Reviewerly/exHarmony huggingface dataset:
A hybrid fast inference approach with distributed neural networks for edge computing enabled UAV swarm

Nowadays, unmanned aerial vehicle (UAV) swarm supported by mobile edge computing is attracting more and more attention, such as smart agriculture, smart transportation, smart security surveillance, and smart environmental monitoring. Nevertheless, small UAV devices cannot deploy advanced best-performing DNN models with insufficient computing and storage resources. Aerial computing centers serving as edges can collect tasks from UAVs, reduce UAV load, and provide high-accuracy inference. Limited radio resources in offloading and load imbalance in computing centers could lead to significant latency in task inference. Considering image processing in UAV applications, we propose a hybrid inference framework combining early exit and task offloading based on distributed neural network. The bottleneck-designed DNN provides a smaller intermediate data size than the original input. By deploying shallow neural networks at the drone terminals and advanced DNNs at the aerial computing servers, latency-constrained tasks can be exited after local inference, offloaded to the edge after local computation, or directly offloaded to the edge. Compared to binary or partial offloading, the early-exit-based framework provides fast inference as the workflow stops when a confident result is obtained. Combining task offloading into the inference process offers a more flexible option to release the UAV computing load. The proposed approach efficiently utilizes wireless transmission and balances the computation load to maximize the system inference accuracy within the latency constraints. Practical task inference simulations demonstrate that our approach obtains higher system accuracy under different radio resources, task generation rates, and terminal computing capacities conditions.
Creation of Namie using Renewable Energy and Educational Support through Revitalizics

Because of the occurrence of the Great East Japan Earthquake, the accident of the Fukushima Nuclear Power Station has occurred, and we had experienced unprecedented large-scale disasters centered on Fukushima Prefecture. The biggest challenge for recovery from nuclear disasters is how to equalize the risk of radiation damage to the health of residents. The quicker risk management methods for safety and security can be applied, the sooner reconstruction can be achieved. In cooperation with the town of Namie in Fukushima Prefecture, we have created a new academic field called "Fukushima Revitalizics" by combining risk communication engineering with decontamination science, robot measurement engineering and renewable energy engineering, and have trained human resources through graduate student training, support for ICT(Information and Communication Technology) education at elementary and junior high schools, and support for science, culture, and robotics classes. In this paper, the creation of Namie Town using renewable energy and educational support through Revitalizics will be reported.
Practice of Energy and Environmental Education in Okinawa

With the support of the "Energy Education Survey Project" of the Agency for Natural Resources and Energy, the "Okinawa Energy and Environmental Education Study Group" was established in 2006. Since then, we have been conducting practical research on energy and environmental education that takes advantage of the characteristics of the Okinawa region. The members of the study group are university teachers, elementary, junior high, and high school teachers, government officials, energy-related companies. We report on the energy teaching materials (wave power generation, PET bottle windmill, energy conversion experimental equipment, model condenser car, polymer electrolyte fuel cell, model fuel cell vehicle, etc.) developed so far, as well as the implementation of visiting classes, lectures and energy-related facilities tours.
Challenges in early years and primary education: employing critical thinking skills during turbulent times

Click to increase image sizeClick to decrease image size AcknowledgmentThe authors are grateful to Lembaga Pengelola Dana Pendidikan (LPDP/Indonesia Endowment Fund for Education), which is part of the Ministry of Finance of the Republic of Indonesia, for supporting our master’s studies and supporting this publication. The authors declare no competing interests.
Artificial Intelligence-Aided Trajectory Planning for UAV

In this work, we investigate the multi-UAV trajectory planning for optimal resource allocation and energy-efficiency maximization. Considering different terrain models, evaluate effective path for UAV to avoid the obstacle and maximize the energy efficiency of the UAV. With the motivation of reducing the total length of UAV trajectory path while maintaining high QoS and energy efficiency, a stochastic obstacle avoidance game based on q-learning is modeled. Here we re-frame the reward function of q-learning algorithm for optimal trajectory path evaluation. Based on the designed reward function, the optimal trajectory path for the UAV deployment is evaluated from the stochastic analysis. It is observed from the analysis that UAV trajectory is improved by zero collision with the obstacle.
Intelligent Vehicle Park Path Planning Based on Improved Artificial Potential Field Method

