Reviewerly/exHarmony huggingface dataset:
Preserving Riau’s Malay Culture Through Virtual Environment Application

Abstract Riau Malay culture provides inspiration and guidance for the community. Malay culture that is based on religion provides many guidelines and advice for the community in acting. Unfortunately, the community is difficult to access Riau Malay cultural objects because of separated locations of each district in Riau Province. Additional factors, many Malay cultural objects have been damaged and lost. This research aims to develop a three-dimensional virtual environment application to facilitate community access in knowing and studying Riau’s Malay cultural objects. Starting from the initiation of the environment, making surface contours, creating environmental objects to the addition of cultural objects are the phases carried out in this study. The results of this study indicate that the application is very interesting and able to facilitate public access in knowing and preserving Riau’s Malay culture.
WTFHE: neural-netWork-ready Torus Fully Homomorphic Encryption

We are currently witnessing two arising trends, which have a huge potential to threaten our privacy: the invasive sensors of the Internet of Things (IoT), and the powerful data mining techniques, in particular we focus on Neural Networks (NN's). For this reason, powerful countermeasures must be called for service: namely end-to-end encryption. Such an approach however requires an encryption scheme that enables processing of the encrypted data - this is known as the Fully Homomorphic Encryption (FHE). In this paper, we revisit an FHE scheme named TFHE, which is suitable for evaluation of NN's over encrypted input data, and we suggest to incorporate a verifiability feature to the evaluation process. Since there already exist other variants of the original TFHE scheme-currently only implemented in C++, which is rigid-we further introduce a library for rapid prototyping of new concepts related to TFHE. Our library is implemented in Ruby, which is an interpreted language and which goes with an interactive shell. Hence any new method can be speedily verified before implemented as a high-performance library.
Classification of Linear Codes by Extending Their Residuals

An approach for classification of linear codes with given parameters starting from their proper residual codes or subcodes is presented. The base of the algorithm is the concept of canonical augmentation which is important for parallel implementations. The algorithms are implemented in the programs LengthExtension and DimExtension of the package QextNewEdition. As an application, the nonexistence of binary [41, 14, 14] codes is proved.
Affordance Requirements in Product Interface Design for Elderly User

The elderly find they have difficulty interacting with products as their physiological functions deteriorate. In interaction design, affordance, a design concept, provides a direction that guides the intuitive behaviors of users. Affordance is considered differently among design applications, and also plays different roles in designing user interfaces. This research aims to discuss the applications of affordance in designing product interfaces for the elderly through focus group interviews. With rice cooker interfaces as the research tool, we have invited 10 elderly people to express and exchange their subjective opinions on the operation and use of product interfaces. The research results show that: the product interfaces for the elderly should be designed to simplify functional affordance (FA), thus reducing the cognitive load of the elderly; conventional affordance (CA) should be designed based on the previous experience and knowledge of the elderly; and physical affordance (PA) should be presented in a streamlined and consistent manner. The research results can provide a reference for the intuitive design of product interfaces for the elderly, and promote effective interaction between elderly users and product interfaces, thereby improving the living quality of the elderly.
Graph Neural Networks for Prevention of Leakage of Secret Data

The study presents the design and development of security solution pertaining to prevention of leakage of secret data that is in transit (DIT) to be deployed in a Network Gateway, the Gateway is the link connecting the Trusted Network with the Un-trusted Network. The entire solution includes, tasks such as classification of data flowing in the network, followed by the confinement of the identified data, the confinement of the identified data is done either by tagging the data or by means of encryption, however the later form is employed to achieve confinement of classified data under secret category thereby achieving confidentiality of the same. GNN is used for achieving the categorization function and the results are found to be satisfying with less processing time. The dataset that is used is the publicly available dataset and is available in its labeled format. The final deployment will however be based on the datasets that is available to meet a particular requirement of an Organization/Institution. Any organization can prepare a customized dataset suiting its requirements and train the model. The model can then be used for meeting the DLP requirement.
Process Automation in the Translation of Standard Language Texts into Easy-to-Read Texts – A Software Requirements Analysis

Many people are denied access to information and communication because they cannot read and understand standard texts. The translation of standard texts into easy-to-read texts can reduce these obstacles and enable barrier-free communication. Due to the lack of computer-supported tools, this is a primarily intellectual process, which is why very little information is available as easy-to-read text. Existing approaches dealing with the automation of the intralingual translation process focus in particular on the sub-process of text simplification. In our study, we look at the entire translation process with the aim of identifying the characteristics of a software system that are required to digitize the entire process as needed. We analyse the intralingual translation process and create a model. In addition, we conduct a software requirements analysis, which we use to systematically analyse and document the demands put to the software architecture. The results of our study form the foundation of the development of a software system that can make the intralingual translation process more efficient and effective.
Peculiarities of Pb, Mo, Cu and Zn Distribution in Water of Artesian Aquifers (Within Kyiv Deposit)

