Reviewerly/exHarmony huggingface dataset:
No-Reference Light Field Image Quality Assessment Based on Micro-Lens Image

Light field image quality assessment (LF-IQA) plays a significant role due to its guidance to Light Field (LF) contents acquisition, processing and application. The LF can be represented as 4-D signal, and its quality depends on both angular consistency and spatial quality. However, few existing LF-IQA methods concentrate on effects caused by angular inconsistency. Especially, no-reference methods lack effective utilization of 2-D angular information. In this paper, we focus on measuring the 2-D angular consistency for LF-IQA. The Micro-Lens Image (MLI) refers to the angular domain of the LF image, which can simultaneously record the angular information in both horizontal and vertical directions. Since the MLI contains 2-D angular information, we propose a No-Reference Light Field image Quality assessment model based on MLI (LF-QMLI). Specifically, we first utilize Global Entropy Distribution (GED) and Uniform Local Binary Pattern descriptor (ULBP) to extract features from the MLI, and then pool them together to measure angular consistency. In addition, the information entropy of Sub-Aperture Image (SAI) is adopted to measure spatial quality. Extensive experimental results show that LF-QMLI achieves the state-of-the-art performance.
Role of Fantasy in Intellectual Development of Children

This paper discusses the concept of fantasy. There is much in the word of fiction today so that the number of writers on imagination is increasing. After people have come to realize that romance is serving as much as a sea in the intellectual development of children, most of them have started to encourage their children to like more reading fantasy books. Some parents have even made it a great deal by deciding to build a small home library of fantasy books for children.The paper’s purpose is to discuss the role of fantasy literature in children’s intellectual development by including different forms of fantasy and its various advantages. The latter include creativity, entertainment, imagination and language skills improvement, the schematic knowledge, enjoyment, strategies applied for problem-solving, knowing the do’s and don’ts of the society, etc. Some Critics have made assertions on children’s ways of learning. This paper incorporates some of the claims and discusses them with some excerpts of illustrative stories related to fantasy.Enhanced by the fact that fantasy is the roadmap to the child thinking ability development, the paper will finally show why parents should motivate their children to get interested in fiction, which has a lot to do with children’s learning process.
Incentives for stable mining in pay per last N shares pools

A large number of blockchain consensus protocols use the Proof of Work (PoW) principle, which relies on miners who exchange computation for newly minted currency. Their task is to support consensus, safeguarding the immutability of the chain’s history. For the sake of regular income, a vast majority of miners team-up in large independent pools. These pools distribute among all their members the rewards gathered from individual miners, thus guaranteeing a stable income for each miner in the pool. The monetary compensation follows a specific reward system enforced by the pool administrator. Pay Per Last N Shares (PPLNS) is one of the most popular reward systems in PoW pools. Despite many desirable properties, in this paper, we show that composition of PPLNS pools may be unstable. To better understand the incentives of miners, we explore the effect of time preferences in the mining decisions of miners. Using a game-theoretical model we study conditions for equilibrium in a game with two different PPLNS pools. We find that the range of parameters that support equilibria between the pools with large number of miners is minuscule. This implies that in many cases, miners may have incentives to migrate towards larger pools, harming decentralization in the process.
Microseismic Data Reconstruction and Location Based on Bayesian Non-Parametric Dictionary Learning

Summary Microseismic data reconstruction is a procedure to compensate for acquisition deficiencies, and to improve data quality, which is very important for subsequent processing steps, such as event location. Some reconstruction algorithms depend on some parameter settings and ignore the strong noise interference, which may not work well for low quality surface microseismic data. In this paper, we propose to use a Bayesian non-parametric dictionary learning method to recover microseismic signal from the noisy data with missing traces. In the proposed method, the beta-Bernoulli process is employed as a prior for learning an appropriate dictionary to sparsely represent microseismic signals. An approximation to the full posterior is manifested via Gibbs sampling, yielding an ensemble of dictionary and sparse coefficients. Finally, the signal of interest is reconstructed by the product of dictionary and sparse coefficients. Tests on synthetic and real microseismic data demonstrate that the proposed method works very well for low signal-to-noise ratio data with missing traces. We also show how the proposed method benefits reverse time migration based event location.
Formal Methods and CyberSecurity

