Reviewerly/exHarmony huggingface dataset:
Symmetric System for Exchange Information on the Base of Surjective Isomorphism of Rings

The paper focuses on the building of a cryptosystem by using finite associative-commutative rings with unity. The algorithms for constructing such rings and exchanging information between subscribers on the basis of a special case of isomorphisms (surjective isomorphisms) are described. Encryption and decryption processes in ring G <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</inf> of order <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$k$</tex> are reduced to computation over ring Z <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</inf> (residues modulo <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$k$</tex> ) by using the linear Diophantine equations over ring Z <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</inf> The complexity of computations in cryptosystems is relatively simple but using surjective isomorphism, all computations are performed over an area that is inaccessible to hackers. The advantages of the system are that: a) the method of frequency analysis is not applicable to it. b) we avoid building tables of ring operations by using surjective isomorphism; c) the rings can be chosen with relatively small orders, which simplifies calculations during encryption and decryption; and d) the solution algorithm of system linear Diophantine equations is polynomial. The disadvantage of our system is that the length of the encryption text is twice as large as the length of the message.
Secure and Encrypted Communication System on Mobile Devices

The term ‘Secure Communication’ constitutes as one of the most important factors of the current types of communication. At today's communication, where the power and the capabilities of the modern computers are continuously rising, it is vital that the encryption systems must keep up with this flow by upgrading the security and the levels of the offered encryption of the data, to ensure the confidentiality and integrity of the exchanged information but furthermore to provide the validation of both of the parties that are participating in the communication. For this purpose, an encryption system will be developed for Mobile (Phone, Tablet) use, in which the cryptographic algorithm AES256 will be deployed for the data encryption. In this paper the overall design is presented and a thorough, organized, and controlled study is performed about the provided security of the encryption system that is being developed. Furthermore, in this algorithm embedded details of advanced encryption principles will be inserted for the purpose of establishing an even higher level of security amongst the parties of the communication. Finally, the level of the offered encryption will be thoroughly examined, in conjunction with the total required time of the message's transmission.
Automatic Speaker Verification on Compressed Audio

Voice-based phishing and wire-fraud attacks have become a topical problem in the recent years due to the emergence of advanced AI-based speech synthesis models. These models can generate realistic speech signal of a known target that is difficult to differentiate from a bonafide voice of real human. This proved to be an issue by the recent security reports related to vishing attacks on bank call centers, fraud or pranking of public figures, and spoofing of voice authentication systems. Current approaches to address voice fraud issue are based on applying an Automatic Speaker Verification (ASV) system. In most cases, these systems are tuned on datasets that consist of wideband quality bonafide and spoofed voice samples. This makes ASV systems vulnerable to speech signal degradation caused by voice encoding in cellular network and Voice over IP (VoIP). However, performance evaluation of ASV (namely Equal Error Rate (EER) estimation) is almost exclusively available only for the cellular networks. Thus, performance of ASV systems for modern VoIP applications remains unclear. In this paper, we evaluate the modern ASV systems on audio compressed with codecs used in both cellular networks (AMR and GSM codecs) and VoIP applications (G.711, G.722, AAC, Lyra and Opus codecs). In addition, ASV performance was tested using popular VoIP application (Discord). Obtained results have shown that codec application results in considerable (up to two times) EER increase compared to the baseline results. Moreover, we observed up to three times increase in EER on data transmitted using Discord. We propose to apply hard samples mining to the training process in order to improve the accuracy of ASV systems on compressed voice samples. It allows to reduce EER from 21% down to 16% even for the most distorted samples obtained after aggressive voice compression by GSM codecs. Note, that improvement for real VoIP application is even higher - with EER on Discord data decrease from 35% to 20%.
The Concept Of Creating A Complex Cryptocompression Image Protection System In Infocommunications

The concept of creating a complex image cryptocompression system is based on changing the standard compression process and integrating cryptographic transformation. The basic requirements for its functional components are formulated. Changing the standard compression process allows you to hide the semantic content of the image by creating code combinations of two types, namely information and system components. The information component does not require additional protection. The system component is the key element for decrypting the information component. Cryptographic transformations are used to ensure the security of the system component.
Technology of Coding Video Images in Structure-Cluster Space to Increase Efficiency and Reliability

