Reviewerly/exHarmony huggingface dataset:
VQ-T: RNN Transducers using Vector-Quantized Prediction Network States

Beam search, which is the dominant ASR decoding algorithm for end-to-end models, generates tree-structured hypotheses. However, recent studies have shown that decoding with hypothesis merging can achieve a more efficient search with comparable or better performance. But, the full context in recurrent networks is not compatible with hypothesis merging. We propose to use vector-quantized long short-term memory units (VQ-LSTM) in the prediction network of RNN transducers. By training the discrete representation jointly with the ASR network, hypotheses can be actively merged for lattice generation. Our experiments on the Switchboard corpus show that the proposed VQ RNN transducers improve ASR performance over transducers with regular prediction networks while also producing denser lattices with a very low oracle word error rate (WER) for the same beam size. Additional language model rescoring experiments also demonstrate the effectiveness of the proposed lattice generation scheme.
Fashion Landmark Detection and Category Classification for Robotics

Research on automated, image based identification of clothing categories and fashion landmarks has recently gained significant interest due to its potential impact on areas such as robotic clothing manipulation, automated clothes sorting and recycling, and online shopping. Several public and annotated fashion datasets have been created to facilitate research advances in this direction. In this work, we make the first step towards leveraging the data and techniques developed for fashion image analysis in vision-based robotic clothing manipulation tasks. We focus on techniques that can generalize from large-scale fashion datasets to less structured, small datasets collected in a robotic lab. Specifically, we propose training data augmentation methods such as elastic warping, and model adjustments such as rotation invariant convolutions to make the model generalize better. Our experiments demonstrate that our approach outperforms stateof-the art models with respect to clothing category classification and fashion landmark detection when tested on previously unseen datasets. Furthermore, we present experimental results on a new dataset composed of images where a robot holds different garments, collected in our lab.
SECURE CLOUD ACCESS USING AES ENCRYPTION AND DECRYPTION ALGORITHM

Distributed resources are shared in an open environment through network in cloud computing. As aresult, users may simply access their data from any location. Security and privacy concerns are present at the same time for a variety of reasons. First, there has been a significant advancement in network technology. Anotheris the rising need for processing power, which forces many businesses to outsource their data storage. Therefore,in an unrestricted cloud environment where the earner is unreliable, there is a necessity for protected cloud packing services. In a cloud computing context, this article discusses several data safety and confidentiality protection concerns and suggests a technique for delivering security services including authentication, authorisation, and confidentiality as well as monitoring in real time. Using the 128 bit Advanced Encryption Standard (AES), data security and confidentiality are improved. In the suggested method, information is encodedusing AES before being uploaded to the cloud. The suggested model prevents unwanted access to user data by using the Mail Service warning mechanism.
Sensemaking Sans Power: Interactive Data Visualization Using Color-Changing Ink

We present an approach for interactively visualizing data using color-changing inks without the need for electronic displays or computers. Color-changing inks are a family of physical inks that change their color characteristics in response to an external stimulus such as heat, UV light, water, and pressure. Visualizations created using color-changing inks can embed interactivity in printed material without external computational media. In this article, we survey current color-changing ink technology and then use these findings to derive a framework for how it can be used to construct interactive data representations. We also enumerate the interaction techniques possible using this technology. We then show some examples of how to use color-changing ink to create interactive visualizations on paper. While obviously limited in scope to situations where no power or computing is present, or as a complement to digital displays, our findings can be employed for paper, data physicalization, and embedded visualizations.
Exploration and Construction of A Practical Course System of Innovation Methods Based on the Knowledge System of Innovation Engineering

Innovation and entrepreneurship education is an important way to cultivate innovative and entrepreneurial talents and improve the quality of talents output from universities. This paper explores and constructs the prototype of the innovation method practice curriculum system of innovation engineering knowledge system. Firstly, the shortcomings of the existing innovation method education model are deeply analyzed; Then, based on the national promotion of innovation method education, the idea of constructing the innovation method practice curriculum system from three aspects, namely talent training, curriculum system and engineering practice, is proposed; Thirdly, relying on the diversified platforms of universities, enterprises and government, the curriculum system integrating industry chain, education chain and innovation chain is built; Finally, it proposes a closed-loop approach to the construction of the system, designing the feedback mechanism for talent training, curriculum system, practice platform and practice courses.
The Influence of Word Vectorization for Kawi Language to Indonesian Language Neural Machine Translation

