bluuebunny/crossref_metadata_2025 huggingface dataset:
VINDICATION MODEL OF CORPORATE RIGHTS RESTORATION
Authors:   Urals State Law University, Murzin D. V. ,   Private Law Research Center named after S. S. Alekseev under the President of the Russian Federation (Urals branch)
Published: December 2023

Abstract: the article deals with issues related to the restoration of the corporate rights of an entity that was unlawfully deprived of legitimation as a copyright holder. The corporate rights embodied in the “share of participation” are the object of civil rights and belong to the participant of the corporation on the absolute right. The cases of protection of the violated rights of a corporation participant provided for by Russian civil legislation are analyzed: the demand for the return of illegally written-off undocumented shares and the recognition of the right to the lost share in the authorized capital of a limited liability company. It is concluded that these methods of protection are built on the vindication model. Such a method of protection as the restoration of corporate control is analyzed. It is concluded that the restoration of corporate control is a restitution in the meaning of an industry-wide measure of protection of a violated right in a restorative form, which includes as an indispensable but auxiliary element, the requirement to return the share of participation that has a vindication character. The vindication model of restoring the corporate rights of a person unlawfully deprived of dominance over a share of participation in a corporation is considered as a way of protecting an absolute right, implemented by restoring the legitimation of the rightholder in order to return to him the dominance over the lost share of participation.
PECULIARITIES OF LEGAL QUALIFICATION OF THE CONTRACT IN FINANCIAL LAW
Authors:   Perm Institute FPS Russia, Prokhorko T. N.
Published: December 2023

Abstract: the article is devoted to the contract as a means of regulating financial social relations and to the peculiarities of its legal qualification in the financial law of the Russian Federation. The developed theory of the contract in civil law does not give an opportunity to answer all questions about the contract in financial law. The general nature of the contract in financial law as well as the nature of the contract in financial and legal regulation as a type of a public contract is analyzed. The attention is paid to the comparison of financial and legal contract with civil law contract, their commonalities and differences. The application of the contract in the regulation of financial relations is a manifestation of disposability in imperative regulation. “Financial disposability” complements imperative regulation in the sphere of financial activity of the state, which is primary in comparison with dispositive regulation. The article considers the expediency of creation of general inter-branch category of contract because of the possibility of application of this legal form in many areas of society.
PROSPECTS FOR INSTITUTIONALIZING AN AGENCY AGREEMENT IN THE LAW OF THE REPUBLIC OF BELARUS
Authors:   Belarusian State University, Lysakovskaya J. O. , Konanevich Y. G. ,   Belarusian State University
Published: December 2023

Abstract: the authors examine the existing models of legal regulation of agency and, on the basis of it, form a unique doctrinal approach to the identity of the agency contract in the law of the Republic of Belarus, based on public law and private law interests.
Mining in the Procrustean Bed of Entrepreneurship: Expectations and Prospects
Authors: Yusupova Anastasiya
Published: December 2023

In the present article the author turns to the study of the topical for the modern Russian legal reality issue – the possibility and conditions of recognition of mining as a permitted activity. Widespread phenomenon in the absence of a formed normative concept inevitably generates a scientific debate, fueled by haphazard attempts of the legislator to pointwise regulate the emerged and constantly complicating legal relations. The author of this article proposes to turn to the definition of mining: due to the specificity of the very type of activity, the legal science is forced to get involved in the initially alien technological areas in an attempt to find systemic, legally significant signs. Initially high variability of doctrinal approaches requires correlation with the legislative vision of the emerging picture of mining. In this regard, the article provides an analysis of both the current legal acts related to the regulation of the turnover of digital assets and digital currencies, and recent legislative attempts to recognize the phenomenon of Russian mining. The article provides a significant enrichment of the foreign experience of friendly states in terms of regulation of mining activities – both in terms of developing an acceptable definition, and in terms of legal consequences of the legalization of the phenomenon. Finally, the key issue of the article should be considered as the author›s attempt to consider the possibility of giving the mining activity in the Russian Federation the properties of entrepreneurial activity. The comparison of the adopted in the civil legislation paradigm of entrepreneurship and the new phenomenon – mining – made it possible to conclude that, despite the specificity of this activity, it has all the signs of economic activity.
The author shows the need to develop clear criteria for the purpose of giving this activity entrepreneurial properties, as well as to distinguish mining as an economic activity, which has the properties of investment, and mining as an activity directly aimed at profit making.
Modus Operandi of the Crime as a System-Forming Element of the Criminalistic Description of Crimes Connected with Altering Identification Marks on Vehicles
Authors: Agafonov Artoym
Published: December 2023

