Reviewerly/exHarmony huggingface dataset:
Engineering of Collaborative Embedded Systems

Abstract Embedded systems are being increasingly used in changing environments where they no longer fulfill their associated stakeholder goals on their own, but rather in interaction with other embedded systems. This transition to networked, collaborative embedded systems is creating new application opportunities that impose numerous challenges for developers of these systems. In this introductory chapter of the book, we present the complexity of these systems and the challenges associated with them in a coherent manner. We illustrate the challenges using two use cases, “Vehicle Platooning” and “Adaptable and Flexible Factory.” Finally, we reference the challenges of developing collaborative embedded systems to the individual chapters of this book, which describe various methods of mastering the complexity in more detail.
Use of visual technologies in the development of digital literacy of University teachers

The article contains the results of research on the use of visualization in the training of University teachers (development of digital literacy). The paper describes the concept of visualization, its main levels (visualization of data, information, knowledge), briefly describes the proposed course, assessment parameters before and after participation, and summarizes the results of the study. The paper also reflects the results of a survey of students who study with these teachers and heads of educational organizations in order to identify possible changes in the professional activities of teachers who have completed the proposed course. The results of the study confirmed the effectiveness of using visualization in improving the quality of professional activity of teachers, and significant differences were found in the assessment of teachers ' attitude to innovation and work in the digital environment before and after the course. According to the results of the study, the features of the use of visual technologies in the training of teachers and the development of their digital literacy were highlighted.
THE EFFECT OF LEARNING MODEL LEARNING LEARNING WITH YOUTUBE VERSUS MEDIA FLASH CARD MEDIA AND LEARNING MOTIVATION ON LEARNING OUTCOMES IN ENGLISH

Learning models only emphasize rote thinking, reproductive and looking for the right answer. Many English teachers only emphasize the theoretical aspects, not the actual function, communication skills. This study aims to determine the effect of active learning model learning with Youtube media versus flash card media and students' learning motivation towards student learning outcomes in SMP N 1 Sidoarjo and SMP N 4 Sidoarjo. The study was conducted with a quantitative approach with a factorial design experimental model. The results showed learning outcomes between learning English using active learning models with Youtube media and learning English with flash card media.
DA-Res2Net: a novel Densely connected residual Attention network for image semantic segmentation

Since scene segmentation is becoming a hot topic in the field of autonomous driving and medical image analysis, researchers are actively trying new methods to improve segmentation accuracy.At present, the main issues in image semantic segmentation are intra-class inconsistency and inter-class indistinction.From our analysis, the lack of global information as well as macroscopic discrimination on the object are the two main reasons.In this paper, we propose a Densely connected residual Attention network (DA-Res2Net) which consists of a dense residual network and channel attention guidance module to deal with these problems and improve the accuracy of image segmentation.Specifically, in order to make the extracted features equipped with stronger multi-scale characteristics, a densely connected residual network is proposed as a feature extractor.Furthermore, to improve the representativeness of each channel feature, we design a Channel-Attention-Guide module to make the model focusing on the high-level semantic features and low-level location features simultaneously.Experimental results show that the method achieves significant performance on various datasets.Compared to other state-of-the-art methods, the proposed method reaches the mean IOU accuracy of 83.2% on PASCAL VOC 2012 and 79.7% on Cityscapes dataset, respectively.
Human Motion Data Retrieval Based on Staged Dynamic Time Deformation Optimization Algorithm

In recent years, with the rapid development of computer storage capabilities and network transmission capabilities, users can easily share their own video and image information on social networking sites, and the amount of multimedia data on the network is rapidly increasing. With the continuous increase of the amount of data in the network, the establishment of effective automated data management methods and search methods has become an increasingly urgent need. This paper proposes a retrieval method of human motion data based on motion capture in index space. By extracting key frames from the original motion to perform horizontal dimensionality reduction and defining features based on Laban motion analysis, the motion segment is subjected to vertical feature dimensionality reduction. After extracting features from the input motion segment, motion matching is performed on the index space. This paper designs the optimization method of the phased dynamic time deformation algorithm in time efficiency and analyzes the optimization method of the phased dynamic time deformation algorithm in time complexity. Considering the time efficiency redundancy, this paper optimizes the time complexity of the phased dynamic time deformation method. This improves the time efficiency of the staged dynamic time warping algorithm, making it suitable for larger-scale human motion data problems. Experiments show that the method in this paper has the advantage of speed, is more in line with the semantics of human motion, and can meet the retrieval requirements of human motion databases.
Investigation of the Relationship between Digital Citizenship and Digital Literacy Levels of Secondary School Students

