Reviewerly/exHarmony huggingface dataset:
PartNRL: Partial Nodes Representation Learning in Large-Scale Network

Recently, the low-dimensional embedding of nodes has received a large amount of attention in the field of network analysis. While the existing methods mostly focus on the network embedding of the entire network, there are also some situations, where people may only be interested in some nodes (i.e., partial nodes) rather than all nodes, especially in large-scale networks. Although there are some approaches dealing with the large-scale network, most of them require that all nodes are present during the optimization procedure. The necessity to generate the embedding results for redundant non-interested nodes makes these methods quite inefficient. In this paper, we present a novel node representation framework termed partial nodes representation learning (PartNRL), which is capable of preserving the local similarity of the interested node pairs and generating the embedding results efficiently. Two phases are carefully designed in PartNRL. The first phase is to use local random walk to capture the t -step local similarity for memory-efficiency. By modeling the inherent properties of nodes through the first phase, we design the second phase to learn the node representations by maximizing a likelihood function based on the skip-gram model. To make the optimization procedure more efficient, the negative sampling strategy is applied. The extensive experiments have been conducted on three tasks: node clustering task, single-labeled classification task, and multi-labeled classification task. The experimental results confirm the superior performance of the proposed model over the state-of-the-art network embedding methods.
Implementation of Cloud Applications

The companies’ move towards cloud applications and cloud solutions is not only a shortsighted trend. It is a clear strategy of the business leaders to “get more bang for the buck”. It is more and faster innovation, more flexibility, more interchangeability of software providers, more focus to the end-customers and end-users, less technology dependency, and it’s cheaper in the long run. The subscription model includes all technology and its operation 24x7; many of the topics that made implementation programs fail in the past (see the previous chapter) are no risk factors during cloud implementation programs. One risk area is dominant: the integration between different cloud solutions and the integration to backend systems on-premise need to be managed with technical knowledge and operational experience as we know from a data center operation.
An Evaluation of the Usefulness of Multi-Search Engines in Scholarly Communication

Academics often use publications from a wide range of sources. Multi-search engines enable simultaneous online searching of these distributed resources, which is claimed to make working easier for users interested in publications on a given topic. Because some multi-search engines are sold as commercial software, often at considerable cost, it may be asked whether the use of such software in an academic environment is beneficial and economically justified. Does the academic community in fact perceive a need to use these programs? Is their function not performed equally well by Google Scholar? Is it not more effective to make exclusive use of specialist databases? These questions are investigated by comparing the effectiveness of searching using Google Scholar and the Primo search engine.
Measurement of arm length difference of interferometric fiber-optic hydrophone using extra-carrier modulation and interference fringe counting method

Due to the characteristics of low loss, passivity, and long-distance transmission, interferometric fiber-optic hydrophones and their arrays have been widely used in engineering detection applications. The arm length difference is one of its main performance parameters. A system for measuring of arm length difference using extra-carrier modulation and interference fringe counting method is introduced in detail. The propagation process of optical signal in the fiber-optic hydrophone is described. The mathematical expression of the phase of interferometric optical signal intensity caused by external carrier is given and analyzed. The expression of arm length difference and its evaluation of measurement uncertainty are obtained. Experimental study on measurement of arm length difference is developed. Both theoretical analysis and experimental results show that the product of the driving voltage of the fiber stretcher and the arm length difference has fixed value. Combining the known arm length difference value and the carrier driving voltage of the reference interferometer, the arm length difference of the hydrophone to be measured can be calculated with the value of its carrier driving voltage accurately. The uncertainty of measurement of the device and method described in this paper is better than 0.5%. The measuring range is 0.1 m to 500 m.
Handcrafted Descriptors-Based Effective Framework for Off-line Text-Independent Writer Identification

Feature extraction is a fundamental process in writer identification that requires efficient methods to characterize and handle local variations of the characters shape and writer individuality. This paper presents a reliable and novel learning-based approach for off-line text-independent writer identification of handwriting. Exploiting the local regions in the writing samples (document or set of word/text line images), we propose a simple, yet adaptive and discriminative feature representation based on handcrafted texture descriptors including Local Binary Patterns (LBP), Local Ternary Patterns (LTP) and Local Phase Quantization (LPQ) to describe characteristic features of the writing style variability. The overall system extracts from the input writing a set of connected components, which seen as texture sub-images where each one of them is subjected to LBP, LPQ or LTP to compute the feature matrix. This matrix is then fed to dimensionality reduction process followed by segmentation into a number of non-overlapping zones, which are afterward subjected to sub-histogram sequence concatenation to form the holistic concatenated component feature histogram. In the identification stage, the writing samples are recognized and classified through their feature histograms using the nearest neighbor 1-NN classifier. Experiments conducted on two handwritten representative databases (AHTID/MW and IAM) indicate that our system performs better than the state-of-the-art systems on the Arabic AHTID/MW database, and show competitive performance on the English IAM database.
Retraction: An Electronic Glove–A Boon to the Deaf and Dumb (<i>J. Phys.: Conf. Ser.</i> <b>1172</b> 012018)

