Reviewerly/exHarmony huggingface dataset:
Texture Image Retrieval Using Multiple Filters and Decoded Sparse Local Binary Pattern

In local pattern based feature extraction, usually the raw spatial image provides limited information about the relationship between the pixels in a local neighborhood. A few recent methods address this issue by first filtering the images with bag of filters and then calculating local pattern over each filtered images. It is observed that the filtered images complement the discriminativeness of local pattern based features which enhances retrieval efficiency. Motivated by these approaches, a new approach based on multiple filters and decoded sparse local binary pattern (MF-DLBP) is proposed in this paper, wherein we first filter the raw spatial image with multiple filters to extract the low frequency and high frequency information. However, unlike previous approaches, we extract features from low pass and high pass filtered images adopting separate strategies, since characteristically they contain contrasting information. From each gradient filtered images, we compute sparse LBPs using LBP4hv (considering only horizontal and vertical neighbors) and LBP4d (considering only diagonal neighbors) techniques. To enhance the discriminativeness of the descriptor, two decoders are also used which compute the inter frequency relationship between the sparse local binary pattern maps of high pass filtered images only. The low pass filtered image is encoded with sign LBP ($$LBP\_S$$) and magnitude LBP ($$LBP\_M$$) to extract sign as well as magnitude information present in this image. The proposed approach is low dimensional and it shows highly competitive retrieval performance when tested on three benchmark texture databases which are Kylberg, Brodatz and STex.
Low-Complexity transform algorithm for Versatile Video Coding

The Versatile Video Coding (VVC) is being currently prepared as the next generation of video coding by the Joint Exploration Team (JVET). The main goal of this standardization job is to improve compression ratio with respect to the actual standard High Efficiency Video Coding (HEVC). The new proposal uses some advanced Transform tools such as DCT8, DST1 and DCTS added to those used in the HEVC transform set. In this paper, a new transform algorithm is presented for VVC. Experimental results prove the effectiveness of the proposed algorithm, which can attain 41.05% complexity reduction.
A Comparative Study of Biometric Authentication in Cloud Computing

Cloud computing has attracted businesses to move from the traditional way of sharing IT resources due to multiple factors including cost, productivity, performance, scalability and security. The benefits of cloud computing are enormous, but it is a complex technology needing complex protocols for human identification for specific applications over the network. Biometric authentication provides one of the promising methods for authentication in a cloud environment. This paper is a survey-based review that summarize the recent schemes used for biometric authentication in the cloud computing and highlights their pros and cons to find the best approach for this purpose. Result of this survey recommended that the multimodal biometric authentication improves and reduces its complexity and computation time with the use of Biometric-as-a-service (Baas).
Optimizing System Efficiency and Performance using Tree Based Indexing Scheme

In today's world of digitalization, the scope of wireless data broadcast (bcast) still persists. Many day-to-day applications such as stock market, news, entertainment industry, sports industry etc. use data broadcasting. Being in use for more than a decade, there is still a possibility of improvement in the system efficiency and performance. Average Access Latency (AAL) and Average Tuning Time (ATT) are two major criterions to assess the performance of such system. There a number of indexing schemes available but the authors have redesigned, evaluated and compared certain most popular tree based indexing, i.e. Huffman and B <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> tree index. Our communication model combined the existing as well as a new theory of probability to evaluate the system performance. Numerical simulations have been carried out to compare both the tree indices in terms of AAL and ATT. After a detailed analysis, a more perceptive assessment has also been presented to make the outcome more evident. Present study shows that the Huffman indexing outperforms the B <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> tree index at various fronts.
Designing Enterprise Architecture for Sports Information System Platform Using the Open Group Architecture Framework Architecture Development Method

Abstract The purpose of this study to along with the development of information technology PSSI ASPROV JABAR, wants to develop information systems but does not have a corporate blueprint in designing information systems. The method used enterprise architecture design is based on TOGAF ADM literature study. The design of an enterprise architecture information system for sports platforms will be designed using TOGAF ADM, in developing the information system phase, the Architecture Phase Architecture, the Business Architecture Phase, the Information System Architecture, and the Architectural Technology Phase. This research produces a blueprint that will be used to create information systems that can support ongoing business processes. TOGAF ADM is designed as a general framework and has good alignment between business and technology. The conclusion of this research is that the company’s architectural design using TOGAF ADM can be used in PSSI ASPROV JABAR according to the documents and processes that are running and can produce a blueprint for creating information systems so that they can support ongoing business processes.
Actual and historical state of side channel attacks theory

