Reviewerly/exHarmony huggingface dataset:
Enhancing Forensic Audio: What Works, What Doesn't, and Why

'Enhancing' has become a routine part of preparing indistinct covert recordings for admission as evidence in criminal trials. Typically, evaluation of its effectiveness is seen as a simple matter of listening to determine whether the enhancement sounds ‘clearer’ than the original. This seems like a straightforward approach, but it brushes over many important issues which can adversely affect the fairness of the trial. This article outlines findings from experiments, case studies and scientific literature to show how enhancing can affect perception in surprising and unpredictable ways, without listeners’ conscious awareness. Discussion demonstrates that enhancing exacerbates, rather than mitigates, known risks of the jury being misled by an unreliable transcript. The conclusion indicates the direction in which to seek better procedures.
Highly Parallel SPARQL Engine for RDF

Abstract In this paper, a highly parallel batch processing engine is designed for SPARQL queries. Machine learning algorithms were applied to make time predictions of queries and reasonably group them, and further make reasonable estimates of the memory footprint of the queries to arrange the order of each group of queries. Finally, the query is processed in parallel by introducing pthreads. Based on the above three points, a spall time prediction algorithm was proposed, including data processing, to better deal with batch SPARQL queries, and the introduction of pthread can make our query processing faster. Since data processing was added to query time prediction, the method can be implemented in any set of data-queries. Experiments show that the engine can optimize time and maximize the use of memory when processing batch SPARQL queries.
Cyber Crimes: Their Impacts & Solutions - A Review

This paper distinguishes the significance of being familiar with the impacts of cyber crime remembering the ongoing exercises that have occurred and offering answers for shield oneself from it. In the present period of web based preparing, limit of the data is on the web and inclined to cyber attacks. There are countless cyber attacks and their conduct is hard to early seeing subsequently hard to limit in the early periods of the cyber attacks. Cyber attacks may have some inspiration driving it or might be prepared unwittingly. The attacks those are handled intentionally can be considered as the cyber crime and they have genuine effects over the general public as efficient upset, mental issue, risk to National safeguard and so on. Limitation of cyber crime is subject to legitimate examination of their conduct and comprehension of their effects over different degrees of society. Along these lines, the present original copy gives the comprehension of digital cyber crimes and their effects over society with the future patterns of digital violations. Keywords: Cyber Crimes, Cyber Attacks, Potential Impacts, Cyber Crime Solutions, Digital Violations. Cite this Article: Arshil Noor.Cyber Crimes: Their Impacts & Solutions - A Review.International Journal of Software Computing and Testing. 2020; 6(2): 1–10p.
A two-step approach for interest estimation from gaze behavior in digital catalog browsing

&#x0D; &#x0D; &#x0D; &#x0D; While eye gaze data contain promising clues for inferring the interests of viewers of digital catalog content, viewers often dynamically switch their focus of attention. As a result, a direct application of conventional behavior analysis techniques, such as topic models, tends to be affected by items or attributes of little or no interest to the viewer. To overcome this limitation, we need to identify “when” the user compares items and to detect “which attribute types/values” reflect the user’s interest. This paper proposes a novel two-step approach to addressing these needs. Specifically, we introduce a likelihood-based short-term analysis method as the first step of the approach to simultaneously determine comparison phases of browsing and detect the attributes on which the viewer focuses, even when the attributes cannot be directly obtained from gaze points. Using probabilistic latent semantic analysis, we show that this short-term analysis step greatly improves the results of the subsequent step. The effectiveness of the framework is demonstrated in terms of the capability to extract combinations of attributes relevant to the viewer’s interest, which we call aspects, and also to estimate the interest described by these aspects. &#x0D; &#x0D; &#x0D; &#x0D;
TEKNIK PENGAJARAN ENGLISH FOR GUIDING BERBASIS ETNOPEDAGOGI

Etnopedagogy is integrating the teaching and learning process with local wisdom including English. This study aims at analyzing teaching techniques in teaching English for guiding in Prodi Pendidikan Bahasa Inggris Fakultas Keguruan dan Ilmu Pendidikan Universitas Dwijendra integrating etnopedagogy. The data are collected through observation and interview to 2 English lecturers, The result shows that there are 7 teaching techniques used by the lecturers; (1) role-play, (2) brainstorming, (3) storytelling, (4) interview, (5) reporting, (6) picture describing, dan (7) find the difference. In the implementation, the lecturers always integrated to local wisdom in Bali.
Peningkatan Hasil Belajar Siswa Melalui Model Pembelajaran Penemuan Example Non-example pada Materi Hubungan Makanan dan Kesehatan Di Kelas V SD Negeri Simbatan Lamongan

