Reviewerly/exHarmony huggingface dataset:
HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions

MobileNets, a class of top-performing convolutional neural network architectures in terms of accuracy and efficiency trade-off, are increasingly used in many resourceaware vision applications. In this paper, we present Harmonious Bottleneck on two Orthogonal dimensions (HBO), a novel architecture unit, specially tailored to boost the accuracy of extremely lightweight MobileNets at the level of less than 40 MFLOPs. Unlike existing bottleneck designs that mainly focus on exploring the interdependencies among the channels of either groupwise or depthwise convolutional features, our HBO improves bottleneck representation while maintaining similar complexity via jointly encoding the feature interdependencies across both spatial and channel dimensions. It has two reciprocal components, namely spatial contraction-expansion and channel expansion-contraction, nested in a bilaterally symmetric structure. The combination of two interdependent transformations performing on orthogonal dimensions of feature maps enhances the representation and generalization ability of our proposed module, guaranteeing compelling performance with limited computational resource and power. By replacing the original bottlenecks in MobileNetV2 backbone with HBO modules, we construct HBONets which are evaluated on ImageNet classification, PASCAL VOC object detection and Market-1501 person re-identification. Extensive experiments show that with the severe constraint of computational budget our models outperform MobileNetV2 counterparts by remarkable margins of at most 6.6%, 6.3% and 5.0% on the above benchmarks respectively. Code and pretrained models are available at https://github.com/d-li14/HBONet.
Douglas-Quaid -- Open Source Image Matching Library

Security analysts need to classify, search and correlate numerous images. Automatic classification tools improve the efficiency of such tasks. However, no open-source and turnkey library was found able to reach this goal. The present paper introduces an Open-Source modular library for the specific cases of visual correlation and Image Matching named Douglas-Quaid. The design of the library, chosen tradeoffs, encountered challenges, envisioned solutions as well as quality and speed results are presented in this paper. We also explore researches directions and future potential developments of the library. Our claim is that even partial automation of screenshots classification would reduce the burden on security teams and that Douglas-Quaid is a step forward in this direction.
Fast Cartesian Tree Matching

Cartesian tree matching is the problem of finding all substrings of a given text which have the same Cartesian trees as that of a given pattern. So far there is one linear-time solution for Cartesian tree matching, which is based on the KMP algorithm. We improve the running time of the previous solution by introducing new representations. We present the framework of a binary filtration method and an efficient verification technique for Cartesian tree matching. Any exact string matching algorithm can be used as a filtration for Cartesian tree matching on our framework. We also present a SIMD solution for Cartesian tree matching suitable for short patterns. By experiments we show that known string matching algorithms combined on our framework of binary filtration and efficient verification produce algorithms of good performances for Cartesian tree matching.
A low-complexity algorithm for shortest Dubins paths with intermediate via points

In this paper we propose a low-complexity algorithm for the selection of the shortest path for a Dubins' vehicle passing through an intermediate point without a prescribed direction based on a novel approach. This problem has been studied in the last years, the solution proposed in this paper is constructive and it leads to a fast and low-complexity algorithm that can be easily implemented for on-line applications. Some examples and simulation results are reported to put in evidence the effectiveness of the solution proposed.
THE IMPACT OF ANIMATION MEDIA ON THE CHARACTER OF CHILDREN IN TK STARLIGHT EDUCATION

This study reports research findings on the use of animated media in a application using in TK Starlight Education which meant to evaluate their effectiveness in supporting teaching and learning for young learners in TK Starlight Education. The researchers have developed a animated picture where designed from scratch using appropriate programs. The study was done in TK Starlight Education, and 15 students aged 4–5 years old participated in it. The research results provide evidence that the use of animated media significantly increases the young students’ knowledge and influenced their characteristic in social life, which are normally difficult to comprehend and often cause misconceptions to them and also they can used the new words.
2015개정교육과정 『고등학교 일본어 1 』교과서의 말하기 활동 고찰

The present study analyzes eight high school textbooks for “Japanese I” based on 2015 Revised Curriculum in order to classify speaking activities in...
Committee Draft of JPEG XL Image Coding System

JPEG XL is a practical approach focused on scalable web distribution and efficient compression of high-quality images. It provides various benefits compared to existing image formats: 60% size reduction at equivalent subjective quality; fast, parallelizable decoding and encoding configurations; features such as progressive, lossless, animation, and reversible transcoding of existing JPEG with 22% size reduction; support for high-quality applications including wide gamut, higher resolution/bit depth/dynamic range, and visually lossless coding. The JPEG XL architecture is traditional block-transform coding with upgrades to each component.
USE OF THINK PAIR SHARE MODELS ON LEARNING TO EDIT SHORT STORY TEXTS

