Reviewerly/exHarmony huggingface dataset:
A Boost Strategy to the Generative Error Based Video Anomaly Detection Algorithms

Surveillance video anomaly detection is to detect events that rarely or never happened in a certain scene. The generation error (GE)-based methods exhibit excellent performance on this task. They firstly train a generative neural network (GNN) to generate normal samples, then judge the samples with large GEs as anomalies. Almost all the GE-based methods utilize frame-level GEs to detect anomalies. However, anomalies generally occur in local areas, the frame-level GE introduces GEs of normal areas to anomaly discriminations, that brings two problems: i) The GE of normal areas reduces the anomaly saliency of the anomalous frame. ii) Different videos have different normal-GE-levels, thus it is hard to set a uniform threshold for all videos to detect anomalies. To address these problems, we propose a promotion method: utilize the maximum of block-level GEs on the frame to detect anomaly. Firstly, we calculate the block-level GEs at each position on the frame. Then, we utilize the maximum of the block-level GEs on the frame to detect anomalies. Based on the existed GNN models, experiments are carried out on multiple datasets. The results demonstrate the effectiveness of the proposed method and achieve state-of-the-art performance.
PENGEMBANGAN PENGAYAAN MATERI BERBASIS E-LEARNINGDI SD MUHAMMADIYAH BLAWONG I

The research was conducted based on the fact in the field that there was a lack ofstudent interest in the material enrichment activities as well as a lack of learning mediaavailable at SD Muhammadiyah Blawong I. The research aims at developing materialenrichment media that can be used by student to develop their understanding in thematerials of animal movement organs. The research in Research and Development (RnD)with ADDIE (Analysis, Design, Development, Implementation, Evaluation) model. Thedata collection method used was a questionnaire, which was then analyzed by usingqualitative and quantitative data analysis. The results of the research indicated thatresearch and development were conducted with the ADDIE model. The average score of thematerial assessment from teachers in small group and large group trials was 85.Therefore, the average score of all assessment was 88.34, which was categorized as “VeryGood”.
Stability of the Decoupled Extended Kalman Filter in the LSTM-Based Online Learning

We investigate the convergence and stability properties of the decoupledextended Kalman filter learning algorithm (DEKF) within the long-short termmemory network (LSTM) based online learning framework. For this purpose, wemodel DEKF as a perturbed extended Kalman filter and derive sufficientconditions for its stability during the LSTM training. We show that if theperturbations -- introduced due to decoupling -- stay bounded, DEKF learns theLSTM parameters with similar convergence and stability properties of the globalextended Kalman filter learning algorithm. We verify our results with severalnumerical simulations and compare DEKF with other LSTM training methods. In oursimulations, we also observe that the well-known hyper-parameter selectionapproaches used for DEKF in the literature satisfy our conditions.
To Move or Not to Move: An Iterative Four-Phase Cloud Adoption Decision Model for IT Outsourcing Based On TCO

Information technology outsourcing (ITO) of organizations on cloud datacenter promises cost effectiveness over traditional on-premises deployment. In this regard, making sustainable decision toward cloud adoption needs profound understanding of cost implications, and social environmental issues. There are several concerns and challenges policymakers face when they encounter with IT options’ dilemma. Although the cloud migration has potentially merits account for reduction in total cost of ownership (TCO), there may exist demerits for especial situation of each industry and organization such as degree of uncertainty on privacy, security and communication delay concerns. This paper introduces an iterative four-phase cloud adoption decision model for IT outsourcing to solve industries’ and organizations’ concerns and challenges by considering cost implication of each contingent options and applying the net present value (NPV) of each alternative during the period of investment along with non-economic issues analysis. Also, the model leverages Moore law and Delphi panelists’ interview to estimate price of IT devices in future and to weight cloud adoption determinants and inhibitors respectively. The new services of Telecommunication Company of Mazandaran province (TCM) which is a large scale industry in IRAN are used as a case study to evaluate the effectiveness of proposed model for six years of investment. Implementation of the model for TCM shows that it is better to establish private datacenter on-premises and apply hybrid deployment in burst of resource demand.
English Language Proficiency And Its Challenges Among Students From Diploma Of Mechanical Engineering

