Reviewerly/exHarmony huggingface dataset:
역사적 행위주체성을 활용한 초중등 학생들의 내러티브 분석 - 대몽항쟁 서술을 중심으로 -

Historical agency is a meaningful concept in itself for understanding history, and is a tool that can further elaborate the three layers from a multi-perspective. Through the selection of historical actors in the context of the social structure, constraints of the time, and the consequences of that choice, students can confirm that decision-making is an important task. By understanding events in context, it becomes a tool for historical understanding and an opportunity for current students to judge past events.In this article, an alternative to thinking about war was presented based on the choices of historical actors who participated in daemonghang, the consequences of their actions, and the different interpretations of historians. It is possible to judge war from various point of view by examining the war chosen by someone in the context of the situation at the time and the outcome of the war, away from examining the background, process, outcome and impact of war.Students can see how complicated history is by observing the Goryeo government''s response to the Mongol invasion, the choice of capital relocation and the people''s resistance to and cooperation with the ruling class during the prolonged war. Through this process, the narrative can naturally shift to ‘Who chose the war for whom?’ rather than ‘Why did the war happen, how it unfolded, and what results did it bring?’ Ultimately, it can give students an opportunity to think about war. In addition, students will be able to cross over past and present and develop their own agency while watching the results of choices and decisions made according to the circumstances of various historical actors.
Empowering Student Workers Using Flipped and Agile Project Management

Presentation introduces the concepts of Flipped Instruction and Agile Project Management and discusses how those methodologies may be applied to student roles in library and digital humanities projects. It was presented at the Association of College and Research Libraries (ACRL) Together Wherever virtual event held on June 8-12, 2020.
Activity recognition from smartphone data using weighted learning methods

Mobile phone based activity recognition uses data obtained from embedded sensors to infer user’s physical activities. The traditional approach for activity recognition employs machine learning algorithms to learn from collected labeled data and induce a model. To enhance the accuracy and hence to improve the overall efficiency of the system, the good classifiers can be combined together. Fusion can be done at the feature level and also at the decision level. In this work, we propose a new hybrid classification model Weighted SVM-KNN to perform automatic recognition of activities that combines a Weighted Support Vector Machines (WSVM) to learn a model with a Weighted K-Nearest Neighbors (WKNN), to classify and identify the ongoing activity. The sensory inputs to the classifier are reduced with the Linear Discriminant Analysis (LDA). We demonstrate how to train the hybrid approach in this setting, introduce an adaptive regularization parameter for WSVM approach, and illustrate how our method outperforms the state-of-the-art on a large benchmark datasets.
En studie om hur en webbapplikation för secondhandmöbler kan designas för att inge förtroende

The aim of this report is to examine the link between usability and trust as well as give an answer to how a e-commerce website that sells second hand furniture to students can be designed in order ...
Exhaustive study on Detection of phishing practices and tactics

Due to the rapid development in the technologies related to the Internet, users have changed their preferences from conventional shop based shopping to online shopping, from office work to work from home and from personal meetings to web meetings. Along with the rapidly increasing number of users, Internet has also attracted many attackers, such as fraudsters, hackers, spammers and phishers, looking for their victims on the huge cyber space. Phishing is one of the basic cybercrimes, which uses anonymous structure of Internet and social engineering approach, to deceive users with the use of malicious phishing links to gather their private information and credentials. Identifying whether a web link used by the attacker is a legitimate or phishing link is a very challenging problem because of the semantics-based structure of the attack, used by attackers to trick users in to entering their personal information. There are a diverse range of algorithms with different methodologies that can be used to prevent these attacks. The efficiency of such systems may be influenced by a lack of proper choice of classifiers along with the types of feature sets. The purpose of this analysis is to understand the forms of phishing threats and the existing approaches used to deter them.
Election Verifiability Revisited: Automated Security Proofs and Attacks on Helios and Belenios.

Election verifiability aims to ensure that the outcome produced by electronic voting systems correctly reflects the intentions of eligible voters, even in the presence of an adversary that may corrupt various parts of the voting infrastructure. Protecting such systems from manipulation is challenging because of their distributed nature involving voters, election authorities, voting servers and voting platforms. An adversary corrupting any of these can make changes that, individually, would go unnoticed, yet in the end will affect the outcome of the election. It is, therefore, important to rigorously evaluate whether the measures prescribed by election verifiability achieve their goals. We propose a formal framework that allows such an evaluation in a systematic and automated way. We demonstrate its application to the verification of various scenarios in Helios and Belenios, two prominent internet voting systems, for which we capture features and corruption models previously outside the scope of formal verification. Relying on the Tamarin protocol prover for automation, we derive new security proofs and attacks on deployed versions of these protocols, illustrating trade-offs between usability and security.
Unsupervised Driver Behavior Profiling leveraging Recurrent Neural Networks.

