Intelligent Parking Management System by Multi-Agent Approach:The Case of Urban Area of Tunis

By coordination and cooperation between multi-agents, this paper proposes the network of intelligent agents which can reduce the search time needed to finding a parking place. Based on multi-agent model, the fined solution is designed to help drivers in finding a parking space at anytime and anywhere. Three services are offered: the search for a vacant place, directions to a parking space and booking a place for parking. The results of this study generated by the platform MATSim transport simulation, show that our approach optimizes the operation of vehicles in a parking need with the aim of reducing congestion, and improve traffic flow in urban area. A comparison between the first method where the vehicles are random and the second method where vehicles are steered to vacant parking spaces shows that the minimization of time looking for a parking space could improve circulation by reducing the number of cars in the morning of 2% and 0.7% of the evening. In addition, the traffic per hour per day was reduced by approximately 4.17%.

An Evidence-Based CoCoSo Framework with Double Hierarchy Linguistic Data for Viable Selection of Hydrogen Storage Methods

Hydrogen is the new age alternative energy source to combat energy demand and climate change.Storage of hydrogen is vital for a nation’s growth.Works of literature provide different methods for storing the produced hydrogen,and the rational selection of a viable method is crucial for promoting sustainability and green practices.Typically,hydrogen storage is associated with diverse sustainable and circular economy(SCE)criteria.As a result,the authors consider the situation a multi-criteria decision-making(MCDM)problem.Studies infer that previous models for hydrogen storage method(HSM)selection(i)do not consider preferences in the natural language form;(ii)weights of experts are not methodically determined;(iii)hesitation of experts during criteria weight assessment is not effectively explored;and(iv)three-stage solution of a suitable selection of HSM is unexplored.Driven by these gaps,in this paper,authors put forward a new integrated framework,which considers double hierarchy linguistic information for rating,criteria importance through inter-criteria correlation(CRITIC)for expert weight calculation,evidence-based Bayesian method for criteria weight estimation,and combined compromise solution(CoCoSo)for ranking HSMs.The applicability of the developed framework is testified by using a case example of HSM selection in India.Sensitivity and comparative analysis reveal the merits and limitations of the developed framework.

Stochastic Design of Enhanced Network Management Architecture and Algorithmic Implementations

The paper is focused on available server management in Internet connected network environments. The local backup servers are hooked up by LAN and replace broken main server immediately and several different types of backup servers are also considered. The remote backup servers are hooked up by VPN (Virtual Private Network) with high-speed optical network. A Virtual Private Network (VPN) is a way to use a public network infrastructure and hooks up long-distance servers within a single network infrastructure. The remote backup servers also replace broken main severs immediately under the different conditions with local backups. When the system performs a mandatory routine maintenance of main and local backup servers, auxiliary servers from other location are being used for backups during idle periods. Analytically tractable results are obtained by using several mathematical techniques and the results are demonstrated in the framework of optimized networked server allocation problems. The operational workflow give the guidelines for the actual implementations.

Fundamentals,recent developments and prospects of lithium and non-lithium electrochemical rechargeable battery systems

The present and future energy requirements of mankind can be fulfilled with sustained research and development efforts by global scientists.The purpose of this review paper is to provide an overview of the fundamentals,recent advancements on Lithium and non-Lithium electrochemical rechargeable battery systems,and their future prospects.The initial part of this review paper is dedicated to the advancement and challenges faced by the conventional rechargeable batteries,such as lead-acid,Ni-Cd and Ni-MH batteries.The subsequent section of this review focuses on an in-depth analysis of two major categories of rechargeable batteries,namely lithium-based rechargeable battery systems and alternative non-Lithium rechargeable battery systems.The working principle,construction,and a few important research progress on Li-ion,Li-O_(2),Li-CO_(2) and Li-S batteries have been highlighted.The recent progress and challenges of the alternate batteries such as Na-ion,Na-S,Mg-ion,K-ion,Al-ion,Al-air,Zn-ion and Zn-air are also discussed in this review.The large gap between theoretical and practical electrochemical values for the alternate battery system must be filled by adopting a series of design architectures followed by modern instrumentation for developing next-generation batteries in a sustainable and efficient way.