Formal methods have been largely thought of in the context of safety-critical systems, where they have achieved major acceptance. Tens of millions of people trust their lives every day to such systems, based on formal proofs rather than ``we haven't found a bug'' (yet!). Why is ``we haven't found a bug'' an acceptable basis for systems trusted with hundreds of millions of people's personal data? This paper looks at some of the issues in CyberSecurity, and the extent to which formal methods, ranging from ``fully verified'' to better tool support, could help. Alas The Royal Society (2016) only recommended formal methods in the limited context of ``safety critical applications'': we suggest this is too limited.
Example: InnoDB Cluster Setup and Administration

Now that we have learned more about what InnoDB Cluster is and the components that make up the feature, we’re almost to the point where we have enough information to begin working with a small, experimental InnoDB Cluster. There are just a few more things we need to learn including how to use the Admin API in the shell as well as become familiar with the steps required to set up not only InnoDB Cluster but also the MySQL Router.
Sistem Presensi Siswa Menggunakan Teknologi RFID SMK Bina Harapan Yogyakarta

Presence in educational institutions are schools, where the school is designed to teach students under the supervision of teachers. In the case of teacher supervision of students, of course the presences are very useful , teachers will not only supervise one or two students but many students. More specifically at SMK Bina Harapan, the presence tool to supervise students still using the manual way is to mention one by one from the name of students then put a sign on the paper containing a list of students. After that, the paper that contains a list of names that have been marked will be collected at the end of the semester by homeroom teacher. This is considered to be less effective, from such problems the presentation application is available to facilitate the teacher when presencing or when collecting student attendance in one semester or according to the desired date. Keywords : Design System, Presence System,RFID Technology.
한국어교육 문법 요소 선정 -접속법을 중심으로-

There are many debates on how to arrange grammatical items in Korean language education. However, these grammatical items are still determined based on the appearance frequency of Korean textbooks or the intuition of Korean teachers or Korean language education experts. The purpose of this study is to select the grammatical elements involved in the Korean conjunctive system based on systematic standards and arrange them appropriately according to the level. We first look at the realization of the conjunctive system that is realized in Korean and classify Korean conjunctive endings. And we selected the conjunctive ending point according to the grammatical item selection criterion. And array criterion is proposed to arrange the connection endings according to the learning level.
Pengukuran Tingkat Kematangan Layanan IT Dengan CMMI

The use of information technology in an organization's business processes does not guarantee that the organization has been able to provide good IT services. This service needs to be measured from the level of maturity. Capability Maturity Model Integration (CMMI) is a framework that can be used to measure the maturity level or intended maturity level. Accurate measurements certainly depend on a valid and reliable measuring instrument. The ITSM matrix is a measuring tool that has been internationally recognized in the ITSM and ITIL concepts. This research makes XYZ Higher Education the object of research. The basis of taking XYZ Higher Education is because these universities have used information technology in their business processes. However, problems are still found in the provision of IT services that have not met the expectations of IT Division and users. This can be seen from the percentage of reports on disruption that can be completed on time, only around 60% of the total reports submitted, and there is also a handling of reports of improper disturbances ranging from 19 - 29%. This is certainly a big concern that needs to be resolved by measuring the current level of IT services. After the measurement results using the ITSM matrix and guided by CMMI, it was found that the maturity level of the current IT service is still at level 1 (initial) where the??? service process runs ad-hoc and chaotic, and the success of the organization still comes from individual competence. This shows that XYZ universities, especially IT Division, need to improve IT services at a higher level in order to continue to improve IT services to users.
A Non-commutative Bilinear Model for Answering Path Queries in Knowledge Graphs