In the era of intelligent transportation, driver behavior profiling has become a beneficial technology as it provides knowledge regarding the driver's aggressiveness. Previous approaches achieved promising driver behavior profiling performance through establishing statistical heuristics rules or supervised learning-based models. Still, there exist limits that the practitioner should prepare a labeled dataset, and prior approaches could not classify aggressive behaviors which are not known a priori. In pursuit of improving the aforementioned drawbacks, we propose a novel approach to driver behavior profiling leveraging an unsupervised learning paradigm. First, we cast the driver behavior profiling problem as anomaly detection. Second, we established recurrent neural networks that predict the next feature vector given a sequence of feature vectors. We trained the model with normal driver data only. As a result, our model yields high regression error given a sequence of aggressive driver behavior and low error given at a sequence of normal driver behavior. We figured this difference of error between normal and aggressive driver behavior can be an adequate flag for driver behavior profiling and accomplished a precise performance in experiments. Lastly, we further analyzed the optimal level of sequence length for identifying each aggressive driver behavior. We expect the proposed approach to be a useful baseline for unsupervised driver behavior profiling and contribute to the efficient, intelligent transportation ecosystem.
Anagram Game to Enhance Students’ Vocabulary Mastery

This research is focused on the effect of Anagram Game on the Students’ Vocabulary Mastery at VII Grade MTs N 2 Padangsidimpuan. This research aims to know the suitable and effective technique in teaching vocabulary. The research was an experimental research that uses one group pre-test and post- test design consist of 39 students in experimental class and 39 students in control class. The data were collected from students’ vocabulary test in the experimental class and control class. The result of this research have found from the t-test, which is t count was higher than t table (3.92>1.666). It was concluded that there was a significant effect of anagram game on the students’ vocabulary mastery. It means that the alternative hypothesis was accepted which indicates that anagram technique was significantly effective in teaching vocabulary. Additionally, anagram is a good vocabulary learning technique. It is an interesting game for learners. Thus, it is strongly suggested that teachers apply this technique to help enrich students’ vocabulary.
Developing Innovative Safety Model and Tool KIT on Prevention Responses Remedial (P2R) towards Property and Violent Crimes

This study examines an approach to property crime prevention and violence strategies that can be used by enforcement agencies as well as the community in ensuring that the crime rate in our country decreases. In addition, the recommendations of the crime safety tool kit are also listed in educating the public on the prevention and response that needs to be done during or before the occurrence of crime as one of the crime prevention processes. This study is quantitative using the questionnaire survey method. The sample of this study is 300 respondents consisting of communities in the northern areas involving the states of Kedah, Perlis and Penang. Based on the results of the study, aspects of strategies that can be used in dealing with property crime and violence nowadays The PDRM needs to work with the community and other agencies to fight crime. Regarding the action that needs to be taken in the event of a criminal incident, the community must first identify the guests who come to the house before allowing guests to enter. And the response that will be made if it is found that a crime has occurred to oneself or another person, the main thing that needs to be done at that time is to win oneself during the incident. Therefore, it can be discussed as a whole that these findings are very useful to the community as a precautionary measure. To ensure the crime of property and violence can be reduced, the emphasis on strategies and tool kits is very important to ensure a quality and prosperous life for the present and future generations.
EMERGENCE OF LIBRARY CONSORTIA IN PRESENT INDIAN SCENARIO; A BRIEF VIEW ON J-GATE CONSORTIUM

The study aims at discussing the importance of library consortia in India in the emerging context of digital resources. Now the libraries have in the transition state and experienced many transformations over the years. Due to the development of Internet and telecommunications technologies, the present situation has changed even further. Information searching pattern, gathering habits and seeking behavior of the users has increasingly complex to the growing knowledge in print as well as electronic forms, and not a single library is self-sufficient to access all books/e-books, journals/e-journals, and other library documents because of their library financial constraints. Moreover, users have diversified demands of the information requirements; it is very difficult to fulfill the demands of the users of the library with the existing library resources and services. To overcome this problem, Library Consortium is the only solutions in the present context. However, for the price of resources, the vendor-conquered market, the lack of competition, and other reasons, we need the consortium's approach. The many experiences of accessing e-journals through this method, is there a viable alternative to journal price increases or not. In this paper an attempt has been made to discuss the advantages and disadvantages of the consortia, the needs of the consortia in the current Indian context, and the advantages and disadvantages of consortia-based subscription, consortia initiatives in India, and the brief view on J-Gate e-Journal Consortium, merits & demerits of J-Gate consortium have been discussed.
Using an improved teo algorithm and an ann for diagnosis of lung cancer.