21st century education (PA-21) aims to create integration between Malaysia’s multi races, ethnicities and building respect toward cultural, religion and racial differences. English language mastery among students in executing the 21st century education is very important so that they can communicate and collaborate with others. Despite that, English language usage among students is hard to reach its target due to psychological and attitude barrier. Through this research, it is hope to identify the challenges in English language usage among Diploma of Mechanical Engineering students and two factors were identified which are psycholinguistics and sociolinguistics. Psycholinguistic focuses on the study of attitude, personality and motivation towards the taught language while sociolinguistic focuses on the student’s family background towards their language learning and mastery. Questionnaire and observation are the methods used in gaining information from 72 students’ respondents. Research data is analysed descriptively using SPSS. The end results shows that both psycholinguistics and sociolinguistics factor is related to each other where mostly challenges comes from applied linguistics factor. Advices are given to the respective lecturers in facing the English language usage challenges and in order to raise their learning motivation so that they can stand to survive the 21st century education (PA-21) challenges.
Decision Making and Obstacle Avoidance for Soccer Robots

Robot-soccer game is characterized by a rapidly changing dynamic environment with moving obstacles. In this environment making a decision in a very short time, on-line adaptation and flexibility are very important parameters used in decision-making. Based on the decision made by a robot, the collision-free navigation of the mobile robot in this dynamic environment is also important. In the paper, the development of decision-making and navigation algorithms of a soccer robot are considered. Behavior-tree algorithm is presented and implemented for control of the mobile robots. At the same time, the type-2 fuzzy logic system is used for solving the obstacle avoidance problem. The use of the presented algorithm allows the decreasing of the path length of the robot. The efficiency of the presented algorithms has been tested with simulations and practical experiments. The obtained results demonstrate the suitability of using presented algorithms in the navigation of holonomic robots.
Nuevas formas de aprendizaje cooperativo en aula, favorecen la atención en estudiantes de institutos superiores

This descriptive study focuses on the student’s lack of attention during their learning process, whereby the key point is the student’s lack of motivation in the classroom. The five phases of the Design Thinking methodology and qualitative techniques such as interviewing and observation were applied. These tools were applied to students and teachers from two professional careers in two higher education institutes, with the aim of adapting our methodology towards new ways of classroom motivation, for them to build, from their own experience of the cooperative work of the students, their own knowledge with new forms of creative learning: the first, based on the visual stimulus that summarizes a lesson theme; the second, combining two stimuli: visual and auditory, illustrating the operational process of a learning theme. It is concluded that both proposals generate an interest to learn in the student, motivating his attention in the classroom.
Saliency Detection Based on Manifold Ranking and Refined Seed Labels

Graph-based manifold ranking has been exploited for saliency detection with seed labels. However, when the selected labels are not accurate, these methods can’t emphasize the foreground and suppress the background effectively. In this paper, we propose a novel saliency detection approach through manifold ranking and refined seed labels. We first construct a half-two layers graph based on the nodes after superpixel segmentation, which is generated by connecting each node to neighboring nodes and the half of the most similar nodes that share common boundaries with neighboring nodes. Then we compute superpixel saliency using manifold ranking with refined labels by two-step manner. After clustering superpixel with K-means, the background-based detection is obtained by refined background labels, which are those clusters containing boundary. The foreground-based detection is acquired with the refined foreground labels which are the complete cluster after thresholding the background-based detection. The proposed method has been tested on four universal datasets: ASD, CSSD, ECSSD and SOD. Experimental results show that our method performs better than prior similar state-of-the-art methods in various assessment indexes.
PROSES EVALUASI KOLEKSI YANG DILAKUKAN DI PERPUSTAKAAN SMA MUHAMMADIYAH 4 YOGYAKARTA

