bluuebunny/crossref_metadata_2025 huggingface dataset:
Analogies for modeling belief dynamics
Authors: Olsson Henrik , Galesic Mirta
Published: September 2023

Belief dynamics plays an important role in shaping our responses to natural and societal phenomena ranging from climate change and pandemics to immigration and conflicts. Researchers often base their models of belief dynamics on analogies to other systems and processes, such as epidemics or ferromagnetism. Like other analogies, analogies for belief dynamics can help scientists to notice and study properties of belief systems that they would not have noticed otherwise (conceptual mileage). However, forgetting the origins of an analogy may lead to some less appropriate inferences about belief dynamics (conceptual baggage). We review various analogies for modeling belief dynamics, discuss their mileage and baggage, and offer recommendations for using analogies in model development.
LRATD2 is differentially expressed in central nervous system metastasis in human breast cancer.
Authors: Mamoor Shahan
Published: September 2023

Metastasis to the brain occurs in a significant fraction of patients with breast cancer (1-3). We mined published RNA-sequencing and microarray data (4, 5) to compare primary and metastatic tumor transcriptomes for the discovery of genes associated with brain metastasis in humans with metastatic breast cancer. We found that LRAT domain-containing 2, encoded by LRATD2, was among the genes whose expression was most different in the brain metastases of patients with metastatic breast cancer as compared to primary tumors of the breast. LRATD2 mRNA was present at increased quantities in brain metastatic tissues as compared to primary tumors of the breast. Expression of LRATD2 in primary tumors, however, was not correlated with patient survival outcomes. Modulation of LRATD2 expression may be relevant to the biology by which tumor cells metastasize from the breast to the brain in humans with metastatic breast cancer.
Control of NFKB2 by NOD2.
Authors: Mamoor Shahan
Published: September 2023

We provide evidence here from overexpression-based gain-of-function studies in human cells (1, 2) which demonstrate control of nuclear factor kappa B subunit 2, NFKB2, by the NLR (nucleotide-binding oligomerization domain-like receptor) family protein NOD2.
The Impact of AI on the Future of Voice Acting
Authors: Niroula Bhawani
Published: September 2023

The integration of Artificial Intelligence (AI) into the field of voice acting is redefining the landscape of this timeless craft. Voice acting, characterized by its blend of artistry and storytelling, is undergoing a profound transformation as AI technology permeates every facet of the industry. This research paper explores the multifaceted impact of AI on voice acting, encompassing character creation, performance recording and editing, collaboration, and remuneration structures. AI's influence on character creation is particularly noteworthy, expanding the horizons of character diversity and authenticity. AI-driven voice performances enable the portrayal of an array of characters, from robotic and extra-terrestrial beings to those hailing from diverse cultural backgrounds. The ability to craft lifelike accents and dialects with AI empowers voice actors to infuse their performances with nuanced realism. AI's integration into performance recording and editing processes streamlines workflows, automates arduous tasks, and provides real-time feedback, affording voice actors more time for artistic refinement. Collaboration within the industry is greatly enhanced, as AI-driven tools facilitate seamless interactions between actors and producers, transcending geographical boundaries and temporal constraints. AI also leaves its mark on remuneration structures, optimizing workflows and reducing production costs, leading to more competitive compensation packages for voice actors. Furthermore, AI introduces novel opportunities, such as the creation of digital libraries and virtual performances, diversifying income sources and transforming traditional models. As the influence of AI on voice acting deepens with each technological advancement, the craft is poised for a transformative future. This evolving synergy between human artistry and AI innovation not only redefines the creative possibilities within voice acting but also reinvigorates the industry's enduring relevance in the ever-evolving landscape of entertainment. Embracing this transformative era, voice actors and industry stakeholders must adapt, fostering a dynamic and prosperous future for voice acting in the digital age.
Vai trò của thực phẩm trong khủng hoảng khí hậu
Authors: Nguyen Minh-Hoang
Published: September 2023

Thức ăn đóng vai trò cực kỳ quan trọng trong cuộc sống. Nó không chỉ cung cấp năng lượng và chất dinh dưỡng cho sự sống và phát triển của con người, mà đôi khi nó còn là hình thức để con người đạt thỏa mãn các nhu cầu văn hóa và xã hội [1]. Việc dân số toàn cầu đang gia tăng nhanh chóng qua từng năm, thức ăn lại ngày càng trở nên quan trọng để đảm bảo an ninh lương thực. Tuy nhiên, các hoạt động nông nghiệp và sử dụng đất đai cho sản xuất thực phẩm là một trong những nguồn phát thải nhà kính chính, góp phần làm biến đổi khí hậu.
Evaluating Intersectional Fairness in Algorithmic Decision Making Using Intersectional Differential Algorithmic Functioning
Authors: Suk Youmi , Han Kyung T.
Published: September 2023

