Reviewerly/exHarmony huggingface dataset:
Fusing local and global features for texture image retrieval

The fusion of multiple complementary features can effectively improve the performance of texture image retrieval. In this paper, a new texture image retrieval method based on spatial domain and dual tree complex wavelet transform (DT CWT) domain is proposed. For obtaining the local features of texture images, the local binary pattern (LBP) histogram is calculated in the spatial domain, and the LBP histogram of the magnitude subband and the local tetra pattern (LTrP) histogram of the relative phase subband are respectively calculated in the transform domain. Then in the transform domain, the energy of the approximate subband is computed, and the gamma distribution model for the magnitude subband and the von Mises distribution model for the relative phase subband are carried out, and the obtained energy and the estimated model parameters are taken as the global features of texture images. Finally, the relative L1 distance is used as the similarity measurement for the local features, and the normalized Euclidean distance and the KullbackLeibler (K-L) distance with closed form are used as the similarity measurements for energy feature and distribution parameter features, respectively. Experimental results on VisTex and Brodatz databases show that, compared with the existing best methods, the proposed method achieves higher average retrieval rates with 90.72% and 84.12% respectively.
ANALISIS PENGUKURAN KUALITAS SISTEM INFORMASI AKADEMIK UNIVERSITAS JANABADRA DENGAN METODE PIESCES

Academic information system (AIS) is software used to present information and organize administration related to academic activities. Janabadra University's academic information system is a web-based system that was built with the aim of managing academic data. The research method used quantitative descriptive assessment with PIECES which was taken with the average value data on each aspect. In this study, there are 6 aspects, namely (a) performance aspects, (b) information aspects, (c) economic aspects, (d) control aspects, (e) efficiency aspects, (f) service aspects. In testing the satisfaction of academic information systems carried out through questionnaires, the results obtained from 75 respondents gave an average value for each statement reviewed on the performance aspect with an average of 3.11, on the information aspect with an average of 3.26, the economic aspect was obtained The average value is 2.65, the control aspect has an average value of 3.18, the efficiency aspect is 3.67 and the service aspect has an average value of 3.18. Based on the results of the average score of the test, the academic information system of the University of Janabadra is the most superior in the satisfaction test on the aspect of efficiency. Keywords  :  SIA,  Universitas Janabadra, PIECES
Application of Analytic Hierarchy Process in the Selection of Educational Supervisors

In this study, through literature review and analytic hierarchy process, expert questionnaires were conducted to explore the dimensions and criteria for selecting educational supervisors, four evaluation dimensions and 22 evaluation criteria were constructed, and the weight and ranking of each criterion item were determined by using hierarchical analysis. Through systematic and scientific professional knowledge, we can find out the key factors that affect the selection of educational supervisors: professional ability is the most important, followed by leadership and personality traits. Experience, team spirit and professional knowledge are the three most important criteria.
Survey on Applications of List Decoding to Cryptography

Since the conception of list decoding is proposed in the 1950s, list decoding not only is applied to communication and coding theory, but also plays a significant role in computational complexity and cryptography. In recent years, with the rapid development of quantum computing, the traditional cryptographic schemes based on factorization and other difficult problems are greatly threatened. The code-based cryptosystems, whose security relies on the NP-hard problems in coding theory, are attracting more and more attention as a candidate of the post-quantum cryptography, and so does the list decoding algorithm. This paper systematically reviews the applications of list decoding to cryptography, including early applications in proving that any one-way function has hard-core bits, designing traitor tracing schemes, designing public key schemes using polynomial reconstruction as cryptographic primitives, improving the traditional code-based cryptosystems and solving Discrete Logarithm Problems (DLP), and recent applications to designing secure communication interactive protocols, solving the elliptic curve discrete logarithm problem, and designs new cryptographic schemes based on error correction codes. Finally, the new research issues of the algorithm improvement of list decoding, its application to the design of cryptographic protocol and cryptoanalysis, and the exploration of new application scenarios are discussed.
Development of a Prototype System for Online Exhibition of the Archival Materials of Scientists: The Case of "Ryokichi Yatabe Digital Archives"

Presentation at the ５th Research Meeting of the Japan Society for Digital Archive. The presentation was originally planned at the 4th Research Meeting but postponed due to COVID-19.
Applied of Multivariate Multilevel Modeling for Student Cognitive Achievement Analysis in AKSI 2019 Survey