ABSTRACTThe purpose of this study was to determine the collection evaluation process carried out in the Senior High School of Muhammadiyah 4 Yogyakarta library with the benefits of research, that is as a matter of consideration in conducting evaluations in the development of collections carried out at the library so that the collections are in accordance with user needs. The research method used is the method of observation, interviews, and documentation. Based on observations, interviews, and documentation with librarian at Senior High School of Muhammadiyah 4 Yogyakarta, we can conclude the following results: Library evaluation in the Senior High School of Muhammadiyah 4 Yogyakarta includes 4 processes that is collecting all collections of data, check the list of standards such as catalogs and bibliographies, gathering opinions from users who normally come to the library, and direct collection checks.
Smoothed Aggregation for Nonsymmetric Linear Systems

Smoothed Aggregation (SA) is a technique from algebraic multigrid methods (AMG) whichhas shown very promising results when solving systems of linear equations with symmetricsystem matrices, but suboptimal results for nonsymmetric system matrices. The purposeof this thesis is to investigate the method EMIN(r) and a closely related method EMINproposed by Sala and Tuminaro. EMIN(r) and EMIN were built on the success of SA insymmetric systems, but perform better in nonsymmetric systems. These methods have amore costly set-up, but promising results were found, in particular when performing onetime-step of linear advection at extremely high CFL numbers.
CREATION OF SERIES OF PROPERTIES OF INDIVIDUAL SUNSPOTS

Data on sunspot area is important for studying solar activity and its long-term changes.In the Kislovodsk Mountain Astronomical Station, we are working on compiling several catalogs of sunspots: processing of photogeliographic data on photographic plates 1954 -2010 (KPD) (KPD), observational data in Kislovodsk on digital CCD (KPDD) 2010-2019, Kislovodsk data SDO/HMI (HMIKD) 2010-2019.We also compiled an additional catalog of sunspots from the digitized images of the Royal Greenwich Observatory for .By comparing these catalogs when they overlap in time, we can examine how various factors affect the measured area of sunspots.
BRAINSTORMING TECHNIQUE TO IMPROVE WRITING SKILL IN DESCRIPTIVE TEXTS OF VOCATIONAL HIGH SCHOOL STUDENTS

The article was based on a research that concerned in improving students’ skill in writing descriptive texts using Brainstorming Technique. The objectives were: 1) To find out whether the use of Brainstorming Technique can improved the writing skill in descriptive texts of tenth grade students of SMK Plus Bhakti Oetama Gondangrejo in the academic year of 2017/2018, and   2)   To   d e s c r i b e   t h e   c l a s s   c o n d i t i o n   w h e n   brainstorming  technique  were implemented in writing skill in descriptive texts of tenth grade students of SMK Plus Bhakti Oetama Gondangrejo in the academic year of 2017/2018. The researcher wa s  conducted in c l a s s  X  wh i c h  c o n s i s t e d  o f  3 0  f e ma l e  s t u d e n t s  from August to September 2017. This Classroom  Action  Research  (CAR)  consisted  of  2  cycles.  Each  cycle  consisted  of  two meetings in 80 minutes for each meeting. The data were collected through test and non-test. The tests consisted of pre-test and post-tests. While, non-tests consisted of observation, interview, field notes and documentation.  Furthermore,  the  researcher  used  qualitative  and quantitative   data analysis to analyze the data. The result of this research showed that Brainstorming Technique could improve the students’ skill  in writing descriptive  texts  at  the tenth  grade  students  especially  class  X  of  SMK Plus Bhakti Oetama Gondangrejo.  The improvement could be seen from the result of the test. The mean score of pre-test was 4.80, post-test 1 was 6.93, and post-test 2 was 7.68. Moreover, the result of t-test was 12.321 in cycle 1 and 3.425 in cycle 2. It meant that there was improvement in students’ skill in writing descriptive texts. K ey w o r d s : W r iting S kill; Descr i p tive Texts; B r a i n s t o r mi n g Tec hn i qu e ; C l a ssr oo m Acti o n Rese a r ch
An improvement model developed for Industry 4.0 : A case study