Learning to edit short story texts is one of the lessons that are difficult for students to master. This is evident when observing the school that students feel difficulty in applying the text according to the grammar in a writing. The purpose of this study is 1) To describe the activities carried out by teachers and students when learning to edit short story texts using the think pair share model. 2) To find out the difference between the results of the initial test and the final test of learning to edit the short story text before and after using the think pair share model. 3) To describe students' responses to learning to edit short story texts using the think pair share model. The researcher used the pre-experimental design method, while the design of this study was one group pretest-posttest design. The population and sample of the study were conducted in one class, namely class XI with samples of class XI AP 2, amounting to 30 people. The results of teacher activity data on learning to edit short story texts using the think pair share model is 92% while student activities are 95%. This shows that the activities of teachers and students run effectively. While the results of the data obtained that there is an increase in the value of students before using the think pair share model on the initial test get an average value of 50 and experience an increase after using the think pair share model on the final test with an average value of 78. There is a difference in the average value students between pretest and posttest is 28. Based on the results of the t-test, the sig value is obtained 0,000, the value is â‰¤ 0.05. Thus, H1 is accepted and Ho is rejected. Then it can be concluded that learning to edit short story texts using the think pair share model increases students' ability to edit short story texts.
Automatisierte Erkennung von Fehlern bei der Wartung von IT-Services

Wartungsfehler sind einer der haufigsten Grunde fur IT-Service-Ausfalle und konnen bei IT-Service-Anbietern Schaden in Millionenhohe verursachen. In diesem Buch wird eine Methode vorgestellt, die es IT-Service-Anbietern ermoglicht, Wartungsfehler automatisiert wahrend der Durchfuhrung einer IT-Service-Wartung zu erkennen. Dadurch konnen Wartungsfehler behoben werden, bevor sie Schaden anrichten konnen. IT services are subject of several maintenance operations like upgrades, reconfigurations or redeployments. Operator errors are one of the main reasons for IT service failures. They can lead to losses running into the millions for IT service providers. This book describes a method, which allows IT service providers to detect operator errors automatically online right when they appear. Thereby, operator errors can be fixed before they can do harm. Umfang: XV, 225 S. Preis: €47.00 | £43.00 | $83.00
A Software to Detect OCC Emotion, Big-Five Personality and Hofstede Cultural Dimensions of Pedestrians from Video Sequences

This paper presents a video analysis application to detect personality, emotion and cultural aspects from pedestrians in video sequences, along with a visualizer of features. The proposed model considers a series of characteristics of the pedestrians and the crowd, such as number and size of groups, distances, speeds, among others, and performs the mapping of these characteristics in personalities, emotions and cultural aspects, considering the Cultural Dimensions of Hofstede (HCD), the Big-Five Personality Model (OCEAN) and the OCC Emotional Model. The main hypothesis is that there is a relationship between so-called intrinsic human variables (such as emotion) and the way people behave in space and time. The software was tested in a set of videos from different countries and results seem promising in order to identify these three different levels of psychological traits in the filmed sequences. In addition, the data of the people present in the videos can be seen in a crowd viewer.
Emotional Intelligence Features Of Students With Different Levels Of Emotional Burnout

Our main objective was to determine the possibility of using emotional intelligence as a potential resource in overcoming emotional burnout among students. The article confirms the assumption about the existence of correlation and casual interconnection between emotional burnout and emotional intelligence. It has been empirically proved that emotional burnout (p≤0.05) and depersonalization (p≤0.01) have a stronger effect on emotional intelligence; and it’s the level of emotional intelligence that determines emotional exhaustion (p≤0.01) and reduction of personality achievements (p≤0.05). Persons’ ability to understand their own emotions (p≤0.01), intrapersonal emotional intelligence (p≤0.01), emotional control (p≤0.05) effect emotional burnout, which in its turn is influencing expression control (p≤0.01). In particular, students with a high level of burnout are characterized by worse level of understanding their own emotions (p=0.003), while it’s a more situational relation in cases with students with average burnout. The relation between the ability to manage one’s own and others’ emotions in this group is weaker (p=0.006) than in a sample of students with a low level of emotional burnout; as well as their relation between intrapersonal emotional intelligence (p=0.006) and control of expression (р=0.044), compared to students with average and low levels of burnout.The obtained data contribute to the study of the burnout phenomenon and provide an opportunity to determine further directions of its prevention and correction in students by means of emotional intelligence development.
Finding Erroneous Components from Change Coupled Relations at Fix-inducing Changes