This paper was retracted by IOP Publishing on 30 Apr 2019. It has come to the attention of the author and the publisher that this article contains language that caused offence. After discussion with the author we have agreed to retract the article.
중한 번역에 나타난 번역투 유형 -초급 중국어 교재를 중심으로

This paper studied the translationese of Primary Chinese textbooks in Korea. According to the analysis, there were many awkward Korean words in the Primary Chinese textbooks. In particular, the Korean language was not natural because it was mostly literal. This paper is analyzed by dividing into person pronouns, nouns, adverbs, parenthesis, noun modifier, and conjunction. Although it is natural to omit the personal pronouns in Korean, the texts analyzed by this paper have translated all of the personal pronouns. The nouns and adverbs were also translated into the meaning of the dictionary, making them very awkward. These texts also translated into very awkward Korean, with most of the sentence being translated into Chinese word order. It is the most frequently seen translationese of Korean beginners. As such, most of the Primary Chinese textbooks translated the vocabulary and word order of Chinese as it was.
View-Invariant Human Activity Recognition using Topic Model on Combined ORB-OF Feature

In this paper, we introduce a human activity recognition method that is able to adaptively handle viewpoint variations. For this work, we also propose a combined ORB-OF feature which is a combination of ORB (oriented FAST and rotated BRIEF) binary feature and optical flow (OF) motion feature; as well as a binary vector clustering algorithm to organize and normalize ORB binary descriptor vectors into clusters. In addition, our proposed method is robust to partial occlusion, subject scale and activity speed variations, as well as less sensitive to lighting condition and actor appearance. We validate the proposed method by conducting experiments using a self-recorded dataset.
Multitask Person Re-Identification using Homoscedastic Uncertainty Learning

In this paper, we propose a new multitask neural network called Part Attribute Loss Net (PALNet) for person re-identification (re-id) with homoscedastic uncertainty learning. Currently, many person re-id algorithms use person identity as the main ground truth information to train and to perform prediction task. This single task approach is simple to setup but usually provides poor generalization performance. Some other person re-id works [1] [2] incorporate additional cues such as body parts to improve the learned representations. However, this requires additional body part annotations. Person attributes, which are present in some of the large person re-id datasets like Market1501 [3] and DukeMTMC-reID [4], are not used. Furthermore, the multitask networks found in some of the recent works use heuristic approach in weighing their task losses. Our PALNet seeks to address these issues by leveraging on person identity classification, body part detection and person attribute prediction, all built into a unified network. We also incorporate the homoscedastic uncertainty learning to automatically determine the weighing of the loss function of the different tasks. The PALNet consists of three tasks, with person identity classification as the main task. The body part detection and person attributes are two sub tasks to share different learning experience with the main task. The uncertainty learning provide us good indication of the observable task noises and allows us to optimize the accuracy performance without the time consuming grid search method. When benchmarking on DukeMTMC-reID dataset [4], our approach outperforms other state-of-the-art methods. On Market1501 dataset [3], we are on par with the best state-of-the-art method but outperforms the rest by at least 6.4% mAP and 3.5% Rank-1 accuracy. These results are reported without re-ranking.
A Size-Dependent Cost Function to Solve the Inverse Elasticity Problem

Characterizing nonhomogeneous elastic property distribution of solids is of great significance in various engineering fields. In this paper, we observe that the solution to the inverse problem utilizing the standard optimization-based inverse approach is sensitive to the sizes of inclusions. The standard optimization-based inverse approach minimizes a cost function, containing the absolute error between the measured and computed displacements in L2 norm. To address this issue, we propose a novel inverse scheme to characterize nonhomogeneous shear modulus distribution of solids. In this novel method, the cost function is modified, and is dependent on the size of the inclusions. A number of simulated experiments are performed, and demonstrate that the proposed approach is capable of improving the shear modulus contrast in inclusions and reducing the size sensitivity. Furthermore, a theoretical analysis is conducted to validate what we have observed in simulated experiments. This theoretical analysis reveals that what we have observed in the simulated experiments is not induced by the numerical issues Instead, the size sensitivity issue is induced by regularization. The findings of this work encourage us to propose new cost functions for the optimization-based inverse approach to improve the quality of the shear modulus reconstruction.
Significant Factors Impacting on Cyber Security

