Proceedings on Engineering Sciences

8

Authors: Zulfia A. Musarova, Chinara U. Adamkulova

This research explores the determinants influencing the economic progress of the Kyrgyz Republic within the context of interregional disputes. Situated in Central Asia, the Kyrgyz Republic is a landlocked nation sharing borders with Kazakhstan, Uzbekistan, Tajikistan, and China. Due to its strategic location and proximity to major powers, this region has a history marked by diverse geopolitical influence. Recent local changes stemming from sanctions imposed on the Russian Federation necessitate an examination of strategic concerns in the politico-economic dynamics of the region, specifically in the realm of food security. It is noteworthy that food security represents a multifaceted issue encompassing not only agriculture but also the economic, social, and political dimensions. A country’s ability to ensure food security can be influenced by its geopolitical circumstances. To provide the most current and reliable insights on this subject, this research references the latest reports and open data from international organizations, government bodies, and research institutions specializing in agriculture and food security matters within the Kyrgyz Republic and the broader Central Asian region. Geopolitical instability, in the event of an escalating Russia-Ukraine conflict, may give rise to heightened tensions in the broader region, potentially impacting neighboring nations, such as Kyrgyzstan, which could experience increased uncertainty, diplomatic strains, and regional conflicts that may disrupt the economic well-being of its population. This research scrutinizes the risks and potential opportunities regarding the economic development and food security of the Kyrgyz Republic.

10

Authors: Maria V. Petrovskaya, Gadzhimirze I. Gadzhimirzoev

The new polycentric format of the interstate association, which is BRICS, serves as the centre of gravity for the dynamically developing world economies. Over the past thirty years, the countries included in the group have gradually increased their economic weight on a global scale, concentrating an increasing part of the world’s industrial, infrastructure, trade, agricultural and other structures. Estimated from 1990 to 2021, BRICS has approximately doubled its economic and political weight on the world stage, mainly due to the growth of the real manufacturing sector. To date, on average, eleven BRICS countries concentrate about half of the world’s socio-economic and resource potential. Moreover, this share has a positive growth trend. It is not surprising that more and more countries are striving to join this association to strengthen their own economic and political position on a global scale.

14

Authors: Mavluda Sh. Akhmedova, Karen A. Meliksetyan, Alexander A. Krutilin, Olga A. Boris

The article aims to develop a new model for the development of industry 4.0 that reveals cause-and-effect relationships and thereby increases the predictability and manageability of this process. The authors has compiled a structural equation model (SEM) based on the empirical experience of 45 of the most developed digital economies in the world in 2022, which has formed a systematic vision of industrial engineering 4.0 in the unity of quality management and the development of high-tech industrial enterprises. Based on the SEM model and the example of Russia, it has been proved that quality management 4.0 plays a central role in the development of high-tech industrial enterprises in developed digital economies. As a result, the article has developed a cyclical model of the development of industry 4.0, explaining the logical sequence and demonstrating the path of continuous development of industry 4.0. The novelty and value of the compiled cyclical model lies in the fact that it has proved for the first time the simultaneous existence of two previously considered alternative effects of industrial and manufacturing engineering 4.0: the effect of transition from quantity to quality and the effect of transition from quality to quantity. The theoretical significance of the model lies in the fact that for the first time it has structured the sequence of this process, by dividing it into two stages: the first is the stage of the initial launch of high-tech industries and the second is the stage of the subsequent development of industry 4.0. The authors’ model demonstrated that quality management 4.0 plays a key role in the development of high-tech industrial enterprises at the second stage, while at the first stage the role of quality 4.0 is insignificant. The practical significance is expressed in the fact that reliance on the cyclical model of development of industry 4.0 will improve the efficiency of management of industrial and manufacturing engineering 4.0, selecting the most effective management measures at each of the identified two stages of development of industry 4.0.

14

Authors: Anastasia A. Sozinova, Nadezhda K. Savelyeva, Alexey V. Tolmachev, Natalya V. Shchukina

The purpose of the article is to determine the prospects for improving the practice of quality management of agricultural products at AIC 4.0 enterprises in order to increase their digital competitiveness in the world food markets in the conditions of the Fourth Industrial Revolution. Based on econometric modeling of international experience for 2022, it has been proved that quality (regression coefficient: 0.3673) contributes more (almost 6 times) to competitiveness than price (regression coefficient: 0.0622). It has also been revealed that the change in the quality and safety of food products by 71.57% is determined by the influence of AIC 4.0 technologies: market data (Big Data, AI, blockchain) and mobile banking; climate-smart agriculture technologies and innovative technologies (IoT, machine learning). A promising organizational scheme of quality management of agricultural products using AIC 4.0 technologies is presented on the example of the framework of the smart vertical farm of the Institute of Scientific Communications (ISC). The key conclusion is that quality management in the activities of agricultural enterprises using AIC 4.0 technologies forms the basis of their digital competitiveness in the conditions of the Fourth Industrial Revolution. The theoretical significance of the authors’ conclusions lies in the fact that they have revealed the peculiarities of the organization of world food markets in the context of global digital competition. The practical significance of the article is due to the fact that it offers a promising scenario for strengthening the digital competitiveness of agricultural enterprises and advancing SDG2 in the “Decade of Action”, as well as a set of authors’ recommendations for the successful implementation of this scenario through improving food quality management based on the engineering of AIC 4.0 technologies.

14

Authors: Alexander A. Solovyov, Tatyana A. Dugina, Svetlana E. Karpushova

The article aims to determine the possibilities of product quality management in industry 4.0 based on digital institutions. Based on international experience for 2022, the authors applied the regression analysis method to compile an econometric model that proves that ensuring digital competitiveness requires state and public management of product quality in industry 4.0 with the help of digital institutions. It has also been proved that digital competitiveness in local and global markets is determined by different institutions. The theoretical significance of the authors’ conclusions is that they have formed a new institutional understanding of product quality in industry 4.0. The contribution of the article to the literature consists in the development of the scientific provisions of the TQM concept through the formation of a new, broad understanding of the quality of Industry 4.0 products in the unity of the completeness of the manufacturer’s technical capabilities and the perceived value and usefulness of this product, as well as through a reconsideration of the approach to measuring and managing the quality of products industry 4.0 in order to strengthen their digital competitiveness in accordance with the new understanding of quality. The practical significance of the article is related to the fact that the monitoring has revealed a favorable institutional environment for quality management of products in industry 4.0 in Russia. The institutional perspective of improving the product quality of industry 4.0 in Russia has also been opened up. The managerial significance is expressed in the fact that the developed institutional approach to product quality management in industry 4.0 will improve the efficiency of this management and ensure a more complete capacity utilization of medium- and high-tech industries, as well as an increase in the export of their products. The proposed approach can be applied in any country of the world, as it has been developed taking into account a broad analysis of international experience.