Ensuring fairness is crucial in developing modern algorithms and tests. To address potential biases and discrimination in algorithmic decision making, researchers have drawn insights from the test fairness literature, notably the work on differential algorithmic functioning (DAF) by Suk and Han (2023). Nevertheless, the exploration of intersectionality in fairness investigations, within both test fairness and algorithmic fairness fields, is still relatively new. In this paper, we propose an extension of the DAF framework to include the concept of intersectionality. Similar to DAF, the proposed notion for intersectionality, which we term "interactive DAF," leverages ideas from test fairness and algorithmic fairness. We also provide methods based on the generalized Mantel-Haenszel test, generalized logistic regression, and regularized group regression to detect DAF, interactive DAF, or other subtypes of DAF. Specifically, we employ regularized group regression with three different penalties and examine their performance via a simulation study. Finally, we demonstrate our intersectional DAF framework in real-world applications on grade retention and conditional cash transfer programs in education.
FIXED TARGET TRAINING: MENINGKATKAN AKURASI SPIKE ANGGOTA UKM BOLA VOLI STKIP BINA MUTIARA SUKABUMI
Authors: Irawan Debi Krisna , Bakhri Rafdlal Saeful , Antafani Ismy
Published: September 2023

The techniques used to attack or score in sports games are important techniques to master. The spike technique in volleyball is carried out with the main objective of producing a score in order to win. The ball that is hit in the spike technique, besides having to be strong and fast, of course, must be directed at an empty area or difficult for the opponent to anticipate. Good spike accuracy is one of the key factors in volleyball, which can contribute to the team's success in scoring points. Therefore proper training is needed to be able to improve volleyball spike skills. This study aims to investigate the effect of fixed target training on increasing the spike accuracy of members of the Volleyball UKM STKIP Bina Mutiara Sukabumi. This study used an experimental method through the One-Group Pretest Posttest design. The research sample consisted of 10 members of STKIP Volleyball UKM Bina Mutiara Sukabumi who were selected by purposive sampling and received fixed target training. The research data were obtained using the volleyball spike test which was carried out at the pretest and posttest stages. The results of data analysis through paired sample t test showed that the p value <0.05. Based on this, it was stated that fixed target training had a positive and significant effect on the results of the spike accuracy of members of the STKIP Volleyball UKM Bina Mutiara Sukabumi.
ANALISIS SHOOTING FUTSAL PUTRA PADA PERTANDINGAN LIGA PROFESIONAL 2021/2022
Authors: Setiawan Aldi , Umam Ramadhan Chairul , Saeful Bakhri Rafdlal
Published: September 2023

This study discusses the analysis of basic shooting techniques and shooting areas for the Bintang Timur Surabaya team in the 2021/2022 proof-of-work league matches. The purpose of this study was to determine the basic technical abilities of the futsal shooting game in the Bintang Timur Surabaya team in the 2021/2022 professional futsal league and the dominant shooting and area shooting techniques carried out by the Bintang Timur Surabaya team. The method used is descriptive quantitative which later the data will be analyzed, processed and arranged to find existing problems. The source of the data taken was by watching the replay of the Bintang Timur Surabaya team in the second round which included an analysis of shooting techniques. The results of the analysis of the basic shooting techniques and shooting areas of the Bintang Timur Surabaya team during the second round. the total shot taken was 459 times, the instep was shot 300 times (65%), the toe was 48 times (11%) and the foot was shot 111 times (24%). Based on the results that have been done, it can be said that the characteristics of the shooting techniques carried out in Professional Futsal League matches use more of the instep. Shooting area (kicking area) The characteristics of the shooting area in the 2021/2022 Professional Futsal League match for the East Bintang Surabaya Team are as follows: a total of 459 shots were taken, with shooting in the weak area 214 times (47%) and shooting in the strong area as much as 245 times (53%). So it can be said that the characteristics of shooting techniques carried out in Professional Futsal League matches are mostly carried out in the strong area.
Story of Cohesion. On the History of an Academic Institution
Authors: ZACHAR PODOLINSKÁ Tatiana , POPELKOVÁ Katarína
Published: September 2023

"This book is a contribution to the anthropology of academic institutions in Central Europe from the latter half of the 20th century until nowadays. On the background of longue durée processes and profound political, ideological, and economic transformations, the book displays the micro-temporalities in the life of the Institute of Ethnology and Social anthropology within the Slovak Academy of Sciences. The book offers critically self-reflective combination of the anthropological perspective, historical ethnography, and memory studies. Besides using the archive, printed and electronic sources, the Authors also conducted comprehensive qualitative research among the members of the Institute to capture imprints of the internalised (hi)stories, attitudes, feelings, and emotions. Using qualitative ethnography, the Authors also pictured the intimate atmosphere and very nature of the Institute as a living organism during the socialist, post-socialist, and post- transitional era. Tracing the internal history of the Institute based on the generations of Founders and Builders, and the Transformation and Innovation generations, the Authors discovered that what is essential in the success of the Institute is a strong positive auto-narrative of internal cohesion and team support, transmitted from one generation to another as a precious legacy. "
Gamma Knife Radiosurgery as a Dependable, Effective Option for Glomus Jagulare Tumors: A Single Institution Long-Term Experience and Review of the Literature
Authors: F.A. Hafez Raef
Published: September 2023