In the article, the authors present their own results of the study of hydrogeochemical peculiarities of distribution of leading ecological-forming microelements (Pb, Mo, Cu and Zn) in potable artesian aquifers of Kyiv groundwater field.A comparative analysis of the values of maximum permissible concentrations (MPC) of the main macro-and microcoelements for potable groundwater in accordance with domestic and foreign regulatory documents was done.It was concluded that the most stringent as to the content of macroelements are the requirements of the World Health Organization, and as to the content of microelements are domestic standards, namely the Sanitary Rules (SanPiN 2.2.4-171-10).By use of statistical methods, the authors analised the investigated microelements in groundwater timed to Cenomanian-Callovian groundwater complex and Bajocian aquifer.As a result of the research the MPC excess for lead was established in single wells.In addition, it was found that the average concentrations of microelements in Bajocian aquifer are higher than that of Cenomanian-Callovian complex.It was suggested that the natural (lithological composition of the waterbearing stratum) and technogenic (aeration zone pollution by heavy metals, confining bed pinching out along the Dnieper River, hydrodynamic flow inversion) factors are mutually reinforcing, which affects the content of these trace elements in deep aquifers of the Dnieper-Donetsk artesian basin.The authors emphasize the need for further research aimed at establishing patterns of distribution and forms of migration of micro-and ultramicroelements in groundwater by use of thermodynamic modeling method.
A Transformer-Based Fusion Recommendation Model For IPTV Applications

Recommendation models are fundamental primitives of recommender systems that select contents to match users' interests. In real-life IPTV applications, a registered account is usually shared by multiple audiences, e.g., family members, invalidating the potential efforts in extracting user interests from the registered user profiles. Moreover, it is difficult to obtain explicit feedback from audiences due to the boring interactions between users and televisions in practice, i.e., using remote controls. Thus, designing recommendation algorithms to exploit user preference with implicit feedback is crucial for developing efficient recommender systems. In this paper, we present a deep model for IPTV applications, which generate recommendations using the implicit feedback of users. A fusion layer is designed on top of the Transformer framework to obtain the semantic preferences of audiences based on their behavior sequences. The presented model is shown to be effective in our real-life IPTV recommender systems. Empirical experiments on two open datasets also show that our method outperforms state of the art baselines.
Cyber Risks in Social Media

Social media is an internet tool often used by businesses to communicate with customers, clients, vendors and other businesses. It is used for financial transactions with customers and to pay employees and manage the company. But social media and the internet are fraught with risks that businesses should be aware of, risks that could impact their company, their employees and their clients. Companies need to be aware of what the social media risks are and mitigations that can be taken to reduce those risks. While social media threats cannot be removed, actions can be taken to reduce the probability that they will be successful and to reduce the impact if they succeed. The impact of a threat gaining internet access to a business could cripple a company financially, others could damage relationships, but all would impact the company's ability to grow and thrive.
The bibliometrical analysis of document flow within the topic “Research methods” (based on VINITI RAS Abstracts Journal “Informatics”)

Today the scientific research has become of increased significance for the library activities. This calls for implementing new research methods. The Abstracts Journal “Informatics” was analyzed for the publications on “Research methods” for the 10-year period; the findings are discussed, i.e. the rise of interest methods in the library and information community toward applying research, positive dynamics of the document flow with the 10-year doubling period. Over 100 research methods are identified. Thematically, the stable part of the document flows make approximately one-fifth of the total volume. Twenty three methods are used most frequently. The subject headings for these methods demonstrate stability which means permanent interest toward these methods and stable vectors of research methods development. Metric methods are dominating, including those being used in the digital environment. The increase of subject headings efficiency evidences on their increasing relevancy. Mobile document flows characterize the newest research methods. These are the methods being borrowed from other fields and used occasionally in the library and information studies. “The research methods” topic appears to be a trending and a developing one. The core methods are defined. Nevertheless, the major part of the document flow remains decentralized and comprises many new vectors that, while being quite relevant, have not found their niche in the library science research.
On the Convergence of Input-Output Fuzzy Cognitive Maps