The system of actions of a person (or persons) involved in unlawful activities of preparing, committing and hiding a criminal act is traditionally called modus operandi in criminalistic publications, it is the basic and one of the most informative elements of the criminalistic description of crimes connected with altering vehicle identification marks (further — VIM). The author analyzed the practice of law enforcement, specialized publications and vehicle technical examinations of VIMs to find and describe 22 methods of altering VIMs, which are then used to single out key features testifying that the initial identifications marks of a vehicle have been altered. Besides, the author found an interconnection and interdependence between the modus operandi of the crime, the object of criminal infringement and the personality of the criminal, which will undoubtedly facilitate the process of proposing and verifying typical investigation leads.
On the Criminalistic Classification of Criminal Proceedings Participants
Authors: Foygel Elena
Published: December 2023

The article is devoted to the criminalistic significance of different participants of criminal proceedings. It is stated that the classifications used in criminalistics are based on the criminal procedure criterion, or on the form of using forensically relevant information. The author analyzes viewpoints of scholars of criminalistics and criminal process on the classification of criminal court proceedings’ participants and identifies controversial aspects that give rise to doubts. The author also presents her own classification of criminal proceedings’ participants depending on the form of activity whose object is forensically relevant information, as well as the type, volume and degree to which this forensically relevant information is formed. It is suggested that two key classification groups should be singled out — subjects of forensically relevant information (the suspect, the accused, the witness, the victim) and subjects of criminalistic knowledge (the investigator, the detective, the operative worker, the expert, the specialist).
Financial Instruments for Stimulating Agribusiness Companies' Innovation Activities in the Far East Region
Authors: Slepneva Tatiana , Shalneva Maria , Timonina Alina
Published: December 2023

For nowadays companies are forced to look for new drivers of performance growth. Today, agricultural holdings are not just manufacturing companies that supply products to both the domestic and foreign markets. These are platforms for the implementation of high-tech and technical capabilities that are being introduced into all segments of the agro-industrial complex in order to increase productivity and achieve social and economic effects. The innovative potential of Russian agro-industrial companies makes it possible to implement truly breakthrough projects, and one of the most attractive and fertile spaces for their implementation is the Far East region. Nevertheless, in the context of sanctions, a decrease in the level of interaction with foreign partners and restrictive measures, a particularly relevant problem is to increase the innovative attractiveness of the domestic agro-industrial complex. The study analyzed the investment attractiveness of the Far East region and main factors for the stable functioning of the agro-industrial complex. Based on the results of the study, we concluded that it is possible to use forward-looking tools to stimulate investment activity of agribusiness companies. It might be corporate programs to increase competitiveness, agreements on the protection and promotion of capital investments and a special investment contract. The study developed a model of a variable matrix of criteria for choosing financial instruments that stimulate innovative activity of agro-industrial companies for fulfilling its innovative potential.
Negative Emotions and Climate Policy Support in Russia
Authors:   Tyumen State University, Valko Danila V. ,   The South-Ural University of Technology, Maltseva Alisa S. ,   South Ural State University (National Research University),
Published: December 2023

Current research suggests that the relationship between negative emotions and pro-environmental behaviour is not consistent across contexts, and that different negative emotions can both increase and decrease motivation to act. This paper is a post hoc analysis of the role of negative emotions in supporting climate change policy in the context of Russia, also examining the role of sociodemographic factors. Based on a randomized controlled experimental design with a total sample size of N = 246, we assess the expression of six negative emotions in relation to perceptions of climate change, and their role in increasing support for a set of key climate policies. The results show that the overall expression of negative emotions is positively associated with support for the full set of climate policies, but the effect varies significantly across policies. In terms of sociodemographic factors, taking into account the factor structure of the climate policy support, support for policies that relate to taxes is more strongly determined by education; support for policies that relate to energy infrastructure and business, as well as forest and water protection, is determined by gender; the latter is also negatively associated with respondents' income level. In practical terms, the results indicate the need to develop a balanced communication strategy to attract the attention of Russian society to climate change, to familiarize population with the short- and long-term effects of the introduction of various policies to counteract climate change, and to create an information flow that promotes an emotional attitude to the problem, which is as effective as possible for supporting policies developed by the state and the scientific community.
RESEARCHING SOCIAL RESILIENCE IN THE CONTEXT OF MIGRANTS’ LIFE TRANSITION: A QUALITATIVE METHODOLOGICAL MOSAIC
Authors:   Lunds University, Qamar Azher Hameed
Published: December 2023

