Reviewerly/exHarmony huggingface dataset:
Experiential Activities for Risk Management Education

A core premise in the instruction of Information Security/Cybersecurity is that risk management is a cornerstone of security management, as evidenced in the promotion of GRC (Governance, Risk Management and Compliance) as the strategic triad in the trade press. While a theoretical exploration of risk management is important, the provision of an experiential activity to support the theory is valuable in cementing the knowledge in students. This paper will discuss popular risk management methodologies and examine a number of tools to support the instruction of the more common methodologies by instructors without substantial cost or learning curve.
Implications of Scientific Aid in Criminal Investigation

Science has the most celebrated feature of stability and certainty. These day science and technology has been playing its role in every sphere of human life. The advancement in medical science and engineering make it possible today to have accurately know the cause of death of a person or reasons of building collapse. But at the same time criminals have also learned a lot from this progress and they also resort to scientific methods and technology while committing the crimes, which either used by them to mislead the police and scientific investigators or for erasing the clues and signs of offence. However, it is also well known fact that despite of all out best efforts a criminal cannot make a crime scene free from evidence. At this point Science and Technology come to aid the law and legal procedure for apprehending the culprit and securing the evidence scattered there in minute forms in the shape of blood patterns, saliva, sweat, trace elements like fragment of glass or paint etc. It is the job of Forensic investigator, who when comes to courts known as Expert Witness, to link such evidence with culprit. This Article analyze the concept of Scientific Aid in relation to Forensic Sciencewhich is the field within it all the above-mentioned activities get the shape of evidence and drive the legal authority.
Text Representation and Similarity Measure for Text Clustering Based on Semantic Strings: A Case Study on Uyghur Language

ABSTRACTIn Uyghur language, the words which are segmented by inter-word space as natural separator can hardly serve as features in text representation, which leads to the low efficiency of text processing, it is still a research topic how to use language units beyond word boundaries as features to represent texts and improve the efficiency of text processing. This paper proposes a semantic string extraction approach, which is a method for extracting language units beyond word boundaries. At the same time, it also proposes the methods for textual representation and similarity measurement, and verifies its effectiveness in Uyghur text clustering tasks. Specifically, a combination of string expansion and language rules are applied to identify the trusted frequent patterns (TFP) in the text set. Next, semantic strings are evaluated and selected from the text set. Regarding similarity measure, each text is represented as a weighted semantic string set, and a set-based text similarity measuring approach is presented. Finally, the above ideas and approaches are applied to the Uyghur text clustering, and the corresponding clustering algorithms are proposed and verified through series of experiments on the large-scale text corpus. Experimental results show that the semantic string-based text representation is in general very useful in processing Uyghur language.
Medical Big Data Mining: Joint Symptom Name Recognition and Severity Estimation

Rapidly growing healthcare big data are becoming a valuable resource for improving clinical activity through technology. Estimation of the severity of diseases and symptoms in electronic medical records is important because it allows physicians to more easily gain an understanding of medical documents. In this paper, motivated by the fact that these two tasks can benefit each other, we propose a clinical multi-task learning approach (CMTL) that integrates severity estimation and symptom name recognition into a unified framework. Specifically, CMTL consists of two key components: (i) a named-entity recognition model that learns rich knowledge-aware entity representations and classifies entity terms into predefined categories; (ii) a severity estimation model that provides the symptom severity stages of patients' self-reported symptom descriptions. These two tasks work on a shared text-encoding layer; then, a multi-head attention mechanism is proposed to learn the important information from different representation subspaces at different positions. Finally, we propose a shared label-transferring network to enhance their interaction in a multi-task learning setting. We created the first symptom severity estimation dataset (SymptomSE) and a gastrointestinal ontology to evaluate the effectiveness of our model. The experiments demonstrate the effectiveness of the proposed method and the improved performance of both tasks.
Multilingual Recognition of Temporal Expressions

The paper presents a multilingual approach to temporal expression recognition (TER) using existing tools and their combination. We observe that the rules based methods perform well on documents using wellformed temporal expressions in a narrower domain (e.g., news), while data driven methods are more stable within less standard language and texts across domains. With combination of the two approaches, we achieved F1 of 0.73 and 0.9 for strict and relaxed evaluations respectively on one English dataset. Although these results do not achieve the state-of-the-art on English, the same method outperformed the state-of-the-art results in a multilingual setting not only in recall but also in F1. We see this as a strong indication that combining rule based systems with data driven models such as BERT is a valid approach to improve the overall performance in TER, especially for languages other than English. Further observations indicate that in the domain of office documents, the combined method is able to recognize general temporal expressions as well as domain specific ones (e.g., those used in financial documents).
Information Security Risk Assessment Evaluation Applying AHP

