Reviewerly/exHarmony huggingface dataset:
An Abstraction Model for 1-bit Probing Attack on Block Ciphers

The threat of physical attacks on crypto devices has been reported. Attack efficiency is determined by the attacker’s ability to measure the physical information leaked from the device, for example, side-channel information, or to control physical disturbance against a device, for example, laser fault injection. Intuitively, the higher the ability of the attacker, the more information can be retrieved. In order to assess attack efficiency, this paper focuses on the 1-bit probing attack, which is one of the strongest attacks in a real-world setting. In the 1-bit probing attack, the attacker can observe a specific 1-bit intermediate value at a certain timing in the cryptographic operation. Firstly, we explain previous studies on an abstraction model for physical attacks. Secondly, we introduce a new model with an ideal property with regard to the probing attacks. Finally, we compare the attack efficiency of seven reported block ciphers with the proposed model value.
Design and Improvement of Hopfield network for TSP

The TSP (travelling salesman problem) is about the combinatorial optimization, many practical applications such as the designing of safe and efficient transportation network, the planning of logistics line, can all be converted to TSP after simplification. The number of possible routes in TSP is growing exponentially with the number of the cities N and the optimum solution is difficult to calculate. So how to find the efficient solving algorithm is of great importance. The Hopfield network is designed to solve traveling salesman problem. Because of the poor convergence and invalid solution of Hopfield network in solving TSP, the energy function of Hopfield is improved and the genetic algorithm is applied in the Hopfield network. The results of simulation show that the improved Hopfield network can get better optimization than the classical Hopfield network to solve TSP.
Multi-wavelength large optics wavefront error metrology bench (Conference Presentation)

We present an optical metrology instrument for measuring both transmitted and reflected wavefront error (TWE and RWE) of coated or uncoated optics over a diameter of 5 inches. Depending on the coating transmittance and reflectance, the measurements have to be done at different wavelengths. Interferometer is a standard instrument to measure the TWE and RWE of uncoated optics. But in the case of coated optics (bandpass filters for example) measurement of TWE is not possible because the optics may not transmit the interferometer laser light. The chosen solution is based on a quadriwave lateral shearing interferometer (QWLSI) wavefront sensor. QWLSI is an achromatic technique, meaning that it measures OPD at any wavelength without any need for recalibration at specific wavelengths. Consequently, various sources at different wavelengths can be used with the same instrument and metrology bench. In addition, QWLSI measures the derivative of phase contrary to interferometer that measures phase. Therefore, QWLSI has by design a better WFE dynamic range for TWE and RWE measurement. Moreover accuracy (below 15nm RMS) and repeatability (below 2nm RMS) is perfectly adapted to optical metrology measurement.The optical solution is a standard double pass configuration composed of a collimator and a beam expander to adapt the size of the beam to the wavefront sensor aperture. We use LED sources to avoid any noise due to interferences within the optics, which occur with coherent light. We can use different wavelength between 400nm and 1100nm. We can optimize the longitudinal chromatic aberration by moving a lens from the beam expander.We characterized the bench according to the ISO 5725 standard for different wavelengths. Its precision was tested with different samples (filters and mirror). The precision on TWE was found to be below 2nm RMS.
On the Effectiveness of Handcrafted and Learned Features in Automated Essay Scoring

The task of Automated Essay Scoring (AES) has been active for more than half a century, starting with handcrafting statistical features used for linear regression, and currently being improved by the latest advancements in machine learning and natural language processing. Most current research uses some form of character or word embeddings to represent the essays rather than statistical features, enabling the models to analyze the text in full and automatically learn what to look for. Handcrafted features have possibly reached their maximum potential, and have been shown to be outperformed by more complex representations of textual data. However, the fundamental differences between handcrafted and learned features have not been properly documented, nor their fundamental strengths and weaknesses compared. In this paper we compare two different kinds of models for automated essay scoring, a Multilayer Perceptron (MLP) using handcrafted features and a standard Convolutional Neural Network (CNN) using word embeddings. The models are trained and tested and their strengths and weaknesses are discussed. We show that a simple CNN outperforms the MLP using handcrafted features, but that the MLP is a viable method to use for small tasks because of the easier implementation and shorter training time. We also provide some tips and suggestions when constructing a CNN for AES, and we discuss a potential downside of the quadratic weighted kappa score that is sometimes a suggested validation metric for AES-systems. (Less)
Gray Level Cooccurrence Matrix Feature Extraction and Fuzzy Based Discriminative Binary Descriptor for Medical Image Retrieval