Objective: Glomus jugulare tumors (GJTs) are benign, slowly growing tumors, highly vascular, with the potential to infiltrate neurovascular structures. Surgical treatment is usually associated with high morbidity and even death. Gamma Knife radiosurgery (GKRS) has been established as an effective treatment option. This retrospective study aims to report and confirm GKRS.'s long-term effectiveness and safety for GJT patients. Methods: A total of 65 patients with GJTs were treated with GKRS, at the authors' center from 2005 to 2020, with a mean follow-up period of 87.7 months. The mean treated GJT volume was 5.4cc with a median prescription dose of 15Gy and a median maximum dose of 42.9Gy. Results: Most patients were females (77%), and the median age at presentation was 48 years. The overall tumor growth control was 93.8% (61 patients) 39% of them achieved tumor size reduction. The overall clinical control was 90.8% (59 patients), and 40.7% achieved clinical improvement. The Actuarial tumor rate free of progression was 100% at 3 years, 91.5% at 5 years, and 86% at 10 years of follow-up. Conclusions: GKRS for GJTs typically results in high long-term tumor control and lower neurological morbidity than those associated with microsurgical resection, therefore should be consider as a dependable effective treatment option.
Юніт-економіка стартапів у сфері гостинності
Authors:   Державний торговельно-економічний університет, БОВШ Людмила
Published: September 2023

Дослідження юніт-економіки стартапу є дуже актуальним завданням, оскільки дає змогу аналізувати вартість та прибут­ковість окремих компонентів продукту сфери гостинності. Це може допомогти фаунде­рам визначити ефективність вкладених ресур­сів та прийняти обґрунтовані рішення щодо подальшого розвитку стартапів. Під дією трендів цифровізації відносин суб’єкти гостин­ності стикаються з новими викликами, що потребують цифрових рішень та розробки стартапів, ефективність впровадження яких потрібно об’єктивно оцінювати. Малодослідже­ність юніт-економіки стартапів спричиняє стратегічні провали в розвитку життє­здатного бізнесу. Метою статті є розгляд підходів до оцінки компонентів юніт-економіки стартапу, що допомагає здійснювати пра­вильне ціноутворення, розробляти ефективні стратегії масштабування, а також забез­печувати вищу рентабель­ність бізнесу у сфері гостинності. Прове­дене дослідження спирається на загально­наукові методи: аналіз, синтез, індукція, порівняння; емпіричні методи та логічне моделювання. Зроблено огляд сутності стартапів й напрямів їх засто­сування у сфері гостинності. Охарак­тери­зовано поняття юніт-економіки та вигод, які ця концепція може приносити стартапам. Стаття розглядає, як оцінка вартості юніту сприяє здійсненню правиль­ного ціноутворення, розробленню ефективних стратегій масштабування, а також забез­печенню більшої рентабельності бізнесу. Визна­чено, які компоненти юніт-економіки можуть бути важливими у сфері гостин­ності. Надано приклади моделі юніт-еко­номіки для ухвалення стратегічних рішень у сфері гостинності. Проведені дослідження формують науково обґрунтовані підходи до визначення напрямів стартапінгу й ідентифікації етапу розвитку бізнесу. Кон­цепція юніт-економіки за постійного моні­то­рингу та контролю продукує переваги під час прий­ня­ття управлінських рішень; створює кому­нікативні механізми з інвес­торами, зацікав­леними у розумінні бізнес-моделі стартапу; допомагає оцінити потен­ціал стартап-продукту, що є особливо корис­ним на ранніх етапах; створює уявлення про терміни досяг­нення прибутковості та стійкості; рівень ціни на пропонований стартап-продукт.
Харчування в закладах освіти: впровадження систем НАССР
Authors:   Державний торговельно-економічний університет, ФЕДОРОВА Діна , ВІТРЯК Оксана ,   Державний торговельно-економічний університет, МАРЦИН Тетяна ,   Державний торговельно-економічний університет
Published: September 2023

У сучасних умовах необхідною вимогою до функціонування підприємств харчування, зокрема й у закладах освіти, є впровадження системи управління безпечністю харчових про­дуктів та створення структурованого підходу для контролю виявлених ризиків. У роботі здійс­нено аналіз практичних аспектів впро­вадження системи харчової безпеки на підприємствах харчування закладів освіти м. Києва та Київської області, а саме розглянуто най­поширеніші проблеми і невідповідності, які виникають під час введення системи HACCP при організації харчування дітей шкільного та дошкільного віку. Важливою перевагою системи є її властивість не виявляти, а саме передбачати та запобігати виникненню ризиків за допомогою поетапного контролю впродовж усього ланцюга виробництва харчових продуктів. Розроблено алгоритм моніторингу функціо­нування системи HACCP в закладах освіти, де визначено шляхи розв’язання проблем і невід­повідностей при впровадженні системи, що гарантує безпечність харчування дітей.
An overview of offences against monuments in the Polish law
Authors: Narodowska Joanna
Published: September 2023