The Indonesian Student Competency Assessment (AKSI) is a national survey conducted by the Ministry of Education and Culture of the Republic of Indonesia which aims to monitor the quality of education. This survey measured students' cognitive abilities which included science, mathematics and reading literacy. Apart from that, this survey also collected a questionnaire of students to measure students' non cognitive abilities in ICT literacy. The sampling technique in the AKSI survey was conducted by multi-stage random sampling in which the first stage was randomly selected schools, then selected students sample in the selected schools. This article aims to identify the factors associated with students' ICT literacy on students cognitive achievement in the fields of science, mathematics and reading. AKSI has a hierarchical data structure with students are nested within school. In general, hierarchical data cause a violation of the assumption of independency of the residual between individual observations (students) and the homogeneity of variance between groups (school). The better statistical method for hierarchical data is multilevel modeling or hierarchical linear models. There are three correlated response variables in this study, so multivariate multilevel modeling is used. The results of this study conclude that the factors that affect the students cognitive achievement sorted according to their size are gender, perception index on the benefits of using ICT, accreditation, school ICT restriction index, father’s education, ICT usage index for other school activities, ICT usage index for school activities, digital device availability index and school digital device usage index. Apart from that, the results of the analysis concluded that there was an interaction effect between father's education and accreditation, meaning that the effect of parental education on students' cognitive achievement also depends on the school quality.
Prediction of a minimal inhibitory concentration of antibiotic using tensor flow on a Linux computer operating system using amd64 computer architecture.

Using Tensorflow to get the values of variables to flow more freely, a neural network uses gradient descent in the form of an optimizer. This recognises a pattern in the input and output data to make a prediction of y = mx + c = 0 on the gradient produced by this function.  A function can be defined as   ‘for a given input there is a given output’. The input is mg / ml of antibiotic and the output is % recovery. If values of the function are plotted on a graph, the gradient of this curve can be used to determine a value of x at y = 0. The sigmoid model was used in this example which takes into consideration non-linear, or chaotic behaviour of the data. I have produced three Python high-level computer programming scripts that implement the Tensorflow sigmoid model for a neural network using three different models for cost, or loss during the training of the network. The loss can be seen as a neural network having an given output for an input, and when the output does not match the input, an error or loss value is produced. If the output of an output neuron matches in the input of  an input neuron in a neural network the weight or activation of this neuron is increased to strengthen the connectivity of the neurons to facilitate the detection of a pattern. The three different models for loss used are maximum likelihood estimation (MLE), sigmoid cross entropy, and mean squared error (MSE). All three models gave a comparable result of -7.5mg / ml of antibiotic as a minimal inhibitory concentration of antibiotic. I have inferred that the value is negative because it depends on a previous dose of antibiotic of 7.5 mg. The conclusion I have made is that the therapeutic value of antibiotic depends on there previous use, possibly for a number of reasons such as a reservoir of bacteria or a persistent plasmid conferring plasmid mediated immunity.
Solar Shutters based on Photovoltaic Power Generation

This paper introduces a set of electrical energy-saving system for commercial office buildings, aiming at making better use of solar energy and photovoltaic power generation. Solar energy is a renewable energy source, which is inexhaustible clean energy and has great commercial application value. Based on this fact, we plan to design a unique and novel solar shutter in combination with the daily observation and the shape of solar panels. The shutter blades are equipped with an automatic light tracking system, and the angle of the blades can be adjusted in time through photoresistor induction, that is, as much solar energy as possible can be converted into electric energy for load use, and at the same time, comfortable light can be provided for the house. In essence, the system is a small photovoltaic power generation system, which runs all day with high-efficiency based on automatic sun tracking. Among them, the basic operation route includes: solar position detection, computer data processing, photovoltaic and electric volt energy conversion, circuit connection, etc. From the current debugging results, the shutter has the characteristics of humanization, high efficiency, cleanliness and so on. Through this energy-saving system, we hope to maximize the use of solar energy in the premise of low cost, so as to achieve the purpose of energy saving.
How Often Do Dictators Have Positive Economic Effects? Global Evidence, 1858-2010

Supposedly well-intentioned dictators are often cited as drivers of economic growth. We examine this claim in a panel of 133 countries from 1858 to 2010. Using annual data on economic growth, political regimes, and political leaders, we document a robust asymmetric pattern: growth-positive autocrats (autocrats whose countries experience larger-than-average growth) are found only as frequently as would be predicted by chance. In contrast, growth-negative autocrats are found significantly more frequently. Implementing regression discontinuity designs (RDD), we also examine local trends in the neighbourhood of the entry into power of growth-positive autocrats. We find that growth under supposedly growth-positive autocrats does not significantly differ from previous realizations of growth, suggesting that even the infrequent growth-positive autocrats largely ride the wave of previous success. On the other hand, our estimates reject the null hypothesis that growth-negative rulers have no effects. Taken together, our results cast serious doubt on the benevolent autocrat hypothesis.
Data Rescue at the U.S. National Agricultural Library: Case Studies of 3 Hybrid Collections