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Bitcoin in Blockchain A Survey

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Structural Model Analysis on the Working Environment, Job-Relationship, Positive Psychology and Innovative Behavior in Employees of Commercial Sports Facilities

This study was to explore the working environment, job-relationship, positive psychology and innovative behavior in employees of commercial sports facilities. For this, the employee of commercial sports facilities(swimming pool, fitness center, table tennis court) in Jeollabukdo provinces were surveyed. Except for thirteen questionnaires, final 287 out of 300 ones was statistically managed and SPSS 23.0 and LISREL 8.80 were used for statistical analysis. The result of this research was as follows.BR First, the working environment of the commercial sports facilities workers are significant to positive psychology. And the working environment of the commercial sports facilities workers are significant to innovative behavior. Second, the job-relationship of the commercial sports facilities workers are significant to positive psychology. And the job-relationship of the commercial sports facilities workers are significant to innovative behavior. Third, the positive psychology of the commercial sports facilities workers are significant to innovative behavior.
Attention Neural Network for User Behavior Modeling

The recommendation system can effectively and quickly provide valuable information for users by filtering out massive useless data. User behavior modeling can extract all kinds of aggregated features over the heterogeneous behaviors to help recommendation. However, the existing user behavior modeling method cannot solve the cold-start problem caused by data sparse. Recent recommender systems which exploit reviews for learning representation can alleviate the above problem to a certain extent. Therefore, a user behavior modeling is proposed for recommendation task using attention neural network based on user reviews (AT-UBM). Firstly vanilla attention was used to sample reviews, and then CNN+Pooling method was applied to extract user behavior features. Finally the long-term behavior was combined with short-term behavior in feature spaces. Experimental results on real datasets show that the review-based user behavior model has better prediction accuracy and generalization capability.
LANGUAGE ATTITUDES AND MOTIVATION FOR LEARNING INDONESIAN LANGUAGE AS A FOREIGN LANGUAGE BY STUDENTS OF MALAY-INDONESIA DEPARTMENT, HANKUK UNIVERSITY OF FOREIGN STUDIES (HUFS) SOUTH KOREA

There are two major factors which influence a person to learn and master a foreign language. These are language attitude and motivation. The aim of this study is to understand how language attitude and motivation of students in Hankuk University of Foreign Studies (HUFS) South Korea affect learning the Indonesian Language. Questionnaires were distributed to 20 students of Malay-Indonesian Department at HUFS, South Korea. The data obtained from the questionnaires were then analyzed by using a scale for measuring attitude (Likert scale). Based on the Likert scale analysis, the results indicated that their language attitudes had an average value of 3.87 (the scale ranges from 1 to 5). This implies that they have a  positive attitude. In a similar manner, the analysis of their motivations shows that their average score is 4.22. Their motivation to learn the Indonesian Language is very positive, that is, very high. This high score is in the aspect of an instrumental motivation with an average score of 4.35. The results of this study show that a positive language attitude and motivation enables the learners to achieve success in learning a foreign language.
Formation of media education in Russia (from the Middle Ages to the present day)

