Reviewerly/exHarmony huggingface dataset:
Transforming legal education In the era of fourth industrial revolution (IR4.0)

The recent technological advances trigger the emergence of the Fourth IndustryRevolution (IR4.0) which is very dynamic and progressive to the extent most of themajor industries in the world have no option left but to transform the industryaccordingly in order to adapt to the changes in the IR4.0 era. Hence, this articleaims at exploring how the legal education offered at higher learning institutes canbe transformed to be in line with the IR4.0 in an efficient manner but withoutcompromising the quality. Tertiary education system should catch up with thisprogress to ensure that modern legal education would be fully modified andconcurrent with it. Currently, there is a significant delay in transforming legaleducational services offered at universities, colleges and other higher learninginstitutes with regard to fields of study, subjects offered, teaching and assessmentmethods, among others. Despite the fact that it is complex, for the time being, totransform the legal education to be in line with the IR4.0, it will benefit the societyunprecedentedly for a long run as it is the ‘game changer’ of this era.
LibGuides: Value of Information: Learning Module

With the vast amount of information that can be found as quickly as a mouse click, it is easy to think that all information is free. However, information and access to it is paid for by someone and is not all created equally.
Lifestyle in a Networked Society

The article discusses the concept of a network society, which shows that not only technologies determine modern society, but also many other factors—economic, cultural, political. Network communities in the information society acquire the status of subjectivity and, therefore, they can be considered as network actors. Modern society based on digital technologies is becoming a global network in which the system of social interactions, the way of life of individuals and social groups, is changing radically. Special attention is paid to the fact that in a networked society an individual is a message generator. However, in order to be included in the life of the network society, it must adequately respond to the emerging message flows and build complex communication and activity configurations. Outside the organization, which is the subject of communication, the individual can not participate in public life. The authors of the article revealed that a number of important features of a network lifestyle are formed on the basis of the information structure. The opportunities that are opening up with the advent of network communication technologies imply both positive prospects and social dangers. The network form of communication transforms the social life of modern society, which is increasingly becoming committed to Internet communications. In a networked society, communications develop along the path of openness, which leads to a change in the hierarchical vertical social connections horizontal, in which all participants in the interactions are equal. The core of the network society is the Internet, which gives a global scale to all network communications.
Towards Secure Data Sharing Processes in Online Social Networks: Trusty

The development of Web 2.0 has remarkably increased in today's world.These development has also been a reason for the increment of online social networks (OSNs).Web 2.0 is the roof of the online social networks since online social networks are built on Web 2.0.Users are given an environment in which they can communicate with others without considering other users locations.The way of communication in OSNs is done via sharing various contents of data, such as photos, texts, and videos.Sharing data sometimes cause privacy problems in OSNs, especially in the case that the content involves different users information on itself.Users are notified after the content is shared and they are allowed to remove tags.The content is still available in OSNs platforms, users, therefore, find a way to punish other users with being unfriend, or they quit from OSNs.However, both cases are contradictory with the main of OSNs.By considering the above issues, we develop a framework in which users' opinions are taken on data sharing process and based on the final decision, which is taken by the user who posts the content, punishing or rewarding technique is used.We also evaluate the proposed work with users interactions.
Ultrasonic navigation to control the movement of a mobile robot

This article considers a control system for mobile robots based on an ultrasonic navigation system. The relevance of the problem is explained, modern methods of location of objects are given. We consider hardware and software that allow us to solve the problem of moving a mobile robot from its current position to a given one, and also highlight their advantages in relation to this task. Nema 17 stepper motors were used as the hardware in the experiments, the BNO080 intelligent sensor, which combines the accelerometer, gyroscope and magnetometer, was used as a relative rotation sensor of the mobile platform. The Probabilistic Roadmaps Method was used to find the optimal path. To identify the beginning of the ultrasonic signal, the extreme filtering method, which proved its effectiveness in the field of seismic signal analysis, was implemented. The article also presents a mobile robot control algorithm that allows to move to the goal coordinates using data from the ultrasonic navigation system, while at the same time correcting the angle error of the mobile platform accumulating in the BNO080 sensor. The control algorithm, the optimal trajectory search algorithm, as well as the signal analysis were processed in the Matlab software package. All the statements and methods were tested on the physical model of a mobile robot, the results of these experiments confirmed the feasibility of using these hardware and software.
Single Image Super Resolution using Residual Learning

