Reviewerly/exHarmony huggingface dataset:
A study on Korean language education in middle and high schools in the refuge capital of Busan during the Korean War - Focusing on the organization of curriculum and the composition of textbook contents -

In this study examined how Korean language education was developed in the refugee capital of Busan during the Korean War and how it was operated by refugee School. The teaching points established during the U.S. military period were not properly reorganized due to the outbreak of the Korean War when the curriculum reorganization was discussed, and each school partially modified and used the teaching points of the U.S. military period according to the war situation. During the Korean War, many refugee schools were established in the refuge capital of Busan, but it was difficult to conduct regular classes due to insufficient supplies and educational facilities. However, despite difficulties in the operation of the regular curriculum under special circumstances during wartime, education continued. Accordingly, the refugee School operated school classes by applying a curriculum according to their respective conditions. A ceasefire agreement was signed in July 1953，and the curriculum was revised and promulgated on April 20，1954 Accordingly, each school also returned to school to reorganize the school system, and school classes were normalized. In addition, Korean language education was actively conducted at each school. Wartime education m the refuge capital of Busan, was developed into real-life-oriented Korean language education that overcomes the disconnection of education and uses Korean in real life. And this can be said to be the basis for the reconstruction of post-war Korean language education. In this study, how Korean language education developed during the Korean War was examined through the U.S. military regular and middle and high school curriculum during the Korean War, and compared with the post-war revised and promulgated curriculum. In addition，the curriculum is intended to substantially implement education, and it is the textbook that consists of specific educational materials specified m the curriculum. Therefore, based on this curriculum, it was also examined how Korean textbooks were compiled and what contents and composition systems Korean textbooks published during the Korean War had.
Transfer Learning for An Transformer-Enhanced ResNet34 Model

Image classification is a well-studied field in the computer vision area. The mile-stone works include VGGNet, AlexNet, ResNet and so on. Meanwhile, the transformer model has been proven the great effectiveness in the computer science domain. In this paper, we focus on the methods incorporated transformer layers which can enhance the model's capability by integrating different strategies upon the state-of-the-art baseline models. Concretely, we propose a novel method that can improve the performance grounded on ResNet34 in a public dataset. The experimental results indicate our model can achieve a higher F1 score compared to other baselines models under the identical settings, which proves the effectiveness of our proposed method.
Prohibited items detection on X-ray images with multi-task learning

Inspection by X-ray has a wide range of applicability in airports, subways, railway stations, bus stations, and shipping ports. However, using X-ray images during security inspections is challenging because the X-ray image containing prohibited items (positive samples) in the real-world security inspection scenario is much smaller than those that do not contain prohibited items (negative samples). This results in low detection efficiency of the auto security inspection and many false detections. Considering this problem, this paper proposes detecting and recognizing prohibited items on X-ray images in real-world security inspections based on multi-task learning (MTL). This method uses an image classification network to filter out most X-ray images that do not contain prohibited items, thus reducing false detections and improving detection efficiency. MTL simultaneously trains the image classification network and the detection network of prohibited items. In addition, the backbone of the MTL network adopts a model sharing method that can reduce model parameters and improve the convergence speed of the model. Based on a dataset of security inspection X-ray images where the ratio of negative samples to positive samples is 100 (SIXray100), we performed data augmentation, estimated the target anchor of the training set, and used the concept of multi-scale training to complete the model training. Compared with the class-balanced hierarchical refinement method (CHR) that proposed a benchmark in detection, our method shows an improvement of 2% to 5%. Moreover, as the number of test images increases, our approach will obtain results that significantly exceed those from previous research. At the same time, this paper’s strategy for detecting prohibited items and its shared neural network framework have significant application value in engineering.
Anonymous Trajectory Method for Indoor Users for Privacy Protection

The privacy of the trajectories of indoor space users is just as important as that of the users of outdoor spaces. Many users of indoor spaces consider it very important to maintain the privacy of their movements within buildings and not reveal their visit to a certain room/cell inside buildings. In this paper, we propose a cloaking diversity approach for moving entities in indoor spaces. This new privacy-assurance approach uses the cloaking concept adapted with processing diversity trajectories to safeguard user privacy in an indoor space. Extensive simulations and evaluations have demonstrated that the proposed privacy approach algorithm performs well and at a low cost.
Speech Manipulation Detection Method Using Speech Fingerprints and Timestamp Data

