Reviewerly/exHarmony huggingface dataset:
｢興味｣と｢関心｣の違いについて －連語とレジスターに注目して－

Regarding the difference between synonyms KYOMI and KANSHIN, paying attention to the three points of generality, register distribution, and collocation characteristics, and based on examples that appear in the modern Japanese written word equilibrium corpus (BCCWJ) analyzed. First, the difference in the frequency of use of KYOMI (8,212, 54.8%) and KANSHIN (6,787, 45.2%) extracted from the BCCWJ interface SHONAGON is very weak, and it is remarkable in the degree of generality. There was no difference. On the other hand, in the register, KYOMI is often used mainly in everyday scenes and simple conversational forms, and is not often used in public scenes or revised sentences, whereas KANSHIN is public. There was a tendency that it was used in typical scenes and modified writing styles, but not used in everyday scenes and simple conversational forms. Conjunctive features focus on the semantic differences of co-activators in typical grammatical patterns of “KYOMI-verb” and “KANSHIN-verb”, and KYOMI is unrelated to the will of the subject. it was found that KANSHIN is a rational and willing psychology, while KYOMI is emotionally and accidentally intriguing.
Insurance Fraud Detection Using Machine Learning

Every year, the insurance industry losing billions of dollars due to fraud. The act when a person makes fake insurance claims to gain benefits, compensation &amp; other advantages to which they are not entitled is known as Insurance Fraud. Nowadays insurance fraud detection is becoming a tedious problem for insurance companies to deal with as they need more investment and workforces to keep track of every transaction. In this paper, we are focusing on the major issue faced by insurance companies that is insurance fraud. we use the machine learning technique to detect insurance fraud based on the transactional data given by the insurance company. We build predictive models and compare their performance by calculation of confusion matrix then it is evaluated on various performance measuring parameters like accuracy, precision, recall, F1 score, and on AUC curve. SVM (Support Vector Machine) and XG Boost (Extreme Gradient Boosting) are the machine learning algorithms used. After model evaluation, we select the best model for prediction.
Exploring Question-Specific Rewards for Generating Deep Questions

Recent question generation (QG) approaches often utilize the sequence-to-sequence framework (Seq2Seq) to optimize the log likelihood of ground-truth questions using teacher forcing. However, this training objective is inconsistent with actual question quality, which is often reflected by certain global properties such as whether the question can be answered by the document. As such, we directly optimize for QG-specific objectives via reinforcement learning to improve question quality. We design three different rewards that target to improve the fluency, relevance, and answerability of generated questions. We conduct both automatic and human evaluations in addition to thorough analysis to explore the effect of each QG-specific reward. We find that optimizing on question-specific rewards generally leads to better performance in automatic evaluation metrics. However, only the rewards that correlate well with human judgement (e.g., relevance) lead to real improvement in question quality. Optimizing for the others, especially answerability, introduces incorrect bias to the model, resulting in poorer question quality. The code is publicly available at https://github.com/YuxiXie/RL-for-Question-Generation.
Odyssey local design cultivation / Faculty of Art and Design UiTM Cawangan Sarawak

REQASENI XV is an event that is meant to showcase the artworks and designs made by the students from the Faculty of Art and Design. The groups that are showcasing their artworks are from Graphic Design and Fine Art. The work of Graphic Design students are more towardsrebranding, redesigning existing designs, and also creating new designs for companies, businesses, and events by utilising the use of technology. As for Fine Art students, the artworks are more on contemporary arts and studying the media dimensions as the main consideration inproducing artwork.
Secure Ob ject Detection Based on Deep Learning

Applications for object detection are expanding as it is automated through artificial intelligence-based processing, such as deep learning, on a large volume of images and videos. High dependence on training data and a non-transparent way to find answers are the common characteristics of deep learning. Attacks on training data and training models have emerged, which are closely related to the nature of deep learning. Privacy, integrity, and robustness for the extracted information are important security issues because deep learning enables object recognition in images and videos. This paper summarizes the security issues that need to be addressed for future applications and analyzes the state-of-the-art security studies related to robustness, privacy, and integrity of object detection for images and videos.
The First Innovation to Record Sound

The First Innovation to Record Sound is an investigation to find the first invention to record sound. A lot of innovations emerged with various titles and purposes of sound recording but lack the ability to contend their presence. The phonograph, phonautograph, and quipu are inventions that claim to be the first device to record sound. It is obvious all three innovations are not the first to record sound, which ignited this historical research study. A thorough examination was conducted upon the phonograph, phonautograph, and quipu to find factual results regarding the First Innovation to Record Sound.
Humanities 3.0 Era and Humanities Engineering