The traditional artificial potential field technique (T-APF) will cause the intelligent vehicle to lead to unattainable goals while facing a complicated and multi-barrier environment, and it will also result in the dynamic obstacle avoidance's restrictions. As a result, it is suggested to use fuzzy potentials and regulators to plan an adaptive fuzzy potential field approach (SA-APF) with dynamic limitations. On this basis, the dynamic obstacle potential field is added, combined with the fuzzy control feedback on repulsion and corner, to realize the autonomous obstacle avoidance and speed adaptation of the vehicle. In addition, the MPC controller design fully combines the status reference output of the upper layer to improve tracking accuracy and driving efficiency. Traditional planning techniques and SA-APF can be compared and analyzed for their impacts in static and dynamic contexts. SA-APF planning can reduce the path by 10.14% and have a smaller curvature. The outcomes of the trajectory tracking experiment demonstrate that the vehicle's lateral tracking error has been successfully managed to within 0.35m. The aforementioned demonstrates the logic of the improvement technique and offers a theoretical framework for increasing the accuracy of intelligent cars' active obstacle avoidance at low speeds.
Vortex phase deterioration common-path interferometry

Abstract Common-path interferometers (CPIs) are significant due to their compactness and vibration resistance. The usual challenge with CPIs arises due to a very small separation between reference and sample beams, where sending a reference beam through a sample is considered to be a limitation. However, this limitation also makes it difficult to probe the interaction of beams with materials as a function of their phase structure. This study paves the way for a new kind of interferometry that can provide unique phase signatures to study the sample. This paper proposes and demonstrates a novel approach based on thermo-optic refraction, to send both beams through the sample and probe the phase deterioration due to the relative interaction of beams in the material medium. Here, thermo-optic refraction interferometry allows the superposition of a higher-order vortex beam with a non-vortex beam through the phenomenon of thermal lensing. The non-vortex beam is made to expand in a controlled fashion by another laser. The relative interaction between the expanding non-vortex beam and the vortex beam within the sample, results in the output interferogram. The phase deterioration analysis of the output interferogram elucidates medium-driven phase changes. This technique is demonstrated using milk samples by recording the root-mean-square azimuthal phase deterioration of the orbital angular momentum beam.
Enhancing Cyber Security through the utilization of Blockchain Technology

In today's digital era, cybersecurity is a matter of utmost importance as both organizations and individuals confront growing risks from unauthorized access attempts aimed at sensitive data and systems. Blockchain technology, initially developed as the foundation for cryptocurrencies like Bitcoin, has emerged as a promising solution to enhance cybersecurity. Operating as a distributed ledger that records transactions across multiple computers, blockchain brings forth several essential characteristics that can contribute to bolstering cybersecurity. While blockchain technology offers numerous advantages in terms of cybersecurity, it also introduces its own set of challenges and considerations, including scalability, privacy, and the potential vulnerabilities of smart contracts. The implementation of cybersecurity solutions based on blockchain necessitates meticulous design, robust key management, and a comprehensive understanding of the specific use case and associated risks. Overall, the incorporation of blockchain technology in cybersecurity holds the potential to elevate transparency, integrity, and resilience, empowering organizations and individuals to mitigate the risks posed by cyber threats and improve their overall security stance. This paper, which involves the analysis of 15 researchers, explores various use cases for applying blockchain in the field of cybersecurity. A significant focus among the researchers centers on leveraging blockchain to safeguard IoT devices, networks, and data. Furthermore, the paper delves into how blockchain can offer security measures for three problematic areas within IT that have been identified by previous studies.
Increasing the motivation of students in conditions of distance learning during military actions

The article is devoted to determining the main ways of increasing students’motivation in distance learning in the conditions of war. The war has completely changed the established way of life in our society, and education is one of the spheres that has undergone global changes and the main task of which is the introduction of innovative technologies that will help to improve the educational process. The concept of «distance learning involves the integration of information and pedagogical technologies that ensure the interactivity of the interaction between the teacher and the student, as well as the productivity of the educational process. The question of the development of students’ motivation is one of the most relevant today, it is determined that internal and external motivation are key. Psychological and pedagogical literary sources and studies of modern Ukrainian and foreign scientists regarding the problem of students’ motivation in distance learning are analyzed. It has been established that the decisive prerequisite for ensuring successful learning is the conscious consideration of the motivational factor and its management throughout the entire educational process. The special importance of improving the goals, content, means and methods of education in order to increase the motivation of students is emphasized. It was established that the implementation of conceptual ideas of education is carried out with the help of information technologies. Modern information technologies such as programmes and applications used in the educational process to increase the level of students’ motivation in education are analyzed. The importance of the teacher’s role in this process, his ability to organize the educational process, to create a positive and friendly atmosphere of communication in the primary environment with the aim of activating the students’ activity during distance learning, is noted. Recommendations have been developed to increase the motivation of students who work remotely during military operations.
Peculiarities of using distance learning technologies in the process of training future teachers of biology