The traditional classification of side-channel attacks is based on the fundamental work of Kocher [1, 2], i.e genesis of modern classical and generally accepted classification of attacks is based on performance, security, hardware, architecture, software solutions for computing devices 1990-2000s. By 2019 the relevance of this method of security analysis (means of obtaining information through side-channels) was tested, but presently there are many new types of side-channel attack (SCA) [3--6]. New methods and algorithms are not presented in the traditional classification of SCA, but significant in the context of the current state of the SCA theory, therefore they require additional systematization. This paper aims to develop a discourse on the current status of SCA, a review of state-of-art edge of SCA theory and extend classical classification scheme to position new SCA methods on it. Also paper include review of current SCA directions for symmetric block cipher (Advanced Encryption Standard (AES), PRESENT, GOST R 34.12-2015 (Magma, Kuznyechik)).
Characterization of a transmitter in a medium frequency maritime terrestrial navigation system

Due to the worldwide recognition of increased jamming and spoofing events, which threaten the usability of global navigation satellite systems (GNSS), positioning systems using signals of opportunity are gaining importance as backup systems. Especially for maritime usage, a terrestrial system called Ranging-Mode (R-Mode) is under development. Among other signals, it utilizes the maritime medium frequency broadcasts of the differential GNSS (DGNSS) service. Currently, the estimation of phase in a time continuous medium frequency signal is used to determine the distance between transmitter and receiver. Here, the delay of a transmitter on the signal phase is of great interest, since it directly affects the performance of the R-Mode system. In this paper, the influence of a medium frequency power amplifier is characterized as part of the transmitter chain. The aim is to give the operators of DGNSS stations the possibility to characterize their station themselves when the R-Mode system is operational. Therefore, widely used measuring instruments are utilized, rather than using well-known cost-intensive techniques like phase delay measurements. A simple setup with different evaluation methods that fit this requirement is presented. Furthermore, it is capable of measuring the absolute time delay. The presented workflow was tested on an amplifier with output power of 100 W at the transmitter station near Koblenz, Germany.
Learning Literary Style End-to-end with Artificial Neural Networks

This paper addresses the generation of stylized texts in a multilingual setup.A long short-term memory (LSTM) language model with extended phonetic and semantic embeddings is shown to capture poetic style when trained end-to-end without any expert knowledge.Phonetics seems to have a comparable contribution to the overall model performance as the information on the target author.The quality of the generated texts is estimated through bilingual evaluation understudy (BLEU), a new cross-entropy based metric, and a survey of human peers.When a style of target author is recognized by the humans, they do not seem to distinguish generated texts and originals.
End-user activities context information management framework for sustainable building operation

Abstract The concept of sustainable buildings includes not only technological aspects related to energy efficiency and resources usage optimization, but also aspects related to end-users’ comfort, wellbeing, and everyday needs support. To understand the end-users’ life activities in general and their preferences in particular, is necessary to enrich standard Building Management Systems (BMS) with human-generated and personal data. In this conceptual paper, we present an end-user context information management framework, which includes a reasoning layer , an acquisition layer , and a dissemination layer . The proposed framework is currently implemented in the KTH Live-in-Lab – a fully equipped testbed for research and innovation in the build environment.
A Framework for Integrating Secure Coding Principles into Undergraduate Programming Curricula

The rise of the use of the internet has led to significant growth in software applications for conducting business, entertainment and socialising, which in turn has led to a higher rate of attacks on software applications. This problem has led to industry requiring software developers skilled in developing software in a secure manner. The problem that industry faces is that many software development graduates do not have the requisite knowledge in secure programming. Academia should thus address these needs of industry by integrating secure coding principles into undergraduate programming curricula. In South Africa, however, this is often not formally done. This paper suggests some secure coding principles that could be integrated into programming curricula, together with various integration approaches and related challenges. It presents a framework for integrating secure coding principles into undergraduate programming curricula to ensure the formal planning and ‘buy-in’ of academic staff at all levels. The purpose of the framework is to guide computing faculties about ‘what’ secure coding principles to teach and ‘where’ to teach them.
A Case Study on Developing Students’ Leadership Skills via Team Work Activities

This paper aims to explore how the students' leadership skills would be developed through team work activities in classes.As the definition of leadership is diverse and elusive, it is hard to evaluate whether the leadership skills of the students have been improved getting involved in team work.So, by extracting the core skills of leadership commonly recognized by both the academic and the business world, questionnaires and interviews are designed and made among two groups of students: teacher-students and vocational college students.Based on the data gathered, it's agreed that leadership can be cultivated through participating in team work teaching activities in classes.
An ontology to improve the first aid service quality

