Reviewerly/exHarmony huggingface dataset:
A Block-chain based Enforcement to Reduce Cybercrimes in Digital Forensics

The fundamental aim of digital forensics is to discover, investigate, and protect an evidence, increasing cybercrime enforces, digital forensics team have to more accurate evidence handling. It makes digital evidence as an important factor to link persons with criminal activities. A chain of custody refers to a process of recording and preserving in court of law. It forms the forensic link of evidence sequence of control, transfer, analysis to preserve integrity, and to prevent its contamination. Thus it is of utmost importance to guarantee integrity, authenticity, of digital evidences in cyber-crime investigation. So guaranteeing the authenticity and legality of processes and procedures used to gather and transfer the evidence in a digital society is a real challenge. Block-chain technologies of enabling view of transaction back to origination provide enormous promise for the coming era.it is also used for securing IoT devices through efficient authentication and data transfer mechanisms. Block-chain based digital forensics chain of custody, influence forensic applications in bringing integrity to digital forensics.
암묵지의 성인학습에 관한 사례고찰

This study aimed to identify the meaning of tacit knowledge as a form of knowledge which can be lost easily in virtual world amid the increase of untact social interaction in evolution and increase of diverse digital communication. In particular, this study tried to examine the features of tacit knowledge, which is created during activity of passing down community spirit or culture. Through previous studies, this study looked into museum activities and candycraft activities by conducting field work and interview after paying attention to three features - non-expressivity, internality, and process of knowing - which are distinguished from scientific knowledge or standardized knowledge amid forms of knowledge called as existing tacit knowledge or local knowledge. As a result of the study, the features from activities related to creation and transmission of culture are the following. First, in many cases, tacit knowledge exists invisibly and inherently within learners with strong demand toward knowing. Second, tacit knowledge is formed based on experiencing relevant scenes. Third, tacit knowledge improves expansion or function of tacit knowledge itself through union with scientific knowledge.
Explanation in Human Thinking

Author(s): Cassens, Jorg; Habenicht, Lorenz; Blohm, Julian; Wegener, Rebekah; Korman, Joanna; Khemlani, Sangeet; Gronchi, Giorgio; Byrne, Ruth M.J.; Warren, Greta; Quinn, Molly S; Keane, Mark T | Abstract: Jorg Cassens, Rebekah Wegener, Lorenz Habenicht, and Julian Blohm discuss the dialogic form of explanations. Explanations are a long established research topic in a wide variety of disciplines, ranging from philosophy (van Fraassen, 1980; Achinstein, 1983) over the cognitive sciences and psychology (Lalljee et al., 1983; Keil and Wilson, 2000; Lombrozo, 2006) to computer science in general and artificial intelligence in particular (Schank, 1986; Leake, 1992; Leake (1995); Sormo et al., 2005). However, while there is compelling research supporting the value, structure and function of explanation, as Edwards et al. (2019) argue, “accounts of explanation typically define explanation (the product) rather than explaining (the process)”. By contrast, we aim at an understanding of explanation as a functional variety of language behaviour that treats explanations as being:
Unsupervised Program Synthesis for Images By Sampling Without Replacement

Program synthesis has emerged as a successful approach to the image parsing task. Most prior works rely on a two-step scheme involving supervised pretraining of a Seq2Seq model with synthetic programs followed by reinforcement learning (RL) for fine-tuning with real reference images. Fully unsupervised approaches promise to train the model directly on the target images without requiring curated pretraining datasets. However, they struggle with the inherent sparsity of meaningful programs in the search space. In this paper, we present the first unsupervised algorithm capable of parsing constructive solid geometry (CSG) images into context-free grammar (CFG) without pretraining via non-differentiable renderer. To tackle the \emph{non-Markovian} sparse reward problem, we combine three key ingredients---(i) a grammar-encoded tree LSTM ensuring program validity (ii) entropy regularization and (iii) sampling without replacement from the CFG syntax tree. Empirically, our algorithm recovers meaningful programs in large search spaces (up to $3.8 \times 10^{28}$). Further, even though our approach is fully unsupervised, it generalizes better than supervised methods on the synthetic 2D CSG dataset. On the 2D computer aided design (CAD) dataset, our approach significantly outperforms the supervised pretrained model and is competitive to the refined model.
Underwater image enhancement using improved Particle Swarm Optimization