This article analysis various crucial factors which have some strong impact and which does not have great impact on cyber security related aspects. In present world cyber security knowledge and applications of Internet services is spell bound. Internet has already occupied the entire world business. In this work we have encountered hypothetical research to identify the crux factors. This article has provided a strong opening on certain significant factors which makes larger impact on cyber security.
Eksperimen Pembelajaran Matematika dengan StrategiCourse Review Horay (CRH) dan Think Pair Share (TPS)terhadap Hasil Belajar Ditinjau dari Keaktifan BelajarSiswa Kelas VIII SMP N 2 Gatak Tahun Pelajaran 2017/2018

Adita Faizah Isnaini / A410140048. MATHEMATICS LEARNING EXPERIMENTWITH COURSE REVIEW HORAY AND THINK PAIR SHARE LEARNINGSTRATEGY ON RESULT LEARNING VIEWED FROM LEARNINGACTIVENESS IN CLASS VIII SMP N 2 GATAK LESSON YEAR 2017/2018.Skripsi. Teacher and Education Training Faculty, University of MuhammadiyahSurakarta. November, 2018.The purpose of this research is to examine and analysis (1) the influence of CourseReview Horay (CRH) and Think Pair Share (TPS) learning strategy towardsmathematics learning results, (2) the influence of learning activeness towardsmathematical learning results, (3) the interaction of learning strategy and learningactiveness towards mathematics learning results. Quantitative research with a quasiexperimental design. Population of this research is eighth grade junior high schoolstudents of 2 Gatak and sample of class VIII A and VIII B of grade junior highschool students of 2 Gatak with using cluster random sampling. The data collectiontechnique using the test methods, questionnaire , and documentation. Data wereanalyzed using analysis of variance of two paths with different cell. The results ofstudy with α = 5% is (1) there is influence of Think Pair Share (TPS) and CourseReview Horay learning strategy towards mathematics learning results with FA =5,1425 > 4,009 = Ftsble, (2) there is influence of learning activeness to themathematical learning results with FB = 3,623 > 3,158 = Ftable, (3) there is nointeraction of learning strategy and learning activeness towards mathematicslearning results with FAB = 3,1425 > 3,158 = Ftable.
Acceleration of 3D Measurement of Large Structures with Ring Laser and Camera via FFT-based Template Matching

For quality inspection and maintenance in the manufacturing industry, it is extremely important to accurately measure the 3D shape of various structures in an efficient manner. In this paper, we propose an accelerated light-section method to accurately measure the 3D shape of large structures. The light-section method is a popular method to measure the 3D shapes accurately, which uses a laser and a camera that can observe the shape of the laser cross-sections. This method consists of two important steps: first, images that include the laser cross-section are captured. Next, the cross-sections are integrated by calculating the transformations between these images. For want of high accuracy, area-based matching methods, such as template matching, which match pixels in an area one-by-one, are used to calculate these transformations. Hence, the processing time is too high and speed/efficiency is quite important for real-life 3D measurement applications. Therefore, we focus on developing a faster template matching method. In this process, the presence of the laser cross-section on the image texture can induce errors in the integration and lower accuracy. Thus, it is required to mask the laser regions inside each image. To solve this problem and make the calculation faster, a masked Fast Fourier Transform (FFT) based template matching is proposed. Via experimental evaluation, we show that the 3D measurement process can be made almost 1.6 times faster, with similar accuracy as compared to previous methods.
Cybercrime: Responding Sensibly in the Age of Uncertainty

Cybercrime is now threatening the very existence of Information Technology critical infrastructure, the greatest human innovation after the industrial revolution. Wrong value system has been identified as key factor encouraging cybercrime in Nigeria and the desire to get rich quick without working for it.  Cyber crime is complex and committed mostly from remote locations making it difficult to police. The absence of enabling law makes policing even more difficult.  This paper has proposed several recommendations including the fact that the National Orientation Agency should shift focus to national re-orientation of the psyche of the whole population and particularly the youths in post-primary and tertiary institutions and to parents, towards raising crop of children with strong religious training, belief and trust in God as well as the infusion of religious training in the curriculum of our educational system at all levels. Cyber-security awareness training should now constitute part of the school curriculum. Government-Private sector partnership should be formed to develop appropriate strategies towards cyber crime monitoring, control and prevention. This is the responsibility of all citizens - government, private sector and individuals.  The paper contends that if action is not taken urgently, Nigeria will head towards self-destruct and the African continent may turn out to become a desolate colony!
IDENTIFIKASI FAKTA DAN OPINI DALAM TEKS EKSPOSISI “MERETAS ASA, MEMBANGUN WIBAWA” DENGAN MEDIA KARTU

