Reviewerly/exHarmony huggingface dataset:
Advanced resource allocation and Service level monitoring for container orchestration platform

Containerization becomes the first choice for faster deployment of application. Lightweight and instant start of containers find its place across various domains including big data and cloud. Due to this wide range in heterogeneity of resources, the orchestration framework is required for the management of containers. Resource selection becomes one of the major challenges in such environment. Although various open-source orchestration available in market for addressing the management of containers across varied platform, they provide only a basic scheduling scheme. In this paper, we highlighted various factors affecting the resource selection and proposed an architecture of resource-aware placement and SLA (Service Level Agreement) based monitoring which provides advanced scheduling and minimizes container migration.
Teaching Research on Computer Programming based on Cultivation of Computational Thinking

Computer programming is one of compulsory courses for science and engineering majors in colleges and universities, and C language is one of the most common programming language. In view of teaching problems of traditional programming course, for example, the concepts are abstract and difficult to understand for students, and students are lack of logical thinking of programming, this paper introduced the concept of computational thinking, analyzed how to integrate computational thinking into teaching contents of computer programming course, and flipped classroom teaching method was discussed too. The teaching practice showed that good teaching effects were achieved.
Analysis of Disadvantages of Using Information and Communication Technology In Higher Education Institutions

In the article the disadvantages of using information technologies in the process of training specialists are analyzed. Possible ways of avoiding them during teaching activity are identified and outlined. The object of study is the process of professional training in higher education institutions. The purpose of this article is to analyze scientific and methodological publications on the problem of research, to identify the existing shortcomings in the use of information technologies in the process of training specialists in higher education institutions and possible ways to overcome them. The analysis of scientific sources showed that the main disadvantages of using information technology include reducing students' attention in the process of working with a computer, the presence of diverse and contradictory information on which to make a decision, the inability of the machine to fully adapt to the abilities and needs of the student, reducing the number of live communication, which can lead to difficulties in discussions on professional topics, thoughtless use of Internet-ready projects, abstracts, reports and difficulties of a personal nature. All this is grounded in the assertion that the use of information technology in the course of study should be methodologically justified, provided with appropriate methodological guidelines for working with the computer while mastering the material, and optimally combined with traditional teaching methods. Prospects for further research are the methodological substantiation and experimental verification of pedagogical conditions for forming the readiness of future specialists of pedagogical specialties for the use of information technologies in the process of professional activity.
NASIG Core Competencies: Building a Bridge to the LIS Curricula and Job Responsibilities

The 2016 revised NASIG Core Competencies for Electronic Resources Librarians broadly defines the areas of work that Electronic Resources Librarians engage with and are responsible for. Using findings from two recent studies, this presentation given at the NASIG 2019 Annual Conference identified trends in electronic resource (e-resource) management on two fronts. The first study investigated the degree to which Library and Information Science programs are addressing e-resources, either as the primary subject of a course or as part of a course related to technical services. The second study addressed the distribution of e-resource management responsibilities at Carnegie-classified doctoral universities based on the areas of competency identified in the Core Competencies.
Competitive Spatial Pricing Model

This paper considers the stabilization of prices, as well as supply and demand in a competitive market with the participation of manufacturers and resellers. A mathematical model of this problem is formulated, the problem of finding a Nash equilibrium is solved, and an example of using this model is also given.
biclustermd: An R Package for Biclustering with Missing Values

Biclustering is a statistical learning technique that attempts to find homogeneous partitions of rows and columns of a data matrix.For example, movie ratings might be biclustered to group both raters and movies.biclust is a current R package allowing users to implement a variety of biclustering algorithms.However, its algorithms do not allow the data matrix to have missing values.We provide a new R package, biclustermd, which allows users to perform biclustering on numeric data even in the presence of missing values.
Safeguard: A Prototype of An Application Programming Interface to Save the Disaster Affected People

The automated chatbot system has introduced a new era of modern technology. Recently the chatbot system plays an important role as a virtual agent in different respects. A chatbot system cannot replace a human agent but it can provide initial support at any time instantly. This type of instant support can help a victim at the time of the natural disaster period efficiently. It can also play a role to reduce the amount of damage. In this research paper, we have proposed a chatbot application programming interface (API) system named Safeguard that can be integrated into different social media as well as in any application. This system will be able to support a victim and give guidelines on disaster period. For this purpose, natural language understanding was used by Dialogflow tool. Dialogflow has helped to create the application programming interface system by using intents, entities and text responses by the implementation of the natural language processing system, cloud storage and JSON.
Cut-Based Graph Learning Networks to Discover Compositional Structure of Sequential Video Data

