Design and pricing of maintenance service contract based on Nash non-cooperative game approach

Nowadays manufacturers are facing fierce challenge.Apart from the products,providing customers with multiple maintenance options in the service contract becomes more popular,since it can help to improve customer satisfaction,and ultimately promote sales and maximize profit for the manufacturer.By considering the combinations of corrective maintenance and preventive maintenance,totally three types of maintenance service contracts are designed.Moreover,attractive incentive and penalty mechanisms are adopted in the contracts.On this basis,Nash non-cooperative game is applied to analyze the revenue for both the manufacturer and customers,and so as to optimize the pricing mechanism of maintenance service contract and achieve a win-win situation.Numerical experiments are conducted.The results show that by taking into account the incentive and penalty mechanisms,the revenue can be improved for both the customers and manufacturer.Moreover,with the increase of repair rate and improvement factor in the preventive maintenance,the revenue will increase gradually for both the parties.

A fixed point theorem for Proinov mappings with a contractive iterate

In this paper,we consider the fixed point theorem for Proinov mappings with a contractive iterate at a point.In other words,we combine and unify the basic approaches of Proinov and Sehgal in the framework of the complete metric spaces.We consider examples to illustrate the validity of the obtained result.

Revision rhinoplasty for contracted nose:A systematic review and meta-analysis

Background:This study aimed to review treatments and evaluate the aesthetic outcomes,complications,and reoperation rates regarding surgical correction for a postoperative contracted nose.Methods:PubMed,MEDLINE,and Embase databases were searched for studies detailing aesthetic outcomes and complications of surgical correction of a contracted nose.Surgical procedures,adjuvant treatment,outcomes,and complications were synthesized and analyzed.Results:Nine articles encompassing 376 patients were included in the systematic review,and six articles(198 participants)were included in the meta-analysis.The most frequently used graft material was the autologous rib cartilage(61.1%).Surgical procedures were heterogeneous in these studies.The nasolabial angle reduced by 9.52°(95%confidence interval(CI):(-11.95,-7.09),P<0.0001),and the nasal length increased significantly(standardized mean difference(SMD)=2.25,95%CI:(1.26,2.23),P<0.00001).However,the evidence was insufficient to determine a significant change in the columellar-labial angle(SMD=-0.95,95%CI:(-2.19,0.29),P=0.13)and columellar-lobular angle(SMD=2.39,95%CI:(-1.20,5.97),P=0.19).Aesthetic dissatisfaction(12.5%)and infection(4.5%)were the most commonly reported complications.Reoperation was performed in 5.3%of patients.Conclusion:Surgical correction can increase the nasal length,reduce the nasolabial angle,and have a low reoperation rate.No significant improvement in the columellar-labial or columellar-lobular angle was observed.

A Framework for Enhancing Privacy and Anonymity in Blockchain-Enabled IoT Devices

With the increase in IoT(Internet of Things)devices comes an inherent challenge of security.In the world today,privacy is the prime concern of every individual.Preserving one’s privacy and keeping anonymity throughout the system is a desired functionality that does not come without inevitable trade-offs like scalability and increased complexity and is always exceedingly difficult to manage.The challenge is keeping confidentiality and continuing to make the person innominate throughout the system.To address this,we present our proposed architecture where we manage IoT devices using blockchain technology.Our proposed architecture works on and off blockchain integrated with the closed-circuit television(CCTV)security camera fixed at the rental property.In this framework,the CCTV security camera feed is redirected towards the owner and renter based on the smart contract conditions.One entity(owner or renter)can see the CCTV security camera feed at one time.There is no third-party dependence except for the CCTV security camera deployment phase.Our contributions include the proposition of framework architecture,a novel smart contract algorithm,and the modification to the ring signatures leveraging an existing cryptographic technique.Analyses are made based on different systems’security and key management areas.In an empirical study,our proposed algorithm performed better in key generation,proof generation,and verification times.By comparing similar existing schemes,we have shown the proposed architectures’advantages.Until now,we have developed this system for a specific area in the real world.However,this system is scalable and applicable to other areas like healthcare monitoring systems,which is part of our future work.