The real problem found in the field is the number of students who think that facts and opinions are the same things, even when describing the meaning and example there are still things that are not appropriate. Facts are events or real events that really happened. The opinion is a statement that contains ideas or assumptions of both individuals and groups. This study aims to determine the skills of students to identify facts and opinions and the extent to which students can sort out the facts and opinions contained in the exposition text with card media. Researchers in conducting this study used a qualitative approach method with descriptive analysis. The results obtained indicate that the knowledge and ability of students in identifying facts and opinions is good enough can be reviewed from the answers obtained, namely, there are 59% of students answered correctly and 41% of students answered incorrectly. There were 12 students who received the KKM score and 8 students who received fewer scores from the KKM. The result is 60% and 40%, indicating that students already understand and are able to show which facts and opinions. Therefore, the implementation of card media that is applied when identifying facts and opinions in exposition text with card media is quite successful in increasing students' knowledge, understanding and abilities.
Images of Science Teachers Represented in Hollywood Films

교사 이미지는 교사 이미지는 교육 환경뿐만 아니라, 대중 매체를 통해서 수많은 인식에 영향을 미칠 수 있다. 효과적인 과학교육의 묘사는 과학 탐구와 다른 표준에 기초한 실제의 복잡한 성격을 감안할 때 특히 상세히 규정하기 어렵다. 이 연구는 할리우드 영화 속에 재현된 과학교사들의 이미 지를 조사하였다. 수집된 초기 데이터에는 이미지 유형(사진, 만화/클립 아트, 텍스트/시각)과 묘사된 과학 교사의 인구통계 정보가 포함되었다. 과학 교사의 복장, 행동, 재료와 장비, 학생과의 상호작용을 포함한 공통 주제를 탐구하고 문서화했다. 또한 과학교육 문헌과 비교를 포함하여 이러한 이미 지의 잠재적 영향에 대해 논의하였다. 이 연구의 시사점으로 과학교사 교육자들이 이러한 이미지를 사용하여 예비교사들과 현직 교사들 간의 반성과 대화를 촉진할 수 있는 방법이 제시되었다. 더욱이 과학교사를 성공적으로 채용하고, 준비하고, 지원하기 위해서 고정관념에 대한 검토는 해결되고 극복되어야 할 필요가 있다.This study examined the images of science teachers represented in Hollywood films. This study is qualitative content analysis research that analyzes the image of science education teachers recreated in movies in as a part of cultural studies. Cultural studies is an academic field of critical theory and literary criticism initially introduced by British academics in 1964 and subsequently adopted by allied academics throughout the world. Characteristically interdisciplinary, cultural studies is an academic discipline aiding cultural researchers who theorize about the forces from which the whole of humanity construct their daily lives. Cultural Studies is not a unified theory, but a diverse field of study encompassing many different approaches, methods and academic perspectives. Distinct from the breadth, objective and methodology of cultural anthropology and ethnic studies, cultural studies is focussed upon the political dynamics of contemporary culture and its historical foundations, conflicts and defining traits. Researchers concentrate on how a particular medium or message relates to ideology, social class, nationality, ethnicity, sexuality and/or gender, rather than providing an encyclopedic identification, categorization or definition of a particular culture or area of the world. Therefore, the purpose of this study is to analyze the image of science teachers recreated in the movies produced by Hollywood. Movies reflect the culture of the time. Images of science teachers expected by the public and recreated in movies are different from the reality. Generally, images of science education teachers in the movies analyzed are positive except for some movies. Therefore, it needs to recognize the image of recreated science teachers in the movies and real science teachers, with critical perspective. Also, Hollywood should try to portray a more positive light on science teachers.
Announcing the SIGCSE test of time award

The SIGCSE Board is pleased to announce the creation of an ACM-approved SIG award, the SIGCSE Test of Time Award. This award will recognize an outstanding paper published in the SIGCSE community that has had meaningful impact on computing education practice and research. Unlike the Top Ten Symposium Papers award, this award will not be restricted to Technical Symposium papers; however, papers will need to have been published at least ten years prior to the award.
Alternative evaluation of the Poisson type distribution

It is shown that for a small sample size, when the maximum likelihood estimators lose its asymptotic properties, a more accurate point and interval estimation of the Poisson distribution parameter requires a direct investigation of the properties of the normalized likelihood function. Alternative p oint and interval estimates of the distribution parameter are obtained.
RANCANG BANGUN SISTEM INFORMASI ONLINE PENERIMAAN SISWA (STUDI KASUS SMP AL-YAUMA JAKARTA)

AbstractData processing new students at SMP AL-YAUMA Jakarta still dome conventionally, prospective applicants should come directly to the registration and fill the registration form and then the data registration was recorded on the books and preparing report also using conventional recap so frequent occurrence as well as the loss of archives time that is used to creat reports require a very long time. This research aims to solve these problems, by designing a new student admission information system based online so that prospective students do not have to come directly to the registration site and make it easier for officers to make reports. The research method that researchers use in this research is collecting reference sources with bibliography, interviews, and observation, and software development methodology with waterfall methodology. For testing the system used blackbox testing system. With this research is expected to help prospective new students and admissions officers new in facilitating the course of existing system.