People relatively use machine translation to learn any textual knowledge beyond their native language. There is already robust machine translation such as Google translate. However, the language list has only covered the high resource language such as English, France, etc., but not for Kawi Language as one of the local languages used in Bali's old works of literature. Therefore, it is necessary to study the development of machine translation from the Kawi language to the more active user language such as the Indonesian language to make easier learning access for the young learner. The research developed the neural machine translation (NMT) using recurrent neural network (RNN) based neural models and analyzed the influence of word vectorization using Word2Vec for the machine translation performance based on BLEU scores. The result shows that word vectorization indeed significantly increases the NMT models performance, and Long-Short Term Memory (LSTM) with attention mechanism has the highest BLEU scores equal to 20.86. The NMT models still could not achieve the BLEU scores on par with those human experts and high resource language machine translation. On the other hand, this initial study could be the reference for the future development of Kawi to Indonesian NMT.
Information Communication Technology and Modern Higher Education

The application of ICT in higher education has grown steadily in the past decade in both developing and developed countries although there are wide variations in the usage between countries and the regions.ICT is believed to specifically strengthen higher education systems. The increasing information and communication technologies has brought changes of teaching and learning at various levels of higher education systems leading to quality enhancements in the century. The adoption and use of ICTs in higher education have a positive impact on learning, research and teaching. In addition to learning and teaching process, ICT also provides the facility of e-learning. ICT increases the flexibility of delivery of education, so that learners can access knowledge at any time and from anywhere. It was observed from the research findings that, the students are very enthusiastic and receptive about the new mode of teaching based on ICT. Information and communication technology has become an integral part of today's teaching and learning process. This paper attempts to study the advantages and conveniences of applying in align with e-learning in higher education and teaching in universities. In this paper facts and figures obtained from various sources were used. Countries across the world are using ICT in facilitating information dissemination and communication in all areas of education and training. Effective use of technology can motivate students, make our classes more dynamic and interesting, and renew teacher enthusiasm as they learn new skills and techniques. Technology is also helping the students to understand any abstract concepts clearly. The use of ICT will not only enhance learning environment but also prepare next generation for future lives and careers. Effective use of technology can motivate the students, make our classes more dynamic and interesting and renew teacher enthusiasm as they learn new skills and techniques. Needless to say that library professional have shown a positive attitude towards the use of ICT applications and library automation, majority expressed the need for appropriate training to make use of ICT tools. Most of the students in higher education have own their laptop and search different sources of online for information and learning about a topic in which they have interest.
Research on Inverse Problem Using Data Mining

An inverse problem in science is the process of calculating from a set of observations the causal factors that produced them.It is called an inverse problem because it starts with the results and then calculates the causes.This is the inverse of a forward problem, which starts with the causes and then calculates the results.
Priming Effect of Violent Internet Words on the aggression of Internet Addicts

Two experiments were conducted to explore the priming effect of violent Internet words on the aggressiveness of Internet addicts. In Experiment 1, using the priming paradigm and word categorization task, it was found that participants' reaction time to aggressive words was faster than that of nonaggressive words. In Experiment 2, participants completed an implicit association task after priming the violent Internet words, and their reaction time in the compatible task was faster than that in the incompatible task. The results show that violent Internet words can prime both explicit aggression and implicit aggression, but there were no differences between Internet addiction and noninterest addiction, which suggests that the impact of violent Internet words on individual aggression (explicit and implicit aggression) was universal. This result provides an important basis for standardizing Internet language and further intervening in aggressive behavior.
Improved Invoice Information Extraction Using NLP and CRF

In a general Invoice processing system, the process starts from manually uploading the different format of invoices like paper, pdf, excel, document, image etc. for handling a invoice, from its receipt to upload in the ERP system and is ready for payment.This invoice process is manually handled for any organization.Each process of manual upload and payments was time consuming.This is an attempt to use AI in invoice processing system, where we can process invoices automatically by extracting the relevant information from the invoices and feeding it to the ERP systems through RPA (Robotic Process Automation). This process will help to reduce costs while improving both the accuracy and the speed of data extraction. Invoice Processing Advisor that can read invoice and extract the accurate information in a representable format. Annotations and Machine Learning for data extraction from the preprocessed data. Intelligent Invoice Processing will help to cater the increasing business needs as we see that majority of organizations spend lot of man FTE's and time for processing invoices. With the help of AI, this solution will be helpful to extract the information from the invoices more accurately and reduce the manual effort as well as the cost. We can easily scale it to multiple type of invoices as well introduce various business rules check that can communicate with the RPA's to perform any type of complex actions.
Secure Access Control Realization Based on Self-Sovereign Identity for Cloud CDM

