Integrated decision-support framework for sustainable fleet implementation

Issues regarding fossil fuel depletion, climate change and air pollution associated with motorised urban transportation have motivated intensive research to find cleaner, greener, and energy-efficient alternative fuels. Alternative fuel vehicles have a pivotal role in moving towards a sustainable future, with many already deployed as public transport fleet. Unlike private vehicles, the process of evaluating and selecting the appropriate fuel technology for the taxi fleet, for instance, can be demanding due to the involvement of stakeholders with different, often conflicting objectives. While many life cycle models have been developed as decision-support tools for evaluating vehicle technologies and fuel pathways based on multiple criteria, the different perspectives of fleet operators, policymakers and vehicle manufacturers may create a barrier towards the adoption of eco-friendly low carbon fleet. At present, the search for one optimal solution that performs the best in all aspects is difficult to achieve in practice. Therefore, there is a need for an integrated tool that can align the different priorities of economic, environmental and social perspectives of decision makers. This research aims to develop a computer-based framework that can be used as a shared justification tool to support multi-stakeholder decision making. The main contribution is the implementation and applicability testing of the framework via a probabilistic life cycle analysis with satisficing model. The model was initially tested and evaluated by representative third-party users from the transport industry. When demonstrated in an illustrative taxi case study, results from the life cycle analysis show constant compensation and trade-offs between the criteria. Subsequently, this thesis provides an example of how the satisficing choice model seeks a satisfactory solution that adequately meets the multiple objectives of decision makers. Also, the research provides insights for other research and industry efforts in developing tools to support decision making towards sustainable development practices

Pengaruh Retribusi Izin Mendirikan Bangunan (IMB) Terhadap Pendapatan Asli Daerah (PAD) Kabupaten Rejang Lebong

Regional Own Revenue is part of regional revenue sources which can be freely used by each region to organize regional government and development. Regional levies are local revenues from payments for services or the granting of certain special permits granted by the local government. Therefore, the purpose of this study was to determine the effect of building permit fees (IMB) on local revenue (PAD) in Rejang Lebong Regency. In this writing, the type of research used is descriptive research and the data collection method used is documentation. The analytical method used is simple linear regression, simple correlation, and termination. The results of this study are that the effect of building permit fees (IMB) on local revenue (PAD) in Rejang Lebong Regency is quite good. With the tendency of revenue realization to increase every year, with an average rate of 1.16%. The regression results show that the effect of IMB levies on achieving the PAD target is positive. The correlation value indicates the close relationship between the IMB levy and the achievement of the PAD target is moderate. The result of the termination test is that the IMB levy affects the achievement of the PAD target of 35%. The results of the hypothesis test show that the IMB levy does not significantly affect the achievement of the PAD target, this is because the target and realization of the IMB levy are still small and statistically have not shown a clear influenc

Study on continuous adsorption process for Monoethanolamine (MEA) wastewater treatment using treated rice husk and sugarcane bagasse

Monoethanolamine (MEA) is a medium that is used for removing the carbon dioxide (CO2) from the raw natural gas in gas processing plant.Foaming phenomena is formed in the absorber when heavy hydrocarbon component carried to the absorber with the feed gas.This phenomenon was reduce the effectiveness of MEA in CO2 stripping and will affect the performance of the unit.This study was conducted to examine the best method to treat the MEA wastewater to gain back its effectiveness towards stripping CO2.Adsorbent those are use in this research is rice husk and sugarcane bagasse.Two different variables that use in this research are adsorbent dosage and mixing time.The parameters that are going to be test in this research are amine concentration, oil and grease concentration and chemical oxygen demand (COD).Rice husk having the higher performance than sugarcane bagasse in removal of oil and chemical oxygen demand (COD).Rice husk achieve 71.11% of oil removal and 42.17% COD reduction. Whereas, sugarcane bagasse shower the lower performance with 46.46%.of oil and grease removal and 12.36% COD reduction. MEA concentration is maintained at 60-70 wt% for both adsorbent

An Investigation of Predictors of Information Diffusion in Social Media: Evidence from Sentiment Mining of Twitter Messages

Social media have facilitated information sharing in social networks. Previous research shows that sentiment of text influences its diffusion in social media. Each emotion can be located on a three-dimensional space formed by dimensions of valence (positive–negative), arousal (passive / calm–active / excited), and tension (tense–relaxed). While previous research has investigated the effect of emotional valence on information diffusion in social media, the effect of emotional arousal remains unexplored. This study examines how emotional arousal influences information diffusion in social media using a sentiment mining approach. We propose a research model and test it using data collected from Twitter

The Effect of Attitude, Social Trust and Trust in Social Networking Sites on Two Dimensions of Sharing Behavior