Migration is a psychosocial challenge, and migrants' transitory experiences in host countries are shaped by a combination of linked environmental factors. The absence of social aspects of resilience, as well as disciplinary limitations and biases, hinder the methodological rigor and flexibility needed to investigate social resilience as a phenomenon that occurs at the intersection of social, cultural, and political environments. Based on the social constructionist perspective, this paper identifies the need for a methodological mosaic and proposes a methodological guideline to investigate social resilience among migrants embedded in a multi-layered environment and person-environment interaction. The proposed methods include participant observation, biographical interviews, resilience diaries, focus groups, participants’ workshops, and expert conferencing. The inclusion of participantfriendly methods provides a space to listen to the voices of participants across the margins, and to engage experts and social workers in a participant-centered data examination. The concept of using a methodological mosaic in social resilience and migration studies provides a solid foundation for conducting multidisciplinary social science research. It gives the freedom to engage experts from various disciplinary backgrounds and benefits from diverse perspectives to connect the methodological pieces. The methodological mosaic described in this paper can be used to advance interconnected and participant-friendly data collection strategies and to gain a holistic understanding of migrants’ lived experiences. The paper, though a methodological proposal, contributes to broadening the methodological scope and integration in migration studies.
О Дворкине всерьез. Современная англо-американская философия права
Authors: Коваль Софья
Published: December 2023

Монография посвящена современной англо-американской философии права и, в частности, теории известного американского философа права Рональда Майлса Дворкина (1931–2013) —одного из самых известных критиков позитивистской теории Г.Л.А. Харта. Для того чтобы определить, какое место философия права Дворкина занимает в мире англо-американской традиции, автор исследует современную философию права (включая ее историю и дебаты о предмете), а также три основных этапа философии права Дворкина (теорию правовых принципов раннего этапа, интерпретивизм среднего и признание права как части политической морали позднего этапа), выделяя основные черты его теории и тестируя на принадлежность к основным направлениям: правовому позитивизму, правовому реализму, школе естественного права. Автор приходит к выводу, что философия права Дворкина хоть и содержит в себе свойства основных правовых школ англо-американской традиции, является самодостаточной и своеобразной междисциплинарной философско-правовой концепцией, которую можно обозначить как «нормативная антипозитивистская теория». Книга адресована специалистам, студентам и кругу читателей, чьи интересы связаны с философией права, политической философией и правоведением.
Essential surgeries for the electrophysiological recording from a behaving non-human primate brain 2 (Craniotomy) v1
Authors: Kase Daisuke , J Lipski Witold , R Harsch Devin , S Turner Robert
Published: December 2023

Outlined below are the steps to complete a craniotomy in an existing recording chamber placed on a cranial implant. This procedure can be done concurrently with the implant surgery (not recommended), or can take place upon recovery from the implant surgery.
A NEEDS ANALYSIS FOR ESP IN A MULTIMEDIA STUDY PROGRAMME OF A VOCATIONAL HIGH SCHOOL
Authors: Santika Susan , Wirza Yanty , Emilia Emi
Published: December 2023

A needs analysis is required to design ESP courses and determine appropriate materials for vocational high school students. Particularly in a multimedia study programme, even while multimedia has become increasingly prominent as a result of digital transformations, there is not much attention given to conducting the need analysis for vocational high school students. Therefore, this research aims to analyze the needs analysis for ESP in a multimedia study programme of a vocational high school. Specifically, it attempts to reveal what difficulties are encountered by the students during their internship programmes, what English language skills are needed by the students to perform their jobs, and what the multimedia study programme needs to offer to allow students’ employability. A case study was conducted on an EFL teacher and eighteen students in a vocational high school. The findings revealed that: First, students had difficulties in Grammar, Vocabulary, and Speaking; Second, the English language skills needed to perform their jobs were listening, reading, and writing; Third, the multimedia study programme should offer copywriting, technical vocabulary and authentic materials related to multimedia to allow students’ employability. This research also recommends three-unit materials for the ESP courses divided into three topics: copywriting, photography, and videography.
MAPPING CURRENT TRENDS OF EFL TEACHING AND LEARNING RESEARCH PRACTICES IN INDONESIA
Authors: Mali Yustinus Calvin Gai , Timotius Anne Indrayanti
Published: December 2023

To date, there have been very few studies that map the major research trends in English as a Foreign Language (EFL) contexts, such as those in Indonesia. To address that gap and to benefit undergraduate and graduate students, EFL researchers, or practitioners looking for a current research topic and theories to frame their studies, this paper reviews the past research studies (n=53) published in four Indonesian national journals to explore Indonesia’s EFL research trends in 2020, including research topics, theoretical frameworks, and research methods. The journals were selected because of their focus and scope related to English language teaching and education as well as their rank in Sinta 1 and Sinta 2 (two of the highest levels out of six Sinta levels) of the Indonesian web-based research information system. Based on a holistic review of the articles checked by the peer-debriefing strategy to ensure the review’s credibility, the analysis results show that the previous studies mainly explore English teaching strategy and education technology research areas and use fairly old theories as their theoretical framework. As for the research method, most of the studies use a qualitative research method, take place in university settings, and involve university students as their research subjects. The meanings of the analysis results, teaching implications for a research class, and directions for further research are presented.
The effectiveness of adding BTS teaching materials to improve the reading ability of Korean language students
Authors: Khairunnisa Fakhirah , Herniwati Herniwati , Triarisanti Risa
Published: December 2023

