Reviewerly/exHarmony huggingface dataset:
Unsupervised Person Re-Identification via Multi-Order Cross-View Graph Adversarial Network

Unsupervised person re-identification (re-id) is an effective analysis for video surveillance in practice, which can train a pedestrian matching model without any annotations, and it is easy to deploy in unseen camera scenarios. The most challenging problem in unsupervised re-id task is the huge distribution-gap among different camera views, and the intrinsic correlations in unlabeled identities are also complicated to sufficiently explored. This paper proposes a Multi-order Cross-view Graph adversarial Network (MCGN) to bridge the cross-view distribution-gap, and mine the inherent discriminative information by multi-order triplet correlations. Specifically, MCGN firstly exploits graph representations by a cross-view graph convolutional network according to intra-view and inter-view graph structure, and then encodes each pedestrian image into a view-shared feature space, which is iteratively trained by a graph generative adversarial learning strategy to deeply bridge the distribution-gap. Finally, this paper proposes a multi-order discriminative learning module for composing reasonable triplet samples according to multi-order similarity correlations among unlabeled pedestrian images. Furthermore, sufficient experiments are conducted in two large scale person re-id datasets (Market-1501 and DukeMTMC-reID). The comparison to state-of-the-art methods and ablation study demonstrate the superiority of MCGN and the contribution of each module proposed in this paper.
Multi-scale Boxes Loss for Object Detection in Smart Energy

The rapid development of Internet of Things (IoT) technologies has boosted smart energy networks in recent years. However, power line surveillance systems still suffer from the low accuracy and efficiency of the power line area recognition and risk objects detection. This paper proposes a new customized loss function to tackle the disequilibrium of the size of objects on multi-scale feature maps in the deep learning-based detectors. To validate the new concept and improve the efficiency, we also presented a new object detection model. Experimental results are provided to exhibit the advantage of our proposed method in both accuracy and efficiency.
Multi-view Document Classification with Co-training

The purpose of the document classification is to assign the most proper label to a document. In real world data, insufficiency of labeled data is a major problem. In this study, a semi-supervised co-training algorithm, which enables classification on a small number of labeled data, is applied on multi-views obtained from 20 Newsgroup datasets. Four different multi-views are obtained using word embedding vectors. Logistic regression and random forest methods are used as the base classification methods. As a result of the experiments, co-training algorithm is found to be more successful than the base classifiers.
Perpustakaan Umum Berbasis Inklusi Sosial: Apa dan Bagaimana Penerapannya? (Sebuah Kajian Literatur)

If we look at the definition of a public library itself, namely a library that is used as a means of lifelong learning regardless of gender, physical condition, race, ethnicity, religion, social and economic status. That means the concept of social inclusion is very suitable to be implemented in the library. The latest public library paradigm is as a vehicle for people to develop their potential so that it leads to an increase in living standards. Regarding the concept of social inclusion, of course, it has a relationship with public libraries because they both talk about equality. Social inclusion means efforts to make society open to one another, especially to vulnerable or potentially marginalized communities, one of which is through community empowerment activities. This research is a qualitative study using the literature study method, namely collecting and analyzing the literature as a data source. To check the validity of the data, data source triangulation was carried out by looking for other data to strengthen the previous data. In this study, it was found that a public library based on social inclusion means a public library that always guarantees its facilities and services in order to encourage people to be open to one another. Several things that need to be considered in building a public library based on social inclusion, namely (1) the existence of community empowerment activities, and (2) the right to get library services, and (3) the accessibility of library information. Therefore it can be concluded that public libraries are closely related to the concept of social inclusion so that they can apply the concept. Of course, this can be seen from the public library itself which has the character of protecting all levels of society without a reed perspective.
Dynamic Genotype Reduction for Narrowing the Feature Selection Search Space

Large search space optimization problems can pose a challenge to any optimization approach, as there are many chances for the algorithm to become stuck in the local optima. In this paper, we present a novel dynamic representation of genotype, where the search areas with low potential are discarded from the search, and areas of the more significant potential for global optimum are kept in focus. The validity of the proposed method is tested on a large scale feature selection problem, using an extensive dataset with a large number of features compared to instances. An arrhythmia dataset was specifically chosen for a case study, and a self-adaptive differential evolution algorithm with the dynamic genotype reduction was implemented. The results of the experiments are promising for the future since the proposed method achieves better results than standard feature selection with stochastic population-based nature-inspired algorithms.
SCRIPTING CARTOGRAPHIC METHODS OF GMT FOR MAPPING THE NEW BRITAIN AND SAN CRISTOBAL TRENCHES, SOLOMON SEA, PAPUA NEW GUINEA