The main purpose of this study is to determine whether digital literacy is a predictor of digital citizenship by examining the relationship between digital citizenship and digital literacy levels of secondary education students in terms of various variables.The study group of the study consists of 847 secondary school students' who study in public schools in Selcuklu central district of Konya province in 2018 -2019 academic year.The screening method, one of the quantitative research methods, was used in the research.As data collection tool; "Personal Information Form" developed by the researcher to reach the personal information of secondary school students, "Digital Citizenship Scale" developed by Som-Vural to determine the levels of digital citizenship, and "Digital Literacy Scale" developed by Hamutoglu and others to determine the levels of digital literacy was applied.At the end of the study, it was concluded that the digital citizenship levels of secondary school students were high.It was concluded that there is a significant difference between the levels of digital citizenship of secondary school students and the year of internet use.It is concluded that there was no significant difference between gender, class level, time spent on daily internet time variables and secondary school students' digital literacy levels.There was no significant difference between class level variable and digital literacy level.In the correlation analysis conducted to determine the relationship between digital citizenship levels and digital literacy levels of secondary school students, it was found that there was a positive directional and significant relationship at the, medium-level.In addition, the effect of digital literacy on digital citizenship was found to be positive directional and significant.
LiARX: A Lightweight Cipher Based on the LTS Design Strategy of ARX

In recent years, technological advancements have led to the production of hardware devices that have extremely constrained resources (viz. RFID tags and sensors). Ensuring the required security guarantees to these low-end devices is a challenging task since conventional cryptographic mechanisms are not suited in such scenarios. For instance, it is advisable to use the Advanced encryption standard (AES) only for those devices where the availability of computational resources is not a major issue. This and more related factors have led to the emergence of Lightweight cryptography. In this paper, we discuss the recommended design principles for constructing a lightweight cipher. From the available literature, we have specifically focused on the Addition-Rotation-XOR (ARX) based design paradigm for this specific purpose. In this work, we have also argued that why the ARX based Long trail strategy (LTS) is a suitable design component for constructing practical lightweight ciphers. Finally, we have introduced a new lightweight cipher named LiARX which is based on the design recommendations of other ARX based ciphers. We have extensively analyzed and compared the performance of our cipher with some existing S-Box and ARX based lightweight ciphers, thereby proving its practicability.
Natural Language Interaction to Facilitate Mental Models of Remote Robots

Increasingly complex and autonomous robots are being deployed in real-world environments with far-reaching consequences. High-stakes scenarios, such as emergency response or offshore energy platform and nuclear inspections, require robot operators to have clear mental models of what the robots can and can't do. However, operators are often not the original designers of the robots and thus, they do not necessarily have such clear mental models, especially if they are novice users. This lack of mental model clarity can slow adoption and can negatively impact human-machine teaming. We propose that interaction with a conversational assistant, who acts as a mediator, can help the user with understanding the functionality of remote robots and increase transparency through natural language explanations, as well as facilitate the evaluation of operators' mental models.
A New Variant of Genetic Algorithm for Solving Gene Selection Problem

Genetic Algorithm (GA) is an evolutionary meta-heuristic approach, motivated by the principle of Genetics and natural selection. The goal of GA is to produce better offspring by genetic operations including selection, crossover, and mutation. In GA, parent selection is essential as the optimization results directly depend on the fitness of next generation (off-springs). In this paper, an improved version of GA, named Elitist Twin Removal Genetic Algorithm (ETRGA) has been proposed to enhance the performance of crossover operator during parent selection. This is to ensure that the best gene template will never be lost. In addition, Twin Removal (TR) operator efficiently balances the intensification (exploitation) and diversification (exploration) of the search process. Proposed ETRGA has been applied to 15 well-known benchmark functions as well as gene selection problem to find critical gene. Here, common disease gene obtained by three algorithms is termed as a critical gene. The performance of ETRGA has been compared with Simple Genetic Algorithm (SGA) and Twin Removal Genetic Algorithm (TRGA). The experimental results confirm that the proposed ETRGA outperforms SGA and TRGA in terms of statistical metrics taken care in the account in benchmark functions and real-life problem. The convergence graph of ETRGA shows that it has better exploration and does not suffer from premature convergence.
Sem gestão não há difusão e acesso: aspectos histórico-conceituais da arquivística canadense e brasileira

We work historically and conceptually with the development of practices related to diffusion and access to archives, building a comparison between Canadian and Brazilian reality from a theoretical point of view, systematizing the possible relations between these countries. It is concluded that access and diffusion are linked to State policies and their legal provisions.Keywords: archival science; access; Brazil; Canada.
Quantum Software Engineering: Quantum Gate-Based Computational Intelligence Supremacy