In the current era, knowledge and technology are rapidly advancing. The rapid development of technology makes it easier for people to access the world. This study aims to determine the effectiveness of Learn Korean with BTS teaching materials in improving Korean reading skills with a sample of 46 Korean Language Education students year of 2020. The data collection technique used test instruments and questionnaires totalling 20 valid and reliable items each. This study used a quasi-experimental research method and the non-equivalent control group design. The results showed that the experimental class got an average pre-test result of 60.87 and an average post-test result of 85.43, while the control class got an average pre-test result of 62.83 and an average post-test result of 68.04. The paired sample t-test was used to determine differences in learning outcomes and the test results showed the significance value (2-tailed) was 0.00 (0.05), which means that there is a significant difference in the results of students’ learning before and after using the Learn Korean with BTS teaching materials. The results of the independent sample t-test show a significance value (2-tailed) was 0.00 (0.05), which means that there is a significant difference in learning outcomes between students who used Learn Korean with BTS teaching materials and those who used traditional learning materials. The results of the questionnaire show that students' opinions about learning using the Learn Korean with BTS teaching materials are positive.
A contrastive analysis of food name forming between Korea and Indonesia: a morphological study
Authors: Megasari Jayanti , Widyana Ashanti
Published: December 2023

Food cannot be separated from our daily lives. The meaning of food in people's lives is to fulfil the needs of the body and other forms of culture. This study compares the formation of Korean and Indonesian food names. This study uses a descriptive research method and uses a morphological study as an analysis. The data used in this study are Korean and Indonesian food names from various relevant sources. This research was conducted as an introduction to culture through the culinary arts and as a form of developing the science of morphology. This study compares the formation and pattern used in naming Korean food names with the formation and pattern of naming Indonesian food names. This research produces formation patterns based on word categories. In Korean food, names produce 12 patterns of formation and in Indonesian food produce 5 patterns of formation.
Code-switching for non-native Korean lecturers in teaching Korean as a foreign language for basic and additional level
Authors: Arti Nurani Sari Tiana
Published: December 2023

Although communication is a means of exchanging ideas between people, it can be challenging due to the abundance of synonyms and the evolution of language. The idea is that rather than code-switching, each person needs to have the aptitude and competence to comprehend different kinds of language. This study focuses on the use of code-switching by lecturers in the learning process. The purpose of this study was to find out what types of code-switching were used by lecturers during the learning process, what was the function of using code-switching, and how students perceived the use of code-switching by lecturers in learning activities. This research is based on the awareness that the ability of students to capture learning in the classroom varies. This research is expected to help Korean language learning effectively. The method used in this research was descriptive qualitative, with one lecturer and 71 students as respondents. Data in the form of a transcription of the lecturer’s speeches were obtained from four learning video documentation and questionnaires. Three types of code-switching were found in the lecturer's speech at each meeting, namely the tag-switching type, the intra-sentential-switching, and the intersentential-switching. Then there were five functions realized at each meeting, namely referential functions, emotive functions, conative functions, fatigue functions, and metalinguistic functions. Students’ responses to the lecturer’s code-switching, as evidenced in the questionnaires, were generally positive, especially in terms of understanding the materials.
The meaning of turtle symbols in the lyrics of the song Geobugi by Davichi
Authors: Hanifah Syifa Muthia , Adnyana Putu Pramania
Published: December 2023

Song lyrics are literary works that comprise linguistic symbols that possess meaning. This study examines the meaning of the turtle symbol used in the lyrics of a Korean song by Davichi named Geobugi. The purpose of this study is to describe the meaning of turtle in the lyrics of the song Geobugi by Davichi. This study uses a qualitative descriptive method to systematically describe the meaning of denotation, connotation, and myth using the theory of semiotics by Roland Barthes. The research results showed that the turtle in the lyrics of the song Geobugi symbolizes cautiousness, patience, self-reflection, hope, and self-defense. The turtle symbol depicted in the lyrics of this song conveys the message that humans can move slowly and patiently, do self-reflection, remain optimistic in difficult times, and have their defense mechanisms. The discovery of the meaning of myth provides a new perspective that something contradictory can be perceived as an option rather than a negative thing, which differs from the general perception of the dynamic and fast-moving Korean society.
The use of the Korean honorific system In the family-themed K-pop (Korean pop) song lyrics
Authors: Rahmah Dwita , Sukyadi Didi
Published: December 2023