The study present a case study of the Generic Mapping Tools (GMT) applied for cartographic modelling, mapping and comparative analysis of the deep-sea trenches located in southwest Pacific Ocean: the New Britain Trench (NBT) and the San Cristobal Trench (SCT). The aim was to evaluate their geomorphic variation using scripting cartographic approach of GMT. The data was processed using a sequence of the GMT modules with the main module 'grdtrack' used to visualize cross-section profiles along the trenches for their geomorphological modelling. The main grid used for topographic mapping is the SRTM DEM with 15-arc second resolution. The statistical analysis shown variability in depths of both trenches by samples in two transects. The cartographic analysis demonstrated following results. The SCT is generally deeper reaching -9,000 m, while the median for the NBT less then 7,000 m. The gradient slope of SCT is more symmetric with accurate 'V' form. In a cross-section graph, the NBT landward slope is markedly asymmetric U-shaped form and has a crescent form in the east. The NBT slope dips westwards with 35° eastward, and 41° westward, while the SCT slope has 33° oceanwards and 33,69° landwards. The difference between the geomorphology of the trenches is explained by the effects of the geotectonic evolution and actual sedimentary processes affected their formation and sculptured their structure. The marine free-air gravity anomaly illustrated density anomalies at the bathymetry in the region of NBT and SCT with range &lt;-60.0 mGal. The geoid values are 56-66 mGal. The study contributed to the submarine geomorphic mapping and presents technical application of the cartographic functionality of GMT used for geomorphological modelling.
A Semantic Segmentation Based Approach for Segmentation and Recognition of Touching and Overlapping Digits

Text line segmentation is one of the most important stages in the Optical Character Recognition systems. In order to acquire a good recognition rate, text lines must be segmented in high accuracy. Accurate separation of characters that overlap and touch each other in handwriting documents increases the accuracy of segmentation and recognition. For this purpose, we propose a new approach to segment the touching or overlapping digits. Two systems are designed for segmentation of overlapping digits and digit recognition. Proposed method is implemented to synthetic images containing two digits touching or overlapping each other. As a result of this implementation, it is seen that overlapping and touching digits are segmented effectively with 99.31% segmentation accuracy. Considering these results, it has been shown that the proposed method can be used as an effective tool in document analysis since it can provide solutions to problems such as text line segmentation and character recognition.
The Effect of Augmented Reality Practices on 6th Grade Students’ Retention Skills in Science Teaching

The role of technology literacy in education, which is one of the 21st century skills that students should have, is very important. This study examines the effect of augmented reality (AR) applications, which is a new technology, on students' academic achievement and the level of recalling the learned knowledge. In this study, quasi-experimental design with pretest-posttest control group, one of the quantitative research methods, was used. The study was carried out with a total of 50 students, 24 in control and 26 in experimental groups, studying in the 6th grade of a secondary school in the Odunpazarı district of Eskisehir. The study lasted for 9 weeks, covering the Solar System and Eclipses unit and the Systems in Our Body unit of the 6th grade Science curriculum. During the process, the lessons instructed in the experimental group (EG) were supported by AR applications, whereas only the textbook was used in the control group (CG). The tools used in data collection were “the Solar System and the Systems in Our Body achievement test”, developed by the researcher and a semi-structured interview form for AR applications. Independent samples t-test, covariance analysis (ANCOVA) and descriptive analysis were used in the analysis of the data obtained from the achievement test. Content analysis was used in the analysis of the data obtained from the interview form. As a result of the research, it was observed that the use of AR applications in the processing of the course was effective in increasing the academic success of the students in the EG and in the permanence of the information they learned compared to the students in the CG, who only used the textbook. In addition the following findings were revealed: students have not used AR applications before, these applications were effective in increasing the academic success of the students, the knowledge that they have learned was permanent mostly because of the 3D feature of the technology, the applications worked smoothly and it may be useful to use them in other courses. Based on these results, it is suggested to use AR applications more frequently and actively in all topics of science and in all grade levels of secondary school.
State space classification of Markov password – an alphanumeric password authentication scheme for secure communication in cloud computing