This study aims to determine the increase in student learning outcomes through the discovery learning model (Example Non-Example) about the relationship of food and health in science lessons in Class V SD Simbatan Lamongan. The subjects in this study were 20 students in class V (five). The research procedures carried out in the form of planning, implementation of actions, observation/observation, and evaluation-reflection. Based on the results of improved learning, student mastery of learning material shows improvement. This can be shown from student learning outcomes from 63.33 to 81.57.
Privacy-preserving consensus averaging

Consensus problem has been a topic of interest for many research areas allowing multiple agents to reach an agreement through local information exchange. The explicit share of the state variables, however, may cause privacy issues due to the confidentiality of the initial values. In this work, asynchronous privacy-preserving consensus average algorithms are proposed which enables the agents to reach the exact average of their initial values while preserving the privacy of them. The research aims to reduce the convergence time and computational complexity compared to the cryptographic solutions. Three methods are proposed and compared. The state decomposition and noise-obfuscation methods preserve the privacy of the initial values given that the semi-honest adversary is not able to listen to one of the neighboring nodes of the targeted node. The hybrid state decomposition approach proposes a way to overcome this assumption by using a minimum number of encryption operations. The initial values are shown to be private against an eavesdropper who is able to tap all communication channels as well as a semi-honest adversary in the system. It has been shown in all proposed approaches that as the noise variance goes to infinity, the adversary does not have any range to estimate the initial value. The noise obfuscation technique futures the same convergence rate as the standard averaging approach while providing a linear increase in the variance of the adversary's estimate with the increasing noise variance. On the other hand, the state decomposition technique futures a lower convergence rate compared to the standard averaging approach while providing an exponential increase in the variance of the adversary's estimate with the increasing noise variance. By optimizing the algorithm, it has been shown that the same convergence rate as the standard randomized gossip can be obtained. The state decomposition approach requires the addition of noise for a bounded amount whereas, the noise obfuscation method requires the addition of noise at each iteration. All three approaches, converges faster than a fully cryptographic approach while promising statistical security guarantees.
SISTEM PAKAR MENENTUKAN PENYAKIT GINJAL DENGAN METODE FORWARD CHAINING

Selection of issues regarding the kind of kidney disease as a sample of this study, is the fact that diseases Kidney is an important organ in our body's metabolic system, because the density of activity, we often forget to take care of. Irregular diet, inadequate intake of fiber and mineral water, as well as the consumption of food or drink high calorie instant, unwittingly aggravate the kidneys. Starting from the filtration, reabsorption, to augmentation of nutrients that under to the kidneys via the blood. The purpose of this research is to build an expert system Kidney disease using Visual Basic 6.0 programming language that is capable of providing services to the public and delivery of information related to kidney disease. In this research, data collection is done by using the method of observation, interviews, and literature. From the results of this study indicate that the presence of kidney disease diagnosis expert system in humans can provide significant benefits, among others, the processing of data and consultation process carried out quickly and produce a fairly accurate report, thus making the job more effectively and efficiently. Keywords: Expert System, Disease, Kidney, Human.
DEVELOPING VOCABULARY MASTERY THROUGH GUESSING WORDS GAME FOR THE SEVENTH GRADE STUDENTS OF SMP NEGERI 10 PALU

The objectives of this research was to know the process of learning English vocabulary by using guessing words game and to know the students’ problem in learning English vocabulary by using guessing words game for the seventh grade students of SMP Negeri 10 Palu in academic year of2019/2020 with the use of guessing words game technique. In this research, the researcher used qualitative research method. The researcher chose class VII D as sample which consisted of 23 students. In collecting the data, the researcher used four kinds of instruments, they were: observation,interview, test and document. Based on the observation, there are some problems in the teaching and learning. To solve those problems, the researcher implemented guessing words game as vocabulary activities. This research was conducted through classroom action research that consisted of two cycles. Each cycles consisted three meetings. The result of the research showed that there were some improvements of the students’ vocabulary. In cycle 1 average score was 62,86 there were some unsuccessful score. Meanwhile, in cycle 2 average score was 72,34 the implementation of guessing words game was successful in developing students vocabulary. Guessing words game gives better result to develop the students’ vocabulary. In other words, guessing words game is effective to use in teaching English vocabulary.
Development of Competency-Based Curriculum Accreditation Model for Quality Management of University Education System