Although social networking sites (SNS) are among the most important means of sharing and communication in today’s virtual world, little work has been done to explain the sharing behavior of SNS users in detail. This study tries to investigate types of sharing behavior of SNS users and to find important factors affecting their sharing behavior. In terms of the width and depth of sharing information, we distinguish two important dimensions of sharing behavior: sharing regularity and sharing density. As a width dimension of sharing behavior, sharing regularity refers to the frequency of sharing information with other SNS users and as a depth dimension of sharing behavior, sharing density deals with the degree of private information sharing with others. Using the Theory of Reasoned Action, we propose a research model of two dimensions of sharing behavior including sharing attitude, social trust, and trust in a social networking site. We find that social trust and trust in the SNS have a significant effect on SNS users’ sharing attitude, which in turn strongly influences on two dimensions of sharing behavior. The implications of the study for research and practice will be discussed with future directions

Social Capital Mobilization in Social Networking Services

The advent of internet-enabled mobile devices has ushered in a new era of online social networking. Recently, there has been an increase in the use of mobile internet and rise in social media access via mobile phones. Many social networking services (SNS) have introduced mobile apps for users to access them “on the fly” via smartphones. Our study contributes to the literature by uncovering the relationships between SNS use and social capital mobilization. The results show that SNS intensity and SNS network size influence social capital mobilization both directly and indirectly by increasing social participation. Furthermore, use of mobile applications for social networking significantly increases SNS intensity. Finally, SNS network size is an important predictor of use of SNS mobile applications

Collaborative gold mining algorithm : an optimization algorithm based on the natural gold mining process

In optimization algorithms, there are some challenges, including lack of optimal solution, slow convergence, lack of scalability, partial search space, and high computational demand. Inspired by the process of gold exploration and exploitation, we propose a new meta-heuristic and stochastic optimization algorithm called collaborative gold mining (CGM). The proposed algorithm has several iterations; in each of these, the center of mass of points with the highest amount of gold is calculated for each miner (agent), with this process continuing until the point with the highest amount of gold or when the optimal solution is found. In an n-dimensional geographic space, the CGM algorithm can locate the best position with the highest amount of gold in the entire search space by collaborating with several gold miners. The proposed CGM algorithm was applied to solve several continuous mathematical functions and several practical problems, namely, the optimal placement of resources, the traveling salesman problem, and bag-of-tasks scheduling. In order to evaluate its efficiency, the CGM results were compared with the outputs of some famous optimization algorithms, such as the genetic algorithm, simulated annealing, particle swarm optimization, and invasive weed optimization. In addition to determining the optimal solutions for all the evaluated problems, the experimental results show that the CGM mechanism has an acceptable performance in terms of optimal solution, convergence, scalability, search space, and computational demand for solving continuous and discrete problems

Kesan Parakuat Terhadap Kadar Fotosintesis Daun Jacquemcmtia paniculata

The rate of photosynthesis of Jacquemontia paniculata leaves and the effect of different concentrations of paraquat solutions on the rate of photosynthesis were studied using the oxygen-electrode Clark-type. The mean value of the photosynthetic rate of Jacquemontia paniculata leaves at room temperature was found to be 60.24 ± 4.20 Ilmol O/dm2/hour. The optimum concentration ofparaquat solution to be used as a sprayed herbicide for Jacquemontia paniculata leaves is 0.0054 M

Antecedents of Online Customers Reviews’ Helpfulness: A Support Vector Machine Approach

Online customer reviews (OCRs) have become an important part of online customers’ decision making and People use online reviews to make decision to buy or not to buy products and services. This study aims to answer two research questions: (1) what are the antecedents of helpfulness of online reviews based on their contents? (2) How do content-based cues on OCRs influence their helpfulness? We posit a research model to study the effect of peripheral and central cues in OCRs on online review helpfulness. Online review web pages will be collected from Amazon website using a web crawler. This article will be one of the first studies that investigate OCRs helpfulness based on the central cues in the text of the review. In addition, this research will be the first study that applied the support vector machine as a machine learning method to analyze the text of OCRs

A Recommender System for Online Consumer Reviews

Online consumer reviews have helped consumers to increase their knowledge about different products/services. While most previous studies try to provide general models that predict performance of online reviews, this study notes that different people look for different types of reviews. Hence, there is a need for developing a system that that is able to sort reviews differently for each user based on the ratings they previously assigned to other reviews. Using a design science approach, we address the above need by developing a recommender system that is able to predict the perceptions of each user regarding helpfulness of a specific review. In addition to addressing the sorting problem, this study also develops models that extract objective information from the text of online reviews including utilitarian cues, hedonic cues, product quality, service quality, price, and product comparison. Each of these characteristics may also be used for sorting and filtering online reviews