The Resnet model is similar to the ensemble, and its performance and parameters can be considered according to the modular design. Currently, Resnet is widely used as a backbone network. In particular, the Resnet module that compensates the weight can consider the similarity of pixels. Therefore, in this paper, we propose a method to increase the similarity between pixels by performing the operation of the Resnet module which has an effect similar to the ensemble operation. It give us a better high resolution image.
VII НАУЧНАЯ МОЛОДЕЖНАЯ ШКОЛА-КОНФЕРЕНЦИЯ «ХИМИЯ, ФИЗИКА, БИОЛОГИЯ: ПУТИ ИНТЕГРАЦИИ»

The introduction opens a special issue of Chemical Safety Science, devoted to the materials of the VII scientific youth school-conference “Chemistry, Physics, Biology: Pathways of Integration”. The conference took place on April 17–19, 2019 in Moscow at the N.N. Semenov Federal Research Center for Physical Physics of the Russian Academy of Sciences.
Adversarial Hard Attention Adaptation

Domain adaptation is critical to transfer the invaluable source domain knowledge to the target domain. In this paper, for a particular visual attention model, saying hard attention, we consider to adapt the learned hard attention to the unlabeled target domain. To tackle this kind of hard attention adaptation, a novel adversarial reward strategy is proposed to train the policy of the target domain agent. In this adversarial training framework, the target domain agent competes with the discriminator which takes the attention features generated from the both domain agents as input and tries its best to distinguish them, and thus the target domain policy is learned to align the local attention feature to its source domain counterpart. We evaluated our model on the benchmarks of the cross-domain tasks, such as the centered digits datasets and the enlarged non-centered digits datasets. The experimental results show that our model outperforms the ADDA and other existing methods.
Pengembangan Media Pembelajaran Akuntansi KD 4 Tentang Memahami Asumsi, Prinsip - Prinsip Dan Konsep Dasar Akuntansi Berbasis Adobe Flash CS6 Siswa Kelas X Akuntansi SMK Muhammadiyah Delanggu

The purpose of this study is to find out (1) To develop accounting learning media based on Adobe Flash CS6 to improve student learning outcomes. (2) To knowing the feasibility of Adobe Flash Cs6-based accounting learning media to improve learning outcomes of Grade X Accounting students of SMK Muhammadiyah Delanggu. (3) To improve in student learning outcomes after the development of accounting learning media based on Adobe Flash CS6.The research method using the development model used is the Research and Development (R & D) method. Research and development methods are research methods used to produce certain products, and test the effectiveness of these products. This subject is intended for media experts, someone who is already an expert and experienced in the field of Adobe Flash CS6. The data analysis technique in this research is to use descriptive analysis techniques of quantitative analysis and different tests. The results of the discussion showed that the learning process using the learning model based on Adobe Flash CS6. The feasibility level of Adobe Flash Cs6 products as an accounting learning media is known based on the assessment of media experts as very feasible categories. The use of Adobe Flash CS6 as a learning medium can improve student learning outcomes.
Best A* discovery for multi agents planning

This paper proposes a new approach for multi-agent planning and decision support. The conventional algorithms such as Dijkstra, A* cannot solve complex problems with spatio-temporal constraints. So we are interested in developing a new strategy for the best path based on BDI agents for an emergency evacuation problem of a population crowd, besides the study of the macroscopic behaviour emerging from simple interactions between agents by decreasing the evacuation time which is a challenge and a very complex task. Multi-agent systems are well suited to modelling such systems. The idea is to make a two-dimensional modelling of the environment as a quadtree graph and an hybrid architecture: A* search from the node, where the individual is located to direct it to the best exit node while adding physiological factors to this research, a robust method for collision avoidance and decision support to help the agent will replace the initial destination with anew one. Our model is implemented and tested with java and Netlogo 5.2.1 platform.
A Novel Method for Super-Resolution

For existing super-resolution reconstruction algorithms, the image upper sampling process and de-blurring process are separated. The developed de-blurring methods can perform well. Thus, most researchers spent more effort on the up-sampling process. In the super-resolution reconstruction of images, although the common algorithms can estimate the transformation and rotation of different sequence frames accurately, they cannot deal with blurred images well. If we separate the upper sampling and de-blurring process in the super-resolution reconstruction, we can’t make full use of the sequence images in the de-blurring process. In this paper, we developed a novel method by combining up-sampling process with the estimation of fuzzy kernel. The experimental results showed that our proposed method outperformed the commonly used algorithms subjectively and objectively. Therefore, our proposed approach is a robust method for the super- resolution reconstruction.
From Spanish to Italian . When teaching to unlearn is needed

