Reviewerly/exHarmony huggingface dataset:
Instance Segmentation based Object Detection with Enhanced Path Aggregation Network

Multi-scale networks rely heavily on the aggregation process to aggregate feature information into other feature maps. However, it has disadvantages in aggregating information, where the localization information becomes inconsistent. An Enhancing Path Aggregation Network through concatenation and attention mechanism is proposed here to improve the aggregation path for generating the feature maps in multi-scale network. This approach helps to keep information consistently during the process of aggregation. The proposed model is evaluated using the COCO dataset, which achieves significant improvements on several metrics.
Novel Image Dataset and Proposal of Framework for Visual Semantic Analysis Applied on Object Dangerousness Prediction

The recent technological advances, combined with the shifting and increasing necessities of the global population in the search for better commodities and ease of life, have propelled research on socially assistive robotics and artificial intelligence. Inside the gap towards complete solutions for intelligent assistive robotics is the need for more complex, autonomous, semantical knowledge-oriented approaches capable of understanding tasks. In this work, we present a novel image dataset for indoor object dangerousness targets in the context of children’s safety called the HOD Dataset. Furthermore, we introduce the concept of a Visual Semantic Analysis framework, an ongoing project for enabling visual machine-learning techniques to boost capacity by merging multiple contextual variables into a final main objective. We use the framework here to set a baseline for the HOD Dataset. The baseline is defined using a no-visual semantic analysis model, obtaining mean average precision (mAP) of 0.785 and mean average recall (mAR) of 0.838 on IoU ranging from 0.50 to 0.95.
Securing Smart Contracts against Re-entrancy Attacks

With cryptocurrencies, blockchain technology has revolutionized the financial industry, but its potential for decentralization extends far beyond finance. Blockchain is now being integrated with a wide range of emerging internet technologies, including the Internet of Things (IoI’), artificial intelligence (AI), and cloud computing. When combined with these technologies, Blockchain has the potential to overcome known flaws like scalability and energy consumption, making it more streamlined, efficient, and suitable for internet decentralization. Blockchain, for example, can provide secure data storage and sharing for IoT devices, preventing data breaches and unauthorized access. Furthermore, the transparency and immutability of Blockchain make it ideal for use in supply chain management, where it can enable transparency and accountability throughout the entire supply chain. Blockchain can also be used in conjunction with artificial intelligence to create decentralized, secure marketplaces for data sharing and storage, thereby preventing data monopolies and promoting fair competition.
Enhancing the Security of E-Healthcare Transactions Using Hyperledger Fabric Modular Blockchain Framework

The most innovative development in recent years is blockchain technology, and its uses are expanding quickly across numerous businesses. It is well known for its capacity to adapt to this technology, which aids in the storing of data at locations linked by peer-to-peer networks. Blockchain technology has recently piqued the curiosity of the healthcare industry. Numerous significant issues that currently plague EHR systems could potentially be resolved by it. This essay offers a thorough analysis of the literature on the application of blockchain technology in the medical industry. The focus of this study is the current system used by tertiary institutions to store, access, and safeguard electronic healthcare data. According to analysis, hospitals maintain electronic health records most frequently using client/server architecture. The existing way of processing transactions in Punjab's tertiary institutions has serious issues with data accessibility and data privacy. After assessing the system's shortcomings, research was carried out. The Hyperledger fabric blockchain technology and pluggable PBFT have been coupled to assure the security of healthcare transactions.
EC-WGAN: Enhanced Conditional and Wasserstein GAN for Fault Samples Augmentation

Considering the issue of limited and imbalanced fault samples, an enhanced conditional and Wasserstein GAN (EC-GAN) is proposed for fault samples augmentation of bearing. At first, random noise along with fault category are inputted into the generator for synthetic samples. Then, the authenticity between real samples and synthetic samples are judged by the discriminator in a minmax cost function with Wasserstein distance. Moreover, the gradient penalty is applied for keeping continuous of the Lipschitz function and gradient vanishing in Wasserstein GAN training. As the collected samples are time series data, one-dimensional convolutional layers replace the fully connected layers of the generator and the discriminator. Finally, the effectiveness of the proposed EC-GAN is verified under the limited data of Case Western Reserve University bearings.
An Efficient Breast Cancer Disease Prediction Method using Deep Learning