Data Rescue project is the product of research conducted under a Non-Assistance Cooperative Agreement #58-8260-6-003 between the University of Maryland and the United States Department of Agriculture (USDA), Agricultural Research Service (ARS), National Agricultural Library with funding provided by the USDA, ARS, Office of National Programs.
The Impact of Deceptive Advertising on Customer Loyalty: A Case of Telecommunication Industry in Karachi, Pakistan

This study examined the impact of Deceptive Advertising on Customer Loyalty in the telecommunication industry of Karachi, Pakistan. This research was quantitative in nature. The sample size was 250; questionnaires were distributed electronically and manually. Exploratory Factor Analysis (EFA) was used to analyze the data with the help of SPSS. Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) using AMOS, conducted to ensure the model and testing the hypothesis. The outcome of the present study verifies that word of mouth has a strong significant influence on customer loyalty. Hence customer satisfaction and customer trust are causing word of mouth in a positive and significant way. So it shows that there is a positive and strongly significant influence of customer satisfaction and trust on customer loyalty with the mediation of word of mouth. On the other hand, deceptive ads are causing word of mouth in a negative way. Hence it is concluded that deceptive ads have a negative influence on customer loyalty with the mediation of word of mouth. This study suggested that in order to increase customer loyalty and build a long-term relationship with the customer's telecom companies should focus on accurate information and rendering the level of competitive services to their customers.
ACO powered by Local Searches Algorithms for the Solution of TSP Problems

&#x0D; Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the social behaviors of insects and other animals. Ants, in particular, have inspired a number of methods and techniques among which the most studied and successful is the general-purpose optimization technique, also known as ant colony optimization, In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. Ant Colony Optimization (ACO) algorithm is used to arrive at the best solution for TSP. In this article, the researcher has introduced ways to use a great deluge algorithm with the ACO algorithm to increase the ability of the ACO in finding the best tour (optimal tour). Results are given for different TSP problems by using ACO with great deluge and other local search algorithms.&#x0D;
THE INFLUENCE OF SELF-DIRECTED DIALOGUE TO THE SECOND GRADE STUDENTS’ SPEAKING ABILITY

The purpose of this research was to investigate the effectiveness of using Self-directed Dialogue Technique in improving the second grade students’ speaking ability of SMP Negeri 2 Palasa. The quasi-experimental research design was used by involving experimental and control groups. The research samples were VIII A as the experimental group with 19 students and VIII B as the control group with 20 students selected by purposive sampling technique. In collecting the data, the researcher gave pre-test and post-test to both experimental and control groups. The treatment was given only to the experimental group. The data were analyzed statistically in order to find out the significant difference of students’ achievement in pre-test and post-test. The mean score of pre-test of the experimental group was 43.8 while the control group was 37.4. The mean score of the post-test of experimental group was 64.04 while the control group was 51.6. By using the 0.05 level of significance and 37 as the degree of freedom (df) = Nx + Ny – 2 = 20 + 19 – 2 = 37, the researcher computed the data and found that the value of the t-counted (2.73) was higher than the t-table (2.02). It means that the hypothesis is accepted. In other words, using self-directed dialogue technique can influence the students’ speaking skill at the second grade of SMP Negeri 2 Palasa. Keywords:Self-Directed Dialogue, Influence, Speaking Skill
Orthogonal Subspace Decomposition: A New Perspective of Learning Discriminative Features for Face Clustering

Face clustering is an important task, due to its wide applications in practice. Graph-based face clustering methods have recently made a great progress and achieved new state-of-the-art results. Learning discriminative node features is the key to further improve the performance of graph-based face clustering. To this end, we propose subspace learning as a new way to learn discriminative node features, which is implemented by a new orthogonal subspace decomposition (OSD) module. In graph-based face clustering, OSD leads to more discriminative node features, which better reflect the relationship between each pair of faces, thereby boosting the accuracy of face clustering. Extensive experiments show that OSD outperforms state-of-the-art results with a healthy margin.
NATURAL AND CULTURAL IN CINEMA BASED ON REAL EVENTS

The article examines the paradox of feature films based on historical events. Such a movie is forced to hide its subjectivity. The historical requires an artistic form, however, it acquires it only by deforming its content or distorting the positions of the creative subject inherent in staged cinema, since desubjectivized or pseudo-subjectivized forms of expression are attributed to it. The author of the article puts forward a hypothesis about the conditionality of this paradox by the very nature of cinema. Turning to the films based on real events, the author demonstrates the contradiction between natural and historical-cultural, which lies at the heart of cinema.
LibGuides: Information Literacy for Children: Middle School