The underwater images are used for monitoring the underwater pipelines and aquaculture. However, obtaining a clear image is a difficult task due to light scattering and absorption issues. Due to these issues, a very low contrast, blur, and color distortion underwater image is obtained. To overcome these issues, enhancement algorithms have been designed. In the literature, conventional algorithms are used for enhancement purposes are histogram equalization, stretching, and power-law expression. However, these algorithms over-enhance the images if proper parameters are not taken under consideration. Therefore, swarm-based optimization algorithms have been used to determine the optimal values of these parameters. In this paper, we have designed an improved particle swarm optimization-based enhancement algorithm. In the proposed method, initially, pre-processing of the underwater image is done and its channels are extracted. After that, based on the mean values of the channels, the channels are classified into three types, namely, superior, intermediate, and inferior. Based on the superior channel, gain factors are determined and enhance the intermediate and inferior channels. Next, the power-law expression is applied to the inferior and intermediate channels to enhances its gamma value. The gamma value in the proposed algorithm is determined using an improved particle swarm optimization (PSO) algorithm. In the improved PSO algorithm, the initial population of the PSO algorithm is defined using a chaotic map algorithm therefore PSO algorithm does not fall into the local optimal solution. In the last, contrast-limited adaptive histogram equalization (CLAHE) for enhancement. The experimental results are performed for the standard dataset images and simulated in MATLAB. Further, qualitative and quantitative analysis is done for the proposed algorithm. The results show that the proposed algorithm is superior as compared to the existing algorithms
The Evolution of Neural Networks [Editor's Remarks]

The focus on evolutionary neural architecture search in this issue has driven me to ponder the evolution of biological neural networks, or rather, the human brain. Researchers in neuroanatomy found that the cognitive and mental development of humans is attributed to the increase of our brain size throughout evolution. Yet bigger is not always better. It was also discovered that, once the brain reaches a certain size, further growth will only render the brain less efficient. In addition, the brain is limited and affected by its inherent architecture and signal processing time. These discoveries in neuroscience are interestingly analogous to the advances in neural networks and evolutionary computation. Stacking of perceptrons empowers artificial neural networks to solve complex problems but detracts from their efficiency. Indeed, the human brain evolution and the artificial neural network evolution both face the trade-off between capacity and efficiency. The workings of nature truly give us a lot to mull over. This issue includes five Features articles. The first article proposes an evolutionary multi-objective model compression approach to simultaneously optimize the model size and accuracy of a deep neural network. The second and third articles adopt the notion of self-supervised learning in the neural architecture evolution, resulting in state-of-the-art performance. To improve the accuracy of wind speed forecasting, the fourth article uses an evolutionary algorithm to optimize the architecture of dendritic neural regression. The fifth article presents a self-adaptive mutation strategy for blockbased evolutionary neural architecture search on convolutional neural networks. In the Columns, the article proposes a multi-view feature construction method based on genetic programming and ensemble techniques.
Learning Probabilistic Sentential Decision Diagrams Under Logic Constraints by Sampling and Averaging

Probabilistic Sentential Decision Diagrams (PSDDs) are effective tools for combining uncertain knowledge in the form of (learned) probabilities and certain knowledge in the form of logical constraints. Despite some promising recent advances in the topic, very little attention has been given to the problem of effectively learning PSDDs from data and logical constraints in large domains. In this paper we show that a simple strategy of sampling and averaging PSDDs leads to state-of-the-art performance in many tasks. We overcome some of the issues with previous methods by employing a top-down generation of circuits from a logic formula represented as a BDD. We discuss how to locally grow the circuit while achieving a good trade-off between complexity and goodness-of-fit of the resulting model. Generalization error is further decreased by aggregating sampled circuits through Bayesian model combination. Experiments with various domains show that the approach efficiently learns good models even in very low data regimes, while remaining competitive for large sample sizes.
Obstacle Avoiding Robot Based on Arduino