The Spanish periphrasis is formally similar to Italian but has a wider range of aspectual values (it can express durativity, in addition to progressivity) and is compatible with more tenses (perfectives, in addition to imperfectives). As an effect of transfer, L1Spanish learners of Italian often use to express durativity and combine it with perfective tenses, thus producing incorrect utterances like *Sono stato studiando. In this paper we report an acquisitional study which reveals that input exposure, intensity of L2 use, and non-focused instruction may not be sufficient to pre-empt the transfer and unlearn the erroneous uses of the periphrasis. Based on this result, we propose that a focused teaching intervention is needed. A small-scale pedagogical study based on a Cognitive Linguistics inspired teaching approach gives encouraging results. Die spanische Periphrase ist strukturell ahnlich wie die italienische Periphrase , bietet aber eine grosere Bandbreite an Aspektfunktionen (sie kann neben Progressivitat auch Dauer ausdrucken) und ist mit mehreren Zeitformen (zusatzlich zu imperfek-tiven auch perfektiven Zeitformen) kombinierbar. In diesem Artikel berichten wir uber eine Fremd-spracherwerbstudie, die zeigt, dass die Input-Exposition, die Anwendungsintensitat der L2 ohne die Anwendung von noticing Strategien moglicherweise nicht ausreichen, um der negative Transfer zu verhindern und die fehlerhafte Anwendung der Periphrase zu verlernen. Auf Basis dieses Ergebnisses wird eine Intervention vorgeschlagen, die auf den Einsatz von noticing Strategien setzt. Eine aus einem kleinem Sampling basierten didaktische Studie, die auf einen von der kognitiven Linguistik inspirierten Lehransatz grundet, liefert bereits vielversprechende Ergebnisse.
Reversibly hiding data using dual images scheme based on EMD data hiding method

This paper presents a novel greyscale image reversible data hiding scheme based on exploiting modification direction (EMD) method. In this scheme, two 5-ary secret numbers are embedded into each pixel pair in the cover image according to the EMD method to generate two pairs of stego pixels. Two meaningful shadow images are obtained by shifting the generated corresponding pixel pairs, and the original image and the secret data can be accurately recovered when the two shadow images are operated together. Experimental results show that the proposed scheme has a good performance in the shadow image quality and the image embedding ratio.
STUDENTS’ MOTIVATION TO SPEAK IN A GROUP DISCUSSION

This research was done to know the factors’ influencing students’ motivation to speak in a group discussion. This research is qualitative survey, in which the subjects are the Third-Semester Students of English Education Study Program of Tanjungpura University in Academic Year 2018/2019. The subjects of this research were 25 students in class A. The data were collected through observation and survey. Based on the data the students are motivated enough in speaking class and the motivation are relatively high across the students but most of the students faced several speaking problems such as afraid of making mistakes, lack of confidence, and lack of motivation. In summary, the factors that influenced the students’ motivation to speak in a group discussion are the students' interest to the materials of learning, the students’ interest to the culture of the target language, and lastly the reinforced that the students receive inside/outside the teaching and learning process. All of the factors are related to types of motivation, such as, intrinsic, extrinsic, instrumental, and integrative motivation. The writer claimed that knowing and understand sorts of motivation is essential with the intention of making a better teaching and learning environment
Anticipation of Everyday Life Manipulation Actions in Virtual Reality

While the comprehension of human actions by computer algorithms is widely used in various disciplines of science and technology, the need to predict the actions before their completion is growing. This prediction allows us to prevent undesirable events and enable an efficient interaction between humans and intelligent systems. Here, we first represent manipulation actions using the Enriched Semantic Event Chain (ESEC) framework which creates a temporal sequence of static and dynamic spatial relations between the objects and next, classify and predict the actions. In this paper, we are interested to compare the predictability power of the ESEC framework with that of human subjects. To this end, we designed an experiment in a virtual reality environment and created 300 video scenarios from 10 every day life manipulations. These While the comprehension of human actions by computer algorithms is widely used in various disciplines of science and technology, the need to predict the actions before their completion is growing. This prediction allows us to prevent undesirable events and enable an efficient interaction between humans and intelligent systems. Here, we first represent manipulation actions using the Enriched Semantic Event Chain (ESEC) framework which creates a temporal sequence of static and dynamic spatial relations between the objects and next, classify and predict the actions. In this paper, we are interested to compare the predictability power of the ESEC framework with that of human subjects. To this end, we designed an experiment in a virtual reality environment and created 300 video scenarios from 10 every day life manipulations. These data were next evaluated by both the framework and 50 human participants. The results were surprising because the framework predicted superior than the humans.
Overview about techniques for extracting information from manuscripts

This paper reviews two types of writing recognition and details the phases incorporated on the online phase, which includes pretreatment, segmentation, characteristics extraction, recognition and decision.
Improving recommendation quality by identifying more similar neighbours in a collaborative filtering mechanism