This is a resource for teachers and librarians to find information on teaching Information Literacy to children.
The Integration of Learning Japanese Writing and Character Education of Students at Japan Language Department of Language and Art Faculty of Manado State University

This research describes the learning of Japanese writing that can improve the ability to write at once to develop students' character. Character formation and academic ability in a learning process are done simultaneously. Research data were taken from various sources through several data collection techniques that are observation, interview, and test. Data is processed manually with the guiding principle of qualitative and quantitative methodology. The research finds some of the following through quality assurance of data quality (triangulation) and its process in strict interpretation. Through activities in learning to write, students gain knowledge, direct experience in writing, and show the learning process characterized by the change of character included cooperation, responsibility, independence, confidence, and creative. Learning writing is used as a vehicle for the implementation of character education so that students can achieve good achievement and character.
Electronic Retrieval System Design for Outpatient Medical Record Filling at Puskesmas Lubuk Buaya Padang

Retrieval or what is known as a delay in returning medical record files is often the result of delays in patient care. The results of a survey conducted at the Lubuk Buaya puskesmas found that the implementation of retrieval was still not optimal and there was a lack of supervision at the manager level. The purpose of this study was to design an electronic retrieval system for medical record filling at Puskesmas Lubuk Buaya Padang. The research was conducted at Puskesmas Lubuk Buaya Padang using the Research and Development (R&D) method. Researchers interviewed 4 people consisting of 1 head of medical records and 3 medical record officers to get an overview of the problems in the retrieval process manually and to test the retrieval application. The results of the study obtained a design with development using the Unified Modeling Language (UML), namely the Use Case, Activity Diagram, Class Diagram, Sequence Diagram which ultimately produces an electronic retrieval application. Researchers find that the lack of supervision of the process of returning medical records and SOPs is running fully so it is increasingly necessary to apply electronic retrieval. The electronic retrieval application has been designed and tested. Positive responses from officers where this application can be easily operationalized so that problems in delays in returning medical record files can be minimized. The application is expected to be used in other health centers with feasibility trials at each puskesmas.
CLUSTERING MODEL OF LECTURERS PERFORMA IN PUBLICATION USING K-MEANS FOR DECISION SUPPORT DATA

This study aims to produce a clustering model using the K-Means algorithm built to map the performance of lecturers' publications. The method used was research and development which includes the stages of data collecting, data preprocessing, clustering process and cluster analysis. The input data consists of 87 with 8 attributes, namely number of articles in Sinta indexed journal, number of articles in Scopus indexed journal, number of citation in Scopus, H-index in Scopus, number articles in Google Scholar indexed journal, number of citation in Googe Scholar, H-index in Google Scholar and H-index10 in Google Scholar. The K-Means algorithm was used with 3 clusters and 100 epoches. The results of clustering were distributed in 3 clusters, namely cluster 1 with 17 members, cluster 2 with 32 members and cluster 3 with 38 members. The results of the cluster analysis with the identification of cluster members and the value of the cluster centroid indicated that cluster 1 is lecturers with relatively high publication performance performance and cluster 3 shows relatively low publication performance performance. The data from clustering results can be used for decision support model input data for broader lecturer performance performance.
Fixing Democracy: The Election Security Crisis and Solutions for Mending It (Fall 2020)

The 2000 presidential election debacle in Florida led to the widespread adoption of electronic voting machines in the United States. Yet these machines have proven to be more problematic than the punch card machines that precipitated Florida's crisis. Poorly built and poorly secured electronic voting machines have left U.S. elections vulnerable to software glitches and manipulation — by foreign adversaries or by malicious insiders — for 20 years. An easy solution exists to help restore integrity to the democratic process. But federal lawmakers have failed to act.
Media Words Card to Improve Reading Skills at the beginning of the First Grade Students in Primary School

This study aims to find the use of word cards to improve reading skills at the beginning by using the action class room method. Based on the results of research conducted in 2 cycles. In cycle I showed that through the Use of Word Card Media in Beginning Reading the average value of student learning outcomes obtained was 68.84 and mastery learning reached 53.85% or there were 14 students out of 27 students who had finished learning. These results indicate that in the first cycle the criteria for student learning are not yet completed, because students who score&gt; 65 are only 68.84% smaller than the desired completeness percentage of 85%, and (2) Furthermore, the results of the study cycle II shows through the Use of Word Card Media in Reading the Beginning obtained the average value of student learning outcomes is 76.92 and mastery learning reaches 88.46% or there are 23 students out of 26 students have finished learning. These results indicate that in the second cycle classically students have finished learning, because students who score&gt; 65 are 92.30% greater than the desired completeness percentage of 85%.