Public healthcare has transformed from treatment to preventive care and disease management. The Common Data Model (CDM) provides a standard data structure defined to utilize hospitals’ data. Digital identity takes a significant role as the body of information about an individual used by computer systems to identify and establish trust among organizations. The CDM research network, composed of users handling medical information, has several digital identities associated with their activity. A high central authority cost can be reduced by Distributed Ledger Technology (DLT). It enables users to control their identities independently of a third party. To preserve the privacy of researchers in clinical studies, secure identification is the main concern of identifying the researcher and its agents. To do so, they should pose a legally verifiable credential in the cloud CDM. By presenting the proof represented by the capability that the user has, each identity has access control that is linked to an authentication credential that the cloud CDM can verify. Assurance in one’s identity is confirmed by asserting claims with the identity and its capability, providing its verifiable credential to the authentication entity in the cloud CDM. This paper describes the user-centric claim-based identity operation model based on use cases to handle researcher identity in the cloud CDM. In this model, credentials are designed as a capability and presented to them to access SPs in the cloud CDM. To provide well-controlled access control in the cloud CDM, we build and prototype a capability based CDM management system.
Review of Computer Aided Detection System for Mammography

Digital image processing is important in numerous areas of research and development which employed to process digital images and generate useful characteristics from the data, which can then be used to take critical decisions with high accuracy. These techniques are also applied for applications in the medical field, specifically in the detection of Breast Cancer. Over the years due to limitations of human observations, computers have played a significant role in detecting early signs of cancer, this conclude a development of Computer Aided Detection System (CAD) of high accuracy. This paper presents a concise review on Computer Aided Detection System which can be developed as a useful decision support system for automatic detection of breast cancer, whereby the predictions from the CAD systems can be employed to enhance diagnosis from radiologists.
TOXIC BEHAVIORS IN SOCIAL MEDIA: AN ANALYSIS OF RAPPORT THREAT BEHAVIORS IN SOCIAL MEDIA INTERACTIONS

Toxic Behaviors are what people do that irritate, annoy, or cause unpleasant feeling to others. These behaviors may cause other people to be depressed, angry, furious, sad, and anxious. In Rapport Management (Spencer-Oatey, 2000), these toxic behaviors are known as rapport threat behaviors since this kind of behaviors can threaten other people interpersonal rapport which is essential for harmonizing relationships between people. The main purpose of this study was to analyze these threatening behaviors to rapport in social media interactions. Social media interactions are the interactions found in social media platforms such as Facebook, Instagram, Twitter, MySpace, and other platforms. The sample for this study was the interactions in two social media platforms which are Facebook and Instagram. The study found that there are several rapport threat behaviors in the two social media platforms interactions. The rapport threat behaviors are accusations, insults, trash talks, the inappropriate use of emoji, the use of all capitalized letters and misunderstanding context and the captions of certain posts.
Virtual staining for mitosis detection in Breast Histopathology

We propose a virtual staining methodology based on Generative Adversarial Networks to map histopathology images of breast cancer tissue from H&E stain to PHH3 and vice versa. We use the resulting synthetic images to build Convolutional Neural Networks (CNN) for automatic detection of mitotic figures, a strong prognostic biomarker used in routine breast cancer diagnosis and grading. We propose several scenarios, in which CNN trained with synthetically generated histopathology images perform on par with or even better than the same baseline model trained with real images. We discuss the potential of this application to scale the number of training samples without the need for manual annotations.
Digital Approach towards Community-Based Activities with Culture and Heritage during COVID-19: Knowledge Transfer A Narrative Experience

Culture and heritage activities have always relied heavily on assembling a group of people to bring the event to life. However, during the pandemic COVID-19, these events cannot be held due to the restrictions and the danger it could bring in spreading the diseases. As a result, new options should be made available to ensure that cultural and heritage activities can continue in the face of adversity. This study describes the researcher’s experience in a knowledge transfer project on the long-term sustainability and conservation of community-based cultural and heritage activities during the COVID-19 epidemic. To preserve and sustain cultural activities, the article suggests a digital approach to culture and heritage activities. The research is based on the researcher’s observations and fieldwork experience. The result indicated that Lambo Sari and the research team kept track of each participant’s progress during the monitoring phase, which was the fourth step of this effort. In addition, the WhatsApp messaging service was used to track the project leader’s core communication with the participants. Apart from the monitoring phase, the fifth phase consists of a webinar delivered by the researcher and team to the general public and participants to increase awareness about the importance of cultural and historical preservation. In conclusion, cultural heritage conservation has been rendered extremely difficult due to the epidemic. If physical preservation of cultural heritage was done back then, revolutionization is required to stay up with the present period and make use of new technologies.
Blockchain-based Cybertwin-V2X Data Aggregation and Cluster Head Multi-hop Distribution Scheme