This study developed a competency-based curriculum accreditation model for quality management of university education. In this vein, this study focused on the cases from domestic and foreign universities, which are currently being operated. By conducting case analyses, the limitations in each model’s implementation and feedback dimensions were found; focusing on the limitations, this study recognized that improvement effort is needed. Therefore, this study aimed to draw a more advanced, concete and realistic blueprint for quality management of curriculum in universities.
Construction and design support for a double Coffer Dam Seawall

Singapore's ongoing economic growth demands more land for infrastructure development. This can be achieved by redeveloping existing inland sites or alternatively by reclaiming land. Reclamation was used for the Marina Coastal Expressway (MCE) which was designed to run parallel to the existing berth an old Marina Wharf. The completed project included construction of service roads, residential towers and the redesign of public spaces. GIKEN Seisakusho Asia (GIKEN) was engaged by Hock Lian Seng Infrastructure Ltd on behalf the Singaporean Land Transport Authority after a successful tender process. The project brief for the Marina Wharf Contract 481 required the proposed marine construction methodology to minimise waterway encroachment as vessel traffic had to be maintained throughout the construction works. The design carried out by Hock Lian Seng Infrastructure Ltd proposed a double cofferdam seawall consisted of 1170 1.2m diameter steel piles (P-P interlock), 19mm thick terminating in hard clay at depths of 28m to 44m. The GIKEN construction technology proved to be a successful option with the works completed in 11 months meeting the strict schedule, noise and vibration restrictions. This paper will discuss the construction challenges overcome including design details for water tightness and complex ground conditions. A detailed description of GIKEN latest Gyro press piling technology and how it can install piles into hard rock within tight boundary conditions and minimised temporary works will also be discussed.
Rhizomatic Learning – Preparation For Uncertainty (Approach To Education 4.0)

A new perspective on teacher training is proposed, as well as the conclusions of the author's research are formulated in the article. Readiness for unpredictable, unexpected and dynamic situations is becoming one of the key parameters of the specialist of the XXI century. In order to organize appropriate professional training, teachers of the new type, those who work on expanding variability, rather than broadcasting a pre-approved pattern of behavior, are needed. Intellectual challenges, open and non-trivial situations, modeled by new type of teachers, are designed to form a set of assumptions, search directions, incomplete results of reflections and completed decisions, appeared working contacts, etc., which together make up the "network/rhizome", which is the internal information basis of the specialist for solving emerging situations. The article describes a pedagogical experiment in which teachers learned to model situations of uncertainty in the classroom. The features of such activities were identified and recommendations were made to overcome the difficulties encountered. The necessary quality of a teacher, who works with uncertainty in the classroom, as shown by the experiment, is flexible thinking, managerial subjectivity and the ability of "co-participation". Rhizomatic training, according to the authors, makes it possible to effectively link possessed, obtained and being received fragments of knowledge, skills, memories, emotions, "intellectual bookmarks" of teachers and students into a common ecosystem. At the same time, it is the modeling situations of uncertainty in the classroom that allows the teacher to manage the attention of students and remain competitive in the modern information environment.
Diversification Of Additional Professional Programs For Preschool Educators

The 21st century marks a new era – the era of education, the peculiarity of which lies in the high importance attached to the growing role of adult education. Rapid dynamic changes in the system of preschool education require a preschool educator to have high professional mobility, the ability for self-development and lifelong education, so the process of personal and professional development of teachers in the system of additional professional education (hereinafter referred to as APE) is of great importance. Studies conducted in Russia and abroad show that diversification in modern conditions is multi-level education, multi-stage vocational training, diversity, expansion, variability and flexibility of educational services and educational programs, the introduction of new areas of study, new courses, as well as going beyond the limits of traditional learning models, which is dictated by the need for modernization of the system of preschool education. The process of diversification will have positive dynamics only if conditions are created for the effective inclusion of vocational education in the processes of increasing the professional competence of teachers of preschool educational organizations (hereinafter referred to as PEO).The experience of diversification of additional professional programs (hereinafter referred to as APP) for preschool teachers was studied at the St. Petersburg Academy of postgraduate pedagogical education (hereinafter referred to as SPb APPE).The most significant results of the diversification of the APP for preschool teachers are the formation of key professional competencies, the need for self-education and self-development of preschool teachers.
The Pedagogical Approach To The Development Of Information Security Culture