Conventional sequential learning methods such as Recurrent Neural Networks (RNNs) focus on interactions between consecutive inputs, i.e. first-order Markovian dependency. However, most of sequential data, as seen with videos, have complex dependency structures that imply variable-length semantic flows and their compositions, and those are hard to be captured by conventional methods. Here, we propose Cut-Based Graph Learning Networks (CB-GLNs) for learning video data by discovering these complex structures of the video. The CB-GLNs represent video data as a graph, with nodes and edges corresponding to frames of the video and their dependencies respectively. The CB-GLNs find compositional dependencies of the data in multilevel graph forms via a parameterized kernel with graph-cut and a message passing framework. We evaluate the proposed method on the two different tasks for video understanding: Video theme classification (Youtube-8M dataset (Abu-El-Haija et al. 2016)) and Video Question and Answering (TVQA dataset(Lei et al. 2018)). The experimental results show that our model efficiently learns the semantic compositional structure of video data. Furthermore, our model achieves the highest performance in comparison to other baseline methods.
Value and Self-Concept: A Study on Reading Habits among Primary School Students in Sarawak

This study analyses the extent to which students’ value of reading and self-concepts as readers affect their motivation to read. The participants included 45 students from a rural primary school in Malaysia aged 8 to 10 years old. They completed the Motivation to Read Profile-Revised (MRP-R) designed by Malloy et al. (2013) which consists of a survey and conversational interview to shed light on students’ attitudes towards reading. The results from the survey demonstrated that the students held high self-concepts of themselves as readers and were able to use reading comprehension strategies. Overall they found reading enjoyable, and preferred collaborative reading tasks and books with visuals. Additionally, students were motivated by engaging classroom activities and trips to the library, and many students preferred digital text. However, the students found reading in another language to be challenging. Through these results, the role of the teacher is highlighted as essential in motivating students to read. By providing opportunities for students to read a variety of texts at students’ reading levels and on different topics, in both students’ native languages and target language. Students may gain reading motivation when they can choose what to read and when instructors create engaging activities that encourage not only independent reading, but incorporate a social aspect as well. Schools may also consider using technology to motivate young readers, and a reading culture should be supported in the students’ homes to further encourage lifelong reading habits.
Developing new Multilevel security algorithm for data encryption-decryption (MLS_ED)

The desire of secrecy has led people to use data cryptography for effective and secure data transmission by applying advanced methods of cryptography.At the same time rival companies have invested a lot of resources to break into these encryptions, steal secrets and gain an upper hand.This research paper will introduce MLS_ED method of data encryption-decryption; this method will be implemented and compared with other existing standard methods of data cryptography.The aim of this research paper is to provide the users with flexible, efficient and secure method of data encryption-decryption.
DESAIN DAN IMPLEMENTASI MEDIA PEMBELAJARAN BERBASIS MOBILE LEARNING MENGGUNAKAN MOODLE MOBILE APP

The purpose of this study is to produce instructional media of ICT guidance based on Mobile Learning using Moodle Mobile App that is valid, practical, and effective. This type of research is Research and Development (R &amp; D). The development model used is the ADDIE model. The experimental method used Intact-Group Comparison. The sample was students of class X at SMA Negeri 1 Sungai Geringging. The instrument was validation questionnaire to measure validity, response questionnaires to measure the practice, and post-test questions of multiple choice to measure the effectiveness of developed media. The results showed that media declared valid by the validator assessment, and practically use by teachers and learners. Percentage of classical completeness at experiment group reached 87,5%, and 12,5% for classical incompleteness. While the control group reached 25% for classical completeness, and 75% for classical incompleteness. It means that ICT guidance media based on Mobile Learning using Moodle Mobile App is "valid, practically, and effective" to use in ICT guidance learning process.
Convenient Real-Time Monitoring of the Contamination of Surface Ion Trap