During the gradual process of software evolution, errors appear in different components of a software system.These errors are later on fixed by developers as part of corrective maintenance activities.However, if errors appear continuously from a particular component, that may indicate design flaws or code smells.Maintenance cost will greatly reduce if design flaws are treated as early as possible.To find out such flaws it may require time-consuming manual inspections.This paper tries to find out such components using the information of change coupled cluster of files or Java classes at fix-inducing changes.In this proposed approach, information (like class, method, parameter of method and variable names) from change coupled relation of a class at Fix-Inducing Changes (FICs) are used to provide information about erroneous components.Then the error history, of software components, is found by using cosine similarity of information from change coupled cluster of classes found in FICs to see with the architectural information found from authenticated sources.Finally, the error history of components is shown as the percentage of change coupled cluster of a class found in FICs of each 100 commits in the version control system.
Implementasi Sistem Informasi Geografis dalam Penentuan Indeks Kesesuaian Lahan Tanaman Padi di Kota Kupang Menggunakan Metode Skoring

Geographic Information System (GIS) is a special information system for managing data that has spatial information. In GIS is often used overlay techniques in merging 2 or more maps in to a unit ofland. In this research, the authors use the scoring method in determining the land suitability index. To get a unit of land done overlay on land type map, slope map, district boundary map, geological map and land cover or land use map. Scoring is done on temperature parameters, rainfall, dry moon, drainage, texture, effective depth, KTK, ground ph, n total, P2O5, K2O, slope, numbers of rock, and rock out crop. The calculationis done by scoring for each parameter based on the predetermined score class, the total of each unit of land will be used to determine the Land Suitability Index based on the classification class. The calculation result is done on 76 land (rice field and rainfed rice field). This test use Simple Linear Regression to find the closeness value between Land Suitability Index and rice produktivity. Linear correlation coeficient (r) obtained value r = 0,77 (positive correlation). The value of this correlation coefficient indicates the degree of closeness of the relationship between the Land Suitability Index and the productivity of the paddy. The value of coefficient of determination R = 0,59 = 59% indicates that 59% of the proposed variation of Y variable (paddy productivity) can be explained by X variable (Land Suitability Index) through linear relationship.
STRATEGI GURU PENDIDIKAN AGAMA ISLAM DAN BUDI PEKERTI DALAM MENGATASI KESULITAN MEMBACA DAN MENULIS ALQURAN PADA SISWA KELAS VII DI SMP NEGERI 14 KOTA BOGOR TAHUN AJARAN 2018/2019

This reseacrh is motivated by the difficulty of reading and writing the Alquran experienced in VII grade students in the Academic Year 2018/2019 at SMPN 14 Kota Bogor. The difficulty of reading and writing the Alquran is a condition where students are unable to follow the study properly. In writing this research the author uses: The methode used is qualitative method. Research location of SMPN 14 Kota Bogor. data collection uses interviews, obsevations, and dokumentations to Islamic Education and Character Educations teachers and VII grade students. Data analysis techniques consist of data presentations, data reduction and conclusion drawing. The results of the study: (1) Teachers of Islamic Education and Characteristics in overcoming the difficulty of reading the Alquran is by using the Talqin and Drill method where the teacher exemplifies the reading in the form of verse fragments in the Alquran then students are asked to follow them until they really can. To write, the teacher uses the Imla' method, and the teacher also gives writing in the form of Qur'anic verse pieces on the board and asks students to copy them in their individual notebooks. (2) Factors that hinder the teachers of Islamic Education and Characteristics in overcoming the difficulties of reading and writing the Alquran are still lack of expert teachers in the field of reading and writing the Alquran in the 14th Public High School of Bogor City. There are also students who are not confident about their abilities because these students have not read fluently and written the Alquran. (3) The factors that support the Islamic Education and Pekerti teachers in overcoming the difficulties of reading and writing the Alquran are the seventh grade students in SMP Negeri 14 Kota Bogor have a strong motivation in learning to read and write the Alquran and the parents of the students motivate their children in order to always study the Alquran. (4) Implementation carried out by Islamic Education and Character Education teachers in learning to read and write the Alquran is to ask students to read or follow the reading in the form of verse fragments that have been exemplified by the teacher one by one.
LibGuides: Services for Faculty: ARKLink

The Dean B. Ellis Library is happy to offer A-State faculty a variety of services. The ARKLink card allows A-State students and faculty the privilege of borrowing library materials from other colleges and universities in Arkansas.
Algorithm Selection for Image Quality Assessment

Subjective perceptual image quality can be assessed in lab studies by human observers. Objective image quality assessment (IQA) refers to algorithms for estimation of the mean subjective quality ratings. Many such methods have been proposed, both for blind IQA in which no original reference image is available as well as for the full-reference case. We compared 8 state-of-the-art algorithms for blind IQA and showed that an oracle, able to predict the best performing method for any given input image, yields a hybrid method that could outperform even the best single existing method by a large margin. In this contribution we address the research question whether established methods to learn such an oracle can improve blind IQA. We applied AutoFolio, a state-of-the-art system that trains an algorithm selector to choose a well-performing algorithm for a given instance. We also trained deep neural networks to predict the best method. Our results did not give a positive answer, algorithm selection did not yield a significant improvement over the single best method. Looking into the results in depth, we observed that the noise in images may have played a role in why our trained classifiers could not predict the oracle. This motivates the consideration of noisiness in IQA methods, a property that has so far not been observed and that opens up several interesting new research questions and applications.
A novel boot strapping algorithm for text extraction in a self-organising neural network model