14

Authors: Nodirjon M. Yuldashev, Lyudmila Yu. Yugay, Elena S. Akopova, Natalya M. Fomenko

The article is devoted to solving the problem of the imperfection of the existing approach to knowledge management in the quality assurance system of Industry 4.0 products, due to the fact that the place of knowledge management outside the quality assurance system of industry 4.0 products, characteristic of this approach, hinders the achievement of sustainability and competitiveness. The authors have compiled an econometric model based on the international experience of the top 40 leading countries of the world with the most developed industry 4.0 for 2023, which mathematically describes and justifies the significant contribution of knowledge management to the product quality of industry 4.0 from the standpoint of sustainability and competitiveness. The model has identified key factors of sustainability (implementation of SDGs 8 and SDGs 9) and competitiveness, namely knowledge capital, research, development and innovation outputs and impact, as well as information and communications technology usage. To solve this problem, an alternative, new approach to knowledge management in the product quality assurance system of industry 4.0 has been developed, which makes it possible to simultaneously and fully achieve sustainability and competitiveness. The originality of the approach is that it considers quality as a result of sustainability and competitiveness; and knowledge management is interpreted as the embodiment of quality, located inside the quality assurance system of products in industry 4.0.The theoretical significance of the authors’ conclusions is that they rethought the place of knowledge management in the product quality assurance system of industry 4.0, which should be inside this system in the interests of sustainability and competitiveness. The practical significance of the developed approach is due to the fact that it will improve the practice of ensuring the product quality of industry 4.0 through the integrated achievement of sustainability and competitiveness through the optimization of knowledge management.

16

Authors: Aleksei V. Bogoviz, Valentina N. Parakhina, Irina A. Morozova, Elena V. Patsyuk

The article aims to determine the current level, reveal the prospects and justify the advantages of further integration of the SDGs into the quality management system of enterprises in industry 4.0 in the "Decade of Action". Global monitoring of the practice of integrating the SDGs into the quality management system of enterprises in industry 4.0 based on the international statistics of the United Nations and the World Bank for 2019-2021 has been carried out. Correlation analysis showed that in both categories of countries considered, the degree of integration of the SDGs into quality 4.0 is moderate. In 2021, it is estimated at 22.83% in developing countries, and at 7.54% in developed countries. The key conclusion of the study is that the SDGs are not yet fully integrated into quality 4.0, which, in particular, has been hindered by the pandemic and the COVID-19 crisis – more serious changes in the information system and product quality management in industry 4.0 are needed to solve this problem. In particular, the following conclusions have been made. The prospects for sustainable development of developed and developing countries in the "Decade of Action" are associated with further efforts to fully integrate the SDGs into the quality management system of enterprises in industry 4.0. This conclusion is supported by the authors’ forecast, which in turn is based on an econometric model obtained using the regression analysis method. The theoretical significance of the author's conclusions is that they have formed a reliable evidence base that, unlike other sectors of the economy, the degree of integration of the SDGs into the product quality management system in industry 4.0 is much lower and insufficient for the implementation of the 17 UN SDGs in the "Decade of Action". The practical significance of the results of the study is explained by the fact that they allow taking into account the specifics of developed and developing countries when integrating the SDGs into management practices of quality 4.0.

16

Authors: Gulchekhra Z. Tulaganova, Dadajon R. Khabibullaev, Olga A. Surkova, Svetlana A. Mustafina

The article aims to support the decarbonization process and the fight against climate change, as well as contribute to the reduction of global energy and environmental inequality. The purpose of the article is to clarify the causal relationships of quality management in Energy 4.0 and to determine the prospects for improving this management based on Smart Grid and EnergyTech. The study is carried out in the context of geographical regions of the world on the example of 115 countries according to data for 2022, based on the method of regression analysis, analysis of variance and the methodology of game theory. As a result, it has been proved that with the spread of digital technologies, not all, but only some indicators in Energy 4.0 improve, that is, the potential for quality improvement is not fully revealed. The authors have also concluded that the quality in Energy 4.0 is determined by the spread of advanced technology and investment in energy with private participation. The theoretical significance is due to the fact that the compiled econometric model has clarified the scale and nature of the impact of Smart Grid and EnergyTech on quality in Energy 4.0. The practical significance of the conclusions made by the authors is related to the fact that the article has revealed the prospects for the development of Smart Grid and EnergyTech in regions of the world through the prism of the consequences for quality in Energy 4.0 and global inequality. The significance of the authors' recommendations for energy policy is that the developed new approach to energy policy 4.0 makes it possible to improve public quality management system in Energy 4.0 based on Smart Grid and EnergyTech. The managerial significance of the article is expressed in the fact that the authors' recommendations make it possible to improve management information systems in the field of quality in Energy 4.0 and to increase the efficiency of corporate quality management in the practice of energy companies using such tool as Smart Grid and EnergyTech.

16

Authors: Alexey V. Tolmachev, Anastasia A. Sozinova, Nadezhda K. Savelyeva, Victoria A. Saidakova

The purpose of the article is to develop a systematic scientific vision of the quality assurance process in industry 4.0 through HRM of digital personnel. This vision is based on a new (“broad”) interpretation of quality in industry 4.0, which can maintain a balance between sustainability (the support of the SDGs) and global digital competitiveness and most completely take into account the characteristics of product quality in industry 4.0. In accordance with the authors' interpretation based on international experience for 2021-2022, the article presents an econometric model that mathematically describes the impact of HRM of digital personnel on product quality in industry 4.0. The key conclusion of the study is that the attraction of job-ready digital personnel makes a much greater contribution to improving quality in industry 4.0 and is therefore preferable as compared to corporate training of digital personnel. For the fullest disclosure of the potential of quality improvement in industry 4.0, the authors have developed a program-target approach to HRM of digital personnel with a balance between sustainability and competitiveness of quality in industry 4.0. The theoretical significance of the research results is due to the fact that they have allowed for the first time to develop an approach to HRM of digital personnel that ensures high quality in industry 4.0 in accordance with its innovative interpretation – with a balance between sustainability and competitiveness. The practical significance of the authors' recommendations lies in the fact that the proposed program-target approach to quality assurance in industry 4.0, with a balance between sustainability and competitiveness, will increase the efficiency of HRM of digital personnel and comprehensively take into account the interests of stakeholders in ensuring product quality in industry 4.0.

