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Profit analysis of a two non‐identical unit cold standby system model with mutual changeover of the units is carried out in this paper. With mutual changeover of the unit, the operating unit, after functioning for some random amount of time, becomes standby to take rest, and the standby unit becomes operative. The failure and repair times of each unit are jointly distributed as bivariate exponential (BVE) with different parameters. Various measures of system effectiveness useful to system engineers and designers are obtained by using the regenerative point technique. Behaviour of the mean time to system failure (MTSF) and availability have also been studied graphically.

Deals with the stochastic analysis of a two identical unit cold standby system model with repair and replacement policies. Taking the bivariate exponential distribution of failure and repair times and using the regenerative point technique, various measures of system effectiveness are obtained.

Investigates a stochastic model of a two identical unit cold standby system. Assumes that, if repair of the failed unit is not completed within a specified time, then an order is placed to replace the failed unit by the new one. The specified time is also known as the maximum repair time limit which may change from user to user of the system, so that it is assumed as a random variable. Joint distribution of failure and repair times is bivariate exponential whereas the distributions of lead time (difference between order and delivery time for a new unit) and replacement time of the new unit are negative exponential. Obtains various reliability characteristics of the system under study by using regenerative point technique. Also studied characteristics through graphs.

In this chapter, an attempt has been made to develop a security-based hardware system using an 8-bit single-chip microcontroller in conjunction with some sensor technology and lighting and alarming actuators. The proposed system aims to ensure the security and privacy of a dedicated area in terms of unauthorized human intrusion, hazardous gas leakage, extreme prolonged temperature changes, atypical smoke or vapor content in space and abrupt drop in illumination. The proposed system is capable of detecting any type of physical intervention and hazardous anomalies in the environment of the reserved space. In order to define the operation of the system, programs written in C++ with the special rule of code structuring have been deployed on the microcontroller using the Arduino Integrated Development Environment. The system is like a small container, enclosing all the respective sensor modules, microcontroller board and open connections for actuators. The proposed system is easy to use hardware and does not demand any human intervention for its functioning and can be installed with almost no changes in the infrastructure.

Denial-of-service (DoS) attacks develop unauthorized entry to various network services and user information by building traffic that creates multiple requests simultaneously making the system unavailable to users. Protection of internet services requires effective DoS attack detection to keep an eye on traffic passing across protected networks, freeing the protected internet servers from surveillance threats and ensuring they can focus on offering high-quality services with the fewest response times possible.

This paper aims to develop a hybrid optimization-based deep learning model to precisely detect DoS attacks.

The designed Aquila deer hunting optimization-enabled deep belief network technique achieved improved performance with an accuracy of 92.8%, a true positive rate of 92.8% and a true negative rate of 93.6.

The introduced detection approach effectively detects DoS attacks available on the internet.

In this study, the authors determined the prevalence of contraceptive use among Pakistani women and assessed factors influencing the utilization of contraception with a particular focus on the experience of gender-based violence.

The dataset used in this study was the Pakistan Demographic Health Survey 2018, which includes married women only. Bivariate analysis and multivariate logistic regression were used to investigate the association between contraceptive use and a number of explanatory variables including experience of gender-based violence.

From 2006 to 2018, the contraceptive prevalence rate (CPR) and the use of modern contraceptive methods increased slowly. The findings of this study demonstrated that higher educational level and wealth index increased the likelihood of contraceptive uptake and the use of modern contraception. Media exposure to family planning and spousal communication were protective factors that encouraged women to use contraception, including modern contraception, to avoid unwanted pregnancy. Women who experienced gender-based violence (GBV) were more likely to use contraception than women who did not experience GBV.

The use of secondary data limited the variety of important variable that should be investigated including knowledge of women on SRH, the attitude of women toward SRH and family planning, the skills of a healthcare provider on counseling family planning, and other barrier variables such as transportation and willingness to pay for contraceptive methods. 10;The sensitivity of the topic is considered as another challenge when collecting data. Women might be hesitant to share about their GBV experience. The experience to GBV is also hard to define and depends on the feeling of each person, especially emotional violence.

This paper is one of the very few studies to examine the association between GBV and contraceptive use, and thus is valuable in opening up debate about the links between these two factors.

