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Dynamic Behaviour Analysis of Multi-Cell Battery Packs: A Simulation Study
In the era of IoT understanding the dynamic behavior of a Lithium-ion Battery Management System (BMS) has become gradually more important. This research investigates the dynamic behaviour of a six-cell Lithium-ion Battery Management System (BMS) through simulation. The study employs a comprehensive model encompassing key battery parameters, including cell capacity, voltage limits, temperature thresholds, and charge/discharge characteristics. Additionally, state variables such as State of Charge (SOC), State of Health, and State of Function are integrated to capture the battery's internal dynamics. The simulation incorporates a sinusoidal current profile to emulate realistic operating conditions. Notably, Coulomb counting is employed for SOC estimation, and protective measures against overvoltage, undervoltage, and overcurrent are implemented. The study also addresses balancing strategies and communication interfaces within the BMS. The results reveal nuanced interactions between voltage, temperature, SOC, and current, offering insights into the intricate behaviour of the battery system under dynamic conditions. This research not only advances our understanding of BMS functionality but also lays a crucial foundation for the evolution of battery technology and energy management systems in the IoT landscape. The Institution of Engineering & Technology 2023. -
Dynamic Channel Allocation in Wireless Personal Area Networks for Industrial IoT Applications
Industrial wireless networks gain a substantial growth in size in the global market. In the congested scenarios of the industrial IoT application instances of wireless personal area networks, it should have a medium access strategy that is efficient and works autonomously to provide a reliable channel by reducing packet collisions. Medium access protocols must consider properties of the links between devices before a node is allowed to access the shared medium. Characteristic metrics of the channel like link quality indicator, received signal strength indicator, and path loss distance have to be considered in the contention resolution process between the nodes. A fuzzy-based channel allocation algorithm is proposed with dynamic adaptation of contention window in channel access strategy of the MAC layer standard. As per the simulation results, the algorithm proposed showed better results in terms of network throughput and packet delivery rate. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Dynamic Connectedness and Volatility Spillover Effects of Indian Stock Market with International Stock Markets: An Empirical Investigation Using DCC GARCH
This study employs the DCC-GARCH model to investigate the dynamic connectedness between the Indian and significant global stock markets. Specifically, we examine daily log returns data of the National Stock Exchange (NSE) index and several international indices, including the United States, Australia, China, Germany, England, Japan, and Taiwan. Our analysis indicates a significant level of volatility spillover between the Indian stock market and the international stock market. Notably, we observe a significant positive spillover effect from the S&P 500 and FTSE 100 to the Indian stock market, suggesting contagion effects. Additionally, we find bidirectional spillover between the Indian stock market and the Nikkei 225 and Hang Seng, indicating a high level of interdependence between these markets. Our research contributes to the growing literature on the dynamic connectedness of stock markets and has important implications for policymakers and investors in emerging economies such as India. Overall, this study provides valuable insights into the nature and extent of spillover effects between the Indian and international stock markets. 2023 University of Pardubice. All rights reserved. -
Dynamic job sequencing of converging-diverging conveyor system for manufacturing optimization
Some sectors, such as dairy, automobile, pharmaceutical, computer and electronics, require a range of manufacturing steps to produce a component. The goods in these industries are produced in varieties and the output volume varies from low to high. Typically, these types of businesses use a conveyor system that could have a combination of a diverging and converging conveyor system due to a variety of processing phases involved in the development of the commodity. A conceptual model of the of conveyor system is described, which works manually and to illustrate the importance of the sequence using buffer the buffer layout is modeled and compared to the manual layout. The genetic algorithm is used to find the optimal buffer storage. It can be observed that by adapting various sequencing methods there will be reduction in manufacturing time and setup cost. 2022 Elsevier Ltd. All rights reserved. -
Dynamic linkage among crude oil, exchange rates and P/E ratio: The case of India /
International Journal of Pure And Applied Mathematics, Vol.119, Issue 18, pp.1-14, ISSN No: 1314-3395. -