A new approach to a circuit implementation design of quantum algorithmic gates for quantum massive parallel computing realization is presented. The main attention is focused on the development of design method of fast quantum algorithm operators as superposition, entanglement and interference which are in general time-consuming operations due to the number of products that have to be performed. SW&HW support toolkit of supercomputing accelerator of quantum algorithm simulation is described. The method for performing Grover’s interference without product operations introduced. New quantum genetic and quantum fuzzy inference algorithm gate design considered.
Automated Diagnosis of Breast Cancer with RoI Detection Using YOLO and Heuristics

Breast Cancer (specifically Ductal Carcinoma) is widely diagnosed by Fine Needle Aspiration Cytology (FNAC). Deep Learning techniques like Convolutional Neural Networks (CNNs) can automatically diagnose this condition by processing images captured from FNAC. However, CNNs are trained on manually sampled RoI (Region of Interest) patches or hand-crafted features. Using a Region Proposal Network (RPN) can automate RoI detection and save time and effort. In this study, we have proposed the use of the YOLOv3 network as an RPN and supplemented it with image-based heuristics for RoI patch detection and extraction from cytology images. The extracted patches were used to train 3 CNNs - VGG16, ResNet-50 and Inception-v3 for classification. YOLOv3 identified 164 RoIs in 26 out of 27 images and we achieved 96.6%, 98.8% and 98.9% classification accuracies with VGG16, ResNet-50 and Inception-v3 respectively.
Developing Database System for Managing Medical Insurance Claims in the Human Resource Department

&lt;p&gt;PT. X Indonesia provides medical insurance for their employee from BPJS Kesehatan and other private company insurance. Currently, the data management of medical insurance members is not efficient and effective because the data regarding medical insurance are managed manually using MS Excel. The manual process leads to incorrect data input and causes a delay in the process of getting treatment and reimbursement claim process. The company will reimburse the payment but the process is long and complicated because the company should check the limitation for reimbursement claim per year. To solve the problem, database systems are constructed using System Development Life Cycle (SDLC) methodology which consists of five phases; systems planning, systems analysis, systems design, systems implementation, and system test, and deployment. The business process flow diagram of the current and proposed system is analyzed. After that, user requirements are determined. The data flow diagram and entity-relationship diagram (ERD) is constructed. And the system is developed using MS Access. Finally, the system is deployed. The result is an application running in MS Access that can manage medical insurance claim with more efficient and effective, compare to previous MS Excel.&lt;/p&gt;&lt;p&gt; &lt;/p&gt;
Role of a Croatian National Repository Infrastructure in Promotion and Support of Research Data Management

The paper will give an overview of national infrastructure for digital repositories, Digital Academic Archives and Repositories (DABAR), and its role as technology steward in raising awareness about research data management (RDM) and promoting good practices in the Croatian A&R community. The University of Zagreb, University Computing Centre (SRCE) is providing national infrastructure DABAR suitable for storing and dissemination of different types of digital objects. Through DABAR, all Croatian higher education and research institutions can establish their digital repository. A strong collaboration between SRCEs DABAR team and institutions repository managers has proven to be important in the process of disseminating knowledge about research data management among researchers and the scientific community at large. The paper will provide information about this collaboration during the project RDA Europe 4.0 – The European plug-in to the global Research Data Alliance (RDA). The main goal of this collaboration is to raise awareness about the importance of managing and sharing research data.
Interactive Visualization with UE4

Unreal Engine 4 is a game engine for building games, architectural walkthroughs, product visualizations, and more using assets and codes. They can be released on any supported platform. UE4 is a very popular game engine. Many AAA developers and indie studios use it to create modern games. Nowadays, if someone wants a job in the game industry, a portfolio that includes UE4 skills is highly recommended.
RSA ALGORITHM ELEMENTS IN TERNARY AFFINE TRANSFORMATIONS IN ENCRYPTION-DECRYPTION OF IMAGES

Regarding image encryption, a crucial task is to implement the application of such an RSA algorithm which will provide an opportunity:not to decay the cryptographic stability of the RSA algorithm; to ensure complete noisiness of an image to prevent the application of methods of visual image processing.An algorithm for encryption-decryption of monochrome images using elements of the RSA algorithm as the most resistant to unauthorized signal decryption in ternary affine transformations is proposed.The developed algorithm is applied to images in which there are strictly delineated contours.Elements of the RSA algorithm are proposed to be used to construct the coefficients of ternary affine transformations.The proposed algorithm has higher cryptographic stability compared to the RSA algorithm.The ways of applying the elements of the RSA algorithm in affine transformations in encryption-decryption of images are described in this article.The results of modeling the affine modified cipher for cryptographic transformations of black and white monochrome images of a given dimension are presented.Modified models and algorithmic procedures of key generation processes, direct and inverse cryptographic transformations, which are reduced to matrix element-by-element operations by module, are developed.
Deformation of the Personality of a Public Servant as a Reason Disciplinary Offenses in the Public Service