Fuzzy cognitive maps are recurrent neural networks, where the neurons have a well-defined meaning. In certain models, some neurons receive outer input, while other neurons produce the output of the system. According to this observation, some neurons are categorized as input neurons and the others are the state neurons and output neurons. The output of the system is provided as a limit of an iteration process, which may converge to an equilibrium point, but limit cycles or chaotic behaviour may also show up. In this paper, we examine the existence and uniqueness of fixed points for two types of input-output fuzzy cognitive maps. Moreover, we use network-based measures like in-degree, out-degree and connectivity, to express conditions for the convergence of the iteration process.
Bridging Conceptual Models and Architectural Interchange for Adaptive Instructional Systems

This paper serves to connect the papers between the AIS conceptual modeling group and the architectural interchange group by deriving requirements for the required components and the information that they need to exchange. It serves as an update to the original work on the subject, prior to the establishment of the conceptual modeling subgroup.
Dealing with Noise in Cluster Pattern Interface

Cluster Pattern Interface (CLUSPI) [6] is an original 2D encoding and a related technology for direct point-and-click interfaces. It allows determining the objects printed on a surface pointed out by the user. The surface is covered by a layer of code composed of tiny dots, which blends with the original surface texture. In practice, however, some of the dots of the code may be damaged or obscured, which creates decoding challenges. In this work we develop theoretical solutions to some of the challenges related to decoding noisy patterns.
Facial Emotion Detection using Action Units

During the last ten years, researchers have paid close attention to the study of emotions to improve communication between humans and machines. A system is proposed with the support of the unit to determine the different types of resources for the unit to automatically detect facial expressions. The proposed system automatically recognizes the faces of recorded images and encodes them into seven parameters: “Anger”, “Disgust”, “Fear”, “Surprise”, “Sadness”, “Contempt”, “Happiness”. This document focuses on the automatic extrusion of facial features and the detection of emotions in a digital bilateral image of the face. Some improvements and simplicity are based on previous research. This method was tested in the Advanced Visual Database and in a natural building database to validate the reliability of the experimental algorithm.
Unlearning Scanner Bias for MRI Harmonisation in Medical Image Segmentation

The combination of datasets is vital for providing increased statistical power, and is especially important for neurological conditions where limited data is available. However, our ability to combine datasets is limited by the addition of variance caused by factors such as differences in acquisition protocol and hardware. We aim to create scanner-invariant features using an iterative training scheme based on domain adaptation techniques, whilst simultaneously completing the desired segmentation task. We demonstrate the technique using an encoder-decoder architecture similar to the U-Net but expect that the proposed training scheme would be applicable to any feedforward network and task. We show that the network can be used to harmonise two datasets and also show that the network is applicable in the common scenario of limited available training data, meaning that the network should be applicable for real-world segmentation problems.
Vision‐based map building and path planning method in unmanned air/ground vehicle cooperative systems

To reduce the casualties and improve the efficiency of robot, unmanned air/ground vehicle (UAV/UGV) cooperative systems are proposed. In this study, mathematical algorithms are applied in a typical-rescue scenario. As a ‘flying eye’, the UAV provided the global information by vision sensor. Then, the images were processed with SURF algorithm and image binarisation to model the environment. Based on the UAV's information, the optimised A* algorithm was proposed. Finally, a feasible path was designed for UGV to rescue. Experiments are performed to evaluate the performances of the proposed method. Results show that SURF algorithm and image binarisation can realise the accuracy and robustness of map building. The optimised A* algorithm can provide a real-time and feasible path.
Performance and Implementation Modeling of Gated Linear Networks on FPGA for Lossless Image Compression

Over recent years, imaging systems have seen explosive increase in resolution. These trends present a challenge for resource-constrained embedded imaging devices. Efficient image compression is essential to reduce bandwidth consumption and to increase the capability of on-board storage. Especially, for imaging systems where information loss is not allowed, for example, in medical, military and remote sensing imaging systems. This paper explores the use of Gated Linear Networks (GLNs) for development of embedded lossless compression systems. GLNs have proved themselves via PAQ archiver series, that have been ranked among the top across several lossless compression benchmarks. We propose an architecture of single neuron GLNs with emphasis on high throughput performance. Proposed architecture is validated by hardware level tests and described by scalable models that allow estimations of both performance parameters and requirements for hardware resources.
Captivating Product Experiences: How Virtual Reality Creates Flow and Thereby Optimize Product Presentations