Dynamic Load Scheduling Using Clustering for Increasing Efficiency of Warehouse Order Fulfillment Done Through Pick and Place Bots
The domain of warehouse automation has been picking up due to the vast developments in e-commerce owing to growing demand and the need to improve customer satisfaction. The one crucial component that needs to be integrated into large warehouses is automated pick and place of orders from the storage facility using automated vehicles integrated with a forklift (Pick and Place bots). Even with automation being employed, there is a lot of room for improvement with the current technology being used as the loading of the bots is inefficient and not dynamic. This paper discusses a method to dynamically allocate load between the Pick and Place BOTs in a warehouse during order fulfillment. This dynamic allocation is done using clustering,an unsupervised Machine Learning algorithm. This paper discusses using fuzzy C-means clustering to improve the efficiency of warehouse automation. The discussed algorithm improves the efficiency of order fulfillment significantly and is demonstrated in this paper using multiple simulations to see around 35% reduction in order fulfillment time and around 55% increase in efficiency. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Dynamic Offloading Technique for Latency Sensitive Iot Applications Using Fog Computing
The Internet of Things (IoT) has evolved as one of the most popular technological newlineinnovations that offers processing power to different types of entities connected to it. IoT has made traditional applications smarter and easier to use. IoT offers reliable service to different sectors such as healthcare, industrial control, agriculture, autonomous vehicles, traffic management etc. IoT nodes are generally energy-constrained and hence depend on cloud platforms for storage and analytics of generated data. The cloud provides required services for the newlineconnected applications based on pay per use policy. But cloud datacenter being at remote location fails to accommodate the time requirements of delay-sensitive IoT newlineapplications. Edge/fog computing was designed to address the demands of timesensitive IoT applications. The IoT-Fog-Cloud architecture reduces the delay and response time incurred by the IoT-Cloud model. The fog layer in the three-tier architecture is distributed in nature. Hence the latency depends on how well the underlying offloading algorithms distribute the tasks among available fog nodes. Different offloading policies are mentioned in the literature to address this issue. This work initially tries to solve the offloading problem using one of the novel newlineoffloading approaches Flamingo Search Algorithm (FSA). Later, the results obtained from FSA are fine-tuned using another metaheuristic algorithm, the Honey Badger Algorithm (HBA). Finally, both FSA and HBA are hybridized to generate the HB-FS algorithm which effectively solves the task offloading problem. The performance evaluation of the proposed approach is done with different existing metaheuristic algorithms and the evaluations show that the newlineproposed work outperforms the existing algorithms in terms of latency, average newlineresponse time and execution time. The methodology also offers a lesser degree of newlineimbalance and standard deviation than the compared approaches. -
Dynamic Offloading Technique for Latency-Sensitive Internet of Things Applications using Fog Computing
Internet of Things (IoT) has evolved as a novel paradigm that provides com-putation power to different entities connected to it. IoT offers services to multiple sectors such as home automation, industrial automation, traffic management, healthcare sector, agriculture industry etc. IoT generally relies on cloud data centers for extended analytics, processing and storage support. The cloud offers highly scalable and robust platform for IoT applications. But latency sensitive IoT applications suffer delay issues as the cloud lies in remote location. Edge/fog computing was introduced to overcome the issues faced by delay-sensitive IoT applications. These platforms lie close to the IoT network, reducing the delay and response time. The fog nodes are usually distributed in nature. The data has to be properly offloaded to available fog nodes using efficient strategies to gain benefit from the integration. Differ-ent offloading schemes are available in the literature to overcome this prob-lem This paper proposes a novel offloading approach by combining two effi-cient metaheuristic algorithms, Honey Badger Algorithm (HBA) and Fla-mingo Search Algorithm (FSA) termed as HB-FS algorithm. The HB-FS is executed in an iterative manner optimizing the objective function in each it-eration. The performance evaluation of the proposed approach is done with different existing metaheuristic algorithms and the evaluations show that the proposed work outperforms the existing algorithms in terms of latency, response time and execution time. The methodology also offers better degree of imbalance with proper load balancing under different conditions. 2023 Authors. All rights reserved. -