Bipartite consensus problems of Lurie multi-agent systems over signed graphs: A contraction approach

This paper examines the bipartite consensus problems for the nonlinear multi-agent systems in Lurie dynamics form with cooperative and competitive communication between different agents. Based on the contraction theory, some new conditions for the nonlinear Lurie multi-agent systems reaching bipartite leaderless consensus and bipartite tracking consensus are presented. Compared with the traditional methods, this approach degrades the dimensions of the conditions, eliminates some restrictions of the system matrix, and extends the range of the nonlinear function. Finally, two numerical examples are provided to illustrate the efficiency of our results.

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.

Preserving Data Secrecy and Integrity for Cloud Storage Using Smart Contracts and Cryptographic Primitives

Cloud computing has emerged as a viable alternative to traditional computing infrastructures,offering various benefits.However,the adoption of cloud storage poses significant risks to data secrecy and integrity.This article presents an effective mechanism to preserve the secrecy and integrity of data stored on the public cloud by leveraging blockchain technology,smart contracts,and cryptographic primitives.The proposed approach utilizes a Solidity-based smart contract as an auditor for maintaining and verifying the integrity of outsourced data.To preserve data secrecy,symmetric encryption systems are employed to encrypt user data before outsourcing it.An extensive performance analysis is conducted to illustrate the efficiency of the proposed mechanism.Additionally,a rigorous assessment is conducted to ensure that the developed smart contract is free from vulnerabilities and to measure its associated running costs.The security analysis of the proposed system confirms that our approach can securely maintain the confidentiality and integrity of cloud storage,even in the presence of malicious entities.The proposed mechanism contributes to enhancing data security in cloud computing environments and can be used as a foundation for developing more secure cloud storage systems.

FADSF:A Data Sharing Model for Intelligent Connected Vehicles Based on Blockchain Technology

With the development of technology,the connected vehicle has been upgraded from a traditional transport vehicle to an information terminal and energy storage terminal.The data of ICV(intelligent connected vehicles)is the key to organically maximizing their efficiency.However,in the context of increasingly strict global data security supervision and compliance,numerous problems,including complex types of connected vehicle data,poor data collaboration between the IT(information technology)domain and OT(operation technology)domain,different data format standards,lack of shared trust sources,difficulty in ensuring the quality of shared data,lack of data control rights,as well as difficulty in defining data ownership,make vehicle data sharing face a lot of problems,and data islands are widespread.This study proposes FADSF(Fuzzy Anonymous Data Share Frame),an automobile data sharing scheme based on blockchain.The data holder publishes the shared data information and forms the corresponding label storage on the blockchain.The data demander browses the data directory information to select and purchase data assets and verify them.The data demander selects and purchases data assets and verifies them by browsing the data directory information.Meanwhile,this paper designs a data structure Data Discrimination Bloom Filter(DDBF),making complaints about illegal data.When the number of data complaints reaches the threshold,the audit traceability contract is triggered to punish the illegal data publisher,aiming to improve the data quality and maintain a good data sharing ecology.In this paper,based on Ethereum,the above scheme is tested to demonstrate its feasibility,efficiency and security.