Korean society, to this day, generally still applies Confucian principles  in its discourse. Confucian principles in speech are expressed through the use of politeness in language This research conducted to determine how the Korean honorific system is used in the family-themed K-POP (Korean Pop) song lyrics and the factors that influence such use. This research was designed as a qualitative study. The data were collected by using a document analysis technique. Meanwhile, the data analyzed by using a linguistic data analysis technique, with reference to Kang, et al.’s (2005) Korean honorific system theory and Lee’s (2002) theory of social factors that influence the application of the Korean honorific system. This research resulted in 38 Korean honorific system expressions. The most commonly used Korean honorific system type is, namely, the honorific vocabulary. Because songwriters often used vocabulary in the form of honorifics, where the vocabulary was a pronoun to mention the characters in the lyrics of the song. The use of the Korean honorific system was influenced by various factors, including age, social status, intimacy, and context. While the gender factor was not found, this is likely due to the speaker and the addressee having different ages and social status.
Numerical analysis of the primary and secondary structural dynamic interaction effects on elastic floor response spectra
Authors:   Dept. of Civil Eng., Koneru Lakshmaiah Education Foundation, Annamdasu Madhavi Latha , Challagulla Surya Prakash ,   Dept. of Civil Eng., Koneru Lakshmaiah Education Foundation, Pesaralanka Vyshnavi ,   Dept. of Civil Eng., Koneru Lakshmaiah Education Foundation, Hossain Ismail ,   School of Natural Sciences and Mathematics, Ural Federal University, Cruze Daniel ,   Dept. of Civil Eng., Hindustan Institute of Technology and Science
Published: December 2023

In modern seismic design, the assessment of seismic behavior in secondary structures relies on the evaluation of the primary structure's acceleration at the support of the secondary structure. To enable effective secondary structure design, a thorough understanding of the interaction between the primary and secondary structures is essential. This article conducts an analysis based on parametric data, delving into the dynamic interaction between these structures. In this study, both the elastic primary and secondary structures are represented as single-degree-of-freedom systems. The governing equations of motion for both the coupled and uncoupled systems are derived and solved using the numerical method. Subsequently, the floor response spectrum (FRS) is computed for both coupled and uncoupled configurations. This investigation focuses on the impact of three crucial parameters: the tuning ratio (T_r), the mass ratio (μ), and the damping ratio (ξ_s) on the FRS. The analytical findings reveal that dynamic interaction does not significantly affect the FRS when the mass ratio is very low, at 0.1%. However, for a range of 0.8 ≤ T_r ≤ 1.2, dynamic interaction has a substantial influence on the FRS. Additionally, this study underscores that lower damping ratios in the secondary structure result in a more pronounced coupling effect on the FRS.
The Soundscape and Listening as an Approach to Sensuous Urbanism: The Case of Puerta del Sol (Madrid)
Authors: Palmese Cristina , Arribas José Luis Carles , Antolín Alejandro Rodríguez
Published: December 2023

This article focuses on the placemaking process and experimental research on the citizens’ assessment of the soundscape in Puerta del Sol in Madrid. Numerous studies conducted in recent decades have shown that sound is a crucial element capable of providing new insights into the relationship between human beings and the environment. Sound possesses physical-sensory-perceptual qualities which connect the emotional and the rational aspects of the experience of the place, overcoming the aesthetic/scientific duality. By default, the soundscape is the result of a collective production. It is the resonant expression of the multiple activities and uses that inhabit a space. The soundscape of everyday life provides a vision of life in a particular place, giving meaning and a singular character to the fact of living there. The concept and methods of the soundscape arise from sensitive experiences of the place in direct relation to a community. This exploratory research focused on in situ methods (soundwalks, improvised interview mappings, sound archives, performances, and collective sound actions) as expressions of collective listening to place. This article also focuses on how to map and share the result of this research, the technology to build a collective digital place as a place of confluence of experiences, citizen knowledge, and reflection on the situated soundscape.
Power Reduction Sleep Scheduling Technique for Cloud Integrated Green Social Sensor Network
Authors: Dave Devangini , Parikh Swapnil , Patel Pratik
Published: December 2023

The wireless sensor network is the maximum appropriate technology nowadays with such awesome applications and areas including Infrastructure tracking, environment tracking, health care tracking, etc. Cloud Computing has fantastic data collecting skills and effective data processing ability. Social Network is a group of People or organizations of human beings with similar intentions. Social Sensor Cloud is one type of expertise-sharing mechanism wherein similar types of human beings can connect. Energy Consumption is nowadays the largest challenge as far as the concern with green environment. Because the battery life of the sensor is so limited, the Social Sensor Cloud must be energy efficient. As a result, this article will concentrate on Energy-Efficient Techniques for the Social Sensor Cloud. According to our findings, findings, the majority of energy-saving measures will cope with not unusual place Parameters including Network Lifetime, Network Work rate, Throughput, Energy, Bandwidth, etc. We will Summarize current Technology and we Will Provide Our Architecture for Energy Reduction in Social Sensor Cloud.
Advanced Soil Moisture Predictive Methodology in the Maize Cultivation Region using Hybrid Machine Learning Algorithms
Authors: S. Vimalkumar Et al.
Published: December 2023