Purpose-The purpose of this research is to develop a future 4.0 improvement model, which improves work efficiently and effectively in a manufacturing company and in line with Industry 4.0. To achie ...
SELECTION OF COLLECTIONS (FICTION) IN AN EFFORT FOR THE DEVELOPMENT OF THE COLLECTION IN THE LIBRARY OF AL IZZAH LPMIINTERNATIONAL ISLAMIC BOARDING SCHOOL BATU CITY OF EAST JAVA

The purpose of this study was to describe the selection of the collections in the library Al Izzah LPMI Batu, East Java. With the benefit of providing research solutions to do the selection collection in the library Al Izzah LPMI Batu City in East Java in overcoming obstacles faced about the selection of the collection. The type of research used in this study is a qualitative research technique of observation and interviews.Based on observations and interviews direct to the Library Manager Al Izzah LPMI stone town, East Java can be summed up as follows. First, the selection process for the collection activities (fiction) does not do any procurement of collection. This selection process was conducted using three tools of seletion i.e. using Catalog for publishers, Indonesia’s national bibliography, and reviews books. Second, the obstacles faced in the activity of a selection of fiction in the library Al Izzah LPMI batu City, East Java, is the lack of human resources, the difficulty of finding fiction collection shades of Islam, and is still limited to the choice of the equipment used
kidslitclub We could organize a few impromptu ...

@kidslitclub We could organize a few impromptu remote sessions for people remoting into #ncte19. No need to spend $1,000s to learn with our peers. I
RETRACTED: Research on the Construction and Service Mode of Digital Library Based On Cloud Computing

Abstract Cloud computing is a data processing process based on the transmission capacity of the Internet, and it provides a certain development opportunity for the construction of digital library at the current stage through the information transformation between the relevant servers of the personal computer and the Internet computing cluster. In this paper, starting from the concept of cloud computing technology, and then discusses the problem of cloud computing technology in the library application, so as to promote the quality of cloud computing technology in the library application.
The Students’ Ability in Japanese Free-Writing (Sakubun)

Writing essays or stories is called sakubun in Japanese. When willing to convey an idea or ideas into essays, learners must master the language skills, such as Japanese characters (Hiragana, Katakana, Kanji), vocabulary, sentence patterns, auxiliary words (particles), and expressions. However, because of different structure between Indonesian and Japanese, Japanese non native learners face problems. The study tries to measure the ability of non-native learners to make essays in Japanese. There were nine respondents from the Japanese Literature Study Program at the Faculty of Cultural Sciences, University of Sumatra Utara (USU) and six respondents from the Japanese Language Study Program at the Faculty of Teacher Training and Education, University of Riau (UNRI). The respondents were university students who passed the international examination in Japanese Language Proficiency Test (JLPT) at / N3 level. The purpose of this study is to analyze the types of errors that are mostly found in the translation from Indonesian essays into Japanese, as well as to describe the factors underlying the occurrence of errors. The research used qualitative and quantitative methods and the percentage of errors is measured. Errors among students were caused by word choice, auxiliary verbs, particle words, sentence structure, and translation abilities. Translation errors by students from USU and UNRI were reaching 4.12% and 1.34% respectively. All this means that they were weak in vocabularies. The dominant factor causing errors is the errors transfer, that is, habits from first language are applied to the learning of foreign language which has different language systems.
Secure Sketch for All Noisy Sources.

Secure sketch produces public information of its input $w$ without revealing it, yet, allows the exact recovery of $w$ given another value $w'$ that is close to $w$. Therefore, it can be used to reliably reproduce any error-prone secret (i.e., biometrics) stored in secret storage. However, some sources have lower entropy compared to the error itself, formally called more error than entropy, a standard secure sketch cannot show its security promise perfectly to these kind of sources. This paper focuses on secure sketch. We propose a concrete construction for secure sketch. We show security to all noisy sources, including the trivial source with zero min-entropy. In addition, our construction comes with efficient recovery algorithm operates in polynomial time in the sketch size, which can tolerate high number of error rate arbitrary close to 1/2. Above result acts in conjunction to our derivation on the solution to two NP-complete coding problems, suggesting P=NP.
Challenging knowledge extraction to support the curation of documentary evidence in the humanities