The aim of the article is to overview the criminal law regulations and the standpoints of Polish doctrine concerning the protection of monuments under Polish law. The main discussion is preceded by an introduction, which explains key concepts relating to crime against monuments, including what is to beunderstood by the criminological term “crime against monuments”. The next part of the study discusses crimes against monuments governed by the Penal Code and the Law on the Act on the Protection and Guardianship of Monuments. The paper closes with brief conclusions. One of the main postulates isthe need to strengthen the criminal law protection of monuments by creatinga separate chapter of the Penal Code dedicated to these assets.
Pranie pieniędzy pochodzących z eko-przestępczości. Wyrafinowane przestępstwo czy prymitywny proceder?
Authors: Tomczyk Arkadiusz
Published: September 2023

Celem artykułu było zwrócenie uwagi oraz przybliżenie problematyki prania pieniędzy pochodzących z eko-przestępczości, również w praktycznym aspekcie tego zjawiska. Proceder ten jest najczęściej typowy dla zorganizowanych grup przestępczych. Został on dostrzeżony przez organizacje międzynarodowe zajmujące się przeciwdziałaniem praniu pieniędzy i finansowaniu terroryzmu, co świadczy o jego doniosłości. Zwalczanie omawianego zjawiska wydaje się mieć kluczowy charakter, bowiem skutecznie powstrzymując możliwości korzystania z bezprawnie uzyskanych środków, dewastacja środowiska naturalnego przestanie być ekonomicznie opłacalna. Dostrzegając poważne zagrożenia płynące z nielegalnego handlu gatunkami fauny i flory, stwierdzić trzeba, że w praktyce pokrzywdzonym tego rodzaju przestępstwami jest każdy z nas, poprzez potencjalne zagrożenie chorobami odzwierzęcymi, wymieranie gatunków, zagrożenie istnienia lokalnych społeczności etc. Odpowiedź na postawione w tytule pytanie nie jest jednoznaczna, choć autor skłania się do stwierdzenia, że w omawianych przypadkach pranie pieniędzy najczęściej przybierało będzie charakter bardzo złożony, stąd też określić je można jako przestępstwo wyrafinowane.
Kryminologiczna osnowa islamskiego fundamentalizmu religijnego – wybrane wymiary
Authors: Ickiewicz-Sawicka Magdalena
Published: September 2023

Zasadnicza teza artykułu głosi, że fundamentalistyczne odłamy islamu nie są wytworem współczesności. Liczne źródła historyczne wskazują na występowanie tego rodzaju ugrupowań od początku istnienia tej religii. Artykuł składa się z trzech zasadniczych części. W pierwszej znajduje się wstęp wprowadzający do tematyki zaprezentowanej w opracowaniu. Druga zawiera zwięzłe informacje na temat teoretycznych i praktycznych powiązań fundamentalizmu religijnego, terroryzmu i przestępczości zorganizowanej. Trzecia dotyczy genezy, funkcjonowania i upadku (a raczej rozproszenia) tzw. Państwa Islamskiego; – w rzeczywistości terrorystycznej organizacji przestępczej cynicznie wykorzystującej surowe nakazy religijne celem podporządkowania sobie podbitych terytoriów i zamieszkującej tam ludności.
Podsumowanie tekstu zawiera wnioski końcowe, które jasno przypominają o radykalnych ruchach religijnych tworzący nie rzadko swoisty kryminalno-terrorystyczny konglomerat przestępczy ujawniający się w różnych częściach świata (zarówno w Europie, Azji i Afryce); z różnym nasileniem. Organizacje te wyraźnie sprzeciwiają się wartościom świata tzw. Zachodu; odrzucają ideę praw człowieka i propagują wartości (czy też antywartości) fundamentalnych ruchów religijnych mających kryminalnych charakter.
Kilka refleksji odnośnie do trybów stosowania pracy zdalnej w świetle przepisów Kodeksu pracy
Authors: Wisniewski Janusz
Published: September 2023

Uregulowanie pracy zdalnej w Kodeksie pracy to bez wątpienia jedno z istotniejszych rozwiązań w prawie pracy. Stanowi wszakże odpowiedź na wyzwania współczesnego rynku pracy. Należy także podkreślić, że regulacja ta była bardzo oczekiwana zarówno przez pracodawców jak i pracowników. Stąd też zasługuje na uwagę ale przede wszystkim ze względu, iż dotychczas w literaturze prawa pracy nie była ona przedmiotem bliższej analizy. Szczególne teoretyczne i praktyczne znaczenie ma zagadnienie trybu stosowania pracy zdalnej. De lege lata fundamentalne znaczenie w tej materii posiadają postanowienia art. 6719 § 1 pkt 1 i 2, § 3, § 6, i § 7; art. 6722 § 1 i 2; art. 6733 § 1 i 2 k.p. Z przepisów tych wynika, że praca zdalna może być stosowana wskutek: uzgodnienia między stronami umowy o pracę, polecenia pracodawcy, wniosku pracownika znajdującego się w szczególnie trudnej sytuacji osobistej lub rodzinnej, wniosek pracownika o zastosowanie do niego elastycznej organizacji pracy, wniosku pracownika o pracą zdalną okazjonalną. Zatem celem artykułu jest analiza wyszczególnionych wyżej trybów stosowania pracy zdalnej, zwłaszcza że przepisy Kodeksu pracy regulujące tę materię budzą wątpliwości interpretacyjne. Przy czym jako najbardziej użyteczną z punktu widzenia systematyczności wywodów, uznałem zasadę dobrowolności pracy zdalnej oraz, że jej istota polega na usankcjonowaniu przez ustawodawcę możliwości przeniesienia pracy do przestrzeni prywatnej pracownika. Warto także podkreślić, że prawna możliwość wykonywania pracy w przestrzeni prywatnej pracownika w istotnym stopniu uwzględnia zdrowotny aspekt pracy zdalnej – ochronę podstawowych dóbr pracownika, tj. zdrowia i życia (art. 6719 § 3 k.p.).
Kryptoreklama stosowana w influencer marketingu jako czyn nieuczciwej konkurencji i nieuczciwa praktyka rynkowa
Authors: Kubanek Anita Joanna
Published: September 2023

