. On the policy perspective, the study recommended the EAC members to strengthen the foreign direct investment policy through inducements to investors, availability of basic infrastructure, and establishment of the better macroeconomic environment.
Strategies for operation safety protection of large solar telescope

The large solar telescope is automatic equipment for observing the sun. The primary mirror of the equipment can concentrate solar energy, and, the accumulation of such energy, if not effectively controlled during the equipment application, will be prone to lead to the deviation of the sunlight focus, which can damage the equipment itself and the surrounding equipment, or even threat people's lives. Therefore, sound safety protection strategies with multiple working scenarios and details taken into account are required in the process of installation, debugging, maintenance and application of the large adaptive solar telescope to effectively ensure the equipment safety.
A Study on Hand Gesture Segmentation Approaches

Computer vision is the study of making machines capable of understanding the input image and video using some algorithms or techniques. As for humans, understanding a scene given in an image or video is not a difficult task. Humans are blessed to understand images and videos effortlessly without knowing the complexities behind the process of image and video understanding. Making machines also capable of understanding their input image and video is not that simple. With ongoing research for making human–computer interaction more natural and realistic, lots of advancements have been done in different components of computer vision. The paper focuses on the image segmentation process used in computer vision and image processing which is a very crucial component while processing images and video. Image segmentation is the process of extracting only relevant content or information while removing irreverent content or information. Image segmentation is the most researched topic in image processing and computer vision. It is one of the major activities that will help the later process to ease its operation by filtering unnecessary and irrelevant contents. The paper aims to describe the segmentation process and highlight different types of segmentation approaches used in recent trends comparing their performances.
Monitoring System of Safe Adult-child Ratio in Childcare Institutions Based on Image Recognition

research-article Share on Monitoring System of Safe Adult-child Ratio in Childcare Institutions Based on Image Recognition Authors: Mingxing Liu College of Information Mechanical and Electrical Engineering, Shanghai Normal University, China College of Information Mechanical and Electrical Engineering, Shanghai Normal University, ChinaView Profile , Haiguang Chen College of Information Mechanical and Electrical Engineering, Shanghai Normal University, China College of Information Mechanical and Electrical Engineering, Shanghai Normal University, ChinaView Profile , Zifeng Qi College of Information Mechanical and Electrical Engineering, Shanghai Normal University, China College of Information Mechanical and Electrical Engineering, Shanghai Normal University, ChinaView Profile , Susheng He College of Information Mechanical and Electrical Engineering, Shanghai Normal University, China College of Information Mechanical and Electrical Engineering, Shanghai Normal University, ChinaView Profile Authors Info & Claims MLMI'21: 2021 The 4th International Conference on Machine Learning and Machine IntelligenceSeptember 2021 Pages 8–14https://doi.org/10.1145/3490725.3490727Online:29 December 2021Publication History 0citation15DownloadsMetricsTotal Citations0Total Downloads15Last 12 Months15Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Statistics with Imprecise Probabilities—A Short Survey

Abstract This chapter aims at surveying and highlighting in an introductory way some challenges and big opportunities a paradigmatic shift to imprecise probabilities could induce in statistical modelling. Working with an informal understanding of imprecise probabilities, we discuss the concepts of model imprecision and data imprecision as the two main types of imprecision in statistical modelling. Then we provide a short survey of some major developments, methodological questions and applications of imprecise probabilistic models under model imprecision in the context of different inference schools and summarize some recent developments in the area of data imprecision.