Purpose Purpose of this study is to classify the states of Markov Chain for the implementation of Markov Password for effective security. Password confirmation is more often required in all authentication process, as the usage of computing facilities and electronic devices have developed hugely to access networks. Over the years with the increase in numerous Web developments and internet applications, each platform needs ID and password validation for individual users. Design/methodology/approach In the technological development of cloud computing, in recent times, it is facing security issues. Data theft, data security, denial of service, patch management, encryption management, key management, storage security and authentication are some of the issues and challenges in cloud computing. Validation in user login authentications is generally processed and executed by password. To authenticate universally, alphanumeric passwords are used. One of the promising proposed methodologies in this type of password authentication is Markov password. Markov passwords – a rule-based password formation are created or generated by using Markov chain. Representation of Markov password formation can be done by state space diagram or transition probability matrix. State space classification of Markov chain is one of the basic and significant properties. The objective of this paper is to classify the states of Markov chain to support the practice of this type of password in the direction of effective authentication for secure communication in cloud computing. Conversion of some sample obvious password into Markov password and comparative analysis on their strength is also presented in this paper. Analysis on strength of obvious password of length eight has shown range of 7%–9% although the converted Markov password has shown more than 82%. As an effective methodology, this password authentication can be implemented in cloud portal and password login validation process. Findings The objective of this paper is to classify the states of Markov chain to support the practice of this type of password in the direction of effective authentication for secure communication in cloud computing. Conversion of some sample obvious password into Markov password and comparative analysis on their strength is also presented in this paper. Originality/value Validation in user login authentications is generally processed and executed by password. To authenticate universally, alphanumeric passwords are used. One of the promising proposed methodologies in this type of password authentication is Markov password.
Analysis of IT Service Quality Elements Using Text Sentiment Analysis

In order to satisfy customers, it is important to identify the quality elements that affect customers’ satisfaction. The Kano model has been widely used in identifying multi-dimensional quality attributes in this purpose. However, the model suffers from various shortcomings and limitations, especially those related to survey practices such as the data amount, reply attitude and cost. In this research, a model based on the text sentiment analysis is proposed, which aims to substitute the survey-based data gathering process of Kano models with sentiment analysis. In this model, from the set of opinion text, quality elements for the research are extracted using the morpheme analysis. The opinions’ polarity attributes are evaluated using text sentiment analysis, and those polarity text items are transformed into equivalent Kano survey questions. Replies for the transformed survey questions are generated based on the total score of the original data. Then, the question-reply set is analyzed using both the original Kano evaluation method and the satisfaction index method. The proposed research model has been tested using a large amount of data of public IT service project evaluations. The result shows that it can replace the existing practice and it promises advantages in terms of quality and cost of data gathering. The authors hope that the proposed model of this research may serve as a new quality analysis model for a wide range of areas.
Current Trend and Methodologies of Content-Based Image Retrieval: Survey

CBIR (Content-Based Image Retrieval) is utilized for retrieval of various kinds of images from a huge database. In the database, the collection of information is available in various formats like chart, graph, image, text, etc. Here, information retrieval is our main focus which is available in the image form. Searching and retrieval of the image from a collection of database is a difficult problem because it utilizes the image visual information like color, text, and shape for indexing and representation of an image. In the previous years, several methods have been established for CBIR. The key goal of the paper is to provide an analysis of CBIR systems. This paper analyzes the current trend and methodologies of CBIR schemes. Moreover, this paper presented the CBIR system in the early years and at the end of the years. Extensive reviews including theory, design, principles, approaches, implementation, challenges, future directions, and performances of CBIR are done in this paper. A comparison between various CBIR systems has been performed. This survey systematically provides a technical direction to the researchers over the CBIR system and discusses the potential future aspects.
DIDACTIC CAPABILITIES OF USING GEOBOARD INTERNET SERVICE FOR STUDYING MATHEMATICS IN ELEMENTARY SCHOOL