This article substantiates the relevance of the introduction of distance learning in the training of students of future biology teachers. The essence of the concepts «vocational training», «distance learning» and «distance technology» is revealed. Also consider the views of various scientists on the process of distance learning. It is established that today the most common e-distance learning using computer networks and information and communication technologies. The authors analyzed the results of student surveys on the features of distance learning and their application of innovative learning technologies. It was found that distance technologies are not used enough in the training of future biology teachers in higher educational institutions of Ukraine. The difficulties and advantages of introducing distance learning in higher educational institutions are indicated. Domestic and foreign experience in the application of distance learning elements in the training of future biology teachers is described. This study theoretically substantiates the feasibility of using distance learning, identifies the main advantages and disadvantages of using distance learning, the possibility of use in the classroom and its impact on the formation of future professionals. The future prospects of the research and the importance of the considered problem at the present stage of society development are determined. Recommendations for the introduction of distance technologies in the pedagogical process of higher educational institutions of Ukraine for the preparation of a new generation of competitive and competent biology teachers have been developed. It is noted that with the development of technical capabilities of teaching methods and technology, it became possible to use new organizational forms of the educational process, using information and communication technologies.
Stem education as an innovative means of increasing students’ creative potential

The article substantiates the relevance of the introduction of STEM-education in the education of secondary school students. This publication highlights the features of STEM-education, because at the present stage of development of society special attention is paid to the problem of forming students’ independence, ability to receive, analyze information and make optimal decisions, use new information technologies in practice. The introduction of the STEM education system will ensure the comprehensive development and preparation and acquisition of knowledge by students from various fields of science, engineering, technology and programming, which will further allow the formation of a competent specialist. The positive aspects of the introduction of elements of STEM education and the difficulties that arise during its implementation are considered. There are also examples of information sites and applications that will help both teachers and students in the implementation of STEM-learning. This study theoretically substantiates the feasibility of using STEM technologies, identifies the main advantages and disadvantages of using this training, the possibility of use in the classroom and its impact on the formation of students’ personalities. The future prospects of the research and the importance of the considered problem at the present stage of society development are determined. Recommendations for the introduction of technology in the pedagogical process of educational institutions of Ukraine for the training of a new generation of competitive and competent professionals have been developed. It is noted that with the development of technical capabilities of teaching methods and technology, it became possible to use new organizational forms of the educational process, using information and communication technologies.
Features of the use of information and communication technologies in higher schools and their influence on the formation of students’ professional competence

The article examines the problem of using information and communication technologies for educational purposes for the formation of professional competencies in future teachers. The relevance of the introduction of e-learning resources into the system of professional education of students is substantiated. The essence of the concepts: «information and communication technologies», «educational electronic resources», «professional competences», etc. have been clarified. Based on the analysis of scientific literature, generalization of own pedagogical experience, student questionnaires, the state of use of information and communication technologies in the professional training of bachelors of chemical-biological and historical faculties was clarified. An analysis of the use of electronic learning tools by students and future teachers was carried out. The results of the survey and questionnaire of students regarding the activity and effectiveness of the use of information and communication technologies in professional training are described. The results of the research on the activity of using ICT, e-learning platforms, and the choice of information and communication technologies based on the questionnaire of teachers are presented. It was revealed which means of information and communication technologies and e-learning teachers consider to be the most effective. It was found out which e-learning platforms are preferred by teachers. The article analyzes and proves that the use of information technologies during student education contributes to increasing students’ motivation for professional education. The relevance of the use of electronic learning technologies and relevant information and communication technologies is substantiated. The problems and shortcomings of the popular implementation of information and communication technologies are characterized.
MTCD: An Efficient Cloning Detection Technique Based on Method Table