In a situation when digitalization becomes a new paradigm of society’s activity and cyber-physical systems are the systems that will organize social and economic space (online and offline) in the near future, an increase in media literacy among the population becomes a very urgent necessity, for, as shown by public opinion, many people do not possess elementary skills of media security and do not have sufficient media knowledge to successfully interact with other people (or, alternatively, computer or bionic systems) in a virtual or real environment. The main purpose of the paper is to show the formation and development of media education in Russia from the 12th century to the 21st century (i. e., from the moment of appearance of the first reliable written sources and up to modern times). Based on the analysis of a wide historical context, the authors explore the functional areas and main media education tools that were used at various historical stages of media education development. In addition, the paper presents data on the state of media literacy of the population in the past and present and also argues that the middle and older generations (Generation Last) are more vulnerable in their interactions with the media than the younger generations (Generation Next). Therefore, as a practical solution to the goal of increasing the overall media literacy of the population, it is suggested to use inter-network collaboration (social networking collaboration), where Generation Next will transmit relevant knowledge to Generation Last and the social networking administration will support the exchange of knowledge using positive reinforcement (for example, by assigning special public statuses to active users).
Soft Subspace Growing Neural Gas for Data Stream Clustering

Subspace clustering aims at discovering the clusters embedded in multiple, overlapping subspaces of high dimensional data. It has been successfully applied in many domains such as financial transactions, telephone records, sensor network monitoring, website analysis, weather monitoring, etc. Data stream are ordered and potentially unbounded sequences of data points created by a typically non-stationary data generating process. Clustering this type of data requires both time and memory restrictions. In this paper, we propose S2G-Stream based on growing neural gas and soft subspace clustering. We introduce two types of entropy weighting for both features and subspaces. Experiments on public datasets showed the ability of S2G-Stream to: (1) detect relevant features and subspaces; (2) detect clusters of arbitrary shape; (3) enhance the clustering results.
Learning Minimal DFA: Taking Inspiration from RPNI to Improve SAT Approach

Inferring a minimal Deterministic Finite Automaton (DFA) from a learning sample that includes positive and negative examples is one of the fundamental problems in computer science. Although the problem is known to be NP-complete, it can be solved efficiently with a SAT solver especially when it is used incrementally. We propose an incremental SAT solving approach for DFA inference in which general heuristics of a solver for assigning free variables is replaced by that employed by the RPNI method for DFA inference. This heuristics reflects the knowledge of the problem that facilitates the choice of free variables. Since the performance of solvers significantly depends on the choices made in assigning free variables, the RPNI heuristics brings significant improvements, as our experiments with a modified solver indicate; they also demonstrate that the proposed approach is more effective than the previous SAT approaches and the RPNI method.
Mobile applications for Indigenous language learning: Literature review and app survey

This paper investigates mobile applications (apps) intended to support Indigenous language revitalization efforts in Canada and the mainland United States. It examines the role that apps may play in language revitalization movements beginning with a literature review which focuses on the benefits and drawbacks of apps as a medium for Indigenous language learning. This paper continues with a review of 32 apps, discussing examples of different pedagogical strategies and trends seen across Indigenous language apps. The community-driven app development process is examined, including funding sources, the role of development companies, and the level of input and recognition of community members. This paper concludes with a discussion synthesizing the findings of the app review in the context of the best practices and challenges identified during the literature review process. The original research conducted during the app review, and the analysis of these findings in light of the literature review, aims to make a contribution to the currently small body of literature focussed specifically on apps for Indigenous language learning.
PERAN TEKNOLOGI DALAM MENDUKUNG PEMBELAJARAN BAHASA INGGRIS DI SEKOLAH DASAR

&lt;p&gt;&lt;em&gt;The new era presents teachers new challenges and responsibilities. The tradition of teaching English has improved dramatically with the inclusion of various types of advanced technology. Technology provides numerous choices such as making teaching interesting and more productive. Technology is one of the most influential boosters of social and language change. Since the use of English has progressed in popularity, the demand for qualified teachers to teach English is unquestionably required. It is true that there are teachers who use 'sophisticated' technology, although most of them still teach in the traditional way. None of these traditional behaviors is bad or damaging to students. In fact, until now they proved it useful too. However, there are various opportunities for students to gain self-confidence to practice and expand themselves, particularly for those who are learning English as a foreign language that learns the language for more than just having fun. If they want to be able to follow the learning process and gain more confidence, they must step into the world of multimedia technology.&lt;/em&gt;&lt;/p&gt;
PENERAPAN ALGORITMA APRIORI UNTUK PENGADAAN OBAT DAN ALAT KESEHATAN PADA DEPARTEMENT RADIOLOGI MAYAPADA HOSPITAL