Breast Cancer is considerable concern among health issues in women. It is one of the higher mortality factors when compared to other cancers. Early prediction of cancer patients helps doctors to give a better diagnosis and prognosis of the disease. The study's goal is to assess how well proposed CNN-based models perform at classifying patients' tumour types as either malignant or benign depending on whether they are cancerous or non-cancerous. The goal of the study is to identify the key factors, such as the number of convolutional layers, the calibre of the training data, and the dependent variable, that influence the model's performance during training. The study makes use of the Kaggle-available Breast Cancer Histopathological data set. It is commonly used to assess CNN-based models in the health care sector. The classification performances of the models are analysed, and the models' training efficacy is assessed. The work demonstrates that robust feature representation and precise patient predictions can be achieved by utilising deep learning techniques, notably CNN models. The metrics for estimation performance were 97.42% accuracy, 97.39 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> Precision, and 97.45 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> Recall, respectively. The study's findings support the idea that using deep learning techniques can help doctors make accurate diagnoses, choose the best course of therapy, and monitor patients' prognoses. In comparison to conventional procedures, it substantially offers clinicians a solution. According to the study, managing and interpreting healthcare data may be done much more effectively when machine learning and deep learning techniques are used.
Scene text detection with gradient guidance

In the process of text detection, we frequently encounter numerous indistinct images, which can easily result in text omission and misdetection. Inspired by the SPSR model, we introduce gradient branching to guide the training of text detection models in order to address this problem. By preserving more image edge features, we expect to improve the text detection performance of fuzzy images and fuzzy regions. The experiment demonstrates that the gradient guidance-based text detection model can detect text in ambiguous images more accurately and reduce instances of missing and incorrect detection.
Using a region-restrictive erasing method for one-stage weakly-supervised semantic segmentation

Image segmentation is a classical and basic problem in the domain of computer vision. Due to the fact that fully supervision segmentation methods require dense time-consuming and expensive manual-annotations, lots of WSSS (Weakly-Supervised Semantic Segmentation) methods have been proposed to take advantage of the simplicity and availability of weak supervision annotations. In this work, we build an integrated framework to jointly train the classification task and the segmentation task guided by a self-supervised thinking with only image-level supervision and a compound refinement strategy. Then, we introduce a restrictive adversarial erasing approach to push our model to find more segmentation cues. We evaluate the proposed method on PASCAL VOC 2012 benchmark, and the experiments show that our method can achieve competitive performance compared with the earlier methods.
A text sentiment multi-classification method based on dual graph convolutional network

At present, text sentiment multi-classification model has problems of insufficient semantic feature fusion and ignore the syntactic structure of sentences. Therefore, this paper proposes a dual graph convolutional network model, which extract semantic and syntactic information of text by semantic graph convolutional network and syntactic graph convolutional network. Also, this paper proposes a label graph embedding method to fuse richer semantic features. Finally, experiments on two public datasets show that our method achieves better results.
Path Planning Approaches for Unmanned Aerial Vehicle

The difficulty of finding the ideal path from the starting point to the destination site for a UAV is one of the most essential challenges related with the deployment of unmanned aerial vehicle (UAV). Path planning algorithms are classified into traditional and intelligent algorithms in this article based on the order of discovery of the path planning methods. Intelligent algorithms are algorithms that are inspired by nature and can efficiently tackle the complex path planning problem. In this article, by introducing the different advantages of traditional algorithms and intelligent algorithms, it proposes employing intelligent algorithms to address the inefficiencies of traditional algorithms in uncertain conditions. The essay also outlines three classical intelligent algorithms and proposes optimization algorithms for their respective deficiencies. The article also discusses the objectives and constraints of UAV path planning. This analysis will help define the outcomes of UAV path planning and suggest the future research directions.
Reinforcement Q-Learning for Path Planning of Unmanned Aerial Vehicles (UAVs) in Unknown Environments

Path planning for Unmanned Aerial Vehicles in environments with obstacles remains a challenging task. Traditional algorithms, such as A* and Dijkstra, have limitations when dealing with dynamic and changing obstacles, as well as unknown environments. In this paper, a Q-Learning approach for the path planning of UAVs in obstacle-rich and unknown environments is proposed. The impact of alpha, gamma, epsilon, the initial matrix, and reward parameters on the learning process is investigated to achieve safe and cost-effective paths with reduced execution time. The proposed approach is evaluated through simulations by adjusting the alpha, gamma, epsilon, initial matrix, and reward values, and the results demonstrate the effectiveness of the proposed method. The simulation results show that adjusting all the studied parameters can significantly improve the performance of the proposed approach, leading to paths that meet cost and timing objectives while avoiding obstacles.
SOPHICALITY IN THE SACRED PRACTICE OF THE EARLY MODERN ERA