The identification and cataloguing of documentary evidence from textual corpora is an important part of empirical research in the humanities. In this position paper, we ponder the applicability of knowledge extraction techniques to support the data acquisition process. Initially, we characterise the task by analysing the end-to-end process occurring in the data curation activity. After that, we examine general knowledge extraction tasks and discuss their relation to the problem at hand. Considering the case of the Listening Experience Database (LED), we perform an empirical analysis focusing on two roles: the 'listener' and the 'place'. The results show, among other things, how the entities are often mentioned many paragraphs away from the evidence text or are not in the source at all. We discuss the challenges emerged from the point of view of scientific knowledge acquisition.
CasNet: Cascaded Architecture for Visual Object Detection Working with Existing CNNs

Imbalanced samples composed of limited number of positive samples corresponding to objects and huge number of negative samples extracted from background regions reduces the accuracy of visual object detection. To solve this problem this paper proposes a novel convolutional neural network named “CasNet”. CasNet introduces cascade structure that is used for rapid and accurate object detector in order to reduce the number of negative samples inputted to a main network for object detection. The CasNet becomes a cascade stage when it is attached to a layer of existing convolutional neural networks to construct cascaded classifier. Each stage composed of a CasNet performs two-class classification to reject easy negatives corresponding to background regions. By this early rejection of easy negatives, a main network can be trained to classify more complex samples. Experimental results using a dataset created from the PASCAL VOC2012 dataset showed that higher accuracy was obtained at less training iterations if CasNets were attached to VGG16 appropriately.
IMPLEMENTASI ALGORITMA APRIORI TID UNTUK MENGETAHUI POLA PENJUALAN KERAMIK

At PT. JUI SHIN INDONESIA Medan Deli is checking the sales of ceramics once a year. The amount of ceramics needed at PT. JUI SHIN INDONESIA Medan Deli is so big. The lack of good sales interactions has resulted in ceramics sales and the quality of service to the council going down. This research expects to analyze the general operating picture, ceramic sales of PT. JUI SHIN INDONESIA Medan Deli. The problem often faced is that goods are not neatly arranged and cannot be utilized for system development and are only used as archives at PT. JUI SHIN INDONESIA Medan Deli. To find out the pattern of ceramics sales, ceramics sales have so far been ineffective because the data stored in Microsoft Excel is still not good so it requires a long time if at any time the warehouse of PT. JUI SHIN INDONESIA Medan Deli and other company administrations do data checking. For that we need a system that can facilitate the warehouse in analyzing the sales data of ceramics. This algorithm is one part of association rule mining. This method aims to obtain the rules of association or relations between groups of items. by using the Tanagra tool application method for testing data on ceramic sales transactions.Keywords: To Know the Pattern of Ceramic Sales Using the Aryri TID Algorithm
A Comprehensive and Practical Image Enhancement Method

Image enhancement is a challenging problem in the field of image processing, especially low-light color images enhancement.This paper proposed a robust and comprehensive enhancement method based several points.First, the idea of bright channel is introduced to estimate the illumination map which is used to attain the enhancing result with Retinex model, and the color constancy is keep as well.Second, in order eliminate the illumination offsets wrongly estimated, morphological closing operation is used to modify the initial estimating illumination.Furthermore, in order to avoid fabricating edges, enlarged noises and over-smoothed visual features appearing in enhancing result, a multi-scale closing operation is used.At last, in order to avoiding the haloes and artifacts presented in enhancing result caused by gradient information lost in previous step, guided filtering is introduced to deal with previous result with guided image is initial bright channel.The proposed method can get good illumination map, and attain very effective enhancing results, including dark area is enhanced with more visual features, color natural and constancy, avoiding artifacts and over-enhanced, and eliminating Incorrect light offsets.