Cell Phone Related Violations and Motorcycle Accidents: A Bayesian Approach

The effects of cell phone use on motorcycle riders’ behaviour are studied in smart city, Bhubaneswar, capital of state odisha, India. Most of motorcycle riders confess using cell phone devices while driving. Moreover, relationship between near miss and accidents has been found with the use of cell phone, reflecting a risk factor for motorcycle riders.“ This study examines the relationship between such type of behaviours, comprising calling and manipulating the screen, and the frequency of near miss and actual accidents among motorcycle riders. We conducted a web based survey measuring cell phone-specific violations, human errors, near miss and accident to motorcycle riders (N=289; age range; 18-60). We hypothesized that the relationship between cell phone use and near miss would be explained by an increase in the number of human errors committed, thus increasing the likelihood of being involved in near miss. Moreover, we hypothesized that near miss will predict actual accidents. Outcomes of path analysis showed that cell phone-specific violations predicted accidents throughout their consecutive effects on human errors and near miss only in the subsample of men. These findings offer an explanation of how cell phone use contributes to increase the likelihood of getting involved in near miss and actual accidents. The current study builds a path model explaining how cell phone-specific violations lead to more near miss among motorcycle riders.

Secure Cloud Auditability for Virtual Machines by Adaptive Characterization Using Machine Learning Methods

With the Present days increasing demand for the higher performance with the application developers have started considering cloud computing and cloud-based data centres as one of the prime options for hosting the application. Number of parallel research outcomes have for making a data centre secure, the data centre infrastructure must go through the auditing process. During the auditing process, auditors can access VMs, applications and data deployed on the virtual machines. The downside of the data in the VMs can be highly sensitive and during the process of audits, it is highly complex to permits based on the requests and can increase the total time taken to complete the tasks. Henceforth, the demand for the selective and adaptive auditing is the need of the current research. However, these outcomes are criticised for higher time complexity and less accuracy. Thus, this work proposes a predictive method for analysing the characteristics of the VM applications and the characteristics from the auditors and finally granting the access to the virtual machine by building a predictive regression model. The proposed algorithm demonstrates 50% of less time complexity to the other parallel research for making the cloud-based application development industry a safer and faster place.

Rankıng value-creatıng green approach practıces and choosıng ıdeal green marketıng strategy for logıstıcs companıes

The deterioration of environmental factors, economic and technological development, the formation of complexity in societies, the rise of complex structures have made the environment and green management practices more important. Especially value-creating green approaches are considered as critical components in both public and private sector applications and defined as indicators of success in terms of sustainability. On the other hand, green marketing strategies are also important practices that have a positive impact on the environment and should be carefully emphasized for the inheritance of nature to future generations. Recently, it has been on the agenda quite a lot and it is understood for all sectors.In this study, it is aimed to determine the criteria for value-creating green approach practices in logistics companies operating in the TR A1 region due to the above mentioned importance and to choose the most ideal green marketing strategy. In solving this problem, Multi Criteria Decision Making (MCDM) methods, which are a complex decision-making method, have been used. According to the results of the research, it was determined that the most important criterion in value creating green approach applications as Environmental Focused Strategic Decisions (C3), and the least important criterion as Environmental Life Cycle Analysis (C2). It has been determined that the most ideal green marketing strategy is Green Innovation (A1). Accordingly the importance of the environmental based strategic decisions is revealed in terms of creating green marketing strategy for companies.

Scheduling with lot streaming in a two-machine re-entrant flow shop

Lot streaming is splitting a job-lot of identical items into several sublots (portions of a lot) that can be moved to the next machines upon completion so that operations on successive machines can be overlapped; hence, the overall performance of a multi-stage manufacturing environment can be improved. In this study, we consider a scheduling problem with lot streaming in a two-machine re-entrant flow shop in which each job-lot is processed first on Machine 1, then goes to Machine 2 for its second operation before it returns to the primary machine (either Machine 1 or Machine 2) for the third operation. For the two cases of the primary machine, both single-job and multi-job cases are studied independently. Optimal and near-optimal solution procedures are developed. Our objective is to minimize the makespan, which is the maximum completion time of the sublots and job lots in the single-job and multi-job cases, respectively. We prove that the single-job problem is optimally solved in polynomial-time regardless of whether the third operation is performed on Machine 1 or Machine 2. The multi-job problem is also optimally solvable in polynomial time when the third operation is performed on Machine 2. However, we prove that the multi-job problem is NP-hard when the third operation is performed on Machine 1. A global lower bound on the makespan and a simple heuristic algorithm are developed. Our computational experiment results reveal that our proposed heuristic algorithm provides optimal or near-optimal solutions in a very short time.

Regional development through energy infrastructure: A comparison and optimization of Iran-Pakistan-India (IPI) & Turkmenistan- Afghanistan-Pakistan-India (TAPI) gas pipelines

Pakistan is working on two pipeline projects, namely, Iran-Pakistan-India (IPI) and Turkmenistan-Afghanistan-Pakistan-India (TAPI) gas pipelines, to meet its energy supply-demand gap. This study's aims to compare these two projects and identify the most suitable option for Pakistan. Furthermore, as the TAPI project is progressing faster than the IPI project, this study also aims to identify the critical activities associated with TAPI projects. Finally, a model is proposed to optimize the material and transportation costs related to the TAPI project. The study's contribution by using fuzzy set theory-based multi-criteria decision-making (Fuzzy MCDM) to compare two projects along with usage of the Fuzzy Critical Path Method (FCPM) for the identification of critical activities associated with the TAPI project. Finally, the Genetic Algorithm is applied to optimize the material and transportation costs of the TAPI project. The results show that IPI has advantages over TAPI in terms of power generation, transportation cost, transits fee, and gas prices. The critical path analysis of the TAPI gas pipeline shows that it will take approximately 75 to 330.5 weeks to complete. The study is useful for the managers who have to work in these projects, the policymakers considering these projects at various levels, and the researcher having an interest in applying Fuzzy set theory with MCDM, CPM, and in the context of the energy infrastructure.