Strategic Contracting for Software Upgrade Outsourcing in Industry 4.0

The advent of Industry 4.0 has compelled businesses to adopt digital approaches that combine software toenhance production efficiency. In this rapidly evolving market, software development is an ongoing process thatmust be tailored to meet the dynamic needs of enterprises. However, internal research and development can beprohibitively expensive, driving many enterprises to outsource software development and upgrades to externalservice providers. This paper presents a software upgrade outsourcing model for enterprises and service providersthat accounts for the impact of market fluctuations on software adaptability. To mitigate the risk of adverseselection due to asymmetric information about the service provider’s cost and asymmetric information aboutthe enterprise’s revenues, we propose pay-per-time and revenue-sharing contracts in two distinct informationasymmetry scenarios. These two contracts specify the time and transfer payments for software upgrades. Througha comparative analysis of the optimal solutions under the two contracts and centralized decision-making withfull-information, we examine the characteristics of the solutions under two information asymmetry scenarios andanalyze the incentive effects of the two contracts on the various stakeholders. Overall, our study offers valuableinsights for firms seeking to optimize their outsourcing strategies and maximize their returns on investment insoftware upgrades.

Smart Contract Vulnerability Detection Method Based on Feature Graph and Multiple Attention Mechanisms

The fast-paced development of blockchain technology is evident.Yet,the security concerns of smart contracts represent a significant challenge to the stability and dependability of the entire blockchain ecosystem.Conventional smart contract vulnerability detection primarily relies on static analysis tools,which are less efficient and accurate.Although deep learning methods have improved detection efficiency,they are unable to fully utilize the static relationships within contracts.Therefore,we have adopted the advantages of the above two methods,combining feature extraction mode of tools with deep learning techniques.Firstly,we have constructed corresponding feature extraction mode for different vulnerabilities,which are used to extract feature graphs from the source code of smart contracts.Then,the node features in feature graphs are fed into a graph convolutional neural network for training,and the edge features are processed using a method that combines attentionmechanismwith gated units.Ultimately,the revised node features and edge features are concatenated through amulti-head attentionmechanism.The result of the splicing is a global representation of the entire feature graph.Our method was tested on three types of data:Timestamp vulnerabilities,reentrancy vulnerabilities,and access control vulnerabilities,where the F1 score of our method reaches 84.63%,92.55%,and 61.36%.The results indicate that our method surpasses most others in detecting smart contract vulnerabilities.

Anonymous TollPass: A Blockchain-Based Privacy-Preserving Electronic Toll Payment Model

As big data,Artificial Intelligence,and Vehicle-to-Everything(V2X)communication have advanced,Intelligent Transportation Systems(ITS)are being developed to enable efficient and safe transportation systems.Electronic Toll Collection(ETC),which is one of the services included in ITS systems,is an automated system that allows vehicles to pass through toll plazas without stopping for manual payment.The ETC system is widely deployed on highways due to its contribution to stabilizing the overall traffic system flow.To ensure secure and efficient toll payments,designing a distributed model for sharing toll payment information among untrusted toll service providers is necessary.However,the current ETC system operates under a centralized model.Additionally,both toll service providers and toll plazas know the toll usage history of vehicles.It raises concerns about revealing the entire driving routes and patterns of vehicles.To address these issues,blockchain technology,suitable for secure data management and data sharing in distributed systems,is being applied to the ETC system.Blockchain enables efficient and transparent management of ETC information.Nevertheless,the public nature of blockchain poses a challenge where users’usage records are exposed to all participants.To tackle this,we propose a blockchain-based toll ticket model named AnonymousTollPass that considers the privacy of vehicles.The proposed model utilizes traceable ring signatures to provide unlinkability between tickets used by a vehicle and prevent the identity of the vehicle using the ticket from being identified among the ring members for the ticket.Furthermore,malicious vehicles’identities can be traced when they attempt to reuse tickets.By conducting simulations,we show the effectiveness of the proposed model and demonstrate that gas fees required for executing the proposed smart contracts are only 10%(when the ring size is 50)of the fees required in previous studies.