This challenging humanities research methodology, which can be conceptualized as “Humanities engineering,” declares the beginning of the 3.0 humanities era. If traditional humanities was humanities 1.0, digital humanities, which actively attempted to recruit IT as a research methodology is 2.0, and humanities engineering that aims to view humans and society from a deeper and broader viewpoint than technology by taking the help of technology is humanities 3.0. Changes in social needs and requirements also reconfigure the role of humanities education. The twenty-first century talent is a self-directed learner who can produce knowledge based on given information and acquire wisdom in the process. The core of intellectualization is creative thinking that addresses information. All newness starts from what is old and familiar. Although technology looks at the future, thinking remembers the past. Reading, understanding, and analyzing the classics is what humanities education can do best. The goal of university education in the digital period is to cultivate the talent needed in the knowledge information period to strengthen humanities education. Humanities education helps us to proceed and maintain moral value as humans; it teaches us the expansion of thinking that sparks the commercialization of information.
Susan Druid and X-treme X-citement

Can a cross-organizational firm work with a more traditional client company to develop new marketing services in a virtual environment? This case looks at the corporate culture of the X-treme X-citement company and how it is fostered and maintained in a virtual setting.
Multilingual Speech Translation with Unified Transformer: Huawei Noah’s Ark Lab at IWSLT 2021

This paper describes the system submitted to the IWSLT 2021 Multilingual Speech Translation (MultiST) task from Huawei Noah's Ark Lab.We use a unified transformer architecture for our MultiST model, so that the data from different modalities (i.e., speech and text) and different tasks (i.e., Speech Recognition, Machine Translation, and Speech Translation) can be exploited to enhance the model's ability.Specifically, speech and text inputs are firstly fed to different feature extractors to extract acoustic and textual features, respectively.Then, these features are processed by a shared encoder-decoder architecture.We apply several training techniques to improve the performance, including multi-task learning, task-level curriculum learning, data augmentation, etc.Our final system achieves significantly better results than bilingual baselines on supervised language pairs and yields reasonable results on zero-shot language pairs.
Gambaran Tingkat Pengetahuan Dan Sikap Ibu Tentang Trauma Gigi Permanen Pada Anak Usia 8-12 Tahun : Kajian pada Ibu dari Murid SD Nabawi Islamic School, Kota Jakarta Timur (Laporan Kasus)

Background: Children's dental trauma mostly occurs in the maxillary anterior teeth, and falls, sports, traffic accidents, etc. can cause dental trauma. Generally speaking, children experience dental trauma when they are 8-12 years old. Therefore, dental trauma is a serious problem that often occurs in children and requires special attention from parents, especially mothers. Objective: To understand mother’s knowledge and attitudes towards children’s permanent tooth trauma Method: A descriptive observational cross-sectional design was adopted to conduct a survey of 70 respondents. The data was collected using a questionnaire, including 21 questions, tested validity and reliability. The research data is presented in the form of a frequency distribution table. Results: The adequate degree of mother's description of children's dental trauma knowledge was 75.7%, less than 15.7%, and less than 8,6%. In terms of attitude, 44.3% of the respondents hold a high attitude, and 55.7% of the respondents hold a low attitude. Conclusion: Most mothers have a high understanding of dental trauma, but there are still many mothers who have a low attitude towards dental trauma.
Boosting Digital Literacy in the Workplace

This brief outlines lessons learned from interviews of business, education, and workforce leaders on how issues of digital literacy are affecting workers and how to acquire them.
‘한국전쟁’ 역사기념시설의 전시 서사와 역사 교육적 의미