Quality improvement of the e-commerce website using integration of Kano model-ipa with QFD approach

This study was conducted to analyze the quality of e-commerce websites, find out which items need improvement, and make improvement design e-commerce websites. This study uses the kano model and Importance Performance Analysis approach based on 7 dimensions with 39 attributes. This study used the survey results from 103 respondents who regularly use the e-commerce website Tokopedia.com. The results of the questionnaire through the validity and reliability tests were used to analyze the reliability of items and the feasibility of the results of the questionnaire. After that, the results of the questionnaire through the corellation and hypothesis tests were used to know the relationship between variables. The findings show that 7 attributes influence customer satisfaction. However, the findings are still nowhere near the expectations. Thus, it requires being the focus of improvement. Improvements in design of 7 attributes in the form of House of Quality with 6 technical features needed to improve the quality of e-commerce website Tokopedia.com. Therefore, effective management strategies can be applied to overcome the intense competition in the e-commerce industry.

Control of Non-instantaneous Degrading Inventory under Trade Credit and Partial Backlogging

Inventory management is an extremely difficult task. It has become usual practice for a provider during the last few decades to provide a retailer with a credit term. In this article, a non-instantly degradable products inventory system is built with a price-sensitive demand and a Weibull credit term allocation reduction rate. Some backlogged deficiencies are permitted. The aim is to maximize the total profit in this study by taking three cases into account. Numerical examples, graphical representations and sensitivity analysis demonstrate the application of the approach developed in this study.

Modified Failure Mode and Effect Analysis Approaching to Improve Organization Performance based on Baldrige Criteria- A Case Study of AN Electro-medic Industry

Full attention is paid to quality in manufacturing; however, less effort is made to develop the organizational performance, which drives overall manufacturing quality. This research measures performance of one manufacturing company that in 2020 experienced surging in demand and experiencing barriers to social activities due to the pandemic. The evaluation was carried out using seven variables from the Malcolm Baldrige Criteria for Performance Excellence (MBCfPE) which were elaborated into 43 indicators of organizational performance. Weaknesses and strengths of organizational performance were sharpened through focus group discussions with experts and ended with a performance improvement solution with a priority rank based on risk priority numbers (RPN) of the FMEA method. The highest RPN is 567 and 432, respectively, for national standard implementation in a particular product and operational scheme during emergency conditions like the Cov-19 pandemic. This study contributes to Indonesian research that combines questionnaires and FMEA improvement analysis based on the US Baldrige criterion.

Assessing country performances during the Covid-19 pandemic: A Standard devıatıon based range of value method

In this paper, we compare the pandemic management performance of 22 countries that belong to the middle-high income class based on criteria including the pandemic data, population characteristics, and health system capacity. The management of the COVID-19 pandemic requires considering many and often conflicting aspects at the same time which necessitates an MCDM approach. We use a standard deviation (SDV) based range of value (ROV) method which coincides with the black-box nature of the disease. The weights obtained from the SDV method reveal that the number of COVID-19 deaths, current health expenditure, and deaths due to cardiovascular diseases are the most important criteria. The ROV method indicates that most Asian countries are ranked in higher positions due to their strong healthcare systems and quick implementation of social distancing rules. The lowest performances belong to Bulgaria, Montenegro, and Bosnia and Herzegovina. They have experienced an elevated number of deaths due to having an elderly population and inefficient usage of healthcare resources. We also show that extreme poverty is an important determinant of country performance. In countries where poverty is higher, as the case with Indonesia, implementing the social distancing rules becomes almost impossible which affects the overall country performance significantly.

Assessing the performance of Sub-Saharan African (SSA) railways based on an integrated Entropy-MARCOS approach

In this study, the performance of Sub-Saharan African railways systems (SSA) is assessed by using an integrated Entropy-MARCOS (Measurement Alternatives and Ranking according to COmpromise Solution) - based methodology. In the first phase, the Entropy method is employed to determine the weights of each sub-criterion of the decision model. This process identifies six main criteria, i.e., safety, security, internal business aspect, intermodal aspect, innovation, and learning aspect, and customer satisfaction which are further supplemented by 13 sub-criteria. In the second phase, the MARCOS method is used to rank the countries based on their railway performance assessment. Based on the results from the proposed method, a sensitivity analysis was carried out through a comparative analysis with seven other multi-criteria decision-making (MCDM) methods. The results of the study indicate that the most weighted sub-criterion is the labor productivity (internal business perspective criteria) followed by the terrorist incidence (security criteria) and the number of employees going through training/exposure sessions (innovation and learning perspective criteria). Moreover, it was revealed that Kenya is the best alternative in terms of its railway performance followed by Ethiopia, Cameroon, Nigeria, and Ghana. Based on the findings from this study, decision-makers can be assisted during the operative, designing, and planning investigations of the railway system through the consideration of these parameters as insert indicators. Also, the findings can help as a benchmark for the performance analysis of other railway systems in other African countries.