Gospodarka wolnorynkowa, postęp technologiczny i mnogość podmiotów na rynku wymagają zapewnienia zasad uczciwej konkurencji w obrocie gospodarczym. Celem Autorki było zbadanie obszaru prawnych aspektów promocji produktów i usług z wykorzystaniem influencer marketingu. W toku badań wysunęła wniosek, że w ramach działalności influencerzy podejmują działania, które mogą naruszyć (i w praktyce często naruszają) przepisy prawa, stanowiąc czyn nieuczciwej konkurencji jak również nieuczciwe praktyki rynkowe.  Analiza aktów prawnych z zakresu prawa ochrony uczciwej konkurencji i konsumentów doprowadziła do wniosku, że ochrona przed naruszeniami jest zapewniona. Jednak poszukiwanie jej zakresu, definiowanie czynów mogłoby być przez ustawodawcę ujednolicone i dostosowane do aktualnych realiów obrotu gospodarczego i marketingu. Jednocześnie warto podkreślić, że reklama z wykorzystaniem influencer marketingu i rzetelność w tym zakresie są przedmiotem wyraźnego zainteresowania Urzędu Ochrony Konkurencji i Konsumentów, czego konkretne przykłady autorka przytacza w artykule.
Prawne aspekty ustanawiania i finansowania stypendium okresowego dla zawodników e-sportowych przez gminy. Kazus miasta Sosnowca
Authors: Kuczkowski Przemysław
Published: September 2023

Celem niniejszego opracowania jest rozwiązanie problemu prawnego, polegającego na znalezieniu odpowiedzi na pytanie o dopuszczalność ustanawiania i finansowania przez gminy okresowych stypendiów sportowych dla zawodników sportów elektronicznych na podstawie art. 31 ustawy o sporcie.
W opracowaniu tym podjęto się również analizy pionierskiej uchwały Rady Miejskiej Sosnowca, dotyczącej stypendiów sportowych dla osób fizycznych osiągających wyniki we współzawodnictwie w zakresie sportów elektronicznych, pod kątem wystąpienia w niej przesłanek podmiotowych oraz przedmiotowych określonych w ustawie o sporcie.  Wyniki badań zawarte w tej pracy dowiodły, iż istnieje prawna możliwość na gruncie ustawy o sporcie (mając zarazem na uwadze przepisy ustawy o finansach publicznych w zakresie wydatkowania środków budżetowych) ustanawiania i finansowania przez gminy, czy szerzej przez wszystkie j.s.t., okresowych stypendiów sportowych dla zawodników sportów elektronicznych.
Artykuł ma charakter oryginalny i został poświęcony w całości problematyce stypendiów okresowych dla zawodników e-sportowych.
Mając na uwadze jednostkowe prace dotyczące finansowania e-sportu, opracowanie tego zagadnienia w ramach artykułu, zdaniem autora, niewątpliwie wzbogaci aktualną literaturę.
Analizy problemu dokonano przede wszystkim w oparciu o polskie przepisy ustawy, w której zawarto regulacje dotyczące stypendium sportowego, a także orzecznictwo oraz doktrynę.
MACHINE LEARNING TECHNOLOGIES OF THE FUNCTIONALLY SUSTAINABLE INTELLECTUAL INFORMATION SYSTEM OF THE INSTITUTION OF HIGHER EDUCATION
Authors:   State University of Telecommunications, Zamriy I. V.
Published: September 2023