High-Level Security Dimension Evaluation of Blockchain BaaS System and Key Technology

In recent years,blockchain technology integration and application has gradually become an important driving force for new technological innovation and industrial transformation.While blockchain technology and applications are developing rapidly,the emerging security risks and obstacles have gradually become prominent.Attackers can still find security issues in blockchain systems and conduct attacks,causing increasing losses from network attacks every year.In response to the current demand for blockchain application security detection and assessment in all industries,and the insufficient coverage of existing detection technologies such as smart contract detectiontechnology,this paper proposes a blockchain core technology security assessment system model,and studies the relevant detection and assessment key technologies and systems.A security assessment scheme based on a smart contract and consensus mechanism detection scheme is designed.And the underlying blockchain architecture supports the traceability of detection results using super blockchains.Finally,the functionality and performance of the system were tested,and the test results show that the model and solutions proposed in this paper have good feasibility.

A Review of Deep Learning-Based Vulnerability Detection Tools for Ethernet Smart Contracts

In recent years,the number of smart contracts deployed on blockchain has exploded.However,the issue of vulnerability has caused incalculable losses.Due to the irreversible and immutability of smart contracts,vulnerability detection has become particularly important.With the popular use of neural network model,there has been a growing utilization of deep learning-based methods and tools for the identification of vulnerabilities within smart contracts.This paper commences by providing a succinct overview of prevalent categories of vulnerabilities found in smart contracts.Subsequently,it categorizes and presents an overview of contemporary deep learning-based tools developed for smart contract detection.These tools are categorized based on their open-source status,the data format and the type of feature extraction they employ.Then we conduct a comprehensive comparative analysis of these tools,selecting representative tools for experimental validation and comparing them with traditional tools in terms of detection coverage and accuracy.Finally,Based on the insights gained from the experimental results and the current state of research in the field of smart contract vulnerability detection tools,we suppose to provide a reference standard for developers of contract vulnerability detection tools.Meanwhile,forward-looking research directions are also proposed for deep learning-based smart contract vulnerability detection.

Contract Mechanism of Water Environment Regulation for Small and Medium Sized Enterprises Based on Optimal Control Theory

The small and scattered enterprise pattern in the county economy has formed numerous sporadic pollution sources, hindering the centralized treatment of the water environment, increasing the cost and difficulty of treatment. How enterprises can make reasonable decisions on their water environment behavior based on the external environment and their own factors is of great significance for scientifically and effectively designing water environment regulation mechanisms. Based on optimal control theory, this study investigates the design of contractual mechanisms for water environmental regulation for small and medium-sized enterprises. The enterprise is regarded as an independent economic entity that can adopt optimal control strategies to maximize its own interests. Based on the participation of multiple subjects including the government, enterprises, and the public, an optimal control strategy model for enterprises under contractual water environmental regulation is constructed using optimal control theory, and a method for calculating the amount of unit pollutant penalties is derived. The water pollutant treatment cost data of a paper company is selected to conduct empirical numerical analysis on the model. The results show that the increase in the probability of government regulation and public participation, as well as the decrease in local government protection for enterprises, can achieve the same regulatory effect while reducing the number of administrative penalties per unit. Finally, the implementation process of contractual water environmental regulation for small and medium-sized enterprises is designed.

Thick-skinned Contractional Salt Structures in the Kuqa Depression,the Northern Tarim Basin:Constraints from Physical Experiments

Thick-skinned contractional salt structures are widely developed in the western Kuqa depression, northern Tarim basin. To understand the mechanisms that govern the development of these structures, physical experiments are conducted and the results show that they are largely governed by the activities of basement faults and the forming of paleo-uplifts and basement slopes. The model materials in this study are dry sand, vaseline and plasticene （or hard foam）, simulating the suprasalt, salt, and subsalt layers respectively. The experiments show that, due to the activities of basement faults and the forming of the paleo-uplifts, salt bodies usually accumulate and thicken significantly on the middle top of the paleo-uplifts which are constrained by the pre-exiting boundary faults. The development of large-scale thrust faults and salt nappes is favored by the basement slops with larger dips. The experiments also conclude that differential structural deformation could occur between the subsalt and suprasalt layers because of the presence of salt layers. Their geometries and the locations of structural highs are different, despite of the great similarities in the uplifted areas. The pierced salt diapir is not observed in the experiments, which indicates that the contractional shortening does not effectively accelerate the development of the salt diapir.