Well-designed and informative product presentations can support consumers in making purchase decisions. There are plenty of facts and details about a product of interest. However, also emotions are an important aspect for the purchase decision. The unique visualization opportunities of virtual reality (VR) can give users of VR applications the feeling of being there (telepresence). The applications can intensely engage them in a flow experience, comprising the four dimensions of enjoyment, curiosity, focused attention and control. In this work, we claim that VR product presentations can create subjective product experiences for consumers and motivate them to reuse this innovative type of product presentation in the future, by immersing them in a virtual world and causing them to interact with it. To verify the conceptual model a study was conducted with 551 participants who explored a VR hotel application. The results indicate that VR product presentations evoke positive emotions among consumers. The virtual experience made potential customers focus their attention on the virtual world and aroused their curiosity about getting more information about the product in an enjoyable way. In contrast to the theoretical assumption, control did not influence the users' behavioral intentions to reuse VR product presentation. We conclude that VR product presentations create a feeling of telepresence, which leads to a flow experience that contributes to the behavioral intention of users to reuse VR product presentations in the future.
An Intuitionist Fuzzy Method for Discovering Organizational Structures that Support Digital Transformation

With recent developments in information technology and the advent of new communication practices, organizations are currently facing enormous changes in the design of their activities and their development strategy. Unfortunately, these changes are not so easy to model and to insert into digital transformation processes. The digital transformation (DT) is triggering changes in operations and organizational processes. The results of this transformation are not often predictable. Sometimes digital transformation leads to entirely new solutions and has a deep impact on the organization. Understanding how organizations operate when undergoing digital transformation is essential, as it is the right way to overcome organizational obstacles and find the optimal path for future-oriented development. By focusing on the processes and on the organizational units resulting from an analytical approach, we show that the development of digital strategies reveals new processes and new organizational structures resulting from emerging strategies. More specifically, we find that a DT is constantly evolving. This paper deals with a new approach to drive the transformation of the organization regarding to digital transformation. Indeed, we propose a fuzzy intuitionist approach to discover organizational structures that support digital transformation. The theory of intuitionist fuzzy sets handles uncertain situations, by extension of the classical fuzzy theory, with the integration of the concept of hesitation.
Authentication of Face using Matlab

The face detection technique is a worldwide used technique which is widely used in many multinational companies and the business purposes also. This gives a clear picture of the correct attendance marking by recapturing the whole face. The office staff is also having the attendance criteria therefore the specification is also necessary for them to apply these criteria in processing the correct flow of the given procedure. Yes, the thumb printing part is considered important for them but the face detection theory is considered more advance and appropriate than the thumb printing technique.
THz wireless communication system based on wavelet transform

Summary With a very wide frequency band not allocated at present, THz waves have many optimal characteristics such as high transmission rate, large capacity, and high security. The research of THz communication technology has become a hotspot in wireless communication. For THz wireless communications, it is crucial to study advanced electrical signal processing techniques. In this paper, in view of the shortcomings of traditional orthogonal frequency division multiplexing (OFDM) technology, we propose wavelet transform orthogonal multicarrier modulation method in THz system. In addition, we study THz channel coding technology to ensure that the THz wireless communication baseband system has better bit error rate (BER) performance and low computational complexity. Based on above, a THz wireless communication baseband system is conceived.
A Comparison of Cartoon Portrait Generators Based on Generative Adversarial Networks

Cartoon portraits are deformed figures that capture the appearance and characteristics of people, and are often used to express one’s image in applications such as social media, games, application profiles, and avatars. Current research regarding the translation of facial images into cartoon portraits focuses on translation methods that use unsupervised learning and methods for translating each part individually. However, studies that reflect the unique personality of professional illustrators have yet to be published. In this study, we examine a suitable network for reflecting the unique personality of a professional illustrator. Specifically, we will consider four networks: pix2pix, Cycle Generative Adversarial Network (CycleGAN), Paired CycleGAN, and Cyclepix. The main difference between these is the loss function. Pix2pix takes the error between the training data and the generated data. However, the main difference in CycleGAN is that it takes the error between the input data and the re-converted data obtained by further translating the generated data. Cyclepix takes both errors. Additionally, pix2pix and Paired CycleGAN require that the input of the discriminator be input data and generated data pairs. The difference between CycleGAN and Cyclepix is that only the input of the discriminator is generated data. Using the cycle consistency loss, considering only the input of the discriminator as generated data, and using the L1 Loss for supervised learning, the experimental results showed that the evaluation of CycleGAN and Cyclepix was high. This is useful for generating high-precision cartoon portraits.