Market development has created a need for widely functional integrated corporate information systems that combine data storage databases, analytical tools, and document management systems. In today's conditions, the question of choosing a corporate information system is often a key strategic decision that largely determines the efficiency of the enterprise. Therefore, the development, support and optimization of intelligent information systems is an urgent issue of ensuring optimal decision-making based on the analysis of current situations to achieve a certain goal. For this purpose, the optimization of clustering algorithms of intelligent data analysis based on cloud technologies and machine learning to increase the efficiency of the intelligent information system of a higher education institution is considered. The choice of the best algorithm under the conditions of a specific task should be reasonably carried out by the person who makes the decision, since the processes of interpretation and evaluation of the obtained results after their analysis are extremely important. At this stage, the main role is played by an expert in the subject field under investigation, who, in addition to using the criteria, can, based on a priori ideas and knowledge of key target indicators, perform additional verification of the results for further decision-making. To achieve the maximum result, a complex approach to data analysis is required, which includes both the use of a priori knowledge of specialists for pre-processing of data and interpretation of results, and the use of specialized algorithms. The paper analyzed the shortcomings, optimized and parallelized the optimized algorithms in order to improve the ability to process a large array of data and increase the effect of the activity of the intelligent information system of the institution of higher education using cloud computing and machine learning of the intelligent information system.
DETECTION OF NETWORK ANOMALIES WITH NEURAL NETWORKS ALGORITHMS
Authors:   State University of Telecommunications, Haidur H. I.
Published: September 2023

The rapid digitalization of the world has led to various attacks on computer systems and networks, so network security is an extremely important and relevant component of information security today. Creating effective cybersecurity tools and mechanisms is becoming increasingly difficult as the number of different devices and services grows. Identification of malicious traffic using deep learning methods has become a key component of intrusion detection systems (IDS). This article compares two deep learning models (recurrent neural network and convolutional neural network) for detecting anomalies in networks. Both neural networks were found to be useful in a wide range of applications. It has been shown that convolutional neural networks are best at detecting network anomalies in synergy with layers of long short-term memory. The development of deep learning technologies, including the considered neural network algorithms, is a promising direction in promoting the development of cybersecurity of information systems. These technologies are unique because they are at the initial stage of creation. The aforementioned technologies are currently not widespread in intrusion detection and network anomaly detection systems due to their novelty, so they require more thorough research. Conventional machine learning algorithms will eventually become insufficient, as they do not have such a good learning capability as deep learning neural networks do. The article provides a detailed analysis of the capabilities of recurrent and convolutional neural networks along with long short-term memory layers, which may be useful for use in further research.
EVALUATION OF HUMAN PSYCHOLOGICAL STATE USING MLP NEURAL NETWORKS
Authors:   National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Krylov Ye. V.
Published: September 2023

This article provides an overview of the construction of an MLP neural network for estimation of a person's psychological state. The problem of critical sessment and direct psychological help is quite important nowadays, as most people are faced with problems, both personal and national or global, such as political instability or a pandemic. Most of the existing systems for assessing the human condition are aimed at helping solve problems related to physical health. A smaller part of similar systems is intended to work with a mental state, however, they are more highly specialized and directed to work with an already known problem. A dataset was formed based on people's responses regarding their well-being. The MLP type of network was chosen, since this type is quite suitable for the given classification task. Three types of models are considered: basic MLP, MLP with ReLU activation and Unet-like model. The process of selecting the optimization algorithm and loss function is described. The article shows an overview and assessment of training effectiveness for each of the chosen models. Accuracy on a test set is shown. In addition, a description of actions related to attempts to improve the accuracy of the network (changing the number of questions, normalizing the initial data) is provided. A description of possible algorithms for data normalization is provided. In general, this article reveals a possible approach to the construction of a neural network, which can be useful not only for assessing one's own psychological state, but also for specialists working in the field of psychology, since they will be able to use a similar network to assess a person's state or compare their own assessment with an assessment system thereby increasing the accuracy of assessment.
Comparative analysis of modern fault tolerance technologies
Authors:   State University of Telecommunications, Solodkyy-­Solodarenko V. D.
Published: September 2023

On-demand cloud applications is one of the rapidly developing technologies that highly demanded on the market. With the increase of computer systems and requirements for real-time business intelligence, potential customers of such services turn to providers of «computing on demand» services. In the data centers that used for such services, computer systems face a large amount of processed data, which in turn leads to an imbalance in the load and provokes system failures. With infrastructure as a service (IaaS) usage, customers expect efficient performance of their tasks at an optimal price. In situation, when a client submits a task for work, it is deployed on a computer system in the data center of the service provider and there is no a hundred percent assurance that task would be completed and not failed because of lack of resources or software failure. Fault tolerance and high availability issues are currently the most acute in that field. The modern set of software tools for providing fault tolerance is quite wide. In general, they are all called to ensure the trouble-free operation of the computer system, but in fact they have significant differences in conceptual terms. High availability solutions provide fully automated failover to a backup system so that users and applications can continue working without disruption. HA solutions must have the ability to provide an immediate recovery point. At the same time, they must provide a recovery time capability that is significantly better than the recovery time that you experience in a non-HA solution topology. Analyzed and compared modern fault tolerance and high availability technologies. Compared modern models of High Availability system and tools for its implementation. Identified the shortcomings of modern models and tools for fault tolerance implementing. Developed recommendations for the usage of approaches that would help to eliminate reviewed shortcomings in different cases.
Automatic selection of transmission frequencies using the method of formation of pseudo­random sequences
Authors:   State University of Telecommunications, Parkhomenko V. L.
Published: September 2023