The imbalance between the reliability of the received information and the speed of its reception, taking into account onboard channels of transmission of video data is justified. The information concerning reducing the informational intensity of video data existing technologies’ shortcomings is given. Among such shortcomings: the gain of efficiency is compensated by the semantic component of the video destruction. Therefore, the risk of informational reliability losing increases. Among such shortcomings: the gain of efficiency is compensated by the semantic component of the video destruction. Therefore, the risk of informational reliability losing increases. Among such shortcomings: the gain of efficiency is compensated by the semantic component of the video destruction. Therefore, the risk of informational reliability losing increases. It is proposed to solve the imbalance by developing new methods of encoding transformed video images. This will increase the level of transformed video compression in ensuring the desired reliability conditions. The information about the transformed video segments encoding in case of their preliminary clustering usage is provided. It is justified that clustering of video segments takes into account the number of series in the binary syntax description of the transformer components. The main stages of the developed forming structural clusters of clustered component-transforms, according to the meaning of their double description – number of unit’s series method are given..
Technology of Coding Video Resource to Increase Their Integrity and Availability

The coding technologies development is proposed to be organized based on standardized concepts. The first difference concerns the additional consideration of uneven distribution of detailed information in the video frame. There is a potential for establishing sections of the video frame: with a minor impact on semantic integrity preserving of the video resource (video resource’s sufficient level integrity); with a significant impact on video resource’s semantic integrity preserving. That is, the video segments have a mixed content. Thus, the purpose of the article is to develop a method of increasing the video resource availability, taking into account the segments structural and statistical saturation level. A method was created to reduce the bit volume of the video resource significant segments for the semantic integrity preservation, which have a mixed content of micro-segments with different structural and statistical saturation levels.
Dynamic Content Generation Methods Based on User Behavioral Ranking

Most information resources have moved away from static to dynamic content. This is caused not only by the peculiarity of creating resources, but also by the desire of developers to deliver the necessary content to the client in the minimum number of clicks. The article discusses the method of generating dynamic content for various user groups, which are grouped on the basis of their behavior. The practical study was to assess the correctness of the automatic ranking of users who were offered an interface different from other user groups.
Method Using Partial Data to Confirm Completion of the Tree Parity Machines Synchronization

This article proposes an approach to partially use the values of synapses for mutual synchronization of neural networks. Tree parity machines are used as mutually synchronizing neural networks. Confirmation of the completion of mutual synchronization is performed by comparing the hash calculated based on the values of the synapses of neural networks. Partial use of synapse values is proposed to save part of the data from transmission over the network in direct or encrypted form. The study experimentally confirmed the possibility of such an approach and the allowable amount of unused data. Improvements to this method have also been proposed and experimentally tested. The tasks of further research are determined.
Mathematical Model of the Process Encoding and Transmitting Video in Face of Cyberattacks

This article was prepared on the basis of contemporary threats analysis to information and telecommunication systems. The protecting of videoinformation resource was urgency. We have shown source coding segment and a segment transmission steps DDoS attack, introduced a mathematical notation and the transition operators, operators action DDoS attack, describe the most significant manifestation of the type of attack “Distributed Denial of Service”. Were offered the basic requirements for source coding technology to fight (localization) DDoS in information and telecommunication systems.
Processing Technology of a Flow of the Differential Provided Frames in Objective Video Inspection Infocommunication Systems

The basic principles of dynamic images compression method creation of a stationary background on the basis of differential provided frame formation are justified. The technology of differential provided frame partition on components is developed: dynamic component, binary mask of a stationary background and matrix of signs, with their subsequent processing. It is shown that the developed encoding technique provides potential opportunities for abbreviation of volume and additional increase in a compression ratio of stationary background dynamic images, and as a whole leads to abbreviation of time for their processing.
Experimental Face Recognition System Based On Improved Artificial Intelligence Model

A comparative analysis of the existing face recognition systems was conducted; their advantages and disadvantages were revealed. The main functional requirements to the experimental sample of the face recognition software system with a built-in improved model of artificial intelligence are determined, and the use cases are formed. The interface of the experimental system, the main capabilities of the created sample are presented. The results of the experiments are given.
Platform Adaptive Integer AC Technology Combination