Bilinear diagonal models for knowledge graph embedding (KGE), such as DistMult and ComplEx, balance expressiveness and computational efficiency by representing relations as diagonal matrices. Although they perform well in predicting atomic relations, composite relations (relation paths) cannot be modeled naturally by the product of relation matrices, as the product of diagonal matrices is commutative and hence invariant with the order of relations. In this paper, we propose a new bilinear KGE model, called BlockHolE, based on block circulant matrices. In BlockHolE, relation matrices can be non-commutative, allowing composite relations to be modeled by matrix product. The model is parameterized in a way that covers a spectrum ranging from diagonal to full relation matrices. A fast computation technique is developed on the basis of the duality of the Fourier transform of circulant matrices.
SPSS Data Curation Primer

This work was created as part of the Data Curation Network “Specialized Data Curation” Workshop #1 co-located with the Digital Library Federation (DLF) Forum 2018 in Las Vegas, Nevada on October 17-18, 2018.
Education for Sustainable Development on the Subject of Arts based on Global Citizen Education

21세기 들어 국가 간 경계를 넘는 여러 문제들로 인해 지구촌의 갈등과 긴장이 커지고 있다. 이 문제들은 인류의 생존을 위협할 만큼 심각한 것으로 인식되고 있으며 국제사회에서 벌어지는 이러한 일들이 결코 나와 무관하지 않다는 깨달음이 필요해졌다. 이러한 위기의식에서 지속가능한 발전의 중요성이 부각 되었으며 장기적인 관점에서 인간의 사고와 행동을 근본적으로 변화시킬 수 있는 교육의 역할에 주목하게 되었다. 이 연구는 이러한 추세와 요구에 발맞춰 미술교육 안에서 세계시민교육과 연계한 지속가능발전교육 프로그램을 개발하고자 하였다. 중점 연구내용은 세계시민교육의 개념과 내용 요소, 세계시민교육 기반 미술과 지속가능발전교육의 방향, 액션러닝 교수·학습방법을 살펴보고 이를 바탕으로 세계시민교육에 기반한 미술교과 지속가능발전교육 프로그램을 개발하는 것이다. 이 연구를 통해 UN의 세계시민교육과 지속가능발전교육(ESD) 의제가 미술교과 안에서 어떻게 구체성을 띠며 교육으로 실현되는지를 보여주고자 하였다.Conflicts and tensions in the world have been expanded due to multiple problems beyond the borderlines between countries in the 21st century. These problems are perceived to be serious enough to threat the survival of the mankind and it is required to realize that these matters in the international society are related to me. Amid this crisis, the importance of sustainable development has been raised and the roles of education that can change men’s thinking and behaviors fundamentally as the long-term perspective have been highlighted. This study aimed to develop sustainable development education programs to be aligned with global citizenship education in the arts education to meet these trends and needs. Main research points are to review the concept and contents of global citizenship education, arts based on global citizenship education, direction of sustainable development education, teaching and learning method of action learning; and to develop sustainable development education programs based on global citizenship education. This study will show how global citizenship education in the UN and sustainable development education are materialized and realized in the subject of the arts.
Regression Under Human Assistance

Decisions are increasingly taken by both humans and machine learning models. However, machine learning models are currently trained for full automation -- they are not aware that some of the decisions may still be taken by humans. In this paper, we take a first step towards the development of machine learning models that are optimized to operate under different automation levels. More specifically, we first introduce the problem of ridge regression under human assistance and show that it is NP-hard. Then, we derive an alternative representation of the corresponding objective function as a difference of nondecreasing submodular functions. Building on this representation, we further show that the objective is nondecreasing and satisfies $\alpha$-submodularity, a recently introduced notion of approximate submodularity. These properties allow a simple and efficient greedy algorithm to enjoy approximation guarantees at solving the problem. Experiments on synthetic and real-world data from two important applications -- medical diagnosis and content moderation-demonstrate that our algorithm outsources to humans those samples in which the prediction error of the ridge regression model would have been the highest if it had to make a prediction, it outperforms several competitive baselines, and its performance is robust with respect to several design choices and hyperparameters used in the experiments.
EFEKTIVITAS PEMBELAJARAN MATEMATIKA REALISTIK DENGAN PERMAINAN GATRIK PADA MATERI OPERASI HITUNG CAMPURAN KELAS IV SD