16

Authors: Lyudmila Yu. Yugai, Maxim V. Otchertsov, Sergey E. Akopov, Iso R. Dusbayev

The research aims to examine the environmental component of product quality as a manifestation of Industry 4.0 business sustainability and its implications for competitiveness. This research is based on Structural Equation Modeling (SEM) methodology on the international experience of 63 countries in 2023 using IMD and UN statistics. The authors analyze the interdependence of sustainability and competitiveness of Industry 4 .0 business, showing that improving the environmental component of product quality as a manifestation of sustainability of Industry 4 .0 business contributes to its competitiveness. The global business disparity of Industry 4.0 is reimagined from a sustainability and competitiveness perspective. The authors reveal the prospect of reducing global inequality by increasing the sustainability and competitiveness of Industry 4.0 businesses in developing countries. The main conclusion of this research is that improving the environmental component of the product quality of Industry 4.0 business products simultaneously improves sustainability and competitiveness, making the environmental component the key to consistent quality management and overcoming global inequalities – the digital and sustainability gaps.The theoretical significance of the research results lies in the fact that they clarified the cause-and-effect relationships of quality management in the business of Industry 4.0, formed a more complete understanding of management information systems in the field of business quality of Industry 4.0, and highlighted the systemic interdependence of competitiveness as the main component of product quality and additional environmental component as a manifestation of the sustainability of Industry 4.0 business. The practical significance of the author’s findings and recommendations is that they will ensure the reduction of global inequality by increasing the sustainability and competitiveness of Industry 4.0 business in developing countries.

6

Authors: Soumya A. K., Ritu Shree, Anu Sharma

The fracture behaviour of particle composites made of polymers under impact loading is predicted in this research using a hybrid machine learning approach dubbed Hybrid Artificial Neural Networks and Random Forest (HANN-RF), with a focus on mode-I fracture. The goal of the study is to create a model for prediction that accurately links input variables to histories of crack initiation, fracture toughness, and the intensity of the stress factor (SIF). A full dataset is created, with inputs for the composites' compositional properties and impact loading scenarios. The HANN-RF model combines a Random Forest (RF) method and an ANN (Artificial Neural Network) in order to improve robustness and accuracy in forecasting. Metrics like MAE, MAPE for short, and accuracy are used in model evaluation. The outcomes show that the HANN-RF technique successfully predicts and forecasts mode-I fracture behaviour, offering insightful information for evaluating the effect on resilience and longevity of particle polymer composites in a variety of applications.

8

Authors: Umesh Kumar Singh, Ramachandran T., Mohit Kumar Sharma

For power systems to operate reliably and effectively, state estimate is essential. For monitoring and control applications, it offers real-time estimates of the system's state indicators, including voltage levels and orientations. In this paper, a novel catagonfly optimization (CFO) technique that aims to improve state estimation effectiveness in electrical systems is presented. The suggested strategy combines optimization techniques from cat swarm and dragonfly. The suggested strategy is evaluated using the IEEE-118 test environment under various simulated scenarios, and the findings are contrasted with those of other methods already in use. The optimization results and statistical error assessment demonstrate the suggested CFO technique's efficiency to the alternatives. The results of this study also have the potential to improve the incorporation of sustainable energy sources, microgrids, and additional emerging innovations into existing power grids.

8

Authors: Pramod Kumar Faujdar, Ashish Simalti, Kannagi Anbazhagan

The issues in Vehicle Routing with Time Windows (VR-TW) are addressed in this study using a novel hybrid swarm-intelligent frog jumping optimisation (HSIFJO) algorithm. The method employs a diversity management strategy for developing memeplexes, which assists in preserving diversity and prevents the premature termination of the search. To increase population diversity and improve solution quality, an enhanced clone selection (CS) process is employed. To maximise the algorithm's potential, an enhanced and extended extremal optimisation (EO) strategy is used, coupled with different move operators. A proposed adaptive soft time windows (ASTW) surcharge approach acknowledges the possibility of impractical solutions during the evolution process. When compared to existing state-of-the-art heuristics, the suggested approach performs exceptionally well in performance evaluation.

8

Authors: R. Kamalraj, Vikas Verma, Manish Joshi

Effective maintenance coordination has become essential to ensuring a reliable electricity supply in power systems primarily powered by renewable sources. On the other hand, the computational complexity of the operational security standards presents difficulties for the existing planning tools. To solve this problem, a research paper suggests applying the machine learning (ML) method known as lightning search optimised random forest (LSORF) to anticipate the results of contingency analyses rapidly and effectively. The entire regional transmission system of Belgium (BE), which includes voltage ranges of 200 kV to 50 kV, is the subject of the study. Results show that LSORF regularly outperforms other benchmarks. The results demonstrate that LSORF consistently outperforms other benchmark methods. Furthermore, the study highlights the impact of projected growth in renewable energy on maintenance feasibility. This strategy provides useful insights for improving maintenance planning in renewable energy systems.

8

Authors: Kishore Kumar P, Alka Kumari, Pradeep Kumar Verma, Mohit Kumar Sharma, Vinod M, Lokesh Varshney

Non-orthogonal signal-based systems are a type of communication system that uses signals that are not mutually perpendicular (i.e., not orthogonal) to transmit information. These types of systems can increase the spectral efficiency of communication systems by allowing for more data to be transmitted in the same bandwidth. Groups of signals with non-orthogonal waveforms can increase spectral efficiency, but they also increase the potential for interference. Spectrally efficient frequency division multiplexing (SEFDM) is a well-studied waveform that was originally proposed for use in wireless systems but has since found application in millimeter wave communications at 60 GHz, optical access network architecture, and long-distance optical fiber transmission. However, non-orthogonal signal-based systems are also more susceptible to interference from other sources, which can degrade the quality of the transmitted signal. To address this problem, this paper suggests using fuzzy learning techniques to cancel out interference and improve the signal-to-noise ratio. Fuzzy learning is a type of machine learning that uses fuzzy logic (FL) to handle uncertainty and imprecision in data. By using FL techniques to cancel out interference, the non-orthogonal signal-based optical communication (OC) system could potentially achieve better performance in noisy environments. Overall, this research topic has the potential to contribute to the development of more efficient and reliable OC systems that can operate in challenging environments.

8

Authors: Ranjan Kumar, Parvesh Belwal, Harsh Shrivastava, Jisha LK, Pankaj Kumar Goswami, Gitanjali Mehta

The fact that they are unpredictable and unreliable, renewable energy sources (RES) are increasingly crucial to the electrical power grid's ability to maintain energy continuity. The challenge of energy sustainability can only be solved by energy storage technology. Regarding a Hybrid Energy Storage System (HESS) powered by a 4-wire, 3-phase grid connected solar Photovoltaic (PV) power system, a novel Smart Energy Control Technique (SECT) with a Whale optimization algorithm is presented in this work. The sustainability of energy via solar PV power generating systems is achieved by using HESS, which consists of batteries and ultra-capacitor storage devices for energy. The suggested SECT has been used for the analysis and experimental testing of several HESS operating scenarios. During experimental testing, the load status of a single sunny day and the PV power outline were constructed and dynamically assessed by utilizing SECT; some test findings in eight distinct operating modes are included in this paper. The system uses 1320W of electricity to charge the battery group, and in one of its modes of operation, the leftover energy is sent to the grid using 5% present harmonics. And because of the system's high power density, quick reaction, and great efficiency, the HESS is a highly efficient energy storage method. Simulation findings and laboratory testing have validated the suggested system.