The purpose of this study is to find ways to reduce the time of delivery of visual information to the user by improving the coding algorithms. In the course of the study, methods based on arithmetic coding were used. The basis is the JPEG algorithm with the introduction of arithmetic coding while eliminating the following shortcomings: it removes a series of repetitions that are equal to one and the last pair after the RLE processing stage. These modifications double the compression efficiency compared to the classical approach. It is also important to note the effect of decreasing the number of elements in the dictionary after zigzag scanning of a group of transformants.
Video Data Compression Coder Based on the Method of Structural Digital Image Representation

The usage of digital images in every aspect of computer and telephone application requires new means of pictures storage, compression and restoration. Such a method is presented in this article, based on discrete wavelet transformation and usage of binary sequences. During investigation, expedience of the use of structural code in the tasks of compression of data was proved. The structural signs of binary sequences of image presentations and limitations that on are laid on them are defined. The rule of determination of amount of binary sequences which form structural groups is described. Also, the rule of calculation of sequence number for binary sequence based on the amount of bit changes is described. The estimation of the expected degree of compression is done for the sequences of different length. The approach is proven to be more adjustable and preferable compared to classic algorithms of image comparison and storage.
Cross-Lingual Named Entity Recognition for the Ukrainian Language Based on Word Alignment

Processing of low-resource languages is one of the most challenging tasks in the area of natural language processing. The lack of datasets makes it complex to create and train corresponding models that are available for high-resource languages. In this paper, the possibility of the usage of the word alignment mechanism for the performing of the cross-lingual tasks has been analyzed for the low-resource language by the example of the Ukrainian language for the solving of the named entity recognition task. Different state-of-the-art word alignment methods have been analyzed. The advisability of the usage of the pre-trained multilingual models for the word alignment of low-resource languages has been shown. The experimental verification of the effectiveness of the chosen word alignment method for the solving of the named entity recognition for a Ukrainian corpus has been performed with different options. The results obtained may indicate the possibility of the usage of the considered word alignment method for the solving of different sequence labeling tasks for the Ukrainian language by performing the cross-lingual mapping of the results for the target English language.
The Methods of Joint Signal Discrimination and Parameters Estimation in non-Gaussian Noise

The use of the probability density distribution of random processes leads to certain difficulties in the implementation of signal processing algorithms, especially for processing non-Gaussian processes. One of the advanced approaches that allows describe non-Gaussian random processes is to use the moment and cumulant description of random variables. Based on this approach, two new methods of joint signal discrimination and parameter estimation are proposed. Nonlinear signal processing and taking into account the parameters of non-Gaussian processes can significantly improve the quality of signal processing compared to known classical methods.
Research of Prospective Encoding Methods for Multimedia Content Protection

the results of the study of a significant number of modern and prospective methods of information protection, in which various methods of encoding of multimedia files are used, are consolidated in the article. The authors focused on special approaches used during cryptographic protection of graphic images, on separate audio encryption schemes and on some methods of hiding regions of interest (ROI) in video materials. Based on existing threats to information security and on the wide variety of effective methods of protecting multimedia components, a system of comprehensive protection of digital multimedia content was formed.
Dynamic obstacle avoidance and trajectory planning of five-axis redundant industrial manipulator

Aiming at the problem that five axis redundant industrial manipulator dynamic obstacle avoidance and trajectory planning algorithm does not consider the minimum difference of each joint of the manipulator, which leads to low success rate of obstacle avoidance planning, slow convergence speed of path cost and long time of obstacle avoidance planning, a simulation study on dynamic obstacle avoidance trajectory planning of five axis redundant industrial manipulator is proposed. According to the D-H rule, the coordinate system of each link joint of the five axis redundant industrial manipulator is established, and the forward and inverse kinematics of the five axis redundant industrial manipulator is analyzed. AABB's hierarchical bounding box tree algorithm is used to detect the collision of five axis redundant industrial manipulator. This paper uses harmony search algorithm to plan the obstacle avoidance path of five axis redundant industrial manipulator, determines the objective function and constraints of the optimization problem, sets algorithm parameters, initializes harmony memory, creates new harmony, updates harmony memory, checks and searches the target state, achieves the maximum number of iterations, and realizes the dynamic obstacle avoidance and trajectory planning of five axis redundant industrial manipulator. The experimental results show that the path cost of the proposed algorithm converges faster, and can effectively improve the success rate of obstacle avoidance planning and shorten the time of obstacle avoidance planning.
Federated Learning over Coupled Graphs