Dynamic optimal network reconfiguration under photovoltaic generation and electric vehicle fleet load variability using self-adaptive butterfly optimization algorithm
Currently, electrical distribution networks (EDNs) have used modern technologies to operate and serve many types of consumers such as renewable energy, energy storage systems, electric vehicles, and demand response programs. Due to the variability and unpredictability of these technologies, all these technologies have brought various challenges to the operation and control of EDNs. In this case, in order to operate effectively, it is inevitable that effective power redistribution is required in the entire network. In this paper, a multi-objective based dynamic optimal network reconfiguration (DONR) problem is formulated using power loss and voltage deviation index considering the hourly variation of load, photovoltaic (PV) power, and electric vehicle (EV) fleet load in the network. This paper introduces recently introduced meta-heuristic butterfly optimization algorithm (BOA) and it's improve variant of self-adaptive method (SABOA) for solving the DONR problem. The simulation study of IEEE 33-bus EDN under different conditions has proved the effectiveness of DONR, and its adoptability for real-time applications. In addition, by comparing different performance indicators (such as mean, standard deviation, variance, and average calculation time) of 50 independently run simulations, the efficiency of SABOA can be evaluated compared with other heuristic methods (HMs). Comparative studies show that SABOA is better than PSO, TLBO, CSA and FPA in the frequent occurrence of global optimal values. 2021 Walter de Gruyter GmbH, Berlin/Boston 2021. -
Dynamic Pricing in Airline Industry
Asian Journal of Research in Business Economics and Management, Vol. 7, Issue 1, pp. 15-29, ISSN No. 2249-7307 -
Dynamic response of parabolic reflector antenna subjected to shock load and base excitation considering soil-structure interaction
Parabolic reflector antenna structures are subjected to dynamic loads along with normal loads. Determining the dynamic response of the antenna structure subjected to short-duration loads such as earthquake loads and shock loads considering soil-structure interaction is very important to ensure the safety and functionality of the antenna system resting on soft soil. A 7.2m diameter parabolic reflector antenna with a 90-degree elevation orientation is considered for the study. A triangular pulse of shock load is applied to the antenna at different locations and responses are estimated to understand the coupling effect of soil and structure on frequencies, damping, and response. Transient response analysis is carried out. Earthquake analysis is also carried out as per IS 1893 part 4:2016 considering Zone V site location. The foundation soil below the antenna is considered homogeneous with shear wave velocity (Vs) of 100m/sec. A direct method of analysis considering soil-structure interaction as per ASCE 4-16 is performed. FEM software MSC NASTRAN is used for analysis. The absorbing boundary conditions are used to reflect radiation damping. The depth-wise stress variation in foundation soil is evaluated. The results of free vibration analysis, transient response analysis with fixed base and SSI are compared. 2022 the Author(s). -
Dynamic route scheduler in vehicular ad hoc network for smart crowd control
Revenue generated by tourism is positively correlated with the development of any city. In recent years, tourism is getting peak focus among the government, local bodies, and researchers. This has led to increase in initiatives to grow tourism in and across the country. Being one of the most flourishing sectors, tourism in India shows bold signals of emerging as a strong participant in the world of tourism. In addition to safeguarding its culture and deep-rooted traditional values, tourism provides a way to increase employment opportunities as well as increase the foreign exchange within the country. There are many open research problems arising in the domain, which need the attention of researchers. City traffic management is one among the major concern for cities around the world. Scheduling dynamic travel plans for tourists with crowd and traffic awareness has high scope for research. In this paper, a system is proposed which connects the vehicles to a centralized sink for getting the optimal routes. Route scheduling is done based on a prediction model. Different parameters were collected from the environment that includes crowd, traffic, and schedule of other vehicles. The system has modules like static nodes, mobile nodes, host nodes, and sink node for the control and management. Selection of path and protocol is a primary strategy to design any VANET systems. Hence, performance analysis of routing protocols for the proposed system is done as a major step in selection of protocols. Packet delivery ratio, jitter, and throughput are common measures used for the comparison of protocols. 2019, Springer-Verlag London Ltd., part of Springer Nature. -
Dynamic strategies and evolutionary trajectories: A comprehensive review of experiential marketing in the soft drink industry