Traffic Queuing Management in the Internet of Things: An Optimized RED Algorithm Based Approach

Congestion control is one of the main obstacles in cyberspace traffic.Overcrowding in internet traffic may cause several problems;such as high packet hold-up,high packet dropping,and low packet output.In the course of data transmission for various applications in the Internet of things,such problems are usually generated relative to the input.To tackle such problems,this paper presents an analytical model using an optimized Random Early Detection(RED)algorithm-based approach for internet traffic management.The validity of the proposed model is checked through extensive simulation-based experiments.An analysis is observed for different functions on internet traffic.Four performance metrics are taken into consideration,namely,the possibility of packet loss,throughput,mean queue length and mean queue delay.Three sets of experiments are observed with varying simulation results.The experiments are thoroughly analyzed and the best packet dropping operation with minimum packet loss is identified using the proposed model.

Optimization of Energy Resource Management for Assembly Line Balancing Using Adaptive Current Search

This paper aimed to present the optimization of energy resource management in a car factory by the adaptive current search (ACS)—one of the most efficient metaheuristic optimization search techniques. Assembly lines of a specific car factory considered as a case study are balanced by the ACS to optimize their energy resource management. The workload variance of the line is performed as the objective function to be minimized in order to increase the productivity. In this work, the ACS is used to address the number of tasks assigned for each workstation, while the sequence of tasks is assigned by factory. Three real-world assembly line balancing (ALB) problems from a specific car factory are tested. Results obtained by the ACS are compared with those obtained by the genetic algorithm (GA), tabu search (TS) and current search (CS). As results, the ACS outperforms other algorithms. By using the ACS, the productivity can be increased and the energy consumption of the lines can be decreased significantly.

Understanding the adoption context of China’s digital currency electronic payment

Central banks worldwide have started researching and developing central bank digital currencies(CBDCs).In the digital economy context,concerns regarding the integrity,competition,and privacy of CBDC systems have also gradually emerged.Against this backdrop,this study aims to evaluate users’willingness to use China’s digital currency electronic payment(DCEP)system,a digital payment and processing network,and its influencing factors by comprehensively considering and comparing the characteristics of cash and third-party payment services.Combining the push-pull-mooring frame-work(PPM)and task-technology fit(TTF)theory,we discuss the scenarios and mecha-nisms that may inspire users’DCEP adoption intention through an empirical study.The results reveal that privacy concerns regarding the original payment methods and technology-task fitting level of DCEP positively impact users’willingness to adopt DCEP.The technical characteristics of DCEP,users’payment requirements,and government support positively affect users’adoption intention by influencing the task-technology fitting degree of DCEP.Switching cost significantly and negatively impacts adop-tion intention,whereas relative advantage exhibits no significant effect.This research contributes to a better understanding of the factors that influence switching intentions and the actual use of DCEP,and provides policy guidance on promoting the efficiency and effectiveness of DCEP.

Comparative Analysis of COVID-19 Detection Methods Based on Neural Network

In 2019,the novel coronavirus disease 2019(COVID-19)ravaged the world.As of July 2021,there are about 192 million infected people worldwide and 4.1365 million deaths.At present,the new coronavirus is still spreading and circulating in many places around the world,especially since the emergence of Delta variant strains has increased the risk of the COVID-19 pandemic again.The symptoms of COVID-19 are diverse,and most patients have mild symptoms,with fever,dry cough,and fatigue as the main manifestations,and about 15.7%to 32.0%of patients will develop severe symptoms.Patients are screened in hospitals or primary care clinics as the initial step in the therapy for COVID-19.Although transcription-polymerase chain reaction(PCR)tests are still the primary method for making the final diagnosis,in hospitals today,the election protocol is based on medical imaging because it is quick and easy to use,which enables doctors to diagnose illnesses and their effects more quickly3.According to this approach,individuals who are thought to have COVID-19 first undergo an X-ray session and then,if further information is required,a CT-scan session.This methodology has led to a significant increase in the use of computed tomography scans(CT scans)and X-ray pictures in the clinic as substitute diagnostic methods for identifying COVID-19.To provide a significant collection of various datasets and methods used to diagnose COVID-19,this paper provides a comparative study of various state-of-the-art methods.The impact of medical imaging techniques on COVID-19 is also discussed.