Information security has turn into a vital issue to most firms, organizations, or governmental institutions today. Anyone can transfer any data through a borderless world that causes great risk for everything connected to network. In this environment, information risk assessment is essential approach to monitor the specific threats for individuals/organizations, beside to identify and emphasize information. Nevertheless, organizations confront some problems in selecting most convenience method in meeting their needs. Main cause of this the existence of various approaches for the problem. This paper proposes a famous decision-making method, analytic hierarchy process (AHP), for information security assessment, which operates on—de facto language of data science—R. In order to perform this evaluation, this study demonstrate the use of AHP with “ahp” package provided by R project. We believe that proposed risk assessment approach may help organizations to understand cyber security risk evaluation better by using decision making modeling with powerful R software
تعليم مفردات اللغة العربية باستخدام نموذج سكرامبل (Scramble)

The study aims to reveal the differences between students' ability to the vocabulary using the scramble model and without using the scramble model. This research uses quantitative approaches with experimental research types. Researchers conducted a pre-test and post-test to know students' initial skills in vocabulary learning and their ability to vocabulary after completing vocabulary learning using scramble model. Researcher use Test T to know the influence of the use of these models in the learning of vocabulary in school. After analyzing the data, researchers gain an average score from the 80.75 experiment group and the average result of the 71.36 control group. After calculation, the results of table (tt) 4.6 and results of observation (to) is 1.66. Then the result To greater than Tt. This explains that alternate hypotheses (Ha) is accepted and the null hypothesis (Ho) is rejected. As such, researchers conclude that the use of the scramble model in student vocabulary learning has influential effect in students' vocabulary ability.
Bayesian Learning: Challenges, Limitations and Pragmatics

This dissertation is about Bayesian learning from data. How can humans and computers learn from data? This question is at the core of both statistics and — as its name already suggests — machine learning. Bayesian methods are widely used in these fields, yet they have certain limitations and problems of interpretation. In two chapters of this dissertation, we examine such a limitation, and overcome it by extending the standard Bayesian framework. In two other chapters, we discuss how different philosophical interpretations of Bayesianism affect mathematical definitions and theorems about Bayesian methods and their use in practise. While some researchers see the Bayesian framework as normative (all statistics should be based on Bayesian methods), in the two remaining chapters, we apply Bayesian methods in a pragmatic way: merely as tool for interesting learning problems (that could also have been addressed by non-Bayesian methods).
Are the university websites accessible?

Today, the Web is considered an important resource for work, entertainment, services and communication. It is a fact that has become indispensable nowadays. Although the advancement of recent years has made the Web more popular, not all potential users have easy use of the sites available. In this group are the visually impaired. Visually impaired users still face many difficulties in using the services available on the web. In this sense, it is important to evaluate the accessibility of the websites and to verify how much is still necessary to increase the accessibility level of the websites. In this work, an automated evaluation of Universities websites was performed to verify how accessible these websites are. The assessment was based on W3C recommendations. The results point to a need to know and comply more with accessibility standards, so that visually impaired users can better understand the websites available.
Minimisation of Motion Sickness in Autonomous Vehicles.

This paper presents the application of optimal control problem formulation for motion planning in order to minimise motion sickness in autonomous vehicles. The optimum velocity profile is sought for a predefined road path from a specific starting point to a final one within specific and given boundaries and constrains in order to minimise the motion sickness without compromising the journey time. For the representation of the motion sickness as a cost function to our optimal control problem, the illness rating is used. The influence of road width flexibility on illness rating and for a set of fixed journey times are investigated. According to the results, the road with flexible lateral manoeuvrability is found to provide lower sickness compared to the fixed road path. Moreover, the correlation between sickness and journey time can be represented as a Pareto front.
위임명령의 헌법적합성 담보와 통제에 관한 연구 - 전기사업법 시행령 개정안을 중심으로 -