Convergence Theorems of φ-pseudo Contractive Type Mappings in Normed Linear Spaces

In this paper, by virtue of an inequality and sane analysis techniques, we prove sane convergence theorems cm the iterative process for nonlinear mappings of-pseudo contractive type in named linear spaces, which extend and improve the corresponding results obtained by others recently.

Effects of adenosine triphosphate concentration on motor force regulation during skeletal muscle contraction

We employ a mechanical model of sarcomere to quantitatively investigate how adenosine triphosphate (ATP) concentration affects motor force regulation during skeletal muscle contraction. Our simulation indicates that there can be negative cross-bridges resisting contraction within the sarcomere and higher ATP concentration would decrease the resistance force from negative cross-bridges by promoting their timely detachment. It is revealed that the motor force is well regulated only when ATP concentration is above a certain level. These predictions may provide insights into the role of ATP in regulating coordination among multiple motors.

Effects of Amrinone on Cardiac Contraction and Relaxation in Isolated，Perfused Rat Heart

The effects of amrinone on cardiac contraction and relaxation were assessed in isolated, perfused rat hearts. It was found that the left ventricular developed pressure (LVDP), dp/dtmax and -da/dtmax did not significantly increase . and the time constant (τ) did not markedly shorten with perfusion of low concentration ( 1 nmol/L , 100 nmol/L) of amrinone. The perfusion with higher concentration (1000 nmol/L) of amrinone reduced LVDP (P<0. 01 ) ,dp/dtmax (P<0.01) , -dp/dtmax (P<0. 01). and prolonged τ(P< 0. 05) significaiatly. It was assumed that amrinone has no direct positive inotropic effect. and can not improve cardiac relaxation. On the contrary, the cardiac contraction and relax ation will be inhibited at higher concentration of amrinone.

Projection and Contraction Methods for Nonlinear Complementarity Problem

We applied the projection and contraction method to nonlinear complementarity problem (NCP). Moveover, we proposed an inexact implicit method for (NCP) and proved the convergence.

Effect of thienorphine on intestinal transit and isolated guinea-pig ileum contraction

AIM: To evaluate the effect of thienorphine on small intestinal transit in vivo and on guinea-pig ileum (GPI) contraction in vitro . METHODS: The effects of thienorphine on intestinal transit were examined in mice and in isolated GPI. Buprenorphine and morphine served as controls. The distance traveled by the head of the charchol and the total length of the intestine were measured in vivo . Gastrointestinal transit was expressed as a percentage of the distance traveled by the head of the marker relative to the total length of the small intestine. The isolated GPI preparations were connected to an isotonic force transducer and equilibrated for at least 1 h before exposure to drugs. Acetylcholine was used for muscle stimulation. RESULTS: Thienorphine (0.005-1.0 mg/kg, ig ) or bu-prenorphine (0.005-1.0 mg/kg, sc ) dose-dependently significantly inhibited gut transit compared with saline. Thienorphine inhibited gut transit less than buprenorphine. The maximum inhibition by thienorphine on the intestinal transit was 50%-60%, whereas the maximum inhibition by morphine on gut transit was about 100%. Thienorphine also exhibited less inhibition on acetylcholine-induced contraction of GPI, with a maximum inhibition of 65%, compared with 93% inhibition by buprenorphine and 100% inhibition by morphine. Thienorphine induced a concentration-dependent decrease in the basal tonus of spontaneous movement of the GPI, the effect of which was weaker than that with buprenorphine. The duration of the effect of thienorphine on the GPI was longer than that with buprenorphine. CONCLUSION: Thienorphine had less influence, but a longer duration of action on GPI contraction and moderately inhibited intestinal transit.