10

Authors: Moiz Mohammed, Mohammed Ahmed Hussain

The pre-engineered steel framed structure (PEB) introduced in 1960’s includes a structural frame, roofing system and wall supports; for the construction of industrial structure like ware houses, car showrooms, workshops, function halls, stadiums, aircraft hangars etc. is found to be economical, light weight and fast erection process. The PEB’s are built to perform some important functions, provide enough space for storing goods; aircrafts etc.. and protecting the storage items against natural disasters, wind forces, and rain. In this research work a hangar for airbus A-380 has been designed considering its dimensions; for maximum span of 120M and width of 115M and a height of 30M as a pre-engineered framed structure. For designing the structural members staad pro (V8i) software is used. This structural design is in accordance with the specification of the general construction in steel confirming to IS:800-2007 (limit state design) and wind application as per latest code confirming to IS:875-2015 ( part-III) and earthquake analysis has been done as per IS-1893-2016 (part-IV). For the first time a hangar for A-380 has been designed for using above IS Codes, structural design details, connection details have been produced and found that the total steel is 3502.43 Metric Tons.

10

Authors: Bhuvana J., Jitendra Kumar Katariya, Shambhu Bhardwaj

Mass customization is becoming the more and more of emphasis on the production optimization. In many manufacturing and service organizations, production planning and scheduling are characterized as the daily decision-making procedures. The significance of the choices made is therefore to shown in the areas of work orders, manufacturing, transportation, and distribution of the finished goods. Production scheduling is the process of regulating, determining, and maximizing the restricted resources of the production system. In this study, a novel Hybrid Dynamic Genetic-Adaptive Improved Gravitational Optimization Algorithm (HDG-AIGOA) approach is introduced to optimize the production schedule. In this case, the AIGOA classification effectiveness is increased by using the HDG method. The small and benchmark iMOPSE dataset has been used to assess the success of suggested approach. The noisy data from raw data samples are removed using the Adaptive Median Filter (AMF) filter. To extract the properties from the segmented data, a Kernel Principal Component Analysis (KPCA) is performed. The results of the research show that the recommended methodology beats earlier approaches in terms of the accuracy, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Square Error (MSE). Our proposed method might consider to improve the production scheduling in an dynamic environment.

10

Authors: Preeti Verma, Sashilal Singh M., Ravi Angadi V., Garima Goswami, Gnana Jeba Das, Kanika Jindal

The reduction of carbon emissions in the transportation sector will be aided by the electrification of transportation in RES-based energy systems. However, the inactive addition of electric vehicles is expected to hinder sustainability efforts owing to the rise in power consumption and the significant peak impacts of charging. The three main charging methods for Electric Vehicles (EVs) in Europe are: Smart Charging (SC), Power Charging (PC), and Vehicle-To-Grid (V2G) that give varying degrees of flexibility are examined in this research. This flexibility is compared to the flexibility provided by interconnections. We depict immediate action and future planning in the power organization using the Balmorel optimization tool, and we advance the state of the art by creating new approaches to stand for battery deterioration & at-home charging. Our results show that, up to the year 2050, any rise in charging flexibility reduces system costs, modifies the energy mix, affects spot prices, and reduces CO2emissions.We quantify the reciprocal benefits of flexible charging and variable generation, which limits the economics of permanently installed batteries and causes solar energy to take the place of wind energy in passive charging. The framework that includes and lacks connection development highlights the interplay between European countries in terms of the power price framework of electric mobility. The condition of the nations with the cheapest and most decarbonizes power mix is harmed beneath the most bendable situation at the EU level, even if the best result is achieved. This necessitates an adjusted coordinating strategy at the EU level.

12

Authors: Nisha Sahal, Preethi D., Dushyant Singh,

The term deep learning-based framework for smart mobility refers to a concept or research article that suggests a framework for traffic pattern prediction using deep learning methods in the context of smart mobility. To improve traffic prediction skills and create more intelligent and effective transportation systems, the Autonomous traffic prediction: A deep learning-based framework for smart mobility idea proposes to make use of the potential of deep learning algorithms. In this study, a new Improved Spider Monkey Swarm Optimized Generative Adversarial Network (ISMSO-GAN) approach is introduced to forecast autonomous traffic for smart mobility. In this case, the GAN's classification effectiveness is increased by using the ISMSO method. The Regional Transportation Management Center's traffic dataset for Twin Cities' metro freeways is used to assess the success of the suggested approach. The noisy data from raw data samples are removed using the Adaptive Median Filter (AMF) filter. To extract the properties from the segmented data, a Kernel Principal Component Analysis (KPCA) is performed. The results of the research show that recommended methodology beats earlier approaches in terms of accuracy, Mean Square Error (MSE), Mean Absolute Error (MAE), and Prediction Rate. Our proposed method might considerably enhance traffic management and maximize resource allocation.

7

Authors: Sunthan Chayanon, Wijittra Srisorn

The objectives of this research were: 1) to study the level of application of knowledge of honesty in daily life among youth in Ranong province, and 2) to compare the level of the application of knowledge of honesty in daily life among youth in Ranong province classified by personal factors. The sample group used in the research was 400 youths in Ranong province. The statistics used for data analysis were percentage, mean, standard deviation, t-test, and analysis of variance. The statistical significance was determined at the 0.05 level. The results of the study showed that most of the youths in Ranong province were females (211 people), most of them were between the ages of 15-18 years old (254 persons), having education level below Mathayom 3 (Junior high school) (149 people), and most of them had been to the moral camp (211 people). The overall level of applying knowledge of honesty in daily life among youth in Ranong province was at a high level in all items (x ̅ = 3.68). If considered on a case-by-case basis, the honesty to others was at the highest level (x ̅ = 3.75), followed by honesty toward duty (x ̅ = 3.67), integrity to oneself (x ̅ = 3.66), and honesty to the community and society (x ̅ = 3.65), respectively. The youth residing in Ranong province with different personal factors had no difference in the level of application of the knowledge of honesty to their daily lives at the statistically significant value of 0.05.

8

Authors: Monika Dangore, Hare Ram Sah

Since past two decades MANET researchers have focused on providing security solution to MANET to protect them from various network attacks. Most of the recent security approaches are restricted to address specific attacks only. This makes them obsolete when a different attack is introduced in the network. The objective of this research work is to offer a comprehensive solution to protect MANET from different security threats. We have proposed Multiple Attacks Protected Ad-hoc On-demand Distance Vector (MAPAODV) Routing Protocol. It provides a consolidated approach to address different security threats in the network with the lowest computational overhead. The Node Behavior Score (NBS) module of the proposed protocol performs precise detection of the attack whereas Node Reliability Analysis (NRA) module achieves attack mitigation and reliable route formation. The efficiency of the proposed protocol is tested in the simultaneous presence of grayhole and wormhole nodes using NS2 simulation and compared against two existing protocols. The simulation results show better performance of the proposed protocol against different attack types.