The present article deals with the idea of information and communication technologies, game technologies and is about basic possibilities of using GEOBOARD Internet service for studying Mathematics in elementary school. The scientific approaches to the concept of information and communication technologies, game technologies are described and the potential possibilities of using the GEOBOARD Internet service in elementary education as an option of educational technologies, the influence of the GEOBOARD Internet service on the development of primary school students, advantages and directions of application are analyzed. The important aspect of using GEOBOARD Internet service is the ability to use it both from a personal computer and a Google Chrome web page. Also, users can download the app from the App Store to work with Apple products. The peculiarities of using GEOBOARD Internet service on mathematics lessons are systematization of material, strict logic, the interdisciplinary nature of the service, the learning process systematization, mastering the basics of spatial imagination, mathematical knowledge usage in solving educational, cognitive and educational and practical problems and depiction of geometric shapes. The use of the GEOBOARD Internet service in mathematics lessons promotes the complex development of elementary school children; the formation of a holistic picture of the world, knowledge of the world; the development of constructive skills, spatial relations and spatial thinking, vision of geometric figures, numbers, arithmetic, etc. Working with the GEOBOARD Internet service application allows an elementary school student to learn a lot of important information, prepares students for further study of the geometry course at school and develops their skills of being a socially active, creative person who generates new ideas and makes non-standard decisions. And it all happens in the form of a cognitive game. The GEOBOARD Internet service that is made by The Math Learning Center (MLC) has a wide range of functional and didactic capabilities and will fully meet the needs of elementary school teachers to cover many topics in mathematics lessons. The visualization allows elementary school students to summarize, systematize and discard redundant information just playing a game, so this is the way to improve the educational process. The service is important because it actively involves elementary school students in the process of learning geometric material.
Sentence Contextual Encoder with BERT and BiLSTM for Automatic Classification with Imbalanced Medication Tweets

This paper details the system description and approach used by our team for the SMM4H 2020 competition, Task 1. Task 1 targets the automatic classification of tweets that mention medication. We adapted the standard BERT pretrain-then-fine-tune approach to include an intermediate training stage with a biLSTM architecture neural network acting as a further fine-tuning stage. We were inspired by the effectiveness of within-task further pre-training and sentence encoders. We show that this approach works well for a highly imbalanced dataset. In this case, the positive class is only 0.2% of the entire dataset. Our model performed better in both F1 and precision scores compared to the mean score for all participants in the competition and had a competitive recall score.
ROS-based Motion Planner for Gazebo-Simulated Rescue Robots in RoboCup

One of the key accepts of the fourth industrial revolution (called industry 4.0) is the proper usage of mobile robots, for which using an efficient motion planning algorithm is of importance. Every year, universities and educational institutes from around the world present their accomplishments in robotics within the RoboCup competitions. One of the main purposes of the rescue robots competitions is to increase the awareness of robots during their missions. This paper presents an open-source motion planning algorithm, simulated in the robot operating system (ROS) platform. The proposed planner develops a semiautonomous algorithm for the rescue robots utilized in the RoboCup competitions. The Gazebo-simulated results validate the efficient performance of the presented algorithms.
The principles of equality and non-discrimination under viral attack: Stigma, hate speech, xenophobia, racism and discrimination during the COVID-19 pandemic

The principle of equality – the belief that all human beings are born free and equal – along with the correlated prohibition on discrimination are foundations of society. Equality is one of the most basic aspects of the Universal Declaration of Human Rights and a pillar on which the United Nations (UN) was founded in 1945. Yet, following the emergence of the coronavirus in December 2019, this long-established fundamental human right is being increasingly threatened. Indeed, as the UN Special Rapporteur on Minority Issues, Fernand de Varennes, observed, “COVID-19 is not just a health issue; it can also be a virus that exacerbates xenophobia, hate and exclusion.”
The methodology of using information technology and visualisations to optimize and improve management in the effectiveness of a student’s work in the laboratory

The United Nation has adopted the Sustainable Development Goals and goal No. 4 ‘Quality Education’ is one of them. Information and communication technology transforms education at different levels. For the successful collection, system analysis and processing of large amounts of heterogeneous data, special tools were developed (including specialized indicators), algorithms (including the processing of statistical information in fields of nonparametric information to detect the presence of correlations between various factors) and databases. An example of the use of such indicators is a system for testing the effectiveness of a student’s work in the laboratory. The initial assessment of the state of the laboratory was carried out using a sociological survey of persons associated with the organization of the educational process in the laboratory and subsequent data visualization. Which allowed us to determine that students and management perceive the state of the laboratory differently.
Determination of The Best Location Garden of Public Reading (TBM) in Surabaya Using the Method Analysis Overlay and AHP

The growth of organizations in the field of literacy is very good for the development of children's interest in reading and insight at an early age, especially in the city of Surabaya. Taman Bacaan Masyarakat (TBM) is an organization that has an important role to support and facilitate the community in seeking knowledge in the field of literacy in particular. The addition of TBM in Balai RW, Kelurahan, Kecamatan, and in the corners of community crowds is a tangible manifestation of the role of the Surabaya City Library and Archives Service as the authority that intersects directly in the field of literacy to facilitate the reach of the public in finding quality sources of information. However, several technical factors influence the selection of TBM addition locations that are still very objective. And the limited budget for the establishment of TBM also affects the number of TBM founding locations