Main objective of the study is to reveal the issues of the existence of sacred musical art of the early modern era through the prism of the signature of sophicality as the ideological core that creates the national image of the world. In the course of the research the source-historical, historical, musical-theoretical methods of research were used. This aspect of the study allows for a wider disclosure of the world view features of musical art as an integral branch of national culture. The task of the research is to examine the influence of sophicality on the sacred practice of monodic singing of the early modern era. The cherubic song samples of the Kyiv and Bulgarian versions of singing chosen for analysis allow us to identify and highlight signs of sophicality in the ancient sacred art. Different aspects of sophicality appear on the figurative, melodic and intonation, as well as structural and compositional levels of singing. Light feelings reflected in the angelic hymn are associated with the sophical images of enlightenment, spiritual vision, and insight, which have grasped the meanings of Kyiv culture. With the help of such a technique as raising the melody to a quart and returning to the smooth, lateral movement, the elevation of the soul state is revealed. Structural and compositional decisions of both cherubic songs indicate the meaningfulness of details and form intact. An important dramatic and semantic function is played by repetitions and returns to the constructions, which are based on the main melodic course, the fluctuations of the melody in the form of a dotted, syncopated rhythm, its temporal expansions or contractions. Emotional sense defines the originality of the metric and modal resistance feeling. These and other means enhance the understanding of the text through emotional perception. The inexhaustible wisdom inherent in the structure, as well as emotional and expressive means of monody, turns it into a cultural and artistic phenomenon of the era, which is simple from the outside but extremely deep in its inner essence. The practical significance of the publication is to use the proposed aspect of the analysis of monodic heritage in further artistic studies, as well as in training courses on the history, philosophy, and psychology of art.
A Study on the defense perception and response in 『HadongYuksa』

In the Chosun dynasty, the academic logic that Japan should be viewed from an objective point of view has begun to emerge from the previous notion of emotional and enemy. The reason for this change was that the Chosun scholars were able to rediscover Japan by reading the visiting records of Korean diplomats. Diplomats visiting Japan were allowed to give their friends the records they wrote while visiting Japan.&#x0D; As a result, the change in the perception of diplomats about Japan could be conveyed to the contemporary scholars of the Chosun dynasty. Meanwhile, in the early 19th century, with the introduction of Western, there was a heightened sense of spirit for the invasion of external forces in society as a whole. As a result, a sense of crisis over Japan's re-invasion increased and awareness of national defense was strengthened.&#x0D; In the process of revising and supplementing Han Chi-yoon’s 『 HadongYuksa』, this background of the times played a role, and it was expressed as a 「Bonzobeigo」 item in 「Ilbonko」 and the aspect of national defense was further strengthened.&#x0D; This change is related to the rise of foreign scholars in Japan, creating a national academic climate, and as a result, calls to change Japan’ region where diplomats go, which has led to a general heightened sense of external crisis in the Chosun.&#x0D; In 『HadongYuksa』, it was urged to defend the gateway and the sea through the explanation of the change of the northern tribe and the sea route, and emphasized the preparation of the defense measures for the territorial defense.&#x0D; The Defense perception In 『HadongYuksa』 is largely due to the heightened interest in the historical geography of Korea and territorial consciousness, which is in line with the silhak scholars who were one of the central tasks of establishing the status of their own country and grasping their own history.
A Study of Children’s Play Songs Published in the Eorini (Children) Magazine

This study focuses on the children’s songs featured in the Eorini started publication in 1923. The significance of children’s play music was investigated by examining newspaper articles, focusing on Dance and Recreation Schools which were popular in the late 1920s, and examines the correlation between Eorini and the Dance and Recreation School.&#x0D; The research examined songs featured across 116 editions of the Eorini, pinpointing six children’s play songs and a play chang'ga. The findings were as follows:&#x0D; First, a total of six children’s play songs were published in the Eorini, including a play chang'ga. Four songs were accompanied with photos, and two songs had commentary. The music were interesting to children, while being easy to sing and follow.&#x0D; Second, the study examined the correlation between children’s play songs featured in the Eorini and the School. From 1928 to 1949, it offered courses tailored for kindergarten educators. The study found that Kim Young-jae, served as the primary contributor, writing dances for four out of the six songs in the Eorini. He was the most active trainer in the School, and worked in many nursery schools. Dance and play education in the 1930s was considered important based on newspaper articles at the time. The play songs in the Eorini were disseminated to kindergartens through the School, primarily by Kim Young-jae, influenced education in kindergartens. This study demonstrates the magazine’s stature, societal, educational impact, and influence in the 1920s and 1930s.
Study of Korean Studies in China from the Perspective of Area studies