Recent studies indicated that contamination by adatoms on the surface ion trap can generate contact potential, leading to fluctuations in patch potential. By investigating contamination induced by surface adatoms during a loading process, a direct physical image of the contamination process and the relationship between the capacitance change and the contamination from surface adatoms is examined theoretically and experimentally. From the relationship, the contamination by surface adatoms and the effect of in situ treatment process can be monitored by the capacitance between electrodes in real time. This study is foundational to further research on anomalous heating with practical applications in quantum information processing from surface ion traps.
Novel high functionality fault tolerant ALU

Miniaturization, cost, functionality, complexity and power dissipation are important and necessary design traits which need attention in circuit designing. There is a trade off between miniaturization and power dissipation. Smart technology is always searching for new paradigms to continue improve power dissipation. Reversible logic is one of smart computing deployed to avoid power dissipation. Researchers have proposed many reversible logic-based arithmetic and logic units (ALU). However, the research in the area of fault tolerant ALU is still under progress. The aim of this paper is to bridge the knowledge gap for a new researcher in area of fault tolerance using parity preserving logic gates rather than searching huge data through various sources. This paper also presents a high functionality based novel fault tolerant arithmetic and logic unit architecture. A comparison on optimization aspects is presented in tabular form and results shows that proposed ALU architecture is optimum balance in terms of all aspects of reversible logic synthesis. The proposed ALU architecture is coded in Verilog HDL and simulated using Xilinx ISE design suit 14.2 tool. The quantum cost of all gates used in proposed architecture is verified using RCViewer + tool.
Creating Activities for After School Robotic Workshop with Ozobot Evo

For several years we have been developing and adjusting the structure and content of the university course about educational robotics based on the number and characteristics of our students. In the paper, we present the results of our qualitative research in the field of educational robotics, which we conducted in this course designed for master students. As part of the research topic, we have chosen two areas that we are focusing on: (1) process, form, content, and results of a university course of educational robotics for future teachers; (2) advantages and disadvantages of working with Ozobot Evo robot. During the course, our students were creating activities for leisure time robotic workshops for pupils aged between 7 and 15. These activities were tested in parallel at workshops in a leisure time center, so students were given immediate feedback on the materials they had created. In our course, we used modern learning concepts such as project-based learning. We observed students having developed several competencies.
XML-Based Video Game Description Language

This paper presents the XML-based Video Game Description Language (XVGDL), a new language for specifying Video games which is based on the Extensible Markup Language (XML). The proposal is portable and extensible, and allows games to not only be defined at engine level but also includes specific features that can lead the game design process whilst simultaneously reducing the gap between game specification and its corresponding game implementation. XVGDL is as generic as possible, making it possible to describe different genres of games. This paper focuses on presenting the basis of the language. The paper describes the syntax as well as the components of XVGDL, and provides examples of their use. Defining games via XML structures provides all the advantages of the management of XML files and opens up interesting lines of research. Our proposal provides a number of novel features. So, XVGDL game definitions can be managed as any other XML file, which means that it can be automatically handled by any XML file management software. Another interesting feature is that XVGDL can specify game components (e.g., game Artificial), in-game processes (e.g., the procedural generation of maps) or in-game events (e.g., the checking of the conditions to end a game match) via the association with external (possibly non-XML) files. Moreover, XVGDL files can be easily validated as any XML file what means that validations against a particular Document Type Definition (DTD) or XML Schema Definition (XSD) are possible. In addition, the paper presents a first prototype implementation of a (text-based) interpreter that allows XVGDL game specifications as a playable game to be executed. This tool not only validates our proposal but also represents a first step towards smoothing the path to obtaining an executable version of a game from its game specification.
Panoptic Segmentation-Based Attention for Image Captioning

Image captioning is the task of generating textual descriptions of images. In order to obtain a better image representation, attention mechanisms have been widely adopted in image captioning. However, in existing models with detection-based attention, the rectangular attention regions are not fine-grained, as they contain irrelevant regions (e.g., background or overlapped regions) around the object, making the model generate inaccurate captions. To address this issue, we propose panoptic segmentation-based attention that performs attention at a mask-level (i.e., the shape of the main part of an instance). Our approach extracts feature vectors from the corresponding segmentation regions, which is more fine-grained than current attention mechanisms. Moreover, in order to process features of different classes independently, we propose a dual-attention module which is generic and can be applied to other frameworks. Experimental results showed that our model could recognize the overlapped objects and understand the scene better. Our approach achieved competitive performance against state-of-the-art methods. We made our code available.
Pruning of Network Filters for Small Dataset