The moisture level in the soil in which maize is grown is crucial to the plant's health and production. And over 60% of India's maize cultivation comes from the states of South India. Therefore, forecasting the soil moisture of maize will emerge as a crucial factor for regulating the cultivation of maize crops with optimal irrigation. In light of this, this research provides a unique Improved Hybridized Machine Learning (IHML) model, which combines and optimizes several ML models (base learners-BL). The convergence rate of all the considered BL approaches and the preciseness of the proposed approach significantly enhances the process of determining the appropriate parameters to attain the desirable outcome. Consequently, IHML contributes to an improvement in the accuracy of the overall forecast. This research collects data from districts in South India that are primarily committed to maize agriculture to develop a model. The correlation evaluations served as the basis for the model's framework and the parameter selection. This research compares the outcomes of BL models to the IHML model in depth to ensure the model's accuracy. Results reveal that the IHML performs exceptionally well in forecasting soil moisture, comprising Correlation Coefficient (R2) of 0.9762, Root Mean Square Error (RMSE) of 0.293, and Mean Absolute Error (MAE) of 0.731 at a depth of 10 cm. Conceptual IHML models could be used to make smart farming and precise irrigation much better.
An Effective Supply Chain Model using Blockchain in IoT with Trust Enabled Hybrid Concensus Algorithm
Authors: Yassir Farooqui Et al.
Published: December 2023

With the rapid growth of multiagent systems, concerns about privacy and security have assumed a position of paramount importance. Blockchain technology has gained a lot of attention since it first appeared because of its benefits in terms of decentralization, accessibility, traceability, and the capacity to be trustless. The increasingly complicated supply chains in today's world face significant issues regarding traceability and integrity. Blockchain technology holds out the possibility of developing a new concept for supply chain traceability, lapping these worries. Thus, in this research, the trust enable hybrid consensus algorithm is proposed for establishing consistency in the network with the irrelevant traders. The authorization is identified by the proposed model for accessing the Blockchain network depending on the accessibility rules. Depending on the various information sources, the authenticity of data is calculated, which makes the interaction between both the agent as well as the resource. The efficiency of the proposed model is determined by three different measures for secure data transfer. The attained minimal transaction time is 0.856 ms, memory usage is 87.684 KB, and responsiveness is 3.599 ms, respectively.
Sentence Semantic Similarity based Complex Network approach for Word Sense Disambiguation
Authors: Gopal Mohadikar Et al.
Published: December 2023

Word Sense Disambiguation is a branch of Natural Language Processing(NLP) that deals with multi-sense words. The multi-sense words are referred to as the polysemous words. The term lexical ambiguity is introduced by the multi-sense words. The existing sense disambiguation module works effectively for single sentences with available context information. The word embedding plays a vital role in the process of disambiguation. The context-dependent word embedding model is used for disambiguation. The main goal of this research paper is to disambiguate the polysemous words by considering available context information. The main identified challenge of disambiguation is the ambiguous word without context information. The discussed complex network approach is disambiguating ambiguous sentences by considering the semantic similarities. The sentence semantic similarity-based network is constructed for disambiguating ambiguous sentences. The proposed methodology is trained with SemCor, Adaptive-Lex, and OMSTI standard lexical resources. The findings state that the discussed methodology is working fine for disambiguating large documents where the sense of ambiguous sentences is on the adjacent sentences.
SSFSCE: Design of a Sleep Scheduling based Fan Shaped Clustering Model to enhance working Energy Efficiency of WSN
Authors: Annaji M Kuthe Et al.
Published: December 2023