In the context of circular economy, tourism resources development and integrated marketing need to interact with multiple businesses, data processing with big data technology, and in the information age, the best means of integrated marketing is to integrate business through an information platform. The research purpose of this article is to improve the intelligence of the tourism platform by constructing an OR model, integrate information and improve the data processing effect in an all-round way through data mining.

This study builds the business interaction in the form of OR (operations research model) model and combines this model with the e-commerce platform to build an online travel consumption model based on the user's online operation mode.

With the development of the times and the upgrading of industries, tourism and other industries have provided new tourism resources and tourism methods for human beings by virtue of the beautiful environment, special experiences and colorful stories and related industries have been related to the tourism industry based on natural resources, customs and folklore and agricultural experiences. By identifying important nodes with high connectivity in the social network, the weighted centrality algorithm can mine the importance of interest tags.

In addition, this research builds a test platform for model performance analysis and integrates various factors. The results show that the model constructed in this study can further promote the development of tourism, improve the efficiency of tourism resources, provide marketing effects and meet the circular economy theory.

This paper aims to implement quality of service(QoS) dynamic optimization for the integrated satellite-terrestrial network(STN) of the fifth-generation Inmarsat system(Inmarsat-5).

The structure and operational logic of Inmarsat-5 STN are introduced to build the graphic evaluation and review technique(GERT) model. Thus, the equivalent network QoS metrics can be derived from the analytical algorithm of GERT. The center–point mixed possibility functions of average delay and delay variation are constructed considering users' experiences. Then, the grey clustering evaluation of link QoS is obtained combined with the two-stage decision model to give suitable rewards for the agent of GERT-Q-learning, which realizes the intelligent optimization mechanism under real-time monitoring data.

A case study based on five time periods of monitoring data verifies the adaptability of the proposed method. On the one hand, grey clustering based on possibility function enables a more effective measurement of link QoS from the users' perspective. On the other hand, the method comparison intuitively shows that the proposed method performs better.

With the development trend of integrated communication, STN has become an important research object in satellite communications. This paper establishes a modular and extensible optimization framework whose loose coupling structure and flexibility facilitate management and development. The grey-clustering-based GERT-Q-Learning model has the potential to maximize design and application benefits of STN throughout its life cycle.

The present study aims to examine the impact of social media marketing activities (SMMAs) on the adoption of food waste reduction behavior among Generation Z consumers within the restaurant service industry in Pakistan. The study focuses on the impact of social media advertisements and investigates the mediating influence of waste reduction intentions on actual behavior. This underscores the significance of contextual and emotional variables in comprehending consumer behaviors.

The study used a cross-sectional research methodology to examine the impact of SMMAs on the behavior of Generation Z consumers in Pakistan’s food service industry with regard to reducing food waste. A study was conducted to investigate the restaurant purchasing behaviors of a sample consisting of 449 individuals belonging to the millennial generation, often known as Generation Z.

The majority of variables related to SMMA, except for interactivity and personalization, were shown to have a positive impact on individuals’ intents to reduce food waste. The study observed a significant relationship between consumers’ intentions to decrease waste and their actual behavior in waste reduction. Furthermore, this relationship was shown to be influenced by the mediating role of waste reduction intention.

Examining how social media affects Pakistani Generation Z’s efforts to reduce food waste is what makes this study distinctive. According to the research, the majority of social media factors positively influence intentions to reduce waste. The relationship between intentions and actual behavior, which highlights the impact of social media campaigns and emotional aspects in promoting waste reduction, is one of the important conclusions.

As the core technology of blockchain, various consensus mechanisms have emerged to satisfy the demands of different application scenarios. Since determining the security, scalability and other related performance of the blockchain, how to reach consensus efficiently of consensus mechanism is a critical issue in the blockchain.

The paper opted for a research overview on the blockchain consensus mechanism, including the consensus mechanisms' consensus progress, classification and comparison, which are complemented by documentary analysis.

This survey analyzes solutions for the improvement of consensus mechanisms in blockchain that have been proposed during the last few years and suggests future research directions around consensus mechanisms. First, the authors outline the consensus processes, the advantages and disadvantages of the mainstream consensus mechanisms. Additionally, the consensus mechanisms are subdivided into four types according to their characteristics. Then, the consensus mechanisms are compared and analyzed based on four evaluation criteria. Finally, the authors summarize the representative progress of consensus mechanisms and provide some suggestions on the design of consensus mechanisms to make further advances in this field.

This paper summarizes the future research development of the consensus mechanisms.