We propose a method for detecting tampering of audio recordings using speech fingerprinting and time stamp data concurrently. In the proposed method, fingerprints extracted from audio recordings along with the time stamp data are embedded into audio recordings as watermarks for tamper detection. The decoder uses fingerprints extracted from the audio recording itself to detect tampering. The vector distance between fingerprints obtained from the watermark and the fingerprints obtained from the recorded audio is calculated. If the distance is greater than a predetermined threshold, the system determines that it has been tampered with. Concurrently, the time stamp data obtained from the watermark is checked for continuity, and if the values are discontinuous between consecutive frames, it is determined that the data has been tampered with. The fingerprints prove that the audio recording is original, and the time stamp data proves the consistency of the recording. Together, they guarantee the authenticity of the recording. In this paper, we evaluated the accuracy of tampering detection against speech substitution, insertion, and deletion and obtained 100% accuracy.
Acoustic Nudging-Based Model for Vocabulary Reformulation in Continuous Yorùbá Speech Recognition

Speech recognition is a technology that aid processing of speech signals through communicating with computer applications. Previous studies exhibits speech recognition errors arising from users’ acoustic irrational behavior. This research paper provides acoustic nudging-based model for reformulating the persistence of automatic speech recognition errors that involve the user’s acoustic irrational behavior and distortion of speech recognition accuracy. Gaussian mixture model (GMM) helped in addressing the low-resourced attribute of Yorùbá language to achieve better accuracy and system performance. From the implemented results, it was observed that the proposed acoustic nudging-based model improves accuracy and system performance based on Word Error Rate (WER), validation, testing and training accuracy. The evaluation results for the mean WER was 4.723% when compared to existing models. This approach thereby reduces error rate when compared with previous models by GMM (1.1%), GMM-HMM (0.5%), CNN (0.8%), and DNN (1.4%). Therefore, this work was able to discover a foundation for advancing the current understanding of under-resourced languages and development of an accurate and precise model for speech recognition.
Why Students’ Quality Circles is Necessary in Academics?

An educational institute is not only a center for providing appropriate knowledge and skills but a character building institution as well. We define total quality person (TQP) as a person having pro-social personality or in other words who is smart as well as good in nature. TQP is a smart person having the right attributes to compete and excel in the society. Also, TQP is a good person who possesses the pro-social character to work collaboratively for the betterment of the society. When a person is young and his mindset is clean, it is easier to change his perception and develop his personality traits and habits. Students’ Quality Circle (SQC) is an innovative intervention process at educational institution for students’ personality development. SQC is a small team of like-minded students who meet regularly in their institutional premises to identify, analyze, and solve their own problems. The primary purpose of SQC is to enhance the pro-social personality of students and thus empower them with modern tools and technology as well as boost their moral values. Research finding has shown that students who have practiced SQC at their early age have developed 11 character attributes, skills, and habits.
An Enhanced Bats Algorithm for Optimization Thresholds in Medical Image Segmentation

The key to threshold segmentation is choosing the thresholds that will decide the segmentation’s outcome—the calculation complexity increases as the number of thresholds increases, which causes challenges with traditional methods. This study introduces an enhanced bats algorithm (EBA) for selecting optimal picture segmentation thresholds and applies it to the global optimization issue of the segmentation function’s objective function. The EBA blends well with picture segmentation that produces exceptional computation in global convergence and robustness and prevents trapping into local optimization. It is particularly well suited to solving complex functions with high dimensions and multiple peaks. Compared to GA and PSO, extensive theoretical study and simulation results reveal that EBA has greater efficacy, efficiency, stability of the range of thresholds, and quality in multi-image and multi-thresholds segmentation.
Recent Advances in Sign Language Detection: A Brief Survey

The phenomena related to the domain of detecting an individual’s sign gestures and converting it into text in real-time has been an elucidating outlook for the people possessing disabilities. The diversity of researches is in existence for contemplating and actuating the ideation. Varied methodologies have also been induced for amalgamation of sign gesture detection with text-to-speech enabling the possibilities of helping the ones in need. Through this aid, they can convey their message through sign language which can be easily understood by people unfamiliar with it after converting it into text and thus devices that can convert this text to speech may also be developed. In this paper, we’ve tried to collate various modus operandi’s revolving around such approaches and also scrutinized over it for displaying comparative perspective.
Model Aplikasi Animasi Berbasis Android Untuk Pembelajaran Bahasa Isyarat Indonesia Bagi Penyandang Tunarungu