Graphs are widely used to represent the relations among entities. When one owns the complete data, an entire graph can be easily built, therefore performing analysis on the graph is straightforward. However, in many scenarios, it is impractical to centralize the data due to data privacy concerns. An organization or party only keeps a part of the whole graph data, i.e., graph data is isolated from different parties. Recently, Federated Learning (FL) has been proposed to solve the data isolation issue, mainly for Euclidean data. It is still a challenge to apply FL on graph data because graphs contain topological information which is notorious for its non-IID nature and is hard to partition. In this work, we propose a novel FL framework for graph data, FedCog, to efficiently handle coupled graphs that are a kind of distributed graph data, but widely exist in a variety of real-world applications such as mobile carriers’ communication networks and banks’ transaction networks. We theoretically prove the correctness and security of FedCog. Experimental results demonstrate that our method FedCog significantly outperforms traditional FL methods on graphs. Remarkably, our FedCog improves the accuracy of node classification tasks by up to 14.7%.
Design and Control of a Novel Detachable Driving Module for Electrification of Manual Wheelchairs

We developed a detachable electric module that converts a manual wheelchair into an electric wheelchair. The existing electric module requires several parts to be fastened to the wheelchair, which complicates its assembly. In addition, because the overall size of the wheelchair increases after its assembly and the turning radius increases compared to the manual wheelchair, controlling the wheelchair becomes difficult for the user. To compensate for these shortcomings, a new type of electric module composed of two omni-wheel driving units is proposed in this study. Because the two modules can independently move forward or backward and change directions, the same movement as that of the existing manual wheelchair is possible. In addition, a mechanism for easy attachment and detachment is proposed and its versatility is verified by mounting it on various wheelchairs. For the stable operation of the module, field-oriented control was applied, and the wheelchair was controlled for stably moving against external forces and ground disturbances according to the module mounting location. A driving test was conducted according to the mounting location of the developed module, and the proposed driving module and applied algorithm were verified through statistical analysis.
An Alternative Hard-Parameter Sharing Paradigm for Multi-Domain Learning

Hard-parameter sharing in multi-domain learning (MDL) allows domains to share some model parameters in order to reduce storage cost while improving prediction accuracy. One traditional paradigm of the sharing practice borrows an idea from multi-task learning (MTL), which is to share bottom layers of a deep neural network among domains while using separate top layers for each domain. However, it is unclear whether the effectiveness of sharing bottom parameters in MTL can transfer to MDL or not. Therefore in this work, we revisit this common practice via an empirical study on image classification tasks on a diverse set of visual domains and make two surprising observations. (1) Using separate bottom-layer parameters could achieve significantly better performance than the common practice and this phenomenon holds for the different number of domains jointly trained on different backbone architectures with different quantities of domain-specific parameters. (2) A multi-domain model with a small proportion of domain-specific parameters from bottom layers can achieve competitive performance with independent models trained on each domain separately. Our observations suggest that people adopt the new paradigm of using separate bottom-layer parameters as a stronger baseline for model design in MDL.
Contextualization

Abstract The term ‘contextualization’ concerns the uses to which AI is put. This overarching task is a key part of the transition from laboratory to society. It is also a complex and often underestimated process. In practice AI will have to operate in specific contexts, each with its own systems, practices, rules and logic. This process is known as contextualization and involves adaptation and integration, which are both very time-consuming. That delays the maturation of new system technologies. As a result, it often takes longer than we might expect for them to become part of our everyday lives. The overarching task of contextualization therefore raises the following question: ‘how will AI work?’
A Novel CDMA-Based Secret Message Multiplexing Scheme by Image Data Hiding

In this paper, based on the concept of Code Division Multiple Access (CDMA), we propose an innovative secret message multiplexing scheme by digital image data hiding. Multiple secret messages distributed for several participants are encoded into a CDMA codeword through CDMA multiplexing and then embedded into a grayscale image. At the receiving side, each intended recipient will be assigned a distinct spreading code as the secret key for data extraction. In this way, even the authorized user can only extract his or her own secret message using an exclusive secret key and has no knowledge about other user’s secret. This characteristic helps to ensure data security. Experimental results demonstrate that the scheme is also resistant to Gaussian noise attack, salt-and-pepper noise attack, and cropping attacks. Those merits sustain the feasibility of the proposed scheme.