Proceedings on Engineering Sciences

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.

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.

8

Authors: Janka Kopčáková, Katarína Petrovčiková, Eva Manová

Small and medium-sized enterprises constitute a strong potential in the economy of the entire European Union, but also in the Slovak Republic. The significance of these enterprises is not only at the national level, but also reaches a transnational dimension. Small and medium-sized enterprises resist not only various external influences, but also frequent legislative changes. Individual legislative changes can also result in a change in the financial performance of small and medium-sized enterprises. The aim of the paper is to point out the change in results through the method of principal components, which was performed from the input data of ratio indicators, in the event of a mandatory transformation of national accounting standards into international accounting standards. At present, however, small and medium-sized enterprises are not obliged to present financial statements according to international accounting standards, but the progressing time and the Slovak Republic's part in the European Union may also cause the harmonization of financial statements itself.

8

Authors: Arulkumar Subramanian, K.E.Lakshmi prabha, A. Abitha, Lukas Gebremariam Lapiso, Kedir Beshir, Abrha Ftsum Berhe

Harmonic contamination, non-linear loads, voltage sag-swell and other issues can all have an impact on the quality of electricity. The fluctuation of load side voltage has made it extremely difficult to maintain power quality in recent years. The load side voltage variation solved by optimization technique is suitable for attain good result. The work consist of additional solar system provided with Maximum Power Point Tracking controlled by a Particle Swarm Optimization Technique and fuzzy, Artificial Neural Network based Proportional Integral control technique, which is used in the Unified Power Quality Conditioner, in order to balance and increase to maintain the load side power. Total harmonic distortion has decreased from an average of 2.77 percent for voltage to 1.16 percent, and from an average of 4.48 percent to 2.02 percent for current. Results of the simulation run using MATLAB software.

10

Authors: Rajiv Kumar Sharma

Smart manufacturing is the modern form of manufacturing that utilizes Industry 4.0 enablers for decision making and resources planning by taking advantage of the available data. With the advancement of digitalization and industrial machine connectivity, it is now feasible to gather data in real-time from a variety of sensors (e.g. current, acoustic, vibration etc.) while the process is being carried out. The aim of the paper is to propose a framework for predictive maintenance PdM 4.0 and validate the framework by implementing it for a manufacturing process, milling in which a public data set from NASA repository is used to build and test the proposed PdM 4.0 system. The various machine learning classifiers such as: support vector regression SVR, RF, DT, XGBoost and MLP regressor have been used for remaining useful life and tool wear rate prediction. The model evaluation and comparison is based on metrics like (R- square), root mean square error and mean absolute error.

12

Authors: Saman Yapa, Rangesh Fernando

This paper outlines the findings of a research done to see whether the SERVQUAL model, which was developed for a Western industrialized nation, could be applied to the automobile service industry in Sri Lanka, a developing nation in South Asia. Only a few studies on the auto service business are found in literature, despite the fact that many studies have been carried out using the SERVQUAL model. Additionally, many scholars have emphasized the need for the development of industry/culture-specific tools to measure service quality. Both of these needs are met by the current research. According to the investigation, the chosen industry's dimensions of service quality are reliability of work, responsiveness, assurance and tangibles. Except empathy, these dimensions are comparable to the original SERVQUAL model dimensions. The managers of auto service centers in nations that are socially and economically similar to Sri Lanka might utilize the modified questionnaire created in the current study to assess the level of customer service provided by those facilities. Additionally, it was discovered that, with the exception of tangibles, customers were dissatisfied with all dimensions of service quality. Managers of service centers must therefore focus more on enhancing the human components of the service.

14

Authors: Mohsen Anvari, Alireza Anvari

Total quality management is a management approach for the continuous improvement of products and services with the participation of all employees and the organization. Innovation refers to the commitment to create new and improved versions of existing products, services, operations, and other items. TQM and innovation predict the survival determinants of micro, small and medium enterprises, so TQM practices support the realization of innovation. The main objective of this research is to investigate the impact of TQM practices on the realization of innovation. For this purpose, by examining quality system management and innovation from a process point of view while identifying 13 tools of TQM and five factors of innovation, the relationship between these two has been investigated. FAHP and DEA techniques are used to develop this model. The results indicate that TQM components develop organizational innovation. As a result, the TQM environment could be an appropriate platform to flourish innovation in an organization.

14

Authors: Asmae Mohib, Abdelali En-nadi, Brahim Herrou

Lean initiatives have been largely implemented in organisations as a means to increase productivity and improve performance. Lean has recorded success in different sectors including the food industry. This article focuses on determining the critical success factors (CSFs) for the implementation of lean in the Moroccan food industry then ranking them using fuzzy TOPSIS. The results highlighted that the most six CSFs of Lean in the Moroccan food context are perceptively: communication, leadership and top management commitment, training and education, skills and expertise, employee involvement, and change in the company culture. This paper can help practitioners and professionals in the food industry as a guide for the success of lean implementation in their organisations.

16

Authors: B.M. Golam Kibria, Shipra Banik

The process capability index (Cp) measures the amount of dispersion a process involves relative to the limits of specification. This paper considers sixteen different available confidence intervals for estimating the population process capability index. A simulation study under different conditions has been conducted to compare the performance of the estimators. Our vast simulation records reveal that both augmented large sample (ALS) and modified augmented large sample (MALS) intervals have better coverage probability and shorter average width in all simulation conditions. We expect that the results of this paper will contribute to the literature on process capability and will guide the researchers to select an interval estimator when they are interested to estimate the population process capability index.