Abstrak. Jumlah pengajar yang terbatas dan Kamus Bahasa Isyarat Indonesia (Bisindo) yang tidak tersebar secara merata menyebabkan penyandang tunarungu yang tidak mengikuti pendidikan formal dan masyarakat umum yang ingin mempelajari bahasa isyarat mengalami kesulitan. Makalah ini menyajikan model aplikasi visualisasi untuk pembelajaran Bisindo berbasis Android bagi penyandang Tunarungu. Pengembangan sistem mengikuti tahapan dalam metode &lt;em&gt;Multimedia Development Life Cycle&lt;/em&gt; (MDLC), menggunakan &lt;em&gt;software Adobe Flash Profesional&lt;/em&gt; CS6 dan &lt;em&gt;CorelDraw X7&lt;/em&gt; dalam pembuatan gambar animasi. Fitur dasar aplikasi terdiri atas penyajian bahan ajar berbasis animasi dan Kuis. Ruang lingkup pembelajaran mencakup pembelajaran mendasar 1 yang terdiri atas abjad, angka, dan perkenalan hingga pembelajaran mendasar 5 yang mencakup kata tanya, salam, serta kata benda. Kuis disajikan dengan teknik acak bertingkat dan bersyarat. Hasil pengujian fungsionalitas sistem yang terdiri dari fungsi penyajian materi, penyajian kuis, pengujian animasi, serta pengujian &lt;em&gt;backsound&lt;/em&gt; telah valid sesuai hasil analisis kebutuhan sistem. &lt;br /&gt;&lt;p&gt;&lt;em&gt;Kata kunci: &lt;/em&gt;&lt;em&gt;Aplikasi Animasi, &lt;/em&gt;&lt;em&gt;Bahasa Isyarat, &lt;/em&gt;&lt;em&gt;Berbasis Android, &lt;/em&gt;&lt;em&gt;Multimedia Develoment Life Cycle &lt;/em&gt;&lt;em&gt;(MDLC)&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;&lt;strong&gt;Abstract. &lt;/strong&gt;The limited quantity of teachers and the unequal distribution of the Indonesian Sign Language Dictionary (Bisindo) cause deaf people who do not attend formal education and the general public who want to learn sign language to experience difficulties. This paper presents a visualization application model for Android-based Bisindo learning for people with hearing impairments. System development follows the stages in the Multimedia Development Life Cycle (MDLC) method, using Adobe Flash Professional CS6 and CorelDraw X7 software in making animated images. The basic features of the application consist of presenting animation-based teaching materials and quizzes. The scope of learning includes basic learning 1 which consists of the alphabet, numbers, and introductions to basic learning 5 which includes question words, greetings, and nouns. The quiz is presented with a stratified and conditional randomized technique. The results of the system functionality testing consisting of the function of presenting material, presenting quizzes, testing animations, and testing backsound have been valid according to the results of the analysis of system requirements.&lt;/em&gt;&lt;em&gt;&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords&lt;/em&gt;&lt;/strong&gt;&lt;em&gt;: Animation Application, Sign Language, Android Based, Multimedia Development Life Cycle (MDLC)&lt;/em&gt;&lt;/p&gt;
J. Hintikka’s Interrogative Model of Inquiry and Prospects for Its Application in the Study of Artificial Intelligence

The article outlines the prospects of using J. Hintikka’s interrogative epistemology for modelling cognitive operations carried out by a cognizing agent to create a machine capable of full cognition. It was established that modeling is divided into two objectives: modeling the cognitive operations and modeling the strategic reasoning. Interrogative epistemology presents a solution to the first objective. It relies on a game-theoretic formal apparatus that allows one to correctly describe all types of possible moves within the framework of a particular cognitive game. The second objective cannot be accomplished in a general epistemological theory framework since strategic considerations about the organization of research and even the concept of knowledge inevitably depend on the broader context of an agent’s practical activity. Therefore, interrogative epistemology does not claim a universal and complete description of the process of cognition, focusing on other tasks: primarily on identifying hidden premises that cognitive agents use in their reasoning. For the same reason, interrogative epistemology deems the possibility of the existence of a cognizing machine as formally unsubstantiated and questionable. However, arguments are given in favor of the fact that interrogative epistemology serves as an acceptable conceptual framework for clarifying the nature of the difficulties that arise with attempts to accomplish the second objective and improving the quality of philosophical discourse in the field of artificial intelligence research. The author substantiates this position by arguing that the ability to cognize presupposes the ability to perform all the essential functions that are usually called mental.
Humanities, Scientometrics, and Blockchain