8

Authors: Tikhamporn Punluekdej, Lynda Buranachon, Nichapa Leeteerachoti, Phongphan Polyiem, Pinrutai Sutheerapong

The results of a research on “Charismatic Leadership and the Success Towards Social Work Operation: A Case Study of Phra Phisarn Prachathorn Vi (Phob Chokh Tissawongso), Wat Huay Pla Kang, Chiang Rai Province” showed that: 1) Wat (temple) HuayPla Kang is a private monastery under the Maha Nikaya Sangha located in Rim Kok sub-district, Mueang Chiang Rai district, Chiang Rai province with approximately 15 rai in total area having Phra Acharn Phob Chokh as the first abbot of the temple. He has begun his social work about 8 years ago when the villagers brought two orphans under his patronage. 2) The vision and missions performed by Phra Phisarn Prachathorn Vi. regarding the social work operations included: a vision; maintenance of Buddhism, creation of prosperous monastery, continuous cooperation with the community, and helping every walk of life, while the missions are: nothing is much more important than helping people, to be excellent in giving and sharing, and to become a great sacrifice. 3) The characteristics of a charismatic leadership of Phra Phisarn Prachathorn Vi. are:(1)vision, (2)confidence, (3)inspiration, (4) communication, (5) risk taking, and (6) morality and ethics.

8

Authors: Mohammed Qelhas

This systematic review examines the current state of digital intelligence in the age of artificial intelligence. A total of 26 relevant papers were shortlisted for a review based on a keyword search of academic databases. The review looked at the literature relating to the fields of artificial intelligence, machine learning, deep learning, and other related fields to understand the current advances in digital intelligence. It considers the impact that digital intelligence has had on society in terms of economic, political, and social implications. The review also considers potential ethical concerns related to digital intelligence and its use in the age of artificial intelligence. Systems utilising artificial intelligence can benefit from considering its impact and digital intelligence and vice versa. This can lead to better quality systems.

10

Authors: Ritesh Kumar Jain, Anil Kumar Nanda

In coal-fired power producers coal is majorly used in production. It was utilized for charging in the furnace boilers in the form of cones. These the lumps were usually immersed continuously in a moving gate. With the rise in temperature, the ash takes on a molten form. After chilling, it turns into cinder containing little ash. It has been proven as power saver. Global production of lake ash is growing every year. Both in disposal, and in practice, appropriate measures should be taken to protect the person life, wildlife and nature. Accordingly, a study was conducted for different combinations of sand, pond ash along with fibers encapsulated into the geo fiber sheet were subjected to different overburden pressures and were tested for varied permeability conditions.

10

Authors: Waiphot Kulachai, Sutham Cheurprakobkit, Layla Kurniawati, Patipol Homyamyen , Pennapa Pornsupikul, Thaywuse Borriraksuntikul

This paper aimed to examine the relationship between servant leadership, employee engagement, and quality of service delivery. For this purpose, a structural equation modeling with AMOS was used to test the model fit and the relationship between each latent variable. Findings reveal that the model was fit with the empirical data. Servant leadership had a positive impact on employee engagement mediating the association between servant leadership and quality of service delivery. However, servant leadership had a negative impact on the quality of service delivery. In addition, the findings reveal a positive relationship between employee engagement and quality of service delivery. Relevant implications for future studies in this area are discussed.

12

Authors: Xi Zhang, JianYin, Fang Wei Li

Buildings are key contributors to the emissions of toxic carbon dioxide, which is a global greenhouse gas, and lowering the concentration of this gas is an essential mitigation in mitigating the effects of climate change. This study majorly focused on the strategies that could be applied in the building and construction industry to help in lowering carbon concrete in concrete mixes. Various challenges were reported to be prevailing when it comes to the adoption of the use of low-carbon concrete in the construction sector. The cost of low-carbon concrete alternatives was among the topmost challenges that made most of the owners of the construction projects apply them. The study was conducted at Huajie Construction Company, which was among the leading construction companies in China. This facilitated the acquisition of accurate information as per the needs of the research objectives. For data collection, 150 participants were selected from this company through the implementation of a purposive sampling technique. Therefore, to address all these, some low-carbon concrete alternatives were suggested for adoption in construction activities. These alternatives included: carbon capture concrete, hempcrete, ferrock, recycled aggregate concrete, and geopolymer concrete. All these alternatives had safe properties that could help to lower carbon emissions.

12

Authors: Hristo Uzunov, Silvia Dechkova, Vasil Uzunov

Safe driving is related to the choice of speed by automobile drivers according to atmospheric conditions, as well as when driving in zones of both reduced visibility and of limited visibility. Reduced visibility is associated with natural phenomena, such as fog, rain, snow, darkness, etc. Limited visibility is related to objects located on the traffic lane and near it, as well as topography of the area that obstruct the visibility of the driver. This paper outlines a dynamic study of a significant problem in driving connected with limited visibility from the driver’s seat due to automobile interior equipment. The research was done implementing experimental and numerical study, obtaining the relative motion of a zone of partially limited visibility from the front left and right car pillars in relation to the trajectory of the pedestrian. At the moment of pedestrian detection, they fall into the danger zone for the car.

14

Authors: Luís César Ferreira Motta Barbosa, José Salvador da Motta Reis, Maria Augusta Siqueira Mathias, Fernando Juliani, Otávio José de Oliveira, Gilberto Santos

This study analyzed the most recurrent elements in the scientific literature on business strategy (BS) formulation, implementation, management, and execution. Through a content analysis it was possible to identify (21) elements that were grouped into (6) principles according to their similarities, synergies, and convergences. These principles were named as: (1) Scenario Analysis, (2) Business Definition, (3) Systemic Vision, (4) Management Support Processes, (5) Strategic Information and Indicators, and (6) Competitive Strategy. Among the main results of the research is the compilation of a new and relevant body of scientific knowledge related to BS. These findings may assist managers and organizations that want a better understanding for BS development. This theoretical framework also serves to establish a common baseline for future studies related to the theme, such as empirical research and case studies through the concepts and structure of the BS principles and elements systematized here.