In recent history education, interest in civic education has been increasing, and attention has been paid to the influence of the form and contents of exhibition narratives of museums or historical memorial facilities that are delivered to visitors in the context of citizens’ social memories and memory culture. Among the historical memorial facilities, war memorial facilities have great social influence. In particular, memories of the “Korean War” have been deeply involved in the historical consciousness and historical culture of members of post-war Korean society. Thus, the “Korean War” as a theme of history learning or exhibition has significant meaning in the context of history education oriented toward citizen education. With this in mind, this study analyzed the potential wartime history of The Warmemorial of Korea, Patriot and Peace Memorial, DMZ Museum, and War and Women’s Human Rights Museum focusing on the importance of the educational and social role of historical memorial facilities and the growing influence of the Korean War.The theory of historical consciousness and type of narrative (traditional type, typical type, critical type, and genetic type) of Jorn Rusen was borrowed to analyze the exhibition narrative of the historical memorial facilities. Using Rusen’s historical consciousness as a tool to analyze the history of the Korean War, Rusen analyzed the exhibition narratives of each historical memorial facility by linking the past to the present and the future in a way that embodies the past. After reviewing and analyzing the large narrative of the exhibition and the ‘Narrative abbreviation’, historical memorial facilities showed overlapping narrative and historical consciousness types. Meanwhile, traditional and typical types of wartime narratives stood out at the War Memorial of Korea and Patriot and Peace Memorial. In particular, the Patriot and Peace Memorial wanted to convert traditional and typical narratives into memories for local identity. The War and Women’s Human Rights Museum showed critical and genetic exhibition narratives from the perspective of approaching the ''war'' itself, although it is not a memorial facility directly related to the Korean War. While revealing typical and traditional war narratives and their corresponding historical consciousness, the DMZ Museum attempted various angles of narrative, conscious of critical discourse.We learn history and try to understand the direction of our lives through understanding history. As historical memories are valued, the impact of memories other than textbooks on our perception of history is growing. The memory of war is stronger in that character. In particular, war memories by monuments are typical. Since it is an interface between knowing about war and learning how to remember war, it is necessary to think about the historical educational meaning of developing the power to analyze the exhibition history of historical memorial facilities.
Nearest Neighbor Search Under Uncertainty

Nearest Neighbor Search (NNS) is a central task in knowledge representation, learning, and reasoning. There is vast literature on efficient algorithms for constructing data structures and performing exact and approximate NNS. This paper studies NNS under Uncertainty (NNSU). Specifically, consider the setting in which an NNS algorithm has access only to a stochastic distance oracle that provides a noisy, unbiased estimate of the distance between any pair of points, rather than the exact distance. This models many situations of practical importance, including NNS based on human similarity judgements, physical measurements, or fast, randomized approximations to exact distances. A naive approach to NNSU could employ any standard NNS algorithm and repeatedly query and average results from the stochastic oracle (to reduce noise) whenever it needs a pairwise distance. The problem is that a sufficient number of repeated queries is unknown in advance; e.g., a point may be distant from all but one other point (crude distance estimates suffice) or it may be close to a large number of other points (accurate estimates are necessary). This paper shows how ideas from cover trees and multi-armed bandits can be leveraged to develop an NNSU algorithm that has optimal dependence on the dataset size and the (unknown) geometry of the dataset.
Big Data Integration.

Until recently, structured (e.g., relational) and unstructured (e.g., textual) data were managed very differently: Structured data was queried declaratively using languages such as SQL, while unstructured data was searched using boolean queries over inverted indices. Today, we witness the rapid emergence of Big Data Integration techniques leveraging knowledge graphs to bridge the gap between different types of contents and integrate both unstructured and structured information more effectively. I will start this talk by giving a few examples of Big Data Integration. I will then describe two recent systems built in my lab and leveraging such techniques: ZenCrowd, a socio-technical platform that automatically connects Web documents to semi-structured entities in a knowledge graph, and Guider, a Big Data Integration system for the cloud.
Il passato perfettivo in italiano L2: analisi di testi scritti

This study aims to investigate the strategies used by university students to express completed actions in the past in their written work in Italian as a second language. In particular, we focus on issues of morphological nature; however, we also pay attention to phenomena of cross-linguistic influence. In conclusion we share our observations as far as the teaching of the perfect aspect during Italian L2 classes. Data has been collected by the researcher in various Italian Universities.
Home's Décor - Home Decoration Implementing Augmented Reality

Abstract: Home’s Decor is a combination of Augmented Reality (AR) technology and interior design integrated into a smartphone application. The aim of this project is to present the implementation of an interior design mobile application using AR technology, a new alternative technology to projecting a virtual object into the real world with the device as an interface. The interior design application has the capability to project a three dimension (3D) object that can then be scaled, rotated and displaced by the user from multiple perspectives on a flat ground plane. This project was conducted by following the ADDIE Model while the project was designed and developed using Unity 3D and Vuforia. The Home Decor application prototype will widen the perspective of technology advancement where users can visualize the virtual world within the real world.
Using Variational Multi-View Learning for Classification of Grocery Items