With rapid growth in internet and its associated communication protocols, need for printed documents to be carried over from one place to another has been reduced to minimise the cost and time. Research contributions in the past have paved the way for implementation of smart and intelligent algorithms to further minimise manual intervention in processing of documents. One such area is the automation of text extraction from documents with increased accuracy and least number of false detections. A wide range of algorithms and methodologies have been reported in the past towards efficient extraction of text from documents which may be online or offline. This research paper proposes an efficient extraction algorithm of text from given set of documents which may or may not be graphic through utilisation of a hybrid SOM-ANN algorithm. The experimentation has been done over a wide variety of inputs and convergence of error in extraction is found to be minimum when compared to other conventional extractors.
A Blockchain Approach to Support Digital Contracts

Distributing computing that work with policies that flirt with democracy, in which parties can interact without an intermediary, has gained strength. In this way, an attractive idea is to support digital contracts by removing the third party and allowing the group to create and store contracts in a reliable and secure way, where contracts are immutable and easily retrievable. We propose a Blockchain approach to aid the management of digital contracts. The proposal considers contract encryption, digital signature, and protocols for chaining blocks with data related to digital contracts. We develop a prototype to ensure the viability of our proposal. We also present a case of use to demonstrate the prototype usage. We argue that proposal and implementation together create an appropriate environment for research and education purposes.
Interval Type-2 Fuzzy Decision Making Based on TOPSIS

Which is based on the idea that the best alternative should have the shortest distance from a positive ideal solution and the farthest distance from a negative ideal solution. In traditional TOPSIS method, the weights of the criteria and the ratings of alternatives are defined as crisp numbers. Fuzzy number.
Hamming Sentence Embeddings for Information Retrieval

In retrieval applications, binary hashes are known to offer significant improvements in terms of both memory and speed. We investigate the compression of sentence embeddings using a neural encoder-decoder architecture, which is trained by minimizing reconstruction error. Instead of employing the original real-valued embeddings, we use latent representations in Hamming space produced by the encoder for similarity calculations. In quantitative experiments on several benchmarks for semantic similarity tasks, we show that our compressed hamming embeddings yield a comparable performance to uncompressed embeddings (Sent2Vec, InferSent, Glove-BoW), at compression ratios of up to 256:1. We further demonstrate that our model strongly decorrelates input features, and that the compressor generalizes well when pre-trained on Wikipedia sentences. We publish the source code on Github and all experimental results.
Relationships Between Teachers’ Characteristics, Job Characteristics And Work Engagement: A Pilot Study

The quality of the educational act is ensured by the teacher’s professional efficacy. The numerous demands the teacher has to face (high job demands, lack of job resources, competitiveness, learning to manage behaviour in the classroom, becoming aware about district policies and job expectations, and translating theory into practice, etc) have as direct effects either stress and burnout or engagement and involvement in the professional activity. The specialty studies assert the idea that a high level of work engagement has positive effects not only upon the level of professional performances and teachers’ life quality but also upon the level of pupils’ acquisitions and performances. Work engagement represents a multidimensional construct and is defined as a fulfilling state of mind in employees that is characterized by vigor, dedication, and absorption. The present study proposes to analyze the factors which contribute to work engagement – personal factors (self- efficacy) and factors related to job characteristics (job resources and job demands), as well as the relation established between them through different stages of the didactic career. The practical implications of the study target interventional modalities meant to increase the level of engagement in professional activity through the improvement of work tasks palpability in accordance with professional competences specific to the development level in teachers’ professional career.
Secure: An Effective Smartphone Safety Solution

With rapid advancements in smartphone and wearable technologies in the past decade, the world has virtually become a smaller place, facilitating connectivity between opposite ends of the globe just by the click of a button. However, certain emergency situations might not provide the opportunity or the window for that click as well. Hence, the need for a semi-automatically triggered distress signal activationKalita, Sampreet scheme arises. In this paper, we introduce such a smartphone-based solution for all-round personal security that takes into account multiple modes of SOS broadcast activation, such as manual, Internet of Things (IoT) device data based and phone state dataBhattacharyya, Dhruba Kumar based. Also, we develop a couple of wearable device prototypes and test them for realtime detection and activation of SOS broadcast using a smartphone application.