14

Authors: Saad Alghamdi, Ben Soh

This study assesses the adoption of Massive Open Online Courses (MOOCs) by Saudi students in Australian universities, exploring its potential impact on achieving Saudi Vision 2030 goals. Utilizing the Technology Acceptance Model, integrated with Personal Innovativeness in Information Technology (PIIT), the study examines the intention to continuously use MOOCs through Perceived Usefulness (PU), Perceived Ease of Use (PEOU), and PIIT. Four hypotheses were validated with survey responses from 141 Saudi students, revealing correlations between demographic factors, learning benefits, and technology adoption. Male students aged 25 to 44, pursuing diverse courses, exhibited a higher likelihood of continuous MOOC adoption. The majority (65-75%) found MOOCs instrumental in various learning tasks, emphasizing ease of use and control. These capabilities fostered a willingness to explore new technologies promptly. Despite hesitations among some students, a significant majority expressed a readiness to predict, plan, and intend to use MOOCs continuously. The study recommends strategies to enhance MOOC adoption in Saudi Arabia, targeting students, faculty, university management, the Ministry of Education, and the government, aligning with Vision 2030 objectives. Acknowledging study limitations, these findings provide valuable insights for future research and initiatives in the evolving landscape of online education.

6

Authors: Snehalatha N, Mohana Kumar S,

The Rapid Industrialization has led to a sudden overwhelming boost in business. With growing advancements in technology and the fast-paced growth of users that have access to said technology everything reaches customers faster. Businesses have also tried their hand at being better at technology and thus boosted growth by appealing to a much larger customer base. Market segmentation is an increasingly important part of a strong marketing strategy and can make all the difference for companies in competitive market landscapes, such as e-commerce. To be in business today means much more than quality of the product and a brand name. It involves the right kind of marketing to the right kind of people. This paper focuses on creating a tool to enable businesses to understand the various customers it has, by segmenting them into groups and providing a detailed statistical model for analyzing where the marketing is needed the most and what would be the best offers the company can afford.

8

Authors: Atul Zope, Raju Kumar Swami, Atul Patil

The purpose of this paper is to identify the various types of lean six sigma (LSS) barriers involved in the assembly process of electric vehicles (EV). An exhaustive literature survey was conducted to identify the critical barriers in LSS implementation. Four main barriers affecting the assembly process are transportation and handling, assembly line processing, EV assembly integration, and human resources and training. The main barriers were further separated into several sub-barriers. The potential solutions to address the sub-barriers are investigated. The implementation of these solutions will help automotive industries to achieve an optimized and economical high volume production, make operations easy, improve process flexibility, and develop human resource essential for the EV assembly process.

8

Authors: Vladimir N Khmelev, Roman Barsukov, Aleksandr Barsukov

The article presents the results of studies aimed at identifying the possibility of using piezoelectric ultrasonic oscillatory systems (USOS), used to form cavitation effects in liquid media, as a sensor for controlling the degree of cavitation erosion of materials for working tools and protective coatings. The studies were carried out on the basis of the analysis of the piezoelectric ultrasonic oscillatory systems (emitters) physical equivalent circuits, formed from electromechanical analogues, taking into account the attached test samples. The results obtained made it possible to confirm the possibility and effectiveness of monitoring the ultrasonic oscillatory system parameters to determine the degree of cavitation destruction of tools and protective coatings, as well as to establish the sensitivity of the proposed control method.

8

Authors: Vladimir Lantsov

A new algorithm is presented to reduce computational costs in solving harmonic balance equations obtained by separating state variables. In the author's previous works, an approach was proposed where the vector (matrix) of unknowns is replaced by two matrices of small dimension, which leads to two systems of balance equations that are solved iteratively. The first equation reduces the number of harmonics in the balance equations, the second equation reduces the number of circuit nodes. In this paper, it is proposed to further reduce computational costs by approximating part of the elements of the balance equations using the decomposition procedure based on singular values. It is proposed to construct a matrix of sets of responses of nonlinear dependencies of circuit models before solving the problem by an iterative method. This matrix reflects all the main changes in nonlinear dependencies with changes in the amplitudes of the input effect and over time. The resulting matrix is then approximated by applying decomposition based on singular values. Comparison of the proposed algorithm with the standard harmonic balance method and algorithms developed by the author earlier showed its high efficiency.

8

Authors: Haitam Ettazi, Najat Rafalia, Jaafar Abouchabaka

In the field of deep learning, a convolutional neural network is a class of artificial neural networks that became dominant in various computer vision tasks, which is widely used to solve complex problems in various areas, including driver assistance systems in the auto- motive field. Convolutional neural networks overcome the limitations of others conventional machine learning approaches since they are designed to automatically and adaptively learn the spatial characteristics of features in an image. In this paper, we are going to evaluate the inference and accuracy of YOLOv5s, for effective traffic sign detection in various environments. The results generated upon five classes gives satisfaction by 63.7% for the mean average precision, and over 80% in accordance to 5 categories set in this study. This article compared to YOLOV4 based CSP-DarkNet53 using Indonesia Traffic Signs generate better precision.

10

Authors: K.Komagal Anupama, C. V. Subramanian

Architecture persistently evolved from the need for shelter and living spaces. Subsequently, this is prominent and reinforced through the knowledge over some time through oral traditions and practices that are time tested and improvised to develop a unique expression termed Vernacular architecture. It is evident from the existing literature that the built environment as a subsystem has the potential to influence and direct behavior among the occupants of the settings. This paper attempts to determine the spatial feature of the vernacular setting in the selected context which has a certain identity and has the potential in inducing specific positive Affect like enthusiasm among the occupants. In pursuit of this, the physical setting feature of the vernacular house Thinnai is studied for its identity of the house in context and its impact in inducing the experience of positive affect enthusiastic effect through a set of data collected by questionnaire survey and semi-structured interview method. The result of the analysis indicates that Physical setting features induce affect when people habituate to the vernacular settings that stand for their identity daily and it confirms the hypothesis that a physical setting has a significant role in inducing Positive affective among the occupants of the vernacular settings.

12

Authors: Vadim A. Chukreev

The research aims to investigate the role of education in the security of the biosocial essence of a person in the implementation of the socio-investment model of economic growth. This research focuses on the concept of the biosocial perspective in the unity of the well-being of humans as a biological species (satisfaction of biological needs) and their position in society (satisfaction of social needs). In the social and investment model of economic growth, the management tool is investments in the increase in the quality ofhigher education services, and the process of human developmentis comprised of biosocial phenomena, social connections (social lifts through obtaining higher education) and context (return of investments in higher education).The authors conducted an econometric study based on correlation analysis. This method is used to determine the relationship between the quality of higher education and official employment, the accessibility of employment and career building for young people (absence of ageism), the gender neutrality of society and the economy, and the absence of poverty. The key conclusion of the research is that the quality of higher education plays an important role in the security of the biosocial essence of a person during the implementation of the socio-investment model of economic growth.This paper also discovered challenges for the engineering of Industry 4.0 technologies, which are connected with the necessity for technologicalsupport for the most successful execution of the role ofthe quality ofeducation in the employment of youth as the central element of ensuring the security ofbiosocial essencein the conditions of the Fourth Industrial Revolution.The novelty of the research lies in the clarification of the causal links between sustainable development and the disclosure of human potential from the perspective of the security of the biosocial essence of a person in support of the implementation of the Sustainable Development Goals (SDGs). The contribution of the research consists of developing a toolkit to implement the socio-investment model of economic growth and thereby improve the manageability and efficiency of this process. The social significance of the research is that it demonstrated the possibility and feasibility and provided a scientific and methodological basis for the systemic implementation of SDG 1, SDG 4, SDG 5, and SDG 8.