Trajectory preparation is a prime method in the mobile robot navigation research. Sampling-based algorithms are capable of creating trajectories that help the robot meet the target avoiding obstacles. Through this proposed study, an Enhanced Artificial Potential Field (E-APF) produces the trajectories for mobile robots and ensures the reliability and stability of the trajectory at the same time. E-APF approach is proposed for Wheeled Mobile Robot (WMR) route planning, aiming at the problem that the classical APF cannot adjust to the dynamic trajectory planning and collapse as a prey to the optimal local solution. Combining the current development status of smart robots, obstacle avoidance and automated tracking is the subject of robot travel issues. Based on the development status of smart domestic control systems, existing technology, etc, this paper uses Arduino as the core control device, combined with an infrared tracking module. Four modules, such as ultrasonic obstacle avoidance module, motor drive module and power module, have developed a strong control system to perform the wheeled robot's intelligent tracking function and obstacle avoidance.
Vagueness in the Scientific Journals Abstracts

A word or a group of words is vague when its meaning imprecise.A research paper begins with an abstract.An abstract should be precise, concise, specific, and coherent.The problem of the present study focuses on to what extent are writers aware of vagueness in writing abstracts?The current study aims at exploring the sources of vagueness in research abstracts.In order to achieve this, it is hypothesized that: research writers of Iraqi academic journals are not aware of vague words or expression in writing abstracts which leads to vague interpretations of sentences.The researcher has analysed two abstracts following Kempson"s (1977) model of vagueness.The model is based on four types of vagueness: referential vagueness, indeterminacy of meaning, lack of specification in the meaning of an item and disjunction in the specification of the meaning of an item.The abstracts are taken from "AL-Kitab Journal for Pure Sciences", Iraq.The results of the study show that the researchers used 16 cases of vagueness for the sample of the study.Referential vagueness scored the highest percentage (75%), lack of specification in the meaning of an item (18.75%), the indeterminacy of meaning (6.25%), and finally, ‫اجمللد‬ ، ‫األساسية‬ ‫لرتبية‬ ‫ا‬ ‫كلية‬ ‫أحباث‬ ‫جملة‬ ، ( ‫لعدد‬ ‫ا‬ ‫لسنة‬ ،)
PERILAKU PENCARIAN INFORMASI MAHASISWA DALAM MEMENUHI KEBUTUHAN INFORMASI SEBELUM DAN SAAT PANDEMI COVID-19

The Covid-19 pandemic has brought changes to every aspect of life, one of which is education. Due to these circumstances, conventional learning has turned into online learning to avoid potential virus-spreading in university clusters, and UPI Library and Information Science 2019 students must follow the policy. The study aims to determine the information-seeking behavior of university students in meeting their information needs and differences in information-seeking behavior before and during the Covid-19 pandemic. This study method uses a descriptive quantitative research method. The sample of this research is students who experience two types of learning, conventional learning (in the classroom) and long-distance learning (online class). The results of this study indicate that there are differences in information-seeking behavior of UPI Library and Information Science 2019 students before and during the Covid-19 pandemic both in terms of motivation, place, sources, strategies, and obstacles in finding information. This is shown from the percentages of respondents' answers that show a decrease in physical activity such as visiting the library and a decrease in the use of printed media in finding information during the Covid-19 pandemic. On the other hand, the use of electronic and online-based media to search for information such as e-journal catalogs is increasing, and the use of electronic information sources has also increased during the Covid-19 pandemic.
Making the Abstract Straightforward: A Pilot of Immersive VR in an Allied Health Program of Study