Terrorism is evolving and changing with the times. It is carried out using new means of terrorism, reflecting the science technology, communication technology and culture. In the face of the recently changed terrorism, a new terrorist entity has emerged. A homegrown terrorist(lone-wolf), who did not belong to any terrorist organization but learned on his own to become a terrorist, new internationally unspecified terrorist group have act. The target of terrorist attacks has changed from hard targets such as national government agencies and major facilities to soft targets such as civilians, private facilities and multiple locations. It is operating using various means of terrorism such as cyberspace, drones, bio-weapon to conduct terrorism to target people or facilities. But the Anti-terrorism Act does not reflect this changes. Under the Anti-Terrorism Act, the targets are limited to the state, local governments and foreign governments. And there is no stipulation at all about the subject of terrorism, so it is not clear who the terrorist is. In addition, terrorist acts and means are stipulated in the list of acts and means for people, aircraft, ships, explosives and nuclear materials. If terrorism is carried out using new means other than those prescribed, it is not an act of terrorism under the Anti-Terrorism Act. In this thesis, the concept of terrorism was redefined under the Anti-Terrorism Act, which reflected the recent changes. First, individuals or organizations were specified so that they could include homegrown terrorists and new terrorist groups, reflecting the emergence and activities of new terrorist entities. Second, the unspecified majority were included in the targets, reflecting the change from hard targets to soft targets. Third, it proposed the provisions of cyber, drone, bio terrorism in terrorist acts, reflecting terrorist activities using various means. Terrorism will continue to evolve and change. No one can predict what it will look like and what means it will use to commit terrorism. These changes may not be reflected in the Anti-Terrorism Act at any time. But we have to try to prevent and respond to terrorism as much as possible, reflecting the changes.
Internal and External Composition of I.A. Bunin’s Diaries

The history of the creation and publication of I.A. Bunin’s diaries are of interest to literary scholars and textual critics, but the study of their linguistic features is not complete. The diaries of I.A. Bunin as a whole and each separately are a communicative, structural and semantic unity, which is reflected in their composition. While retaining the characteristics common to this genre, Bunin’s diaries are original. The author, for example, rejects the classical methods of syntactic connection of records and sentences in them, freely combines fragments of various topics. The integrity of the entire text is preserved not with the help of interphrasal communication, but with the help of keywords repeated in the text, the predominance of certain lexical and semantic series, which determine a certain coherence, that is, a nonlinear type of connectivity that unites elements of different levels of the text. The characteristic properties of Bunin’s diary entries include the parsimony of linguistic means, the accuracy and detail of the chronotope, incomplete sentences, fragmentation and parceling, an abundance of clarifying comments, inserted constructions. Thus, the architectonics of I.A. Bunin, that is, the division of the text into separate semantic fragments, has both common features inherent in the genre and individual ones.
Distribution Based MIL Pooling Filters are Superior to Point Estimate Based Counterparts

Multiple instance learning (MIL) is a machine learning paradigm which learns the mapping between bags of instances and bag labels. There are different MIL tasks which can be solved by different MIL methods. One common component of all MIL methods is the MIL pooling filter, which obtains bag level representations from extracted features of instances. Here, we recommend and discuss a grouping scheme for MIL pooling filters: point estimate based pooling filters and distribution based pooling filters. The point estimate based pooling filters include the standard pooling filters, such as ‘max’, ‘mean’ and ‘attention’ pooling. The distribution based pooling filters include recently proposed ‘distribution’ pooling and newly designed ‘distribution with attention’ pooling. In this paper, we perform the first systematic analysis of different pooling filters. We theoretically showed that the distribution based pooling filters are superior to the point estimate based counterparts in terms of amount of information captured while obtaining bag level representations from extracted features. Then, we empirically study the performance of the 5 pooling filters, namely ‘max’, ‘mean’, ‘attention’, ‘distribution’ and ‘distribution with attention’, on distinct real world MIL tasks. We showed that the performance of different pooling filters are different for different MIL tasks. Moreover, consistent with our theoretical analysis, models with distribution based pooling filters almost always performed equal or better than that with point estimate based pooling filters.
ON THE INFLUENCE OF NOISE ON THE RECOGNITION OF THREEFOLD ROTATIONAL SYMMETRY IN HEXAGONAL IMAGES