14

Authors: Dhrar. M. Hanoon, Qasim A. Aljanabi

The electrothermal method was used to treat soft clay soil under load in this study. The experiment model was adopted to study settlement behavior. The effect of heat on settlement and maximum stress, of soft clay soils, were studied. The variables studied are the distance between the heaters, the heating time, and the temperature of the source. A model was used with dimensions (60 * 40 * 60) cm, and heaters were used in each model, and the power of each heater was 925 watts, and the number of models used was 37 models. The first examination was without heat treatment, and settlement was measured in it directly. As for the rest of the tests, heat treatment was used in it, and the tests were divided into two phases. The first stage is the heat treatment stage, and the second stage is the stage of placing the mechanical load on the soil. The mechanical load is weights placed on the soil through the footing. The tests were divided according to the research structure into three cases and according to the distance between the two heaters (20,30,40) cm. In each case, the tests are conducted according to the heating time, where the heating time was used (4,8,12) consecutive hours, and each time 4 tests were used at different temperatures (200,300,400,500) degrees Celsius. An improvement value of 99.8% in the settlement was obtained when the source temperature was 500°C, with a heating time of 12 hours, and the distance between the heaters was 20 cm. An improvement in maximum stress of 425% was obtained when the source temperature was 500 °C, the heating time was 12 h, and the distance between the heaters was 20 cm. The conclusions of the study are that the settlement decreases with increasing temperature and the ultimate stress increases with increasing temperature.

18

Authors: Evgeniy Pevtsov, Tatiana Demenkova, Alexander Sigov, Alexander Shnyakin, Semyon Moskolenko

This article focuses on software methods for detecting and preventing the introduction of hardware trojans into the topology of integrated circuits at the design stage. An additional recommendation for typical procedures of receiving GDSII files that significantly complicates the introduction of HTs into the topology is to facilitate detection methods by including special self-test structures created after performing transformations of the initial topology and ensuring the effective examination of ICs at the post-manufacture test stage. The proposed method is based on the analysis of synthesis results at the level of netlist description, its subsequent software conversion into a topological drawing, shifting standard cells and filling created voids with special self-test cells. The method is simple to implement during the topology design stage and can be recommended for use in design centres for machine learning of computer-aided design systems.

22

Authors: Vanishree Beloor, T S Nanjundeswaraswamy, D R Swamy

The study aimed in identifying Green supply chain critical success factors, develop and validate the framework through integrated approach of ISM, MICMAC and SEM so as to promote green practices throughout the supply chain activities in Indian manufacturing sectors. Interpretive structural modelling(ISM) is applied to develop hierarchical contextual relationship among identified critical success factors via Pareto analysis. The methodology then follows classification of success factors into four clusters by Matrice d’ Impacts Croisés-Multiplication Appliquée á un Classement (MICMAC) and statistical validation of the ISM model through Structural Equation Modelling(SEM) by AMOS. In this study, 16 critical success factors of Green supply chain practices for manufacturing industries were identified, followed by development of an ISM model using 16 critical success factors, later the model was statistically verified that identified nine CSF’s responsible for generating SEM model by satisfying all the model fit indices.The linkage variables identified are Green manufacturing, Green Procurement, Green marketing and Distribution, Green purchasing, Supplier cooperation, Customer cooperation, Environmental strategies and management, Environmental Participation and Green training that are forming the driving force for practicing green supply chain. Research limitations/implications: The results of the study are restricted to manufacturing industries, which might vary when applied for other sectors. The developed model on green supply chain management practices would help policy makers, decision makers, researchers and industry professionals to anticipate potential success factors to implement green supply chain practices. Accordingly, the focus on critical success factors would be prioritized for obtaining better performance of supply chain and greening the chain.

8

Authors: Yevhen Artamonov, Iurii Golovach, Halyna Rosinska, Svitlana Stanko, Daniil Krant

The relevance of the declared subject of this research work is determined by the need to develop and implement software for users of various skill levels, as well as to create effective multi-scenario systems for describing processes occurring in multiple environments. The primary purpose of this scientific research is to study the principles of modeling the functioning of multi-scenario systems. The basis of the methodological approach in this scientific study is a combination of methods of system analysis of the principles of creating models for the functioning of multi-scenario systems with an analytical study of the prospects for building monolithic architectures of online learning systems. In the course of this scientific research, results were obtained that describe the principles of modeling a multi-scenario online learning system, as well as illustrating the features of the interaction of individual subsystems within a single multi-scenario system, taking into account the effectiveness of each of the subsystems performing the functions assigned to it within a single multi-scenario system. The results obtained reflect the fundamental principles of building the operation of multi-scenario systems in the conditions of the need to process a large amount of data, taking into account the difference in user characteristics, their levels of preparedness, as well as the variety of user requests that have a significant impact on the process of creating a multi-scenario system model and its functioning in constantly changing environments. External conditions. The practical significance of the results obtained in this scientific study, as well as the conclusions formulated on their basis, lies in the possibility of their application in the development of information presentation systems, the operation of which is based on the principle of multi-scenario, in order to provide the option of choosing modes of use and their automatic adjustment.

8

Authors: Vishal B Shinde, Rakesh Kumar

To investigate the deflection, maximum stress, maximum strain, and failure of pavement joints of conventional and remix concrete pavement models. Nine model pavement slab specimens has been cast and statically loaded using hydraulic jack, load cell on loading frame assembly. Two concrete mix design grades and three concrete remixing procedures were chosen and fixed. This work checks the effect of remix concrete on rigid pavements, taking into account time lag (t in hr.) of Concrete (THC) and the blend ratio (r). The methods were a regular mixed with traditional procedures and a remix mixture with selfing and crossing methods. The results of a 3D finite element analysis with ANSYS simulation are compared to experimental trials. By adding a higher graded fresh concrete to the old and partially set concrete, there is improvement in the compressive strength, quality of the concrete, and modulus subgrade reaction, according to this study.

8

Authors: Pramod Gadge, Prakash Burade, Deepak Kadam

Electric utilities are going through a phase of quick changes, especially in the marketplace and rigid policies. Under such circumstances, electricity carrying prices can profile the level of contest in the electricity marketplace. Nodal pricing in such circumstances is one of the valuable schemes to reach transmission pricing goals. The performance of the Electricity Act 2003 has started the entry of the general electricity market in the Indian electricity sector. The implementation of the Transmission Open Access (TOA) regulation in India aims to confirm the required infrastructure and appropriate pricing strategies to support competition in this market. This study seeks to: (1) address the transmission pricing concerns that are prevalent and Nodal pricing that is exacting; (2) formulate the most advantageous Nodal price; and (3) implement the Nodal pricing methodology via IEEE-57. (4) to examine how transmission and generating assets affect nodal prices. Paper finalized that Nodal pricing is easy to execute over real network conditions and precious in achieving transmission pricing objectives.