To enhance energy level in WSN is a research requirement, which assists in improving their lifetime over a series of communications. To achieve this target, a various variety of clustering & sleep scheduling models are discussed by researchers. Most of these models deploy static clustering & sleep scheduling operations, which limits their applicability & scalability levels. Moreover, dynamic clustering & scheduling models are highly complex, which reduces temporal QoS performance under real-time use cases. In order to reduce the probability of these issues, this text discusses design of the proposed Sleep Scheduling based Fan Shaped Clustering Model to enhance working Energy Efficiency of WSN. The proposed model initially deploys a Grey Wolf Optimization (GWO) Method for dynamic sleep scheduling via temporal performance analysis. The GWO Method models a fitness function that combines temporal usage levels, temporal Quality of Service (QoS), and temporal energy levels. Based on this modelling process, nodes were categorized into wake & sleep nodes, which were further clustered via destination-aware Fan Shaped Clustering (FSC), that assisted in improving QoS performance under multiple scenarios. The FSC Model was combined with a QoS-aware routing model, that assisted in selection of routing paths that can achieve low delay, high throughput, and high packet delivery with higher energy efficiency levels. Efficiency of the model was tested on node & network conditions, and its QoS performance was checked in terms of communication delay, consumption of energy, level of throughput, and Packet Delivery Ratio (PDR) levels. On the basis of these comparative evaluations, it is observed that the new proposed model is able to enhance end-to-end delay by 8.5%, reduce level of energy by 15.5%, while increasing throughput by 8.3%, and PDR by 1.5%, thus making it useful for a different real-time conditions.
A Lightweight Deep Learning Model for The Early Detection of Epilepsy
Authors: Saranya Et al.
Published: December 2023

Epilepsy is a neurological disorder and non communicable disease which affects patient's health, During this seizure occurrence normal brain function activity will be interrupted. It may happen anywhere and anytime so it leads to very dangerous problems like sudden unexpected death. Worldwide seizure affected people are around 65% million. So it must be considered as serious problem for the early prediction.  A number of different types of screening tests will be conducted to assess the severity of the symptoms such as EEG,MRI, ECG, and ECG. There are several reasons why EEG signals are used, including their affordability, portability, and ability to display. The proposed model used bench-marked CHB-MIT EEG datasets for the implementation of early prediction of epilepsy ensures its seriousness and leads to perfect diagnosis. Researchers proposed Various ML /DL methods to  try for the early prediction of epilepsy but still it has some challenges in terms of efficiency and precision Seizure detection techniques typically employ the use of convolutional neural networks (CNN) and a bidirectional short- and long-term memory (Bi-LSTM) model in the realm of deep learning. This method leverages the strengths of both models to effectively analyze electroencephalogram (EEG) data and detect seizure patterns. These light weight models have been found to be effective in automatically detecting seizures in deep learning techniques with an accuracy rate of up to 96.87%. Hence, this system has the potential to be utilized for categorizing other types of physiological signals too, but additional research is required to confirm this.
BQL-DRS: A Novel Balanced Q-Learning Based Demand Response System for IoT based Smart Grids
Authors: N.S. Gowri Ganesh Et al.
Published: December 2023

The modernization of electricity networks and the integration of renewable energy resources in Internet of Things (IoT) based smart grids have led to increased variability in market prices, necessitating effective demand response (DR) strategies. To address this challenge, this paper proposes a novel Balanced Q-Learning based Demand Response System (BQL-DRS) that combines both optimistic and pessimistic targets in the Q-learning algorithm to achieve a balanced decision-making process in IoT based smart grids. It optimizes DR actions by efficiently managing consumer demand in real-time, considering IoT data from grid conditions, energy prices, and consumer preferences. The significance of the BQL-DRS lies in its ability to handle dynamic and uncertain IoT based grid environments, enabling it to make informed and cautious decisions while pursuing energy efficiency and cost-effectiveness. By effectively addressing both pessimistic and optimistic scenarios, the BQL-DRS ensures grid stability, load balancing, and substantial cost savings compared to representative models.
Performance Analysis of Adaptive Equalizers Over Multipath Faded Channels: Error Vector Magnitudes
Authors: Annapurna H. S Et al.
Published: December 2023

Due to the increasing popularity of digital transmission systems, the need for channel equalizers has been acknowledged. These techniques are designed to counteract the effects of the inter-symbol interference (ISI) caused by the communication channels. An adaptive equalizer is used to operate on the output of a channel in order to provide an approximation of the transmission medium. An adaptive equalizer usually requires a training period to operate successfully. This method eliminates the effects of the wireless transmission channel and allows the subsequent symbol modulation. The paper presents an overview of the various adaptive equalizers, such as the least mean squares (LMS), decision feedback equalizers (DFE), and the Recursive least squares (RLS). It also explores their performance in terms of error vector magnitudes (EVM) over Rician and Rayleigh channels. The paper looks into the effects of adaptive equalizers on various digital modulation techniques for rectangular quadrature phase shift, amplitude modulation, such as the BPSK, QPSK, 4-QAM, 16-QAM, 64-QAM and 256-QAM. These modulations are analysed and measured in terms of symbol error rates and number of incorrect symbols.
Design and Implementation of Hybrid Multiplier for DSP Applications
Authors: Amgoth Laxman Et al.
Published: December 2023