The pattern of drug and medical device needs at Mayapada Hospital in South Jakarta has a tendency to be repeated and similar in a relatively long period of time, especially in one particular department, because the cases found are often similar or even similar. Ensuring the availability of stock in each department's deposit is very vital, because the procurement of medical equipment must go through a certain process and time, so there are often cases where there is a critical resus but the equipment needed in the deposit does not meet the needs or escape from inventory and must indent first. By calculating the tendency (Apriori Association) demand patterns in the relevant departments, especially in the radiology department at Mayapada Hospital, South Jakarta, a rule was formed that resulted in a pattern of dependency between itemsets that had supporting criteria in the form of support of 33.3% and Confidence by 85%, where the items that appear are items with a high frequency of appearance and association, so they can be taken into consideration to ensure the availability of drugs and medical devices.
Secure Text Encryption in Intranet Using Elliptic Curve Cryptography

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
DeepView: Visualizing the behavior of deep neural networks in a part of the data space

Machine learning algorithms using deep architectures have been able to implement increasingly powerful and successful models. However, they also become increasingly more complex, more difficult to comprehend and easier to fool. So far, most methods in the literature investigate the decision of the model for a single given input datum. In this paper, we propose to visualize a part of the decision function of a deep neural network together with a part of the data set in two dimensions with discriminative dimensionality reduction. This enables us to inspect how different properties of the data are treated by the model, such as outliers, adversaries or poisoned data. Further, the presented approach is complementary to the mentioned interpretation methods from the literature and hence might be even more useful in combination with those. Code is available at this https URL .
Mimesis, Murakami and Multimedia Art: Parallel Worlds in Performance

The artistic techniques of mimesis—the representation of reality in art—make it possible to “render the unreal familiar or the real strangely unfamiliar.” The author, a composer and intermedia artist, uses mimetic techniques in acoustic composition, video art and field recording to reimagine everyday experience, as in his multimedia piece Landscape: Home. The author analyzes passages from the novel Sputnik Sweetheart by Haruki Murakami to understand Murakami’s use of “parallel worlds” and the “reality effect.” This literary analysis aims to highlight the potential of mimetic techniques for artistic practice in sound and image, particularly in the author’s Landscape series.
Neural Network Based Online Anthropomorphic Performance Decision-Making Approach for Dual-Arm Dulcimer Playing Robot

A neural network based online anthropomorphic performance decision-making approach is described for a dual-arm dulcimer playing robot. Because it is difficult to extract experiential rules manually to describe the decision behavior of a human playing a dulcimer, the proposed method relies on the self-learning function of a artificial neural network (ANN). The training data of the network consists of three types of information: the note pitch of adjacent notes, time interval in a piece of music, and decision results in actual performance processes of human beings. A decision-making approach, devised through combining the well-trained ANN with music for which performance decisions were required, is then applied. The numerical results show that, for several pieces of music with different characteristics, the accuracy and precision of the decision results are always relatively high, which verifies the practicability and good generalizability of the method.
Creating Makerspace in School Libraries in Nigeria: Implications and Challenges

Libraries of all types are expected to be places where knowledge and skills are acquired. This paper attempts to look at the implications and challenges of creating makerspace in school libraries in Nigeria. Makerspace creates avenue for students to identify their talents/skills, satisfy their curiosity, bring their imaginative ideas to life and emerge with quality products to show. The paper rests on the theory of constructionism propounded by Seymour Papert which stipulates that learning occurs in the students head. The paper also rests on the theory of participatory culture and learning which simply means that students come together in a social space, put their hands to work and come out with great products. The paper identified the implications and challenges of creating makerspace in school libraries in Nigeria and concluded that there is a need to have makerspace in school libraries in Nigeria as this will create route of networking among students.