8

Authors: Elena Posnaya, Natalya Alesina, Yuliya Zima, Artyom Shevtsov, Andrey Kuzmin

The current economic situation again emphasizes the need to form a banking system management that is resistant to negative external influences. The development vector of the industrial sector management directly depends on the banking system efficiency, which in turn will lead to an increase in the values of macroeconomic parameters. An important role in improving the stability of the modern banking sector is played by the implementation of the Basel III requirements, developed taking into account the experience of the global financial crisis. The article examines the impact of changes in the capital adequacy requirements of Russian banks from the point of view of the need to ensure the sustainable development of both the banking system and the effective management of industry. Based on the identified patterns, recommendations are formulated for organizing a system for assessing the capital adequacy of a commercial bank. The capital of the bank is the basis of the successful lending process, in particular to industry. And the effective management of industrial enterprises serves as a guarantor of the production development, the creation of jobs, and an increase in the values of the main macroeconomic indicators.

10

Authors: Serkan Kivrak, Sengthoeun Say

National culture can influence management practices in any business. Therefore, the impact of national culture on management practices should be examined to minimize conflicts and improve productivity. This study aims to examine the relationship between national culture and total quality management practices in the construction industry. Within this context, a case study was carried out in the Cambodian construction industry. A questionnaire survey was conducted among 84 professionals from 26 construction companies operating in the Cambodian construction industry. Hofstede’s cultural dimensions were used to interpret the study findings. Based on the results, leadership, system approach to management, and customer focus are determined as the most significant total quality management principles. Moreover, uncertainty avoidance, individualism/collectivism, and power distance were found as the most important dimensions influencing total quality management practices. The study findings can help professionals to better understand the role of national culture in implementing total quality management practices in the Cambodian construction industry.

10

Authors: Matthew Barsalou, Robert Perkin

This paper explores the creation of problem statements using 5W2H questions using an is/is-not matrix and seeks to determine if use of 5W2H type questions leads to a quicker resolution of problems. An 8D report database with fields for problem descriptions and days to root cause identification was used to determine if better defined problems were solved quicker than problems that were less well defined. The level of detail in the problem statements was assessed, problems were classified as having a low or high level of detail, and then a statistical hypothesis test was performed. Problems with a better defined problem statement were solved quicker than those without. Those with a more detailed problem statement required a mean of 34.1 day and those with a less detailed problem statement required a mean of 48.0 days.

12

Authors: Mohammad Sultan Ahmad Ansari

Lean Management and Six Sigma (LSS) concepts originated in manufacturing but later it was adopted by service industries including healthcare. This work explores several issues arising while implementing LSS in a healthcare organization by taking questionnaire-based feedbacks from all stakeholders' viz. distributors of pharmaceutical products, healthcare personnel and patients. LSS, though at present at a premature stage, has high potential for superior value creation and operational efficiency. The study reveals and emphasizes that LSS projects can yield significant benefits such as waste reduction, improvement in operational matters, minimizing errors in technical processes and identifying design of new processes.).

12

Authors: Anis M’halla, Mohammed Jawad Abed

Developments presented in this paper are devoted to the dynalic scheduling of railway transport systems. In this context, our study deals with the implementation of cooperative methodologies to solve railway scheduling problems with predictive or unpredictable demands. Stochastic P-time Petri Nets (SP-TPN) are used for modelling. A new scheduling method based on genetic algorithms and allowing the insertion of predicted jobs is presented, in order to improve a number of traffic criteria such as travel time, total cost and maintenance activities. The aim of the proposed insertion method is to integrate the forecasted demand operations in the availabilities of the rolling stock, in order to minimize the inactivity periods and to increase the traffic rate. Finally, to illustrate the effectiveness and accuracy of the insertion approach, an application to a Sahel Railway networks is outlined.

14

Authors: Yevhen Hrabovskyi, Hryhorii Kots, Katarzyna Szymczyk

The article proposes developing a methodology for forming an innovative strategy for implementing information technologies for implementing business projects of multimedia publishing. The work gives a generalized presentation of the business development process based on introducing progressive information technologies. Based on the analysis of functional interrelationships, the authors formed a basic set of IT components for business projects in the form of appropriate information technology clusters. And with the help of the optimization model of cluster efficiency assessment and the matrix model of determining the need for information technology, they analyze the need to include new technology in the commercial activity of a multimedia publishing house. It is proposed to decide on the inclusion of one of the alternative information technologies based on the use of the connectivity indicator, the time characteristics of the information technology, the financial result of the introduction of the new information technology in the business projects of the multimedia publishing house. In this work, a diffusion model of new information technology diffusion was built using differential equations and a saturation function characterizing the moment of saturation of the need for IT innovation.

16

Authors: Ardeshir Bazrkar, Vahid Aramoon, Erfan Aramoon, Mehrdad Moradzad

The main purpose of this study was to investigate the impact of using green human resource management on sustainable environmental performance with respect to the mediating role of environmental knowledge and corporate social responsibility in the Iranian automotive industry. The present study was based on the purpose of an applied research and in terms of method was a descriptive -survey study. A questionnaire was used to collect research data. The statistical population of this study consisted of senior human resource managers of companies active in the automotive industry in Iran. The initial estimate showed that the total number of members of the statistical population is 143 people. After collecting data through a questionnaire, data analysis was performed using structural equation modeling. The results showed that the use of green human resource management methods has a positive and significant effect on the sustainable environmental performance of the companies under study. In addition, the sustainable environmental performance of the companies under study plays an effective mediating role. Therefore, it can be said that organizations can take steps to continuously and sustainable improvement of their environmental performance and increase the profitability of the organization by strengthening the strategies of green human resource management and paying special attention to the components of environmental knowledge and corporate social responsibility.