It is extremely important in many technological areas to provide stable wireless secure communication. A significant contribution to the final result is made by the shape of the transmitter antenna, and more precisely, the signal directional pattern of this antenna. For cases where a significant portion of the system requirements remain unknown, generally the best approach will be to follow universality. But, if the requirements for the final result are precisely defined, it is advisable to maximize efforts to achieve this or that final state. In this case, it will be more correct to choose the shape of the antenna depending on the final conditions, having previously weighed all the features of the available design solutions. The article examines and compares two types of antennas — omnidirectional and narrowly directional. Their strengths and weaknesses are described; situations in which they can be applied and get better results compared to analogues at the same transmitter power. selection of optimal parameters is carried out on the basis of predetermined information about the purpose and features of using the antenna on the transmitter. The considered information allows us to draw a conclusion about the advantage of narrowly directional antennas compared to omnidirectional ones in a situation where one of the main indicators is the distance between the transmitter and the receiver. Also, by changing such parameters as the angle width of a narrowly directional antenna, you can reduce the negative impact of the weaknesses of this type of transmitters. For example, a non-stationary object may accidentally leave the range of a stable radio signal from such an antenna, but the widening of the angle allows you to significantly reduce the probability of such a negative scenario.
Recurrent neural networks in cyber security
Authors:   State University of Telecommunications, Sosnovyi V. O.
Published: September 2023

The recent increase in cyber-attacks and malware clearly demonstrates that current countermeasures do not seem to be enough to protect against it, as hackers become more cautious in their approach with the cunning of developing systems that automatically rewrite and reorder their malicious software to avoid detection. Typical machine learning approaches that learn a classifier based on a manually created feature vector are not robust enough to such reordering. Hence, the need for an effective automated cyber security solution using deep neural networks. In this article, we demonstrate research on the effectiveness of recurrent neural networks (RNNs) for combat in cyberspace. The conducted experiment shows that RNN with Long Short Term Memory (LSTM) performs much better than classical machine learning algorithms (SVM and Random Forest) with accuracy of 99.70%, 98.55% and 99.42%, respectively. This is possible because RNNs have a built-in memory that can remember multiple previous states and implicitly extract distinctive features, hidden complex structure, and complex sequential relationships in the data, which helps achieve better accuracy. This paper describes an investigation of a recurrent neural network (RNN) model for cyber security using domain malware detection as an application area. The performance of RNN and other classical machine learning classifiers is studied and evaluated for malware classification in the cyber security usage domain and compared. From this study, it can be seen that RNN has better accuracy than classical machine learning classifiers (SVM and Random forest). This is possible because RNNs have a built-in memory capability that can store and replay multiple previous states, and implicitly extract salient features, hidden/underlying complex structure, and complex sequential relationships in the data, which help achieve better accuracy. Thus, it will be useful for creating a real-time application for analyzing malicious activities on the network.
Study of interference resistance of autocorrelative receiving methods in broadband communication systems
Authors:   State University of Telecommunications, Haidur H. I.
Published: September 2023

Modern broadband communication systems are not able to completely eliminate the effects of interference characteristic of various communication channels, namely interference caused by the multipath nature of signal propagation and concentrated interference which reduce the reliability of information transmission. Although the picture is qualitatively clear, the variety of interference and the specificity of the impact of some of them on broadband communication systems do not allow one to quantitatively take into account the impact of all interference at the same time. Therefore, there is a need to study the issue of increasing immunity to various reception methods. This article is devoted to the study of methods of increasing immunity to interference in broadband communication systems with fluctuating interference using autocorrelation methods of reception. The probability of errors in a multi-position system with orthogonal signals at incoherent reception with incoherent accumulation is investigated. Probabilities of errors during autocorrelation reception of signals with single phase-difference modulation are analyzed. The article defines that the immunity of intercorrelation methods of reception does not depend on the base of the signal, and the immunity of autocorrelation methods depends on the base and at the same energy is lower in the signal with a larger base (larger number of elements). The results of the work characterize the interference immunity of multi-position systems with different reception methods and the dependence of the immunity of a group of autocorrelation reception methods on the number of elements N or the FT base of the composite signal. According to the results of the work, the composite signals from the FRM in all reception methods provide a gain in energy twice as compared to the systems with orthogonal signals.
Using categories as abstract structures to formalize computational models
Authors:   Taras Shevchenko National University of Kyiv, Provotar O. I.
Published: September 2023

The paper provides an analysis of various formal models of computation, including recursive functions, fuzzy models, and categorical models. These models are subject to research in order to identify ways of performing calculations based on them. In the context of each of these models, the concept of computability and basic arithmetic operations is introduced, which allows to deepen the understanding of their structures and mechanisms. The main conclusion of the study is that the considered formal models of calculations can be simulated in the context of different categories. This approach paves the way for the construction of an abstract theory of computability and corresponding programming languages on a categorical basis. This approach has the potential to create a universal programming language that would support the description of tasks from different subject areas. It is possible to implement the approach by interpreting these problems in the appropriate categories and using a universal category apparatus for their solution. It deserves special attention that such a language should be aimed at solving scientific problems, which reflects its potential value in the field of scientific research. In addition, this study can lay the foundation for further developments in expanding the capabilities of formal computational models. Given the presence of categories including fuzzy sets, fuzzy functions and partially recursive functions, the considered calculation models can be the object of analysis in the context of these categories. This provides an opportunity to construct an abstract theory of computability and corresponding programming languages based on a categorical basis. The development of the Haskell programming language also represents a first step in this direction, highlighting the importance and potential benefits of this approach. It is possible to consider Haskell as an experimental plane for the development of categorical concepts in programming languages, which opens new horizons for further research in this area.
Telecom fraud and it’s impact on mobile carrier business
Authors:   State University of Telecommunications, Sahaidak V. А.
Published: September 2023