Examining the Effectiveness of Virtual Training under the Kirkpatrick Model:A Post-COVID Study

Teaching and training through online tools were used by most Higher Education Institute(HEIs)worldwide during COVID-19 to cater to the needs of students who stay far away from educational institutions.After the pandemic,the virtual model of education and training became a trend.The students and teachers are also more used to this trend which is giving more opportunities to both learners and instructors.One of the notable benefits of virtual teaching and learning platform is that it provides a flexible environment to gain knowledge,skills,and attitude simultaneously along with formal off-line education.From the earlier studies it is found that the majority of studies have focused on traditional,offline training methods and only a few studies have focused on virtual training.Therefore,the present study examined the effectiveness of virtual training using the Kirkpatrick model.For this purpose,a research instrument based on the Kirkpatrick model was constructed and distributed among the UG and PG students in Mangalore City.A total of 143 responses were collected,of which 132 were completed responses and all of them were considered for analysis.Descriptive statistics and one sample t-test are employed to analyse and interpret the data.The findings revealed that virtual training is more effective compared to traditional and offline training methods.Henceforth,the training and education provided through virtual platforms made significant contributions to the employability of youngsters.

Impact of Environmental,Social,and Governance(ESG)Factors on Stock Prices and Investment Performance

This study examines the relationship between Environmental,Social,and Governance(ESG)factors and stock prices as well as investment performance.ESG factors have become increasingly relevant in investment decisions as investors prioritize companies with sustainable practices.Using a sample of publicly-traded companies,this research analyzes the impact of ESG factors on stock prices and investment returns.The findings suggest that companies with strong ESG performance tend to have higher stock prices and better investment performance than those with weak ESG performance.The study also highlights the significance of the individual components of ESG,such as environmental policies and corporate governance practices,on stock prices and investment returns.Overall,this research provides valuable insights for investors seeking to incorporate ESG factors into their investment decision-making processes.

Hybrid Approach for Cost Efficient Application Placement in Fog-Cloud Computing Environments

Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data sources.However,the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes,thus making the application placement problem more complex than that in cloud computing.An approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the placement of applications and services while minimizing costs.This approach is particularly relevant in scenarios where latency,resource constraints,and cost considerations are crucial factors for the deployment of applications.In this study,we propose a hybrid approach that combines a genetic algorithm(GA)with the Flamingo Search Algorithm(FSA)to place application modules while minimizing cost.We consider four cost-types for application deployment:Computation,communication,energy consumption,and violations.The proposed hybrid approach is called GA-FSA and is designed to place the application modules considering the deadline of the application and deploy them appropriately to fog or cloud nodes to curtail the overall cost of the system.An extensive simulation is conducted to assess the performance of the proposed approach compared to other state-of-the-art approaches.The results demonstrate that GA-FSA approach is superior to the other approaches with respect to task guarantee ratio(TGR)and total cost.

Mitigating Blackhole and Greyhole Routing Attacks in Vehicular Ad Hoc Networks Using Blockchain Based Smart Contracts