Emerging technologies in education are offering new tools for teaching and learner engagement. Today’s study and practice can include use of digital technologies far beyond looking at a flat screen: virtual reality, augmented reality, interactive 3D objects and 360 video can provide immersive and impactful teaching and learning. There are a variety of definitions for these “realities” but the overarching impact is one of powerful, immersive, visual learning. Immersive virtual reality in a learner-centric environment can provide more presence and engagement for students, enabling the possibility of enhanced learning experiences relative to conventional classroom practices. This paper presents early results of a pilot study leveraging the possibilities of VR technology in service to an existing program of study in allied health services:graduates surveyed report high degrees of confidence in course materials learned by means of the custom VR components developed, reporting the adjunct course materials substantially helped learners in understanding otherwise difficult to grasp concepts of the course.
Analysis of flood prone areas in nagan raya regency Aceh province / Amsar Yunan

Maps or remote sensing can be interpreted as the process of reading using various sensors where data collected remotely can be analyzed to obtain information about the object, area or phenomenon. In this study, the author develops a flood disaster mapping information system applying overlays with scoring between the parameters. The determinant factors to provide flood hazard levels includes rainfall factors in the dasarian unit, land-use factors and landuse arbitrary factors. Of all these parameters, a scoring process will be carried out by assigning weights and values according to their respective classifications, then an overlay process will be performed using ArcGIS software. The author conducted this study in Nagan Raya Regency since this area experiences flooding annually. Framing a thematic map of flood-prone areas in Nagan Raya Regency was designed using the flood hazard method. Spatial data that has been presented in the form of thematic maps as parameters are land use maps, landform maps, and dasarian rainfall maps (per 10 daily). The design of thematic maps that are prone to flooding is done by overlapping (overlay process). In contrast, the determination of the classification is done by adding scores to each parameter, with low, medium and high hazard levels. Parameter analysis shows the level of flood vulnerability in Nagan Raya Regency of each district, namely Beutong: high 0.21%, medium 13.68%, low 86.12%. Seunagan District: high 51.17%, medium 48.83%, low 0%. Seunagan Timur District: high 10.07%, medium 46.18%, low 43.75%. Kuala Subdistrict: high 29.66%, medium 68.99%, low 1.35%. Darul Makmur District: high 8.57%, medium 63.37%, low 28.06%. From the overall results of the study, it can be concluded that the danger of flooding in Nagan Raya Regency with a level of vulnerability: high 9.92%, moderate 42.65% and low 47.43%.
Right to Access to Internet in India: Fundamental Right, or a Glorified Privilege?

It is no surprise that in contemporary times, the Internet has become a staple of Indian society. However, with the advent of high-handed political and private actions, to the chagrin and prejudice of the freedoms and liberties guaranteed to citizens, the State now aims more on preserving and continuing authority, rather than the welfare of its subjects. In light of the same, the Internet often becomes one of the only podiums where citizens can voice their grievances and place their thoughts with impunity and without fear of being harried at the hands of the State. However, bearing in mind the rampant Internet shutdowns that India has seen in the past decade paints a very gloomy picture of how the very basic and sanctified Fundamental Rights are not spared even at the hands of governmental high-handedness. This research aims to advocate in favor of the proposition of the Right to access the Internet to be regarded as a Fundamental Right under the auspices of Part III of the Indian Constitution and why it is the need of the hour for the same.
Соционика для создания коллективов, авиационных и космических экипажей с высокой степенью совместимости

Informational models of the psyche, offered by the theory of informational metabolism - socionics, show the way to integrate a large array of experimental data, individual psychological theories and concepts into a single model of mental processes, which is able to describe individual psychological profiles of a person.
HUBUNGAN KONDISI SOSIAL EKONOMI ORANG TUA DENGAN HASIL BELAJAR GEOGRAFI SISWA KELAS XI SMA N 1 2x11 KAYUTANAM TAHUN PELAJARAN 2019/2020.