ABSTRACTThis research has purposed to find out the effectiveness of realistic mathematics education with gatrik game on arithmatic operation mix material in elementary school grade IV at Public Elementary School Palang district Tuban. The result data analysis of implementation realistic mathematics education materials revealed to: (1) Teachers be able to teaching the materials nicely, (2) Students activities during learning process is effective, (3) Students responses during learning process are positive, and (4) classical Students completeness is achieved. Based on the result of this research, Researcher concluded that realistic mathematics learning using gatrik game is effective when applied on arithmatic operation mix in elementary school grade IV. Keywords: Realistic mathematic education and gatrik games ABSTRAK Penelitian ini bertujuan mengetahui keefektifan pembelajaran matematika realistik dengan permainan gatrik pada materi operasi hitung campuran di Kelas IV Sekolah Dasar Negeri Palang Kabupaten Tuban. Hasil analisis data implementasi perangkat pembelajaran terungkap bahwa: (1) guru dapat melaksanakan pembelajaran dengan baik, (2) aktivitas siswa selama pembelajaran efektif, (3) respon siswa terhadap pembelajaran positif, dan (4) ketuntasan belajar siswa secara klasikal tercapai.Berdasarkan hasil penelitian tersebut, peneliti menyimpulkan bahwa pembelajaran matematika realistik dengan permainan gatrik efektif digunakan pada materi operasi hitung campuran di kelas IV SD. Kata Kunci: pembelajaran matematika realistik dan permainan gatrik.
Homomorphic Encryption using E-Voting System

A manual voting system can be time consuming and cumbersome and takes a lot of time. With the rapid development of Information Technology an E voting system tends to overcome all these limitations. The E-Voting system guarantees eligibility, privacy, verifiability and also receipt-freelances, no vote selling and uncoercibility. Online voting would be more convenient, relatively secure and utilize fewer resources over the traditional voting system. E-Voting System using Paillier Homomorphic Encryption Scheme which is used to provide security to the voting system and in turn help us to manipulate and transfer data in encrypted form making it impenetrable while preserving its security characteristics.This could actually be a solution for the low voter turnout at the polls which occurs due to the reluctance of voters to show up at the polls as The online voting is more reliable than the traditional system
Overview of One-Pass and Discard-After-Learn Concepts for Classification and Clustering in Streaming Environment with Constraints

With the advancement of internet technology and sensor networks, tremendous amount of data have been generated beyond our imagination. These data contain valuable and possibly relevant information for various fields of applications. Learning these data online by using current neural learning techniques is not so simple due to many technical constraints including data overflow, uncontrollable learning epochs, arbitrary class drift, and dynamic imbalanced class ratio. Recently, we have been attempted to tackle this neural learning problem under the non-stationary environment. In this article, we summarize the new concept of One-Pass-Learning-and-Discard and also new structures, called Malleable Hyper-ellipsoid and Hyper-cylinder, of neural network recently introduced to cope with supervised as well as unsupervised learning under the constraints of data overflow, preserving polynomial time and space complexities of learning process, arbitrary class drift, life of data, and dynamic imbalanced class ratio. Both structures are rotatable, transposable, and expandable according to the distribution and location of data cluster.
Towards Flops-constrained Face Recognition

Large scale face recognition is challenging especially when the computational budget is limited. Given a \textit{flops} upper bound, the key is to find the optimal neural network architecture and optimization method. In this article, we briefly introduce the solutions of team 'trojans' for the ICCV19 - Lightweight Face Recognition Challenge~\cite{lfr}. The challenge requires each submission to be one single model with the computational budget no higher than 30 GFlops. We introduce a searched network architecture `Efficient PolyFace' based on the Flops constraint, a novel loss function `ArcNegFace', a novel frame aggregation method `QAN++', together with a bag of useful tricks in our implementation (augmentations, regular face, label smoothing, anchor finetuning, etc.). Our basic model, `Efficient PolyFace', takes 28.25 Gflops for the `deepglint-large' image-based track, and the `PolyFace+QAN++' solution takes 24.12 Gflops for the `iQiyi-large' video-based track. These two solutions achieve 94.198\% @ 1e-8 and 72.981\% @ 1e-4 in the two tracks respectively, which are the state-of-the-art results.
Crowd Counting on Images with Scale Variation and Isolated Clusters