An ontology is a formal description of knowledge as a set of concepts within a domain and the relationships that hold between them. During the past few years, ontologies became ever more popular. They can be used to describe a lot of scenarios, they are also very useful in the description of real-life situations. Our work stems from a collaboration between two departments of our University, DISIM and MESVA, within a project called eHealth, that, in the first part, focuses on the creation and the querying of an ontology based on anonymous data retrieved from first aid phone services. Once obtained the first aid data and manually created the ontology classes and properties, we are able to automatically insert the data that describes the emergency call received from the first aid operator through a Java application written by us. We analyzed those data through queries, obtaining useful results that can potentially save lives, for example, aiding the operator in the choice of the rescue vehicle to send out for an emergency, depending on the situation.
Development and deployment of automated electronic document management system in municipal units

The paper analyzes the efficiency of development and deployment of automated electronic document management system in municipal units. Even considering the pessimistic forecast, the payback period of automated electronic document management system will not even exceed half a year. The introduction of automated electronic document management system will increase the reliability of the entire infrastructure within municipal administration.
Cloud-Enabled Warship’s Position Monitoring with Blockchain

The paper presents details of the blockchain workshop which was conducted at Polish Naval Academy, Gdynia, Poland in a period of 4 months from February to May 2017. The workshop was incorporated into the Software Engineering subject as a part of regular classes. The paper explores business and technical aspects of blockchain main projects developed under Hyperledger initiative. In the following sections authors focus on: reference architecture, business architecture and technical architecture as well as algorithms used in Hyperledger Fabric, Hyperledger Iroha and Hyperledger SawtoohLake projects. The Hyperledger Fabric blockchain project was chosen for conducting classes. The workshop encompassed blockchain introduction and configuration of simple application in cloud environment. Furthermore, students configured on-premises environment for development of blockchain applications. The last task was the development of complete application combining IBM BlueMix, Watson Internet-of-Things Platform and Blockchain service which monitored position, simulated by Node-Red service, of warship ORP Kosciuszko.
UmpleOnline as a Testbed for Modeling Empirical Studies: A Position Paper

UmpleOnline is a widely used modeling tool that allows practitioners to create class diagrams, state diagrams and several other model types textually, with the option to edit class diagrams graphically. In this paper we propose how UmpleOnline can be used as a tool to conduct modeling empirical studies. UmpleOnline would be instrumented to allow any of its 180,000 annual visitors to volunteer to participate in one of many studies that would be pre-loaded by any member of the modeling research community. Studies could focus on research questions relating to model quality, modeling strategies, modeling errors or many other things. UmpleOnline would be an ideal vehicle for such studies since it is zero-footprint and has demonstrated high usability.
CANVAS: A Drawing Tool for AR-aided Special Needs Education using Interactive Floor Projection

In this paper, we propose a novel floor projection drawing tool for AR-aided special needs education, called CANVAS, which can be easily used by teachers or practitioners. We propose a method of using floor projection to support the activities of children with neurodevelopmental disorders (ND) by summarizing the used elements of past activities: Positions (Points), Lines, Areas, and Symbols (PLAS method). This PLAS method fulfills the design requirements of the content that can be created on CANVAS, which is a tablet type drawing system. The content is transmitted in realtime to the gym projectors to realize realtime and interactive activities based on the projection of geometric shapes, at the intended place on the floor. Experimental results demonstrate that simple shapes such as circles and lines are sufficient to support cognition and changes in the physical behaviors of children with ND.
A data-driven approach to spoken dialog segmentation

In this paper, we present a statistical model for spoken dialog segmentation that decides the current phase of the dialog by means of an automatic classification process. We have applied our proposal to three practical conversational systems acting in different domains. The results of the evaluation show that is possible to attain high accuracy rates in dialog segmentation when using different sources of information to represent the user input. Our results indicate how the module proposed can also improve dialog management by selecting better system answers. The statistical model developed with human-machine dialog corpora has been applied in one of our experiments to human-human conversations and provides a good baseline as well as insights in the model limitation.
Temporal Convolutional and Recurrent Networks for Image Captioning

Recently temporal convolutional networks have shown excellent qualities in sequence modeling tasks [1]. Taking this fact into account, in this paper we investigate the possibilities of replacing recurrent networks in architectures targeted specifically at image captioning. We evaluate the solution on Visual Genome dataset [2], which provides extensive set of labels and descriptions that thoroughly grounds visual concepts to natural language.
E-Learning in India