This article is devoted to the problem of deformation of the personality of a public servant, as a reason condition for the commission of disciplinary offenses in the public service. Based on the analysis of the personal qualities of the civil servant, as well as the genesis of his illegal behavior, it is concluded that scientific research is necessary to study the personality of the civil servant as the subject of disciplinary legal relations, the mechanism of formation of his illegal behavior. The research data should be carried out as part of service-tort studies, as a direction of administrative tortology. It is concluded that in order to prevent deformation of the personality of a public servant, the following are necessary: detailed administrative and legal regulation of the mechanism of psychological selection using the methodology for identifying professional and personal qualities in relation to applicants, including using a polygraph; strengthening the importance and filling the gaps in the legal regulation of such personnel technologies as: mentoring, testing upon admission to the service and certification of public servants; development and implementation of a model of basic personal competencies; conducting a set of measures aimed at preventing and eliminating the problem of professional deformation of the personality of public servants.
Cryptanalysis of Kalyna Block Cipher Using Impossible Differential Technique

The block cipher KalynaKumar Gupta, Sunny hasGhosh, Mohona beenMohanty, Sraban Kumar accepted as an Ukrainian encryption standard in the year 2015. Kalyna supports block sizes and key lengths of 128, 256 and 512-bits. In this block cipher, the key size is either equal to or double the block size. Accordingly, there are five variants of Kalyna block cipher, i.e., Kalyna-128/128, Kalyna-128/256, Kalyna-256/256, Kalyna-256/512 and Kalyna- 512/512. This work analyzes the security of all Kalyna block cipher variants against impossible differential attack. For Kalyna-128/256 and Kalyna-256/512, we first construct 3-round distinguishers and extend them to launch 7-round key recovery attacks on these variants. For Kalyna-128/128, Kalyna-256/256 and Kalyna-512/512, 3, 4, 4-round distinguishers are constructed, respectively, and then used to launch 4,5,5-rounds key recovery attacks, respectively. Our 7-round attacks on Kalyna-128/256 and Kalyna-256/512 have time complexities as $$2^{230}$$ and $$2^{390}$$ and data complexities as $$2^{81}$$ and $$2^{98}$$ , respectively. Our 4, 5, 5-round attacks on Kalyna-128/128, Kalyna-256/256 and Kalyna-512/512 have a time complexity of— $$2^{103}$$ , $$2^{199}$$ and $$2^{454}$$ , respectively, with a data complexity of— $$2^{95}$$ , $$2^{192}$$ and $$2^{199}$$ , respectively. The attacks presented in this work are the first results on security analysis of different variants of Kalyna block cipher against impossible differential attack.
Comparatives Bring a Degree-Based NPI Licenser

Comparatives license the use of negative polarity items (NPIs) within their than-clause. What exactly constitutes the NPI licenser in comparatives? In this paper, I argue that it is the very status of being the standard in a comparison that constitutes the NPI licenser. Based on Zhang and Ling (2020)’s interval-subtraction-based theory on comparatives, I show that by serving as the standard in a comparison and playing the role of subtrahend in a subtraction equation, a than-clause is inherently downward-entailing. Moreover, it demonstrates strong negativity like the classical negation operator not does. Therefore, a than-clause licenses both weak and strong NPIs. Crucially, this NPI licenser is due to monotonicity projection based on degree semantics (implemented with intervals), not due to a set-operation-based negation operator.
Weighted Matrix-Based Random Data Hiding Scheme Within a Pair of Interpolated Image

Secure, high payload, reversibleBera, Debkumar dataJana, Biswapati hidingChowdhuri, Partha scheme with good visual quality is still an important research issue in data hiding andGiri, Debasis designing such a scheme is a technically challenging problem. Tseng et al. proposed a securely weighted matrix-based data hiding scheme for the binary image which can hide only two bits secret data within a $$(3 \times 3)$$ pixel block; meanwhile, Fan et al. suggested an improved weighted matrix-based data hiding scheme for grayscale image which can hide 4 bits secret data within a $$(3 \times 3)$$ pixel block. Both of these weighted matrix-based data hiding schemes performed only one modular sum of entry-wise multiplication operation between image block and weighted matrix. To improve the capacity along with visual quality, we have proposed an innovative, reversible, secure, high payload data embedding scheme in a random location of a pair of color image. The randomness has been achieved by using SHA-512 for selecting the image and PRNG is used to select the specific block of the desired image. The weighted matrix helps to embed the secret information by performing entry-wise multiplication with the image block. The embedding capacity has been increased by performing 16 repeated entry-wise multiplication operations and security has been enhanced by modification of the weighted matrix for each block. Finally, the experimental results are compared with existing state-of-the-art methods and observed that our scheme is superior in terms of capacity, quality, and security.