Lung cancer is responsible for a quarter of all cancer fatalities. Early detection and treatment of this condition, according to studies, is the most effective strategy to extend patient life expectancy. The use of automatic and optimal computer-aided detection for lung cancer is proposed in this research. The procedure begins by normalising and denoising the input images in a pre-processing step. After that, Kapur entropy maximisation and mathematical morphology are used to segment lung areas. For the final evaluations, 19 GLCM features are collected from the segmented images. The photos with the highest priority are then chosen to reduce the system's complexity.
Research on Prevention and Control of the Covid-19 Epidemic: Chinese Experience

China has achieved a lot of successful experience in the prevention and control of the COVID-19 Epidemic outbreak in 2020, which is worthy of reference by other countries. The experience mainly includes the Leadership of the Party in its work, the superiority of the grass-roots mass autonomy system, the effective service of the government to the people, and the full realization of the guarantee of the rule of law.
ASSESSING THE RELATIONSHIP BETWEEN INFORMATION TRANSPARENCY THROUGH SOCIAL MEDIA DISCLOSURE AND FIRM VALUE

The aim of this paper is to investigate the relationship between social media financial disclosure and firm value of theGCC listed firms. To answer to research questions, the researchers collected cross-sectional data from a sample of 241firms
Learning What to Attend to: Using bisimulation metrics to explore and improve upon what a deep reinforcement learning agent learns

We analyze the internal representations that deep Reinforcement Learning (RL) agents form of their environments and whether these representations correspond to what such agents should ideally learn. The purpose of this comparison is both a better understanding of why certain algorithms or network architectures perform better than others and the development of methods that specifically target discrepancies between what is and what should be learned. The concept of ideal representation we utilize is based on stochastic bisimulation and bisimulation metrics, which are measures of whether and to which degree states are behaviorally similar, respectively. Learning an internal representation in which states are equivalent if and only if they are bisimilar and in which distances between non-equivalent states are proportional to how behaviorally similar the states are has several desirable theoretical properties. Yet, we show empirically that the extent to which such a representation is learned in practice depends on several factors and that a precise such representation is not created in any case. We further provide experimental results that suggest that learning a representation that is close to this target internal state representation during training may improve upon the learning speed and consistency, and doing so by the end of training upon generalization.
紫式部の宮仕え決心 ー 『紫式部集』 52から56までの歌を基に考える ー

This paper examines Poems Nos. 52, 53, 54, 55, and 56 of “Murasakishikibusyu”, a collection of Murasakishikibu’s Japanese poems. These poems have been written in the period of three years, after the demise of her marriage and bereavement with the death of Nobutaka. Also, it was the time before she began the ‘Miyazukae’, a court service at the Palace for Queen Shoshi, The Poems Nos. 52 and 53 suggest that mother of Queen Shoshi made an offer but Murasakishikibu didn’t accept. Rinshi, a long󰠏distant cousin, was concerned about Murasakishikibu’s difficult situation that she must raise her very young daughter on her own. Rinshi offered her to be part of the court service knowing there is a need for good teachers for the daughter of Queen Shoshi. It was a very important thing for not only Shoshi but also the glory of the Fujiwara family. The Poem No. 54 shows signs of change in Murasakishikibu’s mind. She decided to live for her young daughter sick and crying beside her. It is a hard thing to live as a woman without any role model and motherless and at such a young age. We can say that the Poem No. 56 explains that Murasakishikibu decided to become ‘Miyazukae’ for her daughter. Such a resolution is none other than her potential motherhood deep in her heart.
THE EFFECT SAP APPLICATION SYSTEM QUALITY AND THE QUALITY OF INFORMATION ON INDIVIDUAL PERFORMANCE DIMEDIATE USER SATISFACTION (At PT. PLN (Persero) CENTRAL JAVA AND D.I.YOGYAKARTA DISTRIBUTION MAIN UNITS)