Many existing object detection networks achieve outstanding accuracy in some open-source datasets, which usually contain a large number of images and target categories. However, a majority of the state-of-the-art networks use hundreds of filters and layers to extract plenty of features on behalf of getting a better result. Also, it is known that the networks tend to be redundant with so many parameters. In order to explain the redundancy more intuitively, we propose to visualize the feature maps, among which some is even found to impact negatively on the detection accuracy, especially when it comes to some small datasets containing only a few target categories. To address this problem, we propose the pruning rules of filters, whereby finding the useless filters and remaining the helpful ones based on feature maps, hence the networks are turned into thinner ones. Our final networks use filters less than one-tenth of the baseline model in some layers, but still outperform some related object detection methods.
Universal Value Iteration Networks: When Spatially-Invariant Is Not Universal

In this paper, we first formally define the problem set of spatially invariant Markov Decision Processes (MDPs), and show that Value Iteration Networks (VIN) and its extensions are computationally bounded to it due to the use of the convolution kernel. To generalize VIN to spatially variant MDPs, we propose Universal Value Iteration Networks (UVIN). In comparison with VIN, UVIN automatically learns a flexible but compact network structure to encode the transition dynamics of the problems and support the differentiable planning module. We evaluate UVIN with both spatially invariant and spatially variant tasks, including navigation in regular maze, chessboard maze, and Mars, and Minecraft item syntheses. Results show that UVIN can achieve similar performance as VIN and its extensions on spatially invariant tasks, and significantly outperforms other models on more general problems.
Modeling and Control Unmanned Surface Vehicle (USV) with Hybrid Drivetrain

With the rapid development of unmanned surface vehicle (USV), the development of hybrid electric vehicles on USV is a technology that has a very important role to overcome the problem of how long the vehicle can be used. In hybrid electric vehicles (HEV), the main components consist of generators, electric motors, and batteries. Modeling component is intended to design models that fit on unmanned surface vehicle and represent the state of USV with hybrid drivetrain. This paper focuses on modeling USV with hybrid drivetrain. This vehicle uses a series configuration so that the generator act as a power generating system. The power system on USV was chosen using hybrid sources of DC generator and lithium-ion battery pack. The optimal size of DC generator and battery pack are very important to ensure that USV can work for a long period of time. This paper describes the simple characteristics of a DC generator with a PI controller and gain-scheduling PI controller which is accurate in generating 380V output voltage according to the initial plan to be built. We also described the model of permanent magnet dc motor as a driver in USV and described simulation about 200Ah 36V lithium-ion batteries. The development of this model will be represented in MATLAB/Simulink.
The Application of Fractal Analysis on Thyroid Ultrasound Images

The concept of fractals is used for complex and irregular objects or structures in systems. The complexity of medical images allows us to use Fractal geometry rather then Euclidian geometry for their characterization. In this paper, we have discussed the analysis of thyroid ultrasound images to calculate fractal dimension. Fractal analysis software was used for the calculation of fractal dimension and correlation coefficient values. In the fractal analysis on the thyroid ultrasound images, the determination of the dimensions of the lesions, nodules or cysts in the region by using fractal concepts can be predicted and used as an assistive system for physicians in the treatment and early diagnosis of thyroid disorders.&nbsp;
An Automated Billing System in Shopping Malls Using Bascart

In modern days, people are getting too busy in their works but still they need to spend time in shopping malls. In Shopping malls, customers face a difficulty to follow a queue for the process of billing, which takes a long time under huge crowd. Customer thought that, to avoid the standing time in the billing section at shopping malls. To overcome the above problems, we emerged the Bascart system. To increase the pace of a billing process, RFID tags in products, then the product is read by the barcode scanner which describes the cost of that product and is displays on the LCD screen attached in our shopping list. As customer buy their exact product its price is add on the previous list. The cost of the product is displayed on the LCD screen by using microcontroller through Zigbee Communication from host PC. Zigbee supports bidirectional communication between microcontroller and host PC. We have proposed the Weighing Sensor for the purpose of checking the weight of the items and it is directly stored in the server database. Customer get direct bill at the billing section which is already stored at host PC which automatically reduces the queue. Then GSM Module in our system is used to detect the Geo-position of the customer’s mobile for the process of intimating the shopping details of the customer through messages which is already updated in database.