The rapid increase in vehicle traffic volume in modern societies has raised the need to develop innovative solutions to reduce traffic congestion and enhance traffic management efficiency.Revolutionary advanced technology,such as Intelligent Transportation Systems(ITS),enables improved traffic management,helps eliminate congestion,and supports a safer environment.ITS provides real-time information on vehicle traffic and transportation systems that can improve decision-making for road users.However,ITS suffers from routing issues at the network layer when utilising Vehicular Ad Hoc Networks(VANETs).This is because each vehicle plays the role of a router in this network,which leads to a complex vehicle communication network,causing issues such as repeated link breakages between vehicles resulting from the mobility of the network and rapid topological variation.This may lead to loss or delay in packet transmissions;this weakness can be exploited in routing attacks,such as black-hole and gray-hole attacks,that threaten the availability of ITS services.In this paper,a Blockchain-based smart contracts model is proposed to offer convenient and comprehensive security mechanisms,enhancing the trustworthiness between vehicles.Self-Classification Blockchain-Based Contracts(SCBC)and Voting-Classification Blockchain-Based Contracts(VCBC)are utilised in the proposed protocol.The results show that VCBC succeeds in attaining better results in PDR and TP performance even in the presence of Blackhole and Grayhole attacks.

Exploring the Reasons for Selfie-Taking and Selfie-Posting on Social Media with Its Effect on Psychological and Social Lives:A Study among Indian Youths

‘Selfie’taking was introduced to the common people by smartphones and has become a common practice across the globe in no time.With technological advancement and the popularity of smartphones,selfie-taking has grown rapidly within a short time.In light of the new trend set by the generation,this study aimed to explore reasons for selfie-taking and selfie-posting on social media and their effects on the social and psychological lives of young adults.A purposive sampling method was adopted to select 20 Indian citizens,between 18 and 24 years.The data were collected through semi-structured interviews and analysed using thematic analysis.Selfie-taking and posting on social media give positive feelings,and it acts as a mood modifier dependent mostly on the favourability and feedback about the post which in turn affects emotions and self-satisfaction.

Discrete Software Reliability Growth Modeling for Errors of Different Severity Incorporating Change-point Concept

Several software reliability growth models （SRGM） have been developed to monitor the reliability growth during the testing phase of software development. In most of the existing research available in the literatures, it is considered that a similar testing effort is required on each debugging effort. However, in practice, different types of faults may require different amounts of testing efforts for their detection and removal. Consequently, faults are classified into three categories on the basis of severity： simple, hard and complex. This categorization may be extended to r type of faults on the basis of severity. Although some existing research in the literatures has incorporated this concept that fault removal rate （FRR） is different for different types of faults, they assume that the FRR remains constant during the overall testing period. On the contrary, it has been observed that as testing progresses, FRR changes due to changing testing strategy, skill, environment and personnel resources. In this paper, a general discrete SRGM is proposed for errors of different severity in software systems using the change-point concept. Then, the models are formulated for two particular environments. The models were validated on two real-life data sets. The results show better fit and wider applicability of the proposed models as to different types of failure datasets.

Seismic behavior of slab-structural wall junction of RC building

In high seismic zone regions, slender reinforced concrete structural walls are commonly used in high-rise buildings as a main lateral load resisting element. These walls are very effective in limiting the lateral drift of the building due to their large in-plane stiffness. However, the presence of floor slabs influences the behavior of the shear wall. Also, the current design requirements do not account for the presence of floor slabs. To understand the behavior of wall-slab junctions and address the shortcomings of the current design requirements, the influence of two parameters, namely(a) aspect ratio and(b) longitudinal reinforcement ratio on the behavior is studied numerically. It is observed that the presence of floor slabs at different levels tends to partition the wall into squat wall panels between two consecutive floors. The wall-slab junctions show large stress concentrations arising from the strut action in the squat panels. It is also observed that the floor slabs can get significantly damaged near the wall-slab junction for lower vertical reinforcement ratios in the wall. Thus, the current codeprescribed minimum reinforcement in shear walls is not sufficient and needs to be revisited at for improved performance.