Modern humanities are in an ambiguous situation. Their organization is experiencing a radical challenge from the expansion of science-based assessment methods from modern business. We are talking about evaluating the results of researchers’ work on indicators (KPI) from scientometrics. As a result, the evaluation subject is not the content of the research result, but their popularity and relevance to dominant views and approaches. The science organization turned upside down: it turns out not scientometrics for science, but rather science for the sake of scientometrics. At the same time, digitalization and related information and communication technologies are a great achievement of civilization. Therefore, it is all the more important and useful to resist the thoughtless digitized bureaucracy using the digitization itself. This article is an attempt not to criticize digital methods, but to consider the possibilities of using blockchain technology, its advantages and the problems it generates. There are such opportunities as transparent self-organization of scientific communities, assessing the contribution and its priority, encouraging researchers. At the same time, the implementation of the blockchain implies the interest of a critically significant group of scientists with a high reputation. It is equally important to demonstrate the convenience and effectiveness of scientific work using the blockchain. The article draw attention to the significance to propose and discuss approaches to methods for assessing the quality of humanitarian and interdisciplinary studies that are adequate to the scientific practice itself, that arouse the general confidence of scientists.
Output Observer based Fault Tolerant Control of Mecanum Wheel Robot

Currently mobile robot platforms are increasingly used as tools for assisting human. The design and research of mobile robot built navigation and control algorithm assuming all actuators in normal condition. This paper proposed the output observer based method to identify the fault components and adapt the navigation strategy. The kinematic of robot is reformulated depending on fault states so that the robot is able to reach the goal. The performance of the proposed fault tolerant control method is verified in simulation.
Artificial Intelligence Machines in Medicine and Healthcare Management

In medicine, as in many aspects of our lives, we are experiencing the implementation of software tools described as artificial ‘intelligence' (AI) or, more precisely, machine learning (ML). These are systems built on a body of mathematics combining Bayesian probability modeling, rules, and neural networks (NN). This transformational technology is a cause for much optimism and concern. The change enabled by any new technology is naturally followed by a gradual appreciation of the impact, as optimism is gradually tempered by real experiences, often as we revise and refine our opinions in a dialectic manner. It takes time to understand the capabilities of these AI and ML tools before we can feel safe and comfortable working with them in critical tasks. These issues are discussed from various perspectives with implications for the future of how we consider evidence in medical decision-making.
An Examination of Learning 3D Modeling Software and Creating 3D Data Using Online Video in a 3D Printer Workshop for High School Students

In the educational use of 3D printers, the key issue is how to support students in learning 3D modeling software. However, students have few opportunities to practice operating them, especially in primary and secondary education in Japan. In order to obtain insight into how to support students in learning to operate 3D modeling software, we used online video to exam whether students could create 3D data similar to their design sketches. Specifically, we learned how long it would take them to create 3D data in a 3D printer workshop for five high school students. We found that all of the students could create 3D data with almost the same shape as their design sketches using online video. The students took 2 to 5 hours to create the first 3D data, and all of the students completed the second and subsequent 3D data in much less time than the first.
Evaluation of Content-based Tour Recommendation Systems

This paper reports preliminary experiments conducted to compare the performances of two content-based tour recommendation systems. These systems receive a tour review as a query, and then recommend related reviews written by others. To evaluate the relevancy of each review to the query, the two systems use the BoW (Bag-of- Words) model and the LSA (Latent Semantic Analysis) model, respectively. From the experiments, we confirmed that both the two models can recommend reviews which are related to the query review. In addition, we confirmed that while the BoW model tends to recommend reviews of tourist spots which are completely same as the query review, the LSA model tends to recommend information about more diverse tourist spots.
Development and Evaluation of a Search Application for Elementary School Programming Materials

Programming education becomes compulsory in Japanese elementary schools from the fiscal year 2020. However, many elementary school teachers have no programming experience. Therefore, in this study, we will develop a programming material search application to assist teachers of programming education in selecting teaching materials. In this paper, the application contains teaching materials presented by the Future Learning Consortium supported by the Ministry of Education, Culture, Sports, Science, and Technology, etc. It not only searches for teaching materials using various criteria but also displays examples of implementation and comments from teachers. The application was also reviewed by active elementary school teachers and received a good evaluation.
Coping Support and Stress Detection Using Ambient Computing

This study employs sensors to create a lifelog that records human biometric and behavioral information as digital data. Then, from the log, we can identify human behavior. Identifying the behavior makes it possible to adopt stress countermeasures. This paper proposes a method to support individuals from mental and physical burdens by analyzing stress countermeasures and providing assistive displays through smart glasses. Also, since the display from the sensor to the smart glasses is automatically processed, no specific operation is required on the human side. Therefore, the system functions as ambient computing. We aim to develop an ambient computing system that can determine the coping contents and display them on the smart glasses based on the user&#x0027;s behavior identification without any operation.