An essential task for computer vision-based assistive technologies is to help visually impaired people to recognize objects in constrained environments, for instance, recognizing food items in a grocery store. In this paper, we introduce a novel dataset with natural images of grocery items -- fruits, vegetables and packaged products -- where all images have been taken inside grocery stores to resemble an actual shopping scenario. In addition to the natural images, we download an iconic image and a text description of each item that can be utilized for constructing better representations of the grocery items. We select a multi-view generative model called Variational Canonical Correlation Analysis (VCCA), which efficiently combines the different information of the items into a single lower-dimensional representation. In the experiments, we show that utilizing the additional information with VCCA yields higher accuracies on classifying grocery items over standard image classifiers that only uses the natural images. We observe from visualizing the latent representations that the iconic images help to construct representations that are separated by the visual differences of the items, while the text descriptions enable the model to distinguish between visually similar items by their different ingredients and flavors. Moreover, we investigate a variant of VCCA called VCCA-private that separates shared and private information of the different data views. We verify that VCCA-private can separate variations in image backgrounds and structures of text sentences from the shared representation to enable a more accurate classification of grocery items in their natural environment.
Portable Virtual Reality-Based Mirror Visual Feedback System for Home Rehabilitation

Mirror visual feedback (MVF) is an ownership illusion that has been applied to manipulate the corporal schema in different kinds of patients. The affected limb is hidden behind a mirror, while the patient observes in the mirror the reflected image of the healthy limb, making him/her believe that it is the affected one. The goal of the present work is to develop a VR-based MVF application that can be used for home rehabilitation, complementing the sessions that take place in the hospital or therapist’s office. In the developed application, the patient visualizes the environment from an egocentric perspective, seated in front of a table where a cube appears at specific moments. The exercise consists of grabbing the cube and moving it to another location. This movement is performed only with the healthy hand, although virtual movements can be observed in both hands. With VR, highly immersive experiences can be created and MVF parameters can be manipulated as needed, which is not possible with a real mirror. These factors, combined with the use of a stand-alone system, make the developed system highly suitable for MVF home rehabilitation.
Pengembangan trainer smart relay zelio sr3b261bd sebagai media pembelajaran pada mata pelajaran sistem pengendali elektronik

This research aims to: (1) develop learning media trainer smart relay zelio SR3B261BD; (2) knowing the feasibility level of learning media trainer smart relay zelio SR3B261BD used in the subjects of electronic control system; and (3) knowing the level of effectiveness of learning media. The research method used is Reaearch and Development (R&D). The development model used is ADDIE with the following stages of research: analyze, design, development, implementation, evalution. The results of the study are: (1) the development of learning media trainer smart relay zelio SR3B261BD according to the design and equipped with a jobsheet and manual book, (2) the feasibility of learning media by media experts get an average score (X) of 3,31 â€œGood/decentâ€, the assessment of material experts received an average score (X) of 3,42 that is â€œvery good/well deservedâ€ and the user ratings are getting a score of 3,44 that is â€œvery good/very decentâ€, and (3) the effectiveness of learning media trainer smart relay zelio SR3B261BD get result score of 0,72 which is catagorized as â€œvery highâ€.Â
A Design of the Improved Data Conversion Process for System Upgrade Project

Data conversion refers to the process of extracting the data existing in the existing system, that is, the past data accumulated by the old information system or other methods and transferring it to the improved table of the new system. The person in charge of data conversion refers to the entire process of converting to the final destination table according to the rules designed/planned in advance. In most cases, data conversion design should be consider when the old system replace or the data of another existing system is converted and applied to a newly constructed information system. The goal of data conversion is to understand the current database system of operating environment, understand the characteristics of the DBMS in use, maintain the optimal database structure, and make the new system perform at its best. Data conversion methods are largely divide into a method using a tool and a conversion method using a program preparation. In this paper, we examine the advantages and disadvantages of the data conversion method, and try to derive the problems of the existing data conversion method. Based on this, an improved data conversion method for the system upgrade project was proposed, and verified through a questionnaire of an IT expert to prove its effectiveness
La virtualización educativa: retos en la formación inicial docente

This article addresses the problem of new challenges in initial teacher training in relation to the Sustainable Development Goals. In this process, the particular role of the trainer in virtual learning environments is identified, which has been amplified since the covid-19 pandemic. Thus, the disruptive changes from face-to-face to virtual teaching have motivated this documentary analysis of hermeneutic orientation, which implies a socio-historical-cultural journey of relevant aspects of initial teacher training, identifying new challenges for teachers in the 21st century, revealing the educational virtualization as a fundamental challenge. The conclusions make it possible to connote the urgency of implementing training processes and pedagogical innovation that allow the teacher to develop skills for the deployment of new methodologies and didactics mediated by ICT.