Crowd counting is to estimate the number of objects (e.g., people or vehicles) in an image of unconstrained congested scenes. Designing a general crowd counting algorithm applicable to a wide range of crowd images is challenging, mainly due to the possibly large variation in object scales and the presence of many isolated small clusters. Previous approaches based on convolution operations with multi-branch architecture are effective for only some narrow bands of scales and have not captured the long-range contextual relationship due to isolated clustering. To address that, we propose SACANet, a novel scale-adaptive long-range context-aware network for crowd counting. SACANet consists of three major modules: the pyramid contextual module which extracts long-range contextual information and enlarges the receptive field, a scale-adaptive self-attention multi-branch module to attain high scale sensitivity and detection accuracy of isolated clusters, and a hierarchical fusion module to fuse multi-level self-attention features. With group normalization, SACANet achieves better optimality in the training process. We have conducted extensive experiments using the VisDrone2019 People dataset, the VisDrone2019 Vehicle dataset, and some other challenging benchmarks. As compared with the state-of-the-art methods, SACANet is shown to be effective, especially for extremely crowded conditions with diverse scales and scattered clusters, and achieves much lower MAE as compared with baselines.
A COMPARATIVE STUDY ON THE EFFECTS OF USING A ROLE PLAY AND A SMALL GROUP DISCUSSION TOWARDS THE SEVENTH GRADE STUDENTS’ SPEAKING ACHIEVEMENT AT SMP NEGERI 1 BANJAR

This study aimed at investigating if there was difference in speaking achievement between students who were taught using role play and those taught using small group discussion. This study used quasi-experimental research design with post-test only control group design. Samples of this study were VII H and VII G. VII H as experimental group and VII G as control group. The samples were taken by random sampling technique. The instrument for collecting data was performance speaking test. The data were analyzed using descriptive analysis and inferential analysis. Result showed that mean score of experimental group was 78.53, while mean score of control group was 73.12. Hypothesis testing showed that the value of sig. (2-tailed) was 0.001. Since the value of sig (0.001) &lt; 0.05, the value of tobserved exceeded the value of tcritical value. In conclusion, there was a difference in speaking achievement between the two methods.
A Study on the Development of North Korean Folk songs for Elementary School Textbook in Preparation for Korean Unification - Focused on integrated subject textbooks and music textbooks-

본 연구는 통일 대비를 위해 초등학교 통합교과 교과서와 음악교과서에 수록할 북한 민요 제재곡을 개발하고 교육 방안을 제시하는 것에 목적을 두었다. 이를 위해 현재 초등학교에서 사용하고 있는 음악교과서와 통합교과 교과서, 국립국악원 악보 자료 5권, &#65378;북녘 땅 우리소리 악보자료집&#65379;, &#65378;임석재 채록 한국구연민요자료집&#65379;에 수록되어 있는 북한 민요를 분석하였다. 이 중 총 10곡의 북한 민요를 선정한 후 교육적으로 활용할 수 있도록 편곡하였다. 그리고 악곡을 각 학년군의 수준에 맞게 배치하고 통일 교육 관련 활동을 타 교과 교육과정과 연계하여 제시하였다.This study aims to develop NK folk songs to be included in integrated subject textbooks and music textbooks of elementary school in preparation for unification and present an educational method. To that end, NK folk songs collected in music textbooks and integrated subject textbooks, which are currently used in elementary schools, were analyzed, along with five printed music books published by the National Music Institute and NK folk songs gathered in 「Music data book of NK folk songs」 and 「Korean folksong data book selected and put on record by Im Seok-jae」. Out of these songs, a total of 10 songs were selected and arranged for educational use. In addition, the NK folk songs was arranged according to the level of each grade group and the activities related to unification education were presented in conjunction with other curricula.