The International Scientific Research Organization for Science, Engineering and Technology (ISROSET) is a Non-Profit Organization; The ISROSET is dedicated to improvement in academic sectors of Science (Chemistry, Bio-chemistry, Zoology, Botany, Biotechnology, Pharmaceutical Science, Bioscience, Bioinformatics, Biometrics, Biostatistics, Microbiology, Environmental Management, Medical Science, Forensic Science, Home Science, Library Science, Material Science Military Science, Physical Science, Physical Education Science, Educational Science, Fisheries, seed technology, Agriculture, Forestry Science, Mathematics, Physics, Statistics and Geology/Earth Science), Computer Science, Engineering and Information Technology, Commerce, Management, Economics Sociology and Social Science.
Evaluating Software Security Change Requests: A COSMIC-Based Quantification Approach

Software project scope defines functional and non-functional requirements. These requirements may change to satisfy the customers' needs. However, the control of scope creep represents one of the success keys in software project management. Changes in non-functional requirements affect the ISO/IEC 25010 quality characteristics such as security, portability, etc. Furthermore, some of these quality characteristics may evolve throughout the software life cycle into functional requirements. In this paper, we explore the use of COSMIC method - ISO/IEC 19761 to quantify and evaluate security change requests. Measuring the functional size of security change requests allows stakeholders to make appropriate decisions about whether to accept, defer, or deny the change.
Advanced Subword Segmentation and Interdependent Regularization Mechanisms for Korean Language Understanding

State-of-the-art neural language models highly rely on fixed-size subword vocabulary based pre-training process to improve the performance of language understanding. Existing subword segmentation algorithms have been researched to generate fixed-size vocabulary by frequency in large text pool without considering the linguistic structures. Also, most of research is focused on widely-used languages such as English and Chinese. However, for Korean, a segmentation algorithm considering the linguistic structure is required, and we thus propose the algorithm considering the characteristics of Korean. For example, Korean words include the special type of suffix called “Josa” that adds grammatical meaning. We also propose subword regularization algorithm based on mutual information, which is interdependence between words. The regularization algorithm customizes the size of vocabulary on demand. In addition, we present an experiment analysis of subword segmentation and interdependent regularization by testing neural language model. It can achieve better performance by small changes of vocabulary.
Smart medical nanotechnology using outlier detection methods

In this paper, we present the importance of nanotechnology for everyday life as well as in medicine. In this context, Nanomedical application is shown. We are also discussing the feasibility of having a data control system using anomaly detection, such as the EEG. In the end, we propose our thought to build this kind of procedures with existing solutions.
Designing of Eid Al-Adha Qurban Meat Stock Information System to Optimize its Distribution

Abstract The purpose of this study is to design information systems to optimize the distribution of Qurban meat in Eid Qurban. During this time each local Qurban organizer carried out their respective Qurban activities. The meat supply in some region have an uneven distribution of qurban meat. They did not know the number of qurban meats in other areas and their distribution. Therefore, as a solution to optimize the distribution of qurban meat, the author designed an information system for searching and requesting qurban meat based on website. This system is designed for each Qurban organizer so that they can inform about the qurban meat stocks which can be requested by another organizer. This research used experimental method. The system designed using the A-star algorithm to find the closest location. The programming languages used are PHP and JavaScript programming languages. While database management used MySQL. This system is applied to search for excess qurban meat stock at the nearest location. The result is that the application could function properly and ready to be used in the public. The existence of this designed system is expected to help the process of distributing qurban meat to become more optimal so that the social objectives of the celebration of the Qurban feast are achieved.
Physical Activity Recognition Using Streaming Data from Wrist-worn Sensors

Most of the existing researches in smartwatches based activity recognition focused on developing the subject (user) specific approach or personal model which the subject must collect the labeled data for training the model. It is inconvenient for the users are unable to perform all activities during the specified times. In this paper, we introduce a cross subjects approach or impersonal activity recognition model based on the fusion of two sensors embedded on smartwatches called S-PAR. It stands for Smartwatches based Physical Activity Recognition. Therefore, the users who utilize the model, are not necessary to gather initial the labeled data. The experiments were carried out to examine the performance of S-PAR model against with state-of-the-art methods by using two public databases collected under realistic conditions. From the results, S-PAR model provides the overall performance in detection and prediction activities type. Therefore, our proposed model can be used in the real life environment.