This research aims to analyze and find empirical evidence about SAP application system quality and the quality of information on individual performance dimediate user satisfaction. The populations of this research were employees at PT PLN (Persero) Main Distribution Unit for Central Java and DIYogyakarta. The samples in this research were 60 respondents. The data are collected by distributing questionnaires. The sampling technique in this research used the Slovin formula and the data were processed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach with the help of the WarpPLS 6.0 program and a significance level of 10%. The results showed that (1) system quality had a positive and insignificant effect on user satisfaction with a path coefficient of 0.12 and p-values of 0.17 so that (0.17 > 0.10), (2) the quality of information had a positive and significant effect. on user satisfaction because it produces a path coefficient of 0.45 with p-values <0.0001 or (0.0001 < 0.10), (3) the quality of the system has a positive and significant effect on individual performance with a path coefficient of 0.26 and p- values 0.02 or (0.02 < 0.10), (4) the quality of information has a positive and significant effect on individual performance with a path coefficient value of 0.16 with a p-value of 0.09 so that (0.09 < 0, 10), (5) user satisfaction has a positive and significant effect on individual performance because the resulting path coefficient is 0.34 with p-values < 0.0001 or (0.0001 < 0.10). The Adjusted R-Squared value for user satisfaction (Y1) is 0.229 which means that the percentage of the influence of system quality (X1) and information quality (X2) on user satisfaction is 22.9% and for individual performance (Y2) is 0.305 which means that the percentage The magnitude of the influence of system quality (X1) and information quality (X2) is 30.5%, then the remaining 77.1% and 69.5% are explained by other variables not examined in this research.Keywords: SAP application system quality, information quality, satisfaction of user and individual performance.
Social Capital and Digital Media Literacy Transformation from The Perspective of Social Science in The Era of Covid-19 Pandemic

The phenomenon of the Covid-19 Pandemic is a worldwide viral phenomenon, all countries in the world feel its impact. New phenomena and habits are born that affect all aspects of human life. The sociocultural and economic factors have given birth to a new order that is more obvious, Garut is included in the yellow line status category because there is an increase in Covid 19 cases every day so that it becomes a standby district in West Java despite the implementation of New Normal Adaptation This study examines how the transformation of social capital and digital literacy in learning in the era of covid 19 and the influence of learning in the era of covid 19 on the transformation of social capital and digital media literacy carried out on high school students in Garut Regency as many as 207 students who successfully captured information in the future. Covid 19 pandemic. The results of the study show that the social/physical distancing policy that has been put in place has become a new order in the lives of people and students in Garut district, the habit of crowding is lost for a moment and replaced by the habit of staying at home and keeping a distance. As a result, the learning that is carried out is forced by utilizing the media owned by schools and students, on average students use their social media to access assignments and learning materials such as Whatsapp, Facebook and school Instagram. While there are still a few who use class application media such as Google Classroom, Microsoft Team, Zoom for reasons of limited credit quota. But in general, there has been a paradigm shift in the use of digital media in the learning process in the Covid 19 Era. There is a significant influence with very high criteria that learning in the Covid 19 Era positively affects the transformation of Social Capital and Digital Media Literacy among High School Students in Garut Regency. Based on this, this research confirms that there is a positive impact related to learning conditions in the Covid Era with the transformation of social capital and digital media literacy. However, there are still obstacles in the use of digital media among students. © 2021 RIGEO. All Rights Reserved.
Lo Sfruttamento Della Notorietà Altrui Tramite Pubblicazione Di Fotografie in Rivista Periodica (The Exploitation of Other's Right of Publicity through the Publication of Pictures in a Magazine)

Italian Abstract: Lo sfruttamento della notorieta altrui viola un diritto sulla notorieta acquisita, diritto non legislativamente tipizzato ma ormai ampiamente riconosciuto? Riflessioni su Cass. 1875 / 2019 (forthcoming in www.medialaws.eu)English Abstract: About the right of publicity, largely accepted also in Italy also if not expressly regulated (about Corte di Cassazione n° 1875 / 2019).
Profiling Online Users

A user's online profile attempts to capture the essence of a user's interests, behaviors, and preferences as they manifest themselves online either in public or to an organization with access to the user's network activity. Profiling online user behavior and gleaning information about individual usage or habits is useful in identifying and confirming suspected cybercriminals. This has obvious utility for corporations and governments seeking to secure their systems but must be counterbalanced against privacy concerns that continue to pose a major challenge to the widespread acceptance of online profiling. This chapter surveys recent developments in online user profiling, including existing approaches, methods, research challenges, and potential applications of online user profiling. We discuss online behavioral models such as ones that model a user's mobile apps behavior as well as online interest models such as YouTube and Twitter behavior models. This discussion will be done with an eye toward data acquisition, feature extraction, profiling techniques, and privacy challenges.
Critical Literature Review of Named Entity Recognition in Symbol Spotting

Symbol spotting is a subset of image recognition that focuses on identifying objects in an image. Symbol spotting has received some research interest lately. Symbol spotting is beneficial for image analytics of engineering diagrams where the goal is to retrieve specific symbols. There are some works done to identify type of entity but very little for Name Entity Recognition (NER). NER is a machine learning feature that can help retrieval of more precise symbols. Semantics analysis of NER in image analytics researches are extensively reviewed. This paper critically compares the state-of-the-arts, merits and gaps in the works. Review reveals the need to focus on techniques to increase accuracy of symbol spotting.