Code cloning is an effective approach to accelerate software development, but may leave potentially significant pitfalls for maintenance. State-of-the-art clone detection techniques rely heavily on accurate syntax and semantic features which are difficult to identify and extract, making them hard to deploy in practice. This paper presents a simple but efficient approach called MTCD which extracts from a Java method (in its Java class file) the method table section of the code as its feature, and then transforms the feature into a decimal series for comparison. MTCD significantly simplifies feature identification and extraction. Experimental results on BigCloneBench suggested that MTCD clearly outperformed other established approaches by achieving an average F1-score of 0.95 with a modest training cost of 181 s for a 60 k dataset.
Lightweight medical image segmentation network based on ghost convolution and attention mechanism

Ghostnet is a lightweight image classification network proposed by Kai Han and other scholars in 2019 which was applied in terms of object detection. Ghostnet has the advantages of few parameters and high accuracy. In this paper, through the idea of transfer learning, ghost net is used as the network of feature extraction and CBAM attention mechanism is added. CBAM is not only a lightweight attention mechanism, but also a good combination of space and channels. CBAM eliminate irrelevant noise intelligences and concern to key intelligences. At the same time, the ghost convolution block is improved, and point-by point convolution is added to the ghost convolution block to obtain more image feature information. Add the squeeze and enumeration module to improve the convolution receptive field, increase the ability of the network to extract multi-scale spatial information, and introduce the residual idea to tackle the problem of information loss and gradient descent disappearance. GAUnet, designed according to the above idea, achieves better intersection and merger ratio than Unet, Unet++, DeepLabV3+and other neural networks on the multi-organ segmented chaos dataset with fewer parameters.
Is ASCON the best choice regarding the Side-channel Analysis?

The National Institute of Standards and Technology (NIST) started challenge for the new standard of lightweight encryption to meet the requirements of IoT devices. One of the requirements for the upcoming standard was resistance against side-channel attacks. This year, they chose ASCON as the winner from the final ten. In this work, we present an overview of each finalist and how ASCON stands against the other finalists regarding side-channel attacks resistance in the research to date.
Real-Time American Sign Language (ASL) Interpretation

Majority of the public do not know how to communicate in sign language. This forms a communication barrier between the public and the deaf community. Thus, a method to bridge communication is required. In this paper, a computer vision solution is proposed with the use of MediaPipe library and Long Short-Term Memory (LSTM) algorithm to identify twelve (12) motion based American Sign Language (ASL) phrases. At present, there is no publicly available sign language dataset that contains motion based phrases with hundreds of videos per phrase. Thus, this paper aims to collect a motion based ASL phrases dataset for future development of sign language interpretation. The MediaPipe and LSTM model has been trained up to 97% train accuracy and 79% test accuracy. Finally, real-time deployment of the deep learning model is achieved by deploying it to a Flutter-based mobile application.
An Efficient Reversible Data Hiding Based on Prediction Error Expansion

Reversible data hiding (RDH) is an approach that facilitates data hiding in a way that both the secret data and cover media can be extracted and recovered in their untouched form. Various RDH schemes have been proposed that utilize pixel value ordering mechanisms for pixel prediction and utilize histogram shifting (HS) criteria for prediction error expansion to implant secret data. However, such schemes are inefficient when it comes to hiding large volumes of data. In this paper, we propose a novel and improved RDH technique that divides the image into two using a checkboard pattern. One part of the image exploits the pixels of another part for prediction and vice versa. Also, as a parameter of smoothness, a fluctuation value is calculated for each pixel to avoid embedding in unsmooth regions of the image. The scheme is efficient in terms of hiding larger capacities of data and better stego-image quality.
Breast Ultrasound: A Valuable Adjunct to Mammography in Breast Cancer Screening

Breast cancer is a significant health concern affecting women worldwide. Mammography has beenthe gold standard for breast cancer screening, enabling the early detection of lesions. However,mammography has limitations, particularly in dense breast tissue. This paper explores the role ofbreast ultrasound as a valuable adjunct to mammography in breast cancer screening. We examinethe benefits, limitations, and emerging trends in breast ultrasound technology. The findingshighlight the increased sensitivity of breast ultrasound in detecting additional cancers, particularlyin women with dense breast tissue. Furthermore, we discuss the integration of breast ultrasoundinto existing screening protocols, its impact on overall cancer detection rates, and the potential forimproved patient outcomes. This paper aims to provide a comprehensive overview of the role ofbreast ultrasound in breast cancer screening and emphasize its value in complementingmammography.