Recommender systems (RS) act as an information filtering technology to ease the decision-making process of online consumers. Of all the known recommendation techniques, collaborative filtering (CF) remains the most popular. CF mechanism is based on the principle of word-of-mouth communication between like-minded users who share similar historical rating preferences for a common set of items. Traditionally, only those like-minded or similar users of the given user are selected as neighbours who have rated the item under consideration. Resultantly, the similarity strength of neighbours deteriorates as the most similar users may not have rated that item. This paper proposes a new approach for neighbourhood formation by selecting more similar neighbours who have not necessarily rated the item under consideration. Owing to data sparsity, most of the selected neighbours have missing ratings which are predicted using a unique algorithm adopting item based regression. The efficacy of the proposed approach remains superior over existing methods.
Ontology-Based Semantic Search on Tourism Information Search System

Nowadays, search engines are used to find various information on the Web.  Search engines that are implied traditional search based on keywords do not always provide relevant information. Meanwhile by semantic search can provide relevant results because it can understand the meaning of the context and its connection. One approach to semantic search is to use ontology. Ontology is used to define concepts and relevant relations in a domain. In Information Retrieval (IR), an ontology  encompasses in returning relevant information from a collection of unstructured information. One application of ontology in IR is query expansion. In this research, The query entered by the users will be searched for its relation to the ontology domain which will be expanded later. We use tourism in Bandung Raya as an ontology domain.  The search in this research is represented by using Vector Space Model (VSM). Furthermore, relevant documents  from search result will be provided to users. Based on the results of testing, the system that is built is able to provide relevant information with an average MAP value better than the search system that only uses traditional search methods.
Removing Mismatches Using Corresponding Circles

We propose an algorithm for elimination of false correspondences from given putative point correspondences in couples of stereoscopic images based on corresponding circles (ICC) technique. In this paper, we propose a new method that reduces the cost of computing false correspondences. The aim of this method is mainly to take better advantage of the corresponding circles. The quantitative results demonstrate the efficiency and performance of our algorithm.
Sonic Conversations for Double Bass, Berimbau and Sámi Joik: Shaping Identity in the Third Space

This exposition presents, unpacks and discusses the effects of intercultural dialogue and collaboration on the formation of an individual personal artistic identity, through the lens of two musical duets. These artistic research case studies are centred around the author in dialogue with a Brazilian berimbau player and a Sámi singer, which act as focal points to examine how intercultural dialogue and collaboration can impact on the formation of a personal artistic identity and how the third space emerging from a transcultural dialogue can be a catalyst for new musical discoveries. In addition, I consider the kinds of musical and communication skills that are needed to co-create music in a transcultural context and which kinds of ethical issues arise. The core thread of discussion and argumentation is centred firstly around the idea that by placing oneself in diverse and unknown musical environments and engaging in dialogue, a dynamic third space emerges, which holds within it the opportunity for new elements and approaches to surface and take shape in unexpected ways. And secondly, I propose that searching for points of resonance with the world around us may be crucial in the creation of meaning and the formation of a personal artistic identity. Although the practice of music making is at the core of this research, the work is viewed with a wide-angle lens, acknowledging findings that point to the importance and potential benefits of increasing intercultural dialogue, understanding, collaboration and resonance at all levels of society. Discoveries also emerge within the areas of extended instrumental techniques and an expanded sonic palette for the double bass, as well as the creation of new music. This exposition zooms in on two examples from my complete artistic doctoral project at Sibelius Academy, Uniarts, Helsinki, namely the two sonic conversations for double bass and berimbau, and double bass and Sámi joik.
Spam Detection for Youtube Comments

Spamming is the use of messaging system, to send an unsolicited message. YouTube is one of the biggest sites for the user to get information. The best thing about the YouTube is the user can subscribe the channel, like or dislike the video and also giving opinion on the comment section on that video, and YouTube has attracted to increase the number of users. This attracts the spammers by spamming the comments. In this paper the spam comments on YouTube offers limited tools for comment moderation, so that the spam volume is shockingly increasing which leads to the owners to disable the comment section in their video. By using machine learning the comments are detected and prevented. Sklearn, numpy, pandas these are the some of the packages for understanding purpose of machine learning. YouTube spam comment has potential to spread malware through comment fields, which will exploit vulnerabilities in the user’s machines. There are many approaches to detect Spam such as Artificial intelligence (AI), Machine Learning (ML), cryptography and others. A you tube has an automatic spam filter; this is the challenge even for the classification method. YouTube classifier classifies the comments by using classification methods as very short, symbols, abbreviations, links.