This study aims to determine the relationship between the socio-economic conditions of parents and the learning outcomes of class XI students of SMA N 1 2x11 Kayutanam in the 2019/2020 academic year. This research uses quantitative research which is classified as a correlation, the sample in the study consisted of 72 students of class XI SMA N 1 2x11 Kayutanam, the sample selection was carried out by total sampling method, namely all students of class XI IPS. Data collection techniques using a questionnaire or questionnaire given to students. Based on the research results, it can be concluded that the data analysis method used is Product Moment Correlation with r count 0.160 and r table 0.235 with the criteria rcount <rtabel or 0.160 <0.235. This shows that there is no significant relationship between the socioeconomic conditions of parents and student learning outcomes. The product moment coefficient of 0.160% results in a determination coefficient of 2.56%. This means that the socioeconomic conditions of parents affect student learning outcomes only 2.56%, while 97.44% are influenced by other factors not discussed in this study.
USING THE BASICS OF REGULAR EXPRESSIONS IN TRANSLATION AND TEXT PROCESSING

The article shows why it is worth introducing the basics of regular expressions in translation curricula.It briefly explains what regular expressions are and presents simple examples of their functionality, illustrating how regular expressions help execute search-and-replace tasks, not accessible for the most commonly used WYSYWIG-text processors.Regular expressions can be widely used in translation processes, namely while defining parsers and segmentation rules; while searching certain words or strings and replacing them; extracting strings for translation; creating checklists for quality assurance; post-editing machine translation, improving the quality of translation memories.Here we show how regular expressions used in a CAT-tool environment help accomplish such tasks as finding different spellings of the same word, finding word forms, finding the source and target segments with different capitalization, replacing the decimal separator, finding and deleting the odd article in the machine-translation output.The basics of regular expressions are explained in the article divided into five main groups: literal characters, metacharacters, quantifiers, characters classes, and groups.Each of these groups is an essential part of regular expressions functionality.Even each one of them separately can significantly widen the search-and-replace possibilities and simplify other text-processing tasks.In many cases, even using one single tool from the regular expressions toolbox can measurably save time for text processing.Besides, regular expressions are also integrated as a tool in many text-processing surroundings like corpus managers or text editors.They are widely used in programming in the form of special libraries.Several examples of such usage are also given at the end of the article.
INTRACTABLE PARADOXES OF EVOLUTION - WITH ALL-ENCOMPASSING GAZE OF A NATURAL PHILOSOPHER

Although Darwin was really ahead of his time on many of the most fundamental issues for science, however, if we talk about the true mechanisms of evolution (as, indeed, about the absence of transitional forms), they still remain the object of sharp, incessant discussions. The same applies to such a fashionable philosophical concept as the noosphere: after all, many people now interpret it in different ways (including as quite real material formations that function, however, according to laws that are not yet completely available to us). Only one thing is clear: these laws are the same for both living and ordinary inert matter. And in addition, in recent years, most modern scientists have begun to tend to the conclusion that the emergence and progressive development of living beings is possible only if there is an appropriate program (plan, project).The article is devoted to the core and most controversial problems of biology. Its main idea is to postulate the individual mental and the collective noosphere derived from it as the leading factors of evolution. After all, one way or another, it is with their interested participation that any dynamic shifts observed in nature are carried out. That is, useful emotional impressions accumulated in ontogenesis by the mental serve as an information base for improving behavioral reflexes in this particular species. And only with some rare saltations (such as, say, the transformation of scales into feathers or forelegs into wings) can we judge the guiding activity of the higher universal mind. Although we are talking about the residual (posthumous) uni-sphere, which is terminologically very little related to the generally accepted, and much more familiar to philosophers,Chardin's. It can be described as a giant biocomputer scattered in space, operating at a slower pace compared to current computers, but still having (through its obedient ubiquitous performers – viruses) so far much more power and influence on the fate of modern world civilizations.