Abstract With the rapid development of the Internet of Things and the continuous progress of 5G technology, intelligent transportation has become the development trend of transportation technology. As an information interaction network, the Internet of Vehicles can share traffic information among vehicles, bringing convenience to vehicle owners while improving traffic efficiency.Data forwarding technology in the Internet of Vehicles (IoV) can realize the safe and efficient forwarding of messages, so that vehicle users can obtain road information as soon as possible and take relevant measures in advance.Cybertwin, as a complete replica of the vehicle in the virtual world, masters all the data and behavior of its physical vehicle. Cybertwin can communicate with other vehicle’s Cybertwin in the virtual world, which provides powerful functions in the data forwarding. On the one hand, it can directly forward data on behalf of the physical vehicle; on the other hand, Cybertwin can make relevant decisions based on forwarded data from other twins. However, it is easy to be eavesdropped when forwarding its physical vehicle data. In addition, there are several Cybertwins that may refuse to forward data in the virtual world. Therefore, the security issues in the data forwarding of Cybertwin face many challenges. In this paper, data aggregation and cluster-head multi-hop transmission scheme based on Cybertwin is proposed. The proposed scheme uses the reversible matrix to construct the data forwarding report of different cyber twins, uses the Paillier cryptosystem to aggregate the ciphertext of the data report, and uses the reversible matrix to decrypt and restore. In addition, use randomizable signatures to protect the privacy of Cybertwin. The security analysis results show that the proposed scheme can effectively improve the efficiency of data forwarding, and better protect the privacy and security issues of Cybertwin data forwarding in the IoV.
Characteristics and Meanings of the 2022 Superintendent Election in S. Korea

본 연구는 2022년 6월에 치러진 제8회 전국동시지방선거 교육감 선거의 특징을 분석하고 그 의미를 논한 것이다. 교육감 선거의 결과, 이전 교육감 선거 대비 이른바 진보 진영의 후보들이 대거 낙선하였고, 보수 진영의 후보들이 다수 당선되었다. 이번 교육감 선거의 특징으로는 후보자간 낮은 경쟁률, 약한 정책 경쟁, 당선자에 대한 낮은 유권자 지지율, 지자체장 등 타 선거와 판이한 선거 결과 등을 들 수 있다. 이와 같은 교육감 선거의 결과는 진보 진영의 패배, ‘혁신교육’에 대한 성찰 요구를 의미하는 것으로 논의하였다. 본 연구는 교육감 선거에서의 높은 무효표 비율, 양 진영 공약의 수렴 현상, 10대 유권자 등 교육 당사자의 선거 영향력 문제 등을 교육감 선거 제도 개선을 위해 논의가 필요한 과제로 제시하였고, 향후 지방교육자치 발전을 위해 교육감 선거 제도 유지 노력, 교육감 선거 제도 개선 논의, 교육자치 영역 확대, 교육자치 시행 단위 하향 등이 필요함을 주장하였다.This study analyzes the characteristics of the 8th Korean National Simultaneous Local Election for Superintendent of Education held in June 2022 and discusses its meaning. As a result of the election, compared to the previous election for superintendent, the candidates from the so-called progressive camp were largely defeated, and a majority of candidates from the conservative camp were elected. Characteristics of this superintendent's election include low competition, weak policy competition, low voter support for the elected candidate, and different results from other elections such as local government heads. The results of the superintendent’s election were discussed as meaning the defeat of the progressive camp and the demand for reflection on ‘innovative education’. In this study, the high percentage of invalid votes in the election for the superintendent of education, the convergence of promises from both camps, and the influence of the parties in education, such as teenage voters, were presented as tasks that need discussion to improve the superintendent's election system. To this end, this study argued that it was necessary to maintain the superintendent's election system, discuss the improvement of the superintendent's election system, expand the area of educational autonomy, and lower the unit for implementing autonomous education.
A Study on the Influence of Ambidextrous Leadership on the Deviant Innovation Behavior of Knowledge Workers

As a special innovation behavior, Deviant Innovation has been widely studied in academia. Based on the theory of social cognition and resource conservation, this article explores the influence of Ambidextrous leadership on knowledge-based employees' Deviant Innovation behaviors. Research shows that Ambidextrous leadership significantly positively affects knowledge-based employees' Deviant Innovation behavior; innovative self-efficacy partially mediates the relationship between ambidextrous leadership and knowledge-based employees' Deviant Innovation behavior; informal status mediates innovative self-efficacy and knowledge The relationship between Deviant Innovation behaviors of type employees. This research not only enriches the theoretical research on DeviantInnovation, but also provides some practical significance for enterprises to explore the Deviant Innovation behavior of knowledge employees.