An enterprise is a set of employees and employees of different positions and responsibilities united by an interest in the result of the main business process in an atmosphere of service and corporate principles of communication and interaction part of which is the culture of information security, which is a collective awareness and respect for information security by all personnel. The urgency and relevance of the concept of information security culture in a modern technological society is noted. The authors test the hypothesis about the possibility of changing a person’s behavior and developing a culture of information security during training in continuing education courses in the field of information security. All employees of the organization participate in the review regardless of their involvement directly in the technological process of information processing. An analysis of the results conducted by the authors made it possible to determine that training the organization’s employees in the field of “information security” guarantees an increase in the average level of competence in information security issues and helps to develop a culture of information security. The development of an information security culture is based at least on an average level of literacy in information security issues. One of the priority points identified in the study is the influence of employees demonstrating high qualifications in information security issues on the training of their colleagues directly in their working places and inculcating an information security culture.
A Year of Papers Using Biomedical Texts:

Objectives: Analyze papers published in 2019 within the medical natural language processing (NLP) domain in order to select the best works of the field. Methods: We performed an automatic and manual pre-selection of papers to be reviewed and finally selected the best NLP papers of the year. We also propose an analysis of the content of NLP publications in 2019. Results: Three best papers have been selected this year including the generation of synthetic record texts in Chinese, a method to identify contradictions in the literature, and the BioBERT word representation. Conclusions: The year 2019 was very rich and various NLP issues and topics were addressed by research teams. This shows the will and capacity of researchers to move towards robust and reproducible results. Researchers also prove to be creative in addressing original issues with relevant approaches.
LibGuides: First Year Experience: 5 Things for First Year Success

This LibGuide was created to provide information on library resources for first-year students and their instructors.
Counterfeit Information and Computer Product as an Object of Forensic Research of Computer Tools and Systems

The paper considers the impact of global digitalization on the detection and investigation of crimes in the field of copyright and related rights violations based on the doctrine of criminalistic research of computer tools and systems, which is part of the private theory of information and computer support for criminalistic activities. It is noted that since the early 2000s, approaches to investigative tactics and forensic research of audio recordings, videos, and software have been considered in isolation from these types of objects. The development of information and computer technologies has led to the transfer of all the above-mentioned objects of copyright and related rights to digital format. Currently, copyright and related rights are protected by digital content, which includes audio-visual products, digital photos, digitized movies, digitized books, and software products. This content is computer-generated information that is independent of its medium and requires a uniform approach to its collection and research. The use of distributed computer technologies makes it possible to store and operate a single information and computer product on different, spaced media. Based on the analysis of existing literature, theoretical research and monitoring of investigative, judicial and expert practice, a new definition of "counterfeit information and computer product" is substantiated. It is a product of conscious human activity which is made using computer-digital technologies, presented in a digital form on one or more information carriers connected via computer networks or data virtualization technology so that several physical data carriers are linked into a logical module. If the product is altered when being manufactured, sold, exchanged, distributed or in any other way introduced into circulation, there is a violation of exclusive rights to the results of intellectual activity or means of individualization. The approach to counterfeit information and computer products as one of the types of digital footprint provides for a new way of tactical and forensic support development for investigative actions, the creation of methods of forensic research.
eXDiL: A Tool for Classifying and eXplaining Hospital Discharge Letters

Discharge letters (DiL) are used within any hospital Information Systems to track diseases of patients during their hospitalisation. Such records are commonly classified over the standard taxonomy made by the World Health Organization, that is the International Statistical Classification of Diseases and Related Health Problems (ICD-10). Particularly, classifying DiLs on the right code is crucial to allow hospitals to be refunded by Public Administrations on the basis of the health service provided. In many practical cases the classification task is carried out by hospital operators, that often have to cope under pressure, making this task an error-prone and time-consuming activity. This process might be improved by applying machine learning techniques to empower the clinical staff. In this paper, we present a system, namely eXDiL, that uses a two-stage Machine Learning and XAI-based approach for classifying DiL data on the ICD-10 taxonomy. To skim the common cases, we first classify automatically the most frequent codes. The codes that are not automatically discovered will be classified into the appropriate chapter and given to an operator to assess the correct code, in addition to an extensive explanation to help the evaluation, comprising of an explainable local surrogate model and a word similarity task. We also show how our approach will be beneficial to healthcare operators, and in particular how it will speed up the process and potentially reduce human errors.