Search results

Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.

The internet of vehicles (IoV) communication has recently become a popular research topic in the automotive industry. The growth in the automotive sector has resulted in significant standards and guidelines that have engaged various researchers and companies. In IoV, routing protocols play a significant role in enhancing communication safety for the transportation system. The high mobility of nodes in IoV and inconsistent network coverage in different areas make routing challenging. This paper aims to provide a lane-based advanced forwarding protocol for internet of vehicles (LAFP-IoV) for efficient data distribution in IoV. The proposed protocol’s main feature is that it can identify the destination zone by using position coordinates and broadcasting the packets toward the direction of destination. The novel suppression technique is used in the broadcast method to reduce the network routing overhead.

The proposed protocol considers the interferences between different road segments, and a novel lane-based forwarding model is presented. The greedy forwarding notion, the broadcasting mechanism, and the suppression approach are used in this protocol to reduce the overhead generated by standard beacon forwarding procedures. The SUMO tool and NS-2 simulator are used for the vehicle's movement pattern and to simulate LAFP-IoV.

The simulation results show that the proposed LAFP-IoV protocol performs better than its peer protocols. It uses a greedy method for forwarding data packets and a carry-and-forward strategy to recover from the local maximum stage. This protocol's low latency and good PDR make it ideal for congested networks.

The proposed paper provides a unique lane-based forwarding for IoV. The proposed work achieves a higher delivery ratio than its peer protocols. The proposed protocol considers the lanes while forwarding the data packets applicable to the highly dense scenarios.

The purpose of this study is to extensively explore the vehicular network paradigm, challenges faced by them and provide a reasonable solution for securing these vulnerable networks. Vehicle-to-everything (V2X) communication has brought the long-anticipated goal of safe, convenient and sustainable transportation closer to reality. The connected vehicle (CV) paradigm is critical to the intelligent transportation systems vision. It imagines a society free of a troublesome transportation system burdened by gridlock, fatal accidents and a polluted environment. The authors cannot overstate the importance of CVs in solving long-standing mobility issues and making travel safer and more convenient. It is high time to explore vehicular networks in detail to suggest solutions to the challenges encountered by these highly dynamic networks.

This paper compiles research on various V2X topics, from a comprehensive overview of V2X networks to their unique characteristics and challenges. In doing so, the authors identify multiple issues encountered by V2X communication networks due to their open communication nature and high mobility, especially from a security perspective. Thus, this paper proposes a trust-based model to secure vehicular networks. The proposed approach uses the communicating nodes’ behavior to establish trustworthy relationships. The proposed model only allows trusted nodes to communicate among themselves while isolating malicious nodes to achieve secure communication.

Despite the benefits offered by V2X networks, they have associated challenges. As the number of CVs on the roads increase, so does the attack surface. Connected cars provide numerous safety-critical applications that, if compromised, can result in fatal consequences. While cryptographic mechanisms effectively prevent external attacks, various studies propose trust-based models to complement cryptographic solutions for dealing with internal attacks. While numerous trust-based models have been proposed, there is room for improvement in malicious node detection and complexity. Optimizing the number of nodes considered in trust calculation can reduce the complexity of state-of-the-art solutions. The theoretical analysis of the proposed model exhibits an improvement in trust calculation, better malicious node detection and fewer computations.

The proposed model is the first to add another dimension to trust calculation by incorporating opinions about recommender nodes. The added dimension improves the trust calculation resulting in better performance in thwarting attacks and enhancing security while also reducing the trust calculation complexity.

The purpose of this study is to investigate the obstacles to mechatronics adoption in the construction industry from a Nigerian perspective. It aims to fill the knowledge gap by focusing on the specific challenges faced in developing countries, considering the unique contexts and constraints of the Nigerian construction industry.

The study used a comprehensive literature review to identify 26 obstacles to mechatronics adoption. These obstacles were used to develop a well-structured questionnaire, which was then distributed to construction professionals using Google Forms through purposive and snowball sampling techniques. The rankings obtained from the questionnaire responses were analyzed to determine the most significant obstacles.

The study revealed the top five most significant obstacles to mechatronics adoption in the Nigerian construction industry. These obstacles include high costs of operation and maintenance, resistance to adopting new technologies, a lack of standardized protocols, insufficient maintenance capabilities and a lack of government support. Factor analysis revealed five clusters of obstacles: technological-related factors, economic-related factors, capability-related factors, government-related factors and awareness-related factors.

Findings from this study have the potential to inform decision-making, drive policy changes and guide future research efforts aimed at promoting the widespread adoption of mechatronics technologies, ultimately leading to the transformation and improvement of the construction industry as a whole.

This study contributes to the field of mechatronics adoption in the construction industry by addressing the gap in research specific to developing countries such as Nigeria. By identifying and analyzing the obstacles from a Nigerian perspective, the study offers unique insights and original findings.