8

Authors: Jyoti Mohan Kharade, P. M. Joshi

The Solid State Transformer (SST) is an advanced power electronics-based key component of the distribution system (SST). This paper presents the application of SST to corporate workspaces and IT environments with nonlinear loads to mitigate harmonics. The three stage SST is designed with rectifier, dual active bridge converter and inverter with suitable converter topologies. The system is controlled with dq-transform based Clarke and inverse Clarke transformation system. The proposed system is designed to eliminate source side current harmonics content by injecting compensating current through inverter. The proposed system is implemented and analyzed for non linear load using MATLAB/ Simulink. The power quality is achieved in terms of improved power factor and decreased % THD to permissible limit.

10

Authors: Oumaima Berguig, Noureddine Abdelbaki, Said Bribich

The purpose of this paper is to identify the quality of work life factors that affect employee turnover intention in Morocco, in a context of Covid-19 pandemic, a source of massive layoffs and labor market disruptions. The data were collected using a questionnaire filled in by employees working in the health, call center, information technology and journalism sectors. The overall results show that, contrary to the existing literature, only organizational factors have a negative impact on turnover intention, however, this impact is not significant. Therefore, we can conclude that the Covid-19 pandemic and its repercussions on the Moroccan labor market have led to a low employee turnover intention.

10

Authors: Rajni Mehra, Prachi Chaudhary

MATLAB GUI provides a friendly graphical user interface. We know that deep learning is very in demand in today’s life. It is used when talking about a large number of data, deep learning is used to learn features of a data set, or we can say that an image. So for this process of convolution, neural networks play an important role. CNN is used for speech recognition, face recognition, image classification, etc. In this research, an experimental set-up has been done for low-light image enhancement based on deep learning, and also enhancement has been done based on intelligent retrieval with the help of GUI in MATLAB. The authors also stressed minimizing the complexity as computational time has been measured, including all parameters. It is also known as Deep Learning. Enhancement, in terms of strengthening, is the same. Deep learning and CNN are the same; it is a subclass of intelligent retrieval. When we talk about a massive number of facts, and we have to classify them, so the system is very complex at that time, so we need to reduce that complexity. If we talk about GPU, it is very expensive. It is used for both software and hardware design; when we need to train data with a large amount of data, system complexity automatically increases.

12

Authors: Nataliia Semenchenko

The relevance of the study consists in highlighting the principles of cybernetics in separating relatively self-sufficient whole economic systems from reality, considering their functioning and the relationship between them and the environment, and discovering analogies and general patterns of development and action in an innovative atmosphere. The purpose of this study is to identify and then apply in practice the general laws and principles governing economic processes in Ukraine, and the transformation of cybernetic information elements in innovative development. Cybernetics, which is an interdisciplinary science, studies the operation and functioning of particularly complex economic systems without regard to the material from which they are created. The cybernetic aspect represents the ability to perceive and capture the surrounding economic reality, to observe the changes occurring in it, their causes, and consequences comprehensively and dynamically. For this purpose, the article used the following methods: functional analysis, logical method, and scientific abstractions. The management principles and general laws of cybernetics look for analogies between all components of economic organisms and social systems, discovering common laws borrowed from various sciences. Cybernetics allows these laws to be transposed into a completely different field, providing a variety of practical applications. The findings indicated the potential for the development of an innovative national economy as a set of interrelated resources and opportunities for their realisation in the context of cybernetic individual, collective and societal systems. The categories of innovative development in the investment potential of Ukraine were considered. Its components are analysed predominantly from the perspective of an innovation management principle, which was implemented gradually according to the achievement of objectives at defined assessment points. The practical relevance lies in the analysis of the principles of cybernetics in the innovation segment, and the examination of the current state of the investment sphere and its policies from the perspective of the cybernetic component of the economic system.

14

Authors: Maqboul Jaouad, Bounabat Bouchaib

Data in our era is characterized by overwhelming volume, variety tends towards unstructured architecture and very high and continuous speed of production and sharing. These characteristics lead organizations to demand a level of quality from their data that must meet the needs and requirements of those requesting their service. Despite the existence of numerous quality procedures, a reference method is essential for the evaluation of data remediation projects. It is in this perspective, this article proposes an approach aimed at helping in the choice of the most profitable scenario according to the gains and benefits expected during the evaluation of data quality projects. The approach assesses the positive impact of process quality and data quality, as well as the complexity of its implementation. It is based on a cost-benefit analysis and a cost-effectiveness analysis as well as on a multi-criteria analysis for the classification of the processes and subsequently of the projects according to their weight of importance. The approach focuses on data. It is also interested in the prioritization of key processes and their collaboration between different process managers. The approach has been put into practice in the health sector for the identification and strengthening of important processes and objects, eligible to be the subject of data quality improvement projects. The approach has been applied to the healthcare sector for the identification and strengthening of important business processes and objects, eligible to be the subject of data quality improvement projects.

14

Authors: Naw Phyu Zar Thwin, Amiya Bhaumik, Midhunchakkaravarthy

Among all the resources an organization owns, human resources play the most critical role. To make a successful organization, management has to commit to continuously satisfying employees. Satisfied employees take risks, think creatively, and care about customers’ satisfaction for achieving organizational goals. The study's primary goal was to look at how rewards and recognition affect job satisfaction among employees of Zalaryathar distribution Co., Ltd. The analysis of the research results was analysis on various theories from the ground of Human Resource Management. In order to determine the degree of employee job satisfaction, the study looked at the impact of extrinsic rewards like income, bonus, promotion, and commission. Additionally, the study looked at how intrinsic rewards like appreciation and recognition affect how satisfied employees are at their jobs. The study adopted a descriptive research survey. For this research study, a sample size of 250 employees has been selected, which represents 20% of the total population. The data for this study were collected primarily through close-ended questionnaires. In this study, Stratified random sampling has to be utilized for administering with and examining the groups within the population. In detail, disproportionate to using Stratified random sampling to pick the employees, top management, middle management, and first-line management because some startups are small. Theoretical and managerial implications, recommendations, and limitations for future research have to be further research references. In this study, data were running with SPSS (Statistical Package for Social Sciences) version 20 for data operation and study. Correlation analysis brings forward to explore the most significant factors which affect the employee’s job satisfaction. The study examines those rewards and recognition had a positive correlation with employee job satisfaction of Zalaryathar distribution company. The study suggests that organizations can achieve their objectives and mission through employee job satisfaction with effective reward and recognition systems.