Coping with Pressures of Modernization by Traditional Farmers: a Strategy for Sustainable Rural Development in Yunnan, China

Traditional farming practices conform to sustainable rural livelihoods, while agricultural modernisation tends to undermine these practices through various perturbations. A case study in Tengchong County (western Yunnan, China) shows that transformation of traditional alder (Alnus nepalensis) and dry rice (upland rice) rotational farming to introduced Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantations leads to localised water scarcity and soil fertility decline. While farmers are aware of ecological sustainability of traditional farming, they prefer Chinese fir forestry because it is less labour-intensive, has a high market value, and releases time for profitable off-farm work. Farmers adapt to economic liberalization by planting high value crops and trees. However, alternatives to make local agricultural production more profitable through competitive business strategies, cooperative approaches, innovations in integrating high value crops and 'downstream' processingfor sustainable rural livelihoods have been overlooked largely due to poor information availability and lack of organisational framework.

Water Pollution and Environmental Governance of the Tai and Chao Lake Basins in China in an International Perspective

The Tai and Chao Lake basins are currently facing a serious water pollution crisis associated with the absence of an effective environmental governance system. The water pollution and the water governance system of the two basins will be compared. The reasons for water pollution in both basins are similar, namely the weak current water environmental governance system cannot deal with the consequences of the rapidly growing economy. China’s water governance system is a complicated combination of basin management with both departmental management and regional management. There is an absence of legal support and sound coordination mechanisms, resulting in fragmented management practices in the existing water environmental governance system. A comparison is made for the Tai and Chao Lake basins and Canada, France, the United Kingdom and the United States. Based on China’s present central-local governance structure and departmental system, an integrated reform of basin level and water environmental governance in China should learn from international experiences. The reforms could consist of improved governance structures, rebuilding authoritative and powerful agencies for basin management, strengthening the organizational structure of the basin administrations, improving legislation and regulatory systems for basin management and enhancing public participation mechanisms.

A model for dependent default with hyperbolic attenuation effect and valuation of credit default swap

A hyperbolic function is introduced to reflect the attenuation effect of one firm＇s default to its partner. If two firms are competitors （copartners）, the default intensity of one firm will decrease （increase） abruptly when the other firm defaults. As time goes on, the impact will decrease gradually until extinct. In this model, the joint distribution and marginal distributions of default times are derived by employing the change of measure, and the fair swap premium of a credit default swap （CDS） can be valued.

Does the EVA valuation model explain the market value of equity better under changing required return than constant required return?

Through the Economic-Value-Added(EVA)valuation model,the expected market value of equity can be determined by adding the book value of equity with the present value of expected EVAs under the assumption of constant required return and constant return on equity.The equation of EVA valuation model has taken its shape under the assumption of constant required return and constant return on equity.However,a large body of empirical evidence indicates that required rate of return never remain constant.The EVA-valuation model formulated under constant required return cannot be implemented under the scenario of changing required return.In this study,we explored whether the EVA valuation model could be implemented under changing required return by making any changes in the model and found that it could be implemented under the scenario of changing required return by replacing the book value of the equity of the existing model with the present value of required earnings or normal market earnings.We further examined whether the explanatory ability of the EVA valuation model under the assumption of changing required return is better than that of the valuation model under the assumption of constant required return.Relative information content analyses were conducted by considering sample of the intrinsic value of equities determined by valuation models and the market value of equities of 69 large-cap,88 mid-cap,and 79 small-cap companies.The results showed that the EVA-based valuation model with changing normal market return outperformed the EVA-based valuation model with constant required return.

Analysis of the Stakeholder Engagement in the Deployment of Renewables and Smart Grid Technologies

The implementation of higher shares of renewables in a global energy mix has to be accompanied by simultaneous deployment of enabling smart grid technologies （SGTs）. This combination will inevitably lead to a revolutionary change in a conventional energy system, particularly, the shifting role of consumers to prosnmers. But resistance may arise from such a dramatic shift, since it is associated with high uncertainty in conjunction with increasing responsibilities of all stakeholders, the urgent need of effective control, and the development of a process. To ensure the positive influence, coherent actions of all players, and appropriate treatment of the spots of resistance, the analysis of the interplay between key stakeholders has been done. The paper introduces the framework for stakeholders＇ analysis, applies it on the European Union （EU） example, and provides recommendations to reduce the resistance of SGTs deployment.