This comprehensive review explores the evolution of experiential marketing in the soft drink industry from 2005 to 2024. It uses analysis from a diverse set of 62 scholarly articles, Google books, Google Scholar, SSRN, Fig share, and various publishers such as Taylor & Francis, IGI Global, and Springer. The study traces the industry's trajectory from traditional marketing approaches to a digital-centric paradigm. The research captures pivotal moments in the development of experiential marketing strategies, emphasizing the integration of technology, sustainability, and community engagement. Key findings highlight the industry's adaptability to changing consumer preferences, the strategic use of data-driven insights, and the importance of inclusivity in crafting compelling brand narratives. The study identifies overarching trends, challenges, and opportunities that shaped the experiential marketing landscape in the soft drink industry over the past two decades. 2024, IGI Global. All rights reserved. -
Dynamic task distribution model for on-chip reconfigurable high speed computing system
Modern embedded systems are being modeled as Reconfigurable High Speed Computing System (RHSCS) where Reconfigurable Hardware, that is, Field Programmable Gate Array (FPGA), and softcore processors configured on FPGA act as computing elements. As system complexity increases, efficient task distribution methodologies are essential to obtain high performance. A dynamic task distribution methodology based on Minimum Laxity First (MLF) policy (DTD-MLF) distributes the tasks of an application dynamically onto RHSCS and utilizes available RHSCS resources effectively. The DTD-MLF methodology takes the advantage of runtime design parameters of an application represented as DAG and considers the attributes of tasks in DAG and computing resources to distribute the tasks of an application onto RHSCS. In this paper, we have described the DTD-MLF model and verified its effectiveness by distributing some of real life benchmark applications onto RHSCS configured on Virtex-5 FPGA device. Some benchmark applications are represented as DAG and are distributed to the resources of RHSCS based on DTD-MLF model. The performance of the MLF based dynamic task distribution methodology is compared with static task distribution methodology. The comparison shows that the dynamic task distribution model with MLF criteria outperforms the static task distribution techniques in terms of schedule length and effective utilization of available RHSCS resources. 2015 Mahendra Vucha and Arvind Rajawat. -
Dynamic vibrational analysis on areca sheath fibre reinforced bio composites by fast fourier analysis
Natural fibre reinforced bio composites [6] are good alternative for conventional materials. Natural fibres are cheaper in cost, environmental friendly and biodegradable. In this project work the effect of varying fibre length is studied and Fast Fourier Technique is used for the analysis of dynamic frequency response. The naturally extracted areca sheath fibres are used as a reinforcement and epoxy L - 12 is used as polymer matrix. Fabrication is done by using hand lay-up method and compression molding technique at 100 - 110 bar pressure and 140 - 150C temperature. Each specimen is cured for 24 h and then test specimens were cut according to ASTM standards i.e., 150 X 150 mm in length and breadth. The dynamic frequency response of specimens with varying fibre length of 29, 27 and 25 mm and thickness 4, 3.5 and 2 mm is obtained by modal analysis. Finite Element Analysis for all specimens is carried out by ANSYS 14.5 and results are compared with the experimental values. These natural areca fibre reinforced polymer matrix composites are defined for particular applications based up on the mechanical and vibrational characteristics obtain from the experimental results. 2018 Elsevier Ltd. All rights reserved. -
Dynamical analysis fractional-order financial system using efficient numerical methods
The motivation of this work is to analyse the nonlinear models and their complex nature with generalized tools associated with material and history-based properties. With the help of well-known and widely used numerical scheme, we study the stimulating behaviours of the financial system in this work. The impact of parameters on price index, rate of interest, investment demand, influence changes and investment cost with respect to saving amount, and the elasticity of commercial markets demand are discussed. The consequences of generalizing the model within the arbitrary order are derived. The existence of the solution for the considered system is presented. This study helps beginner researchers to investigate complex real-world problems and predict the corresponding consequences. 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Dynamical analysis of a model of social behavior: Criminal vs non-criminal population