As the number of devices that connect to the Internet of Things (IoT) has grown, privacy and security issues have come up. Because IoT devices collect so much sensitive information, like user names, locations, phone numbers and even how they usually use energy, it is very important to protect users' privacy and security. IoT technology will be hard to use on the client side because IoT-enabled devices do not have clear privacy and security controls.

IoT technology would be harder to use on the client side if the IoT did not offer enough well-defined ways to protect users’ privacy and security. The goal of this research is to protect people's privacy in the IoT by using the oppositional artificial flora optimization (EGPKC-OAFA) algorithm to generate the best keys for the ElGamal public key cryptosystem (EGPKC). The EGPKC-OAFA approach puts the most weight on the IEEE 802.15.4 standard for MAC, which is the most important part of the standard. The security field is part of the MAC header of this standard. In addition, the MAC header includes EGPKC, which makes it possible to make authentication keys as quickly as possible.

With the proliferation of IoT devices, privacy and security have become major concerns in the academic world. Security and privacy are of the utmost importance due to the large amount of personally identifiable information acquired by IoT devices, such as name, location, phone numbers and energy use. Client-side deployment of IoT technologies will be hampered by the absence of well-defined privacy and security solutions afforded by the IoT. The purpose of this research is to present the EGPKC with optimum key generation using the EGPKC-OAFA algorithm for the purpose of protecting individual privacy within the context of the IoT. The EGPKC-OAFA approach is concerned with the MAC standard defined by the IEEE 802.15.4 standard, which includes the security field in its MAC header. Also, the MAC header incorporates EGPKC, which enables the fastest possible authentication key generation. In addition, the best methodology award goes to the OAFA strategy, which successfully implements the optimum EGPKC selection strategy by combining opposition-based (OBL) and standard AFA ideas. The EGPKC-OAFA method has been proved to effectively analyze performance in a number of simulations, with the results of various functions being identified.

In light of the growing prevalence of the IoT, an increasing number of people are becoming anxious about the protection and confidentiality of the personal data that they save online. This is especially true in light of the fact that more and more things are becoming connected to the internet. The IoT is capable of gathering personally identifiable information such as names, addresses and phone numbers, as well as the quantity of energy that is used. It will be challenging for customers to adopt IoT technology because of worries about the security and privacy of the data generated by users. In this work, the EGPKC is paired with adversarial artificial flora, which leads in an increase to the privacy security provided by EGPKC for the IoT (EGPKC-OAFA). The MAC security field that is part of the IEEE 802.15.4 standard is one of the areas that the EGPKC-OAFA protocol places a high focus on. The Authentication Key Generation Protocol Key Agreement, also known as EGPKCA, is used in MAC headers. The abbreviation for this protocol is EGPKCA. The OAFA technique, also known as the combination of OBL and AFA, is the most successful method for selecting EGPKCs. This method is recognized by its acronym, OAFA. It has been shown via a variety of simulations that the EGPKC-OAFA technique is a very useful instrument for carrying out performance analysis.

In vehicular ad hoc networks (VANETs), the information transmitted is broadcast in a free access environment. Therefore, VANETs are vulnerable against attacks that can directly perturb the performance of the networks and then provoke big fall of capability. Black hole attack is an example such attack, where the attacker node pretends that having the shortest path to the destination node and then drops the packets. This paper aims to present a new method to detect the black hole attack in real-time in a VANET network.

This method is based on capability indicators that are widely used in industrial production processes. If the different capability indicators are greater than 1.33 and the stability ratio (S_r) is greater than 75%, the network is stable and the vehicles are communicating in an environment without the black hole attack. When the malicious nodes representing the black hole attacks are activated one by one, the fall of capability becomes more visible and the network is unstable, out of control and unmanaged, due to the presence of the attacks. The simulations were conducted using NS-3 for the network simulation and simulation of urban mobility for generating the mobility model.

The proposed mechanism does not impose significant overheads or extensive modifications in the standard Institute of Electrical and Electronics Engineers 802.11p or in the routing protocols. In addition, it can be implemented at any receiving node which allows identifying malicious nodes in real-time. The simulation results demonstrated the effectiveness of proposed scheme to detect the impact of the attack very early, especially with the use of the short-term capability indicators (Cp, Cpk and Cpm) of each performance metrics (throughput and packet loss ratio), which are more efficient at detecting quickly and very early the small deviations over a very short time. This study also calculated another indicator of network stability which is S_r, which allows to make a final decision if the network is under control and that the vehicles are communicating in an environment without the black hole attack.

According to the best of the authors’ knowledge, the method, using capability indicators for detecting the black hole attack in VANETs, has not been presented previously in the literature.

Moral consideration is significantly important as social responsibility of economic actions. This article aims to analyze the moral embeddedness of labor market using the typology of moral behavior in market exchange by Beckert (2005).

This study contributes to methodological novelty through a digital research design using Gephi and NVIVO software. Textual Network Analysis (TNA) is used to analyze the moral embeddedness of labor market transaction of Chinese migrant workers.