The article presents an algebraic approach to the representation and processing of digitalimages defined on hexagonal lattices. The described approach is based on the representation of imagesas functions on finite fields of “Eisenstein's integers”. As it turns out, the elements of such fieldsnaturally correspond to the pixels of hexagonal images of certain sizes. The exponential and logarithmictransformations in the Eisenstein fields are described. A method for detecting the centers ofthreefold rotational symmetry in grayscale images is presented and the corresponding normalizedmeasure of symmetry is introduced. The main purpose of the work is to study the effect of noise on theimage on the quality of the symmetry assessment using the introduced measure. The noise factor mustbe taken into account, since a decrease in the measure can be caused not only by the incompletesymmetry of the real object, but also by distortions due to noise, which is almost always the case.Obviously, this difference will be proportional to the level of the noise component. Analytical estimatesof the effect of noise on the criterion for detecting symmetry are obtained in this work. If imagesare subject to random noise, then the measure of symmetry of local image areas will be a randomvariable, the distribution law of which is determined by the distribution laws of noise components. Atthe same time, the standard for image processing assumption is made in the work about the model ofnormal and independent noise level of the brightness function. The peculiarity of the introducedthreefold rotational symmetry measure does not allow directly applying standard methods to obtainprobabilistic estimates. For this purpose, an assessment of the cumulative probability distributionfunction was carried out, on the basis of which an expression was obtained for the probabilities ofdeviation of the symmetry measure from the true value by a given value. By virtue of the a prioriassumptions made, the obtained estimate should be considered as rather "cautious" and it can beexpected that in reality the spread of the measure caused by noise in the image will be significantlyless than the theoretically established boundaries.
Implementasi Keamanan Data Keuangan di SMK Swasta Musda Perbaungan Menggunakan Metode RC4

Data security and confidentiality is currently a very important issue and continues to grow. Several cases concerning data security are currently a job that requires handling and security costs that are so large. To maintain the security and confidentiality of messages, data, or information so that no one can read or understand it, except for the rightful recipients, a data security system application with an encryption method using the rc4 algorithm is designed. RC4 (Rivest Cipher 4) is a synchrone streamcipher, which is a cipher that has a symmetric key and encrypts the plaintext digit by digit or byte per byte by combining binary operations (usually XOR) with a semi-random number.
Is there any licensing in non-DE contexts? An experimental study

Why is weak NPI any sometimes, but not always, licensed in non-downward entailing environments? In this paper, we present a series of experiments, where we probe the role of context in licensing any in the scope of various quantifiers. We compare our results to predictions made by three theories of exceptional NPI licensing. We show that contextual reasoning plays a role in non-monotonic environments, but that it does not in the scope of upward entailing quantifiers. Surprisingly, our results also show individual differences between the non-monotonic environments created by different quantifiers.
Pemanfaatan Permainan Digital sebagai Sarana Edukasi Kesehatan Bagi Anak Usia Sekolah

ABSTRACT Fourth industrial revolution resulting Industry 4.0 affects the changes of technology used for health. Technology is used in various health aspects to achieve a set target. Nowadays, health education comes in a digital form like digital game, video, and augmented virtual as media to replace a conventional one like leaflet. The utilization of digital game is a way to optimize the health education for kids in school age. Thus, digital game reduce the problem in health education process for the kids. Digital game is proven to affect the mindset of kids in school age, resulting a better life style and affecting their growth in a good way. However, digital game as a media for health education comes with its shortcoming: high development and maintenance cost. The purpose of this research is to examine the use and the effectiveness of digital game as health education media for kids in school age. This research uses literature review method in which it compares previous researches about digital game as a media to optimize health education for kids in school age. Keyword : digital game, health education, school age
Unpacking Smart Law: How Mathematics and Algorithms are Reshaping the Legal Code in the Financial Sector

The avalanche of new technologies and artificial intelligence have accelerated financial innovation, compelling the law to undergo a technological update. This phenomenon extends to the likes of regtech, suptech, regulatory big data, algorithmic supervision, etc. The study aims to demonstrate how these new instruments are, in fact, part of an overarching movement observable in numerous fields; that is, the emergence of a scientific, mathematical, algorithmic law driven by risk and technologies (classified as “Smart Law”). The authors will examine the aforementioned theoretical model and highlight the practical implications for banking and finance law. They conclude on the necessity for a structural collaboration between lawyers and engineers in order to manage the inevitable hybridization of the rule of law and its technological integration.
rizeTek: A Decision Support System using Decision Tree Algorithm

Innovations have changed the way people live. Information technology touches almost every aspect of life; the things that were a mere vision before is now slowly turning into reality. The incorporation of information technology will increase productivity in agriculture. Providing farmers with the latest information and inputs necessary for decision making can make them productive in farming.  The developed application aims to guide the rice growers in their farming activities, particularly pest management and decision making concerning rice farming. In the development of the study, the Rapid Application Development software process was adapted as a methodology.  The research had undergone four phases: Requirements Planning, User Design, Construction Phase, and Cutover Phase. A series of interviews were conducted with the agriculturist and with the 120 rice growers to gather data necessary to develop the system. The data collected from the participants were tabulated, analyzed, interpreted, and summarized using descriptive statistics. Frequency counts and mean were utilized to evaluate the efficiency level and assess the system developed. Based on the evaluation results, the developed system was found to be of a very great extent in terms of functionality, efficiency, compatibility, usability, reliability, security, maintainability, and portability