In this paper, we construct a model motivated by the well known predator-prey model to study the interaction between criminal population and non-criminal population. Our aim is to study various possibilities of interactions between them. First we model it using simple predator-prey model, then we modify it by considering the logistic growth of non-criminal population. We clearly deduce that the model with logistic growth is better than classical one. More precisely, the role of carrying capacity on the dynamics of criminal minded population is discussed. Further, we incorporate law enforcement term in the model and study its effect. The result obtained suggest that by incorporating enforcement law, the criminal population reduces from the very beginning, which resembles with real life situation. Our result indicates that the criminal minded population exist as long as coefficient of enforcement lc does not cross a threshold value and after this value the criminal minded population extinct. In addition, we also discuss the occurrence of saddle-node bifurcation in case of model system with law enforcement. Numerical examples and simulations are presented to illustrate the obtained results. 2017 Elsevier Ltd -
Dynamical analysis of fractional yellow fever virus model with efficient numerical approach
In this paper, we have projected the theoretical and numerical investigation of the mathematical model representing the yellow fever virus transmission from infected mosquitoes to humans or vise-versa through mosquito bites in the framework of the Caputo derivative. Theoretical aspects of the dynamics of susceptible individuals, exposed individuals, infected individuals, toxic infected individuals, recovered and immune individuals, and susceptible mosquitoes and infected mosquitoes have been analyzed by using the theory of fractional calculus such as boundedness, uniqueness and existence of the solutions. Sufficient conditions for the global stability of the virus-free point of equilibrium are inspected. T validate the theoretical results numerical analysis is performed using the generalized Adams-Bashforth-Moultan method. 2023, Eudoxus Press, LLC. All rights reserved. -
Dynamics of a fractional epidemiological model with disease infection in both the populations
In order to depict a situation of possible spread of infection from prey to predator, a fractional-order model is developed and its dynamics is surveyed in terms of boundedness, uniqueness, and existence of the solutions. We introduce several threshold parameters to analyze various points of equilibrium of the projected model, and in terms of these threshold parameters, we have derived some conditions for the stability of these equilibrium points. Global stability of axial, predator-extinct, and disease-free equilibrium points are investigated. Novelty of this model is that fractional derivative is incorporated in a system where susceptible predators get the infection from preys while predating as well as from infected predators and both infected preys and predators do not reproduce. The occurrences of transcritical bifurcation for the proposed model are investigated. By finding the basic reproduction number, we have investigated whether the disease will become prevalent in the environment. We have shown that the predation of more number of diseased preys allows us to eliminate the disease from the environment, otherwise the disease would have remained endemic within the prey population. We notice that the fractional-order derivative has a balancing impact and it assists in administering the co-existence among susceptible prey, infected prey, susceptible predator, and infected predator populations. Numerical computations are conducted to strengthen the theoretical findings. 2021 Author(s). -
Dynamics of chaotic waterwheel model with the asymmetric flow within the frame of Caputo fractional operator
The chaotic waterwheel model is a mechanical model that exhibits chaos and is also a practical system that justifies the Lorenz system. The chaotic waterwheel model (or Malkus waterwheel model) is modified with the addition of asymmetric water inflow to the system. The hereditary property of the modified chaotic waterwheel model is analyzed to determine the system's stability and identify the parameter that contributes to the stability We also examine the factor that leads to the bifurcation. We determine the well-posed nature of the modified system. The modified chaotic waterwheel model is defined with the Caputo fractional operator. The existence and uniqueness, boundedness, stability, Lyapunov stability, and numerical simulation are studied for the modified fractional waterwheel model. The bifurcation parameter and Lyapunov exponent are examined to study the chaotic nature of the system with respect to the fractional order. The nature of the system is captured with the help of the efficient numerical approach AdamsBashforthMoulton Method. The numerical approach demonstrates that the chaotic nature of the modified chaotic waterwheel is changed into unstable nature, which could further reduce to the stable case with suitable values of the parameter. This analysis is justified with the help of Lyapunov exponent. We consider irrational order (?,e) in the present work to illustrate the reliability of fractional order. 2023 Elsevier Ltd