Overall, the results show that the presence of Chinese migrant workers in Indonesia is a form of Trojan altruism and harmful to local labor market. This study also provides a theoretical debate that morals are always embedded in markets.

The data and focus of this study are the Indonesian side, particularly the local labor market. In addition, access to interviews with the Chinese government and companies is very challenging and cannot be done because they cannot carelessly provide information to journalists and researchers.

In contrast to previous studies on Chinese migrant workers that tend to use the economic perspective, this study applies the moral perspective that is more sociological and discusses social responsibility of market actions.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0737

Bisphosphonate (BP) medications can be applied to prohibit the damage of bone density and the remedy of bone illnesses such as osteoporosis. As the metal chelating of phosphonate groups are nearby large with six O atoms possessing the high negative charge, these compounds are active toward producing the chelated complexes through drug design method. BP agents have attracted much attention for the clinical treatment of some skeletal diseases depicted by enhancing of osteoclast-mediated bone resorption.

In this work, it has been accomplished the CAM-B3LYP/6–311+G(d, p)/LANL2DZ to estimate the susceptibility of SWCNT for adsorbing alendronate, ibandronate, neridronate and pamidronate chelated to two metal cations of 2Mg²⁺, 2Ca²⁺, 2Sr²⁺ through nuclear magnetic resonance and thermodynamic parameters. Therefore, the data has explained that the feasibility of using SWCNT and BP agents becomes the norm in metal chelating of drug delivery system which has been selected through alendronate → 2X, ibandronate → 2X, neridronate → 2X and pamidronate → 2X (X = Mg²⁺/Ca²⁺/Sr²⁺) complexes.

The thermodynamic results have exhibited that the substitution of 2Ca²⁺ cation by 2Sr²⁺ cation in the structure of bioactive glasses can be efficient for treating vertebral complex fractures. However, it has been observed the most fluctuation in the Gibbs free energy for BPs → 2Sr²⁺ at 300 K. Furthermore, Monte Carlo simulation has resulted by increasing the dielectric constant in the aqueous medium can enhance the stability and efficiency of BP drugs for preventing the loss of bone density and treating the osteoporosis.

According to this research, by incorporation of chelated 2Mg²⁺, 2Ca²⁺ and 2Sr²⁺ cations to BP drugs adsorbed onto (5, 5) armchair SWCNT, the network compaction would increase owing to the larger atomic radius of Sr²⁺ cation rather than Ca²⁺ and Mg²⁺, respectively.

The study aims to identify the predictors of depression and anxiety among carers of hospitalized patients with mental illness in Eradah Complex for Mental Health Hospital.

A descriptive correlational study design was conducted using a convenient sample of family carers of patients with mental illness (N = 216). The study used the Beck Depression Inventory and Anxiety Inventory scales.

The results of regression models revealed that the socio-demographic characteristics of the family carers showed that age is a statistically significant predictor of family carers depression and anxiety scores. In addition, the age of the family carers explained 36% of the variance in the family carers depression and anxiety scores, while marital status explained 64% of the total variance in the family carers’ depression and anxiety scores. Furthermore, having received support in caring significantly predicted depression and anxiety scores, and this was the case for occupation status and being diagnosed with any form of chronic illness.

Based on the findings of this study, the authors opine that evaluations of carers’ cognitive strategies and social support are needed to determine the risk of depression in carers of mental patients.

This study is the one of the limited studies conducted in Saudi Arabia to identify predictor of depression and anxiety among caregivers of hospitalized patients with mental illness. The study has used a validated scales to assess the main study outcomes.

The emission of greenhouse gases has become an increasingly relevant topic in supply chain management. The steel industry is a highly intensive manufacturing industry with significant emission levels, particularly Scope 3 emissions, which are the indirect emissions from suppliers. Since a supply chain is seen as a non-mandatory measurement item within GHG measurement protocols, this article contributes to the literature on assessing the suppliers of a focal company relative to their emissions for complying with Scope 3 (indirect emissions). It adds to the evolving literature on low-carbon supply chains.

This study first conducted a survey with 110 suppliers from a focal transnational buyer company. A cluster analysis was performed, and ANOVA compared constructs relating to public or private ownership and country of origin. Finally, regression tested the relationship between the motivators and governance in the mitigation strategies.

Using cluster analysis, two groups of companies were found that have statistically significant differences. The influence of the country of origin was also found in relation to governance and mitigation strategies, as was the influence of the type of company on governance. Furthermore, the more motivated the suppliers and the more governance measures they adopt, the more companies adopt their own GHG mitigation strategies. These findings are summarized by way of an analytical framework that integrates the constructs with empirical evidence.

The steel industry is a sector that is particularly energy-intensive and produces millions of tons of CO₂ per year. Emissions from its SC (Scope 3) are relevant but still seen as a non-mandatory item for measurement purposes within the GHG measurement protocols, which leads to less attention being paid to the subject. This study contributes by way of its analytical framework that is validated by empirical data that can be tested in further studies.