This article investigates the research prospect of Korean studies after area studies have been newly established as a discipline in China. This study quantitively analyzes the current research situations and research fields of Korean studies based on the examination of the Korean Studies-related research projects sponsored by National Social Science Funding which is the representative national research project in China, and the Korean Studies-related articles published on the journals in China. The findings are: 1) the foundations of Korean studies in China are expanding;2) both the quantity and quality of Korean studies in China are increasingly growing. It is thus shown that more attentions have been paid to East Asian studies, China Theory, China perspective, comparative study and bilateral relation study. However, as an interdisciplinary field, there is a lack of interdisciplinary collaboration and cooperation between Chinese and Korean researchers. It is thus suggested that more exchanges and cooperations should be needed among the researchers from different disciplines, different areas and different nations in order for the problems to be solved.
Development application Smartness Help for the disabled blind with text and image detection

Blindness is a condition in which a person’s sense of sight does not function either partially (low vision) or as a whole (total blindness). Physical limitations make it difficult for them to access information and knowledge in the form of books or other printed media. This study was aimed at developing application smartness help for the disabled blind with text and image. The research method (RD) uses the waterfall model. The study was conducted at SLB-A YPPLB Payakumbuh with the results of the assessment of material experts 93.3%, and media experts 86.7% who stated that the Smartness Help application was “very feasible” to use and be tested on blind people. The results of trials on blind people using the Smartness Help application yielded 87% results, all of which were categorized as very feasible.
THE EFFECT OF USING ENGLISH SONG TOWARDS STUDENTS’ VOCABULARY MASTERY

The aim of this study was to investigate the impact of incorporating English songs in teaching on the vocabulary proficiency of fourth-grade students at SD IT Cahaya Madani. The motivation for the study was due to the challenges that students faced in mastering English vocabulary, including disinterest and lack of motivation, limited vocabulary, and perceived difficulty in understanding the language. To address these challenges, the researcher used a quantitative approach with a quasi-experimental research design that involved two classes, the fourth Abu Ubaidah class (control) and the fourth Umar class (experimental), both comprising 27 students. Each class did the pre-test and post-test. The vocabulary test was the main research instrument, and the data was analyzed using the independent sample T-test in SPSS 26. The findings revealed a significant difference in the vocabulary proficiency of students who were taught with English songs compared to those who were not. The t-table was 2.059, which was smaller than the t-obtained (16.694). It means using English song enables students improve their vocabulary mastery, make fun learning and avoid stressful. Suggesting that the use of English songs had a significant impact on the students' vocabulary mastery.
Development of a Molecular Biology Experimental Program for Gifted Science Students to Understand Biological Characteristics through Protein Profiles

Proteins are essential biomolecules that govern cellular activities and play a crucial role in understanding the characteristics of living organisms. A proper understanding of proteins is essential for comprehending the life sciences at the molecular level. In this study, our objective is to provide an experimental educational program for science-gifted middle school students to grasp the concepts of protein-based molecular biology. The experiments we have designed aim to analyze proteins from various organisms, helping students gain insights into their characteristics. To achieve this, we extract proteins from Escherichia coli, yeast, and human plasma/blood cells, and then separate total proteins by size using protein electrophoresis after adjusting their concentrations. Subsequently, we qualitatively determine the quantity and size of proteins through protein staining/de-staining processes. This is followed by discussions and comprehension of the major proteins in relation to biological characteristics. The entire experiment takes approximately 6 hours, allowing participants to learn diverse and universally applicable molecular experimental techniques related to protein analysis. To assess the effectiveness of this program, we conducted both a pre-test and post-test with nine participants who completed the experimental module, and we also gathered additional program feedback. The results of the experimental module showed high satisfaction among the participants, who did not encounter significant difficulties in understanding the experimental content. Furthermore, there was a slight increase in interest and career aspirations in molecular biology, and knowledge of intracellular protein roles and related molecular biology significantly improved. Therefore, This experimental program is expected to facilitate students in comprehending molecular biological concepts based on proteins and establishing a foundation for conducting molecular biology-related research, and ultimately to assist in making their informed career choices in the life sciences.
THEATRICAL ART IN THE CONDITIONS OF SOCIO-CULTURAL TRANSFORMATIONS

Objective of the study is to present a socio-cultural analysis of the changes taking place in the domestic theatrical art. &nbsp; The methodological basis of the research is based on a combination of sociological and culturological approach, which allows us to show the external and internal factors of the transformation of the theatrical and artistic process. Research results. The dynamics of the development of theatrical art in the country is manifested in the strengthening of trends in the preservation of national traditions and the desire to answer the burning questions of our time. &nbsp; Prospects of the study are associated with the increasing importance of theatrical art in the socio-cultural development of Russian society, which requires systematic sociological research of creative processes in the sphere of theater and changes in the spiritual needs and tastes of the audience. &nbsp