In this article was described most common types of fraud on mobile network and its impact on carrier business. Most common fraud types were described such as IRSF, wangiri, interconnect bypass fraud, arbitrage, traffic pumping. IRSF takes advantage of premium phone rates, which are then dialed unwittingly by users. Reviewed OTP-based IRSF and wangiri fraud realization. Wangiri is a telephone scam where criminals trick you into calling premium rate numbers. Interconnect bypass fraud takes advantage of something called a termination rate to make cheaper phone calls. VoIP bypass was studied as type of Interconnect bypass fraud. Arbitrage is the general practice of capitalizing on price differences in the long-distance rates between countries. Traffic pumping is a dubious practice by which some local exchange telephone carriers in rural areas of the United States inflate the volume of incoming calls to their networks to profit from the greatly increased inter-carrier compensation fees. Following conclusions were made: Telecom fraud is very complex and variable phenomenon due to carrier network specifics. With new technologies and services delivered on their network telecom operators should adapt their fraud monitoring and analysis methods up to date with minimum delay; In reviewed fraud examples we can see that one fraud activity can use realization technics of several different fraud types. Detection of such activities will require a flexible solution, that can adapt with or without man interaction; Fraud happens, when victim is not expecting it. Fraudsters can make calls, when subscriber is outside of business hours, they can make attempts to multiple subscribers during day and carrier won’t notice it until subscriber complain or someone notice strange trend. Scammers can even hack subscriber device or PBX and owner won’t even notice it until service payment; Premium or service number can be used by fraudster in order to realize scam. In such case there should be an agreement with carrier and business for list of allowed or blacklisted numbers; Fraud is not limited only to voice services. Realization methods can be used to SMS or IP network services.
Investigation of the positioning accuracy of wireless sensor networks
Authors:   State University of Telecommunications, Mitin Ye. Yu.
Published: September 2023

The creation of large-scale wireless sensor networks with a large number of cheap and energy-intensive sensors is associated with advances in miniaturisation and integration of sensor and communication technologies. In wireless sensor networks, hundreds or even thousands of tiny nodes equipped with batteries are scattered over the study area. Each node collects information. The nodes transmit the collected information to neighbouring nodes and then to a specified destination where the data is processed. This data is used to describe the neighbourhood in real time. Over the past decades, we have seen the rise of the Internet, which provides us with the ability to transmit various types of information and this is revolutionising business, manufacturing, science, education and our way of life. Wireless sensor networks have replaced standard computer networks. They were envisaged as a preventive computer world in which networked nodes automatically receive information about the environment in real-time. The modern telecommunications market offers a wide range of wireless sensor network technologies, with hundreds of companies offering their solutions. The capabilities of modern microelectronics and wireless networking technologies open up great prospects for creating various network complexes with a wide range of applications. This study examines the concept of the Internet of Things, the technological basis of which in its applications is wireless sensor networks, meaning, first of all, a fundamental change in the quantitative characteristics of the network. The author describes the main problems of designing sensor networks, algorithms for determining the location of sensor network devices, and investigates the positioning accuracy with a different number of reference nodes. A computational experiment was chosen as a research method. The analysis will help to improve the efficiency of wireless sensor network management and rational use of its resources.
Research of mobile broadband communication using artificial intelligence
Authors:   State University of Telecommunications, Rudenko N. V.
Published: September 2023

The current conditions force us to think about what will be the sixth generation (6G) mobile communications with the introduction and deployment of fifth generation (5G) technologies. The path of development of 6G and the further development of technologies will be considered in this article. First, let's get acquainted with modern 5G technologies and point out the need to study 6G. Considering the current and new development of wireless communication, we expect 6G to include three main aspects, namely mobile ultra-wide communication, super internet of things (IoT) and artificial intelligence (AI). Terahertz (THz) communications can be used to support mobile ultra-broadband, symbiotic radio and satellite communications can be used to achieve the super-internet of things, and machine learning methods are promising candidates for AI. The idea of a deep learning algorithm is considered, which is to resemble the process of perception in the brain using a deep neural network. Generally, a deep neural network consists of three layers i.e. input layer, hidden layer and source layer. In particular, the input layer provides input ports for information about the state of the environment observed by the learning agent, the hidden layer extracts the characteristics of the input information, and the output layer makes decisions regarding classifications or regressions. The minimum element of a deep neural network is a neuron responsible for processing and transmitting information between different neurons/layers. For each technology, we provide the basic principle, key tasks, as well as the most modern approaches and solutions.