In recent decades, there has been a consistent reduction in feature sizes in integrated circuit (IC) technology, leading to the need for increased placement of functional circuits on each chip. When it comes to the design of digital circuits, there is a significant focus on hybrid logic. Hybrid logic is highly regarded due to its ability to consume less power while achieving higher efficiency. Hybrid logic circuits have similarities to complementary metal-oxide-semiconductor (CMOS) transistors, yet possess a reduced transistor count while offering enhanced performance and reliability capabilities. This study examines the modeling and implementation hybrid multiplier with of help of hybrid adder. The functionality of adder is determined with the help of hybrid logic producing XOR/XNOR functionalities in single circuit.    The proposed hybrid Multiplier, which incorporates a hybrid Adder, has been successfully designed and implemented using CMOS 45nm technology and Mentor Graphics software the hybrid transistor logic multiplier demonstrates a decrease in total delay of 60% compared to CMOS.
Enhancing Image Quality: A Comparative Study of Spatial, Frequency Domain, and Deep Learning Methods
Authors: Rashmi Agrawal Et al.
Published: December 2023

Image restoration and noise reduction methods have been created to restore deteriorated images and improve their quality. These methods have garnered substantial significance in recent times, mainly due to the growing utilization of digital imaging across diverse domains, including but not limited to medical imaging, surveillance, satellite imaging, and numerous others.

In this paper, we conduct a comparative analysis of three distinct approaches to image restoration: the spatial method, the frequency domain method, and the deep learning method. The study was conducted on a dataset of 10,000 images, and the performance of each method was evaluated using the accuracy and loss metrics. The results show that the deep learning method outperformed the other two methods, achieving a validation accuracy of 72.68% after 10 epochs. The spatial method had the lowest accuracy of the three, achieving a validation accuracy of 69.98% after 10 epochs. The FFT frequency domain method had a validation accuracy of 52.87% after 10 epochs, significantly lower than the other two methods. The study demonstrates that deep learning is a promising approach for image classification tasks and outperforms traditional methods such as spatial and frequency domain techniques.
Brain Tumour Detection Using Resnet 50 and Mobilenet
Authors: G.V.S.N.R.V. Prasad Et al.
Published: December 2023

The scientific community defines a brain tumour as  a mass or growth of abnormal cells in the brain. A brain tumour is a development of abnormal cells, some of which may develop  into cancer. MRI scans are the most common way to find brain  tumours and are used to detect brain cancer. There are different  types of tumours exist. They are cancerous(malignant)and non- cancerous(benign) in the brain identification of unchecked tissue growth in MRI may help us diagnose brain cancer. Machine Learning and Deep Learning algorithms are used to identify this tissue growth. When these algorithms are applied to MRI scans, a faster prediction of brain tumours is made, and   a better degree of accuracy aids in treating patients. MRI scans   allow us to perform rapid analysis and identify the exact location of unwanted tissue growth. Various uses include image   recognition and identifying objects, image classification, segmentation, neural network and data processing. The proposed model successfully classified the MRI image into four   classes: glioma, meningioma, and pituitary tumour and no tumour, indicating that the given brain MRI has no tumour. In  this paper the proposed models are MobileNet and Resnet50 and gives accuracy of 0.98. These models classifies the type of tumour very accurately.
Domain Classification for Marathi Blog Articles using Deep Learning
Authors: Kiran N. Girase Et al.
Published: December 2023

Nowadays the exponential growth of online content, particularly in the form of blog articles is tremendous, the need for effective techniques to automatically categorize them into relevant domains has become increasingly important. To overcome the challenges the domains like natural language processing (NLP), machine learning (ML) and deep learning (DL)are being working as booster effect to emerge out with solutions. In this proposed system methodology-based NLP and DL domain the long short-term memory (LSTM) classifier for domain classification and compared the existing multiclass classification techniques with having accuracy around 94% and 91% by long short-term memory (LSTM) model using two different data sets one is Marathi new article and another one Financial article data set. The proposed model is being compared with multiple other models like naïve bayes (NB), XGBoost, support vector machine (SVM) and random forest (RF). The final estimated result achieved is best combination of dataset and deep learning algorithm LSTM.
Efficient Model based on Deep Learning for the Classification of Dementia
Authors: Hemant Choubey Et al.
Published: December 2023

Alzheimer's disease to severe dementia are all forms of dementia, which are neurodegenerative disorders that affect brain memory. The most prevalent type of dementia that impairs thinking and memory is Alzheimer's disease. Network width, depth, and resolution are scaled uniformly by Efficient Net using a set of compound coefficients. This study uses callback functions to diagnose four types of dementia in order to slow down the learning process and increase accuracy. Additionally, contrast CNN and the Inception V3 model with the EfficientNet deep learning model. Using EfficienNetB2, classification accuracy is approximately 99.3%.