bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling and Optimization of Heterogeneous Vehicle Routing Problem in Emergency Resource Distribution after Disaster
Authors: Zhou Haibin 
Published: September 2019

Abstract
In recent years, natural disasters have occurred frequently around the world. There are many kinds of disasters in China, which are diversified in form and widely distributed. How to reduce the damage caused by disasters to humans is one of our urgent tasks. Firstly, a heterogeneous vehicle routing optimization model is constructed, and a genetic algorithm is designed to solve the model. Secondly, the optimal path of heterogeneous vehicle resource transportation is solved by using examples to verify the effectiveness of the model and algorithm. Finally, this paper puts forward the prospect of research on the problem of heterogeneous vehicle routing for emergency resource transportation after disasters.
Monthly Runoff Prediction Using Wavelet Transform and Fast Resource Optimization Network (Fron) Algorithm
Authors: Lu Jiahai , Li Aiyun 
Published: September 2019

Abstract
In this study, Discrete Wavelet Transform (DWT) and a Fast Resource Optimization Network (FRON) Algorithm were integrated to forecast monthly runoff and improve the accuracy of forecasting models. The original monthly runoff sequence is reconstructed by DWT processing into two components of deterministic and stochastic components, then these two components were inputted into two different FRON model respectively, and finally the prediction results of the two models were summed up as the final forecasts of monthly runoff. The WFRON1 model is compared with the WFRON2 model and the FRON model without discrete wavelet transform. The mean absolute error (MAE), the deterministic coefficient (DC) and the correlation coefficient (R) are used as the model evaluation index. The model is applied to the prediction of monthly runoff at the Pantuo hydrological station in Shangyuan River. The results show that: The evaluation index of WFRON2 model is better than WFRON1, and both models predict the effect better than FRON model.
A Study on the Development of Small Tourist Towns under the “Internet Plus” Background
Authors: Lin Qian , Wei Wei 
Published: September 2019

Abstract
With the development of the times, people’s pursuit of personalized and unique tourism has also spawned the product of a small tourist town. The combination of the Internet and the small tourist towns is a collision of the new era, the tourism industry is actively seeking market positioning, and reshaping the competitive advantage and realizing the transformation and development in the Internet era. The article mainly studies the current situation and countermeasures of the development of small tourist towns under the background of “Internet Plus”. Firstly, it introduces the status quo of the construction of small tourist towns, and then analyses the main problems in the development of the small tourist towns, and from the “Internet Plus” perspective of these problems, the corresponding solutions are proposed. It found that the Internet would become the main driving force and support for the innovation and development of tourism.
The Smart Elderly Care Service in China in the Age of Big Data
Authors: Zhou Guangtao 
Published: September 2019

Abstract
China is just experiencing a period of population aging accelerating. With the approaching of an aging society, elderly care becomes increasingly challenging; however, a variety of disadvantages has been exposed gradually, including unsatisfactory health care, unstable daily care, insufficient emotional comfort, no timely emergency aids, and so forth. The traditional elderly care model has already impeded, to a large extent, the sustainable development of elderly care. As the rapid development and wide application of big data, smart elderly care comes into being, which shows various advantages while comparing with traditional elderly care services. The Chinese government has the responsibility to implement the smart elderly service in its initial stage of development.
High-speed Railway Fastener Detection Using Minima Significant Region and Local Binary Patterns
Authors: Fan Hong , Xiong Ying , Fei Yaodong 
Published: September 2019

Abstract
Railway fastener is an important part of the railway system. Keeping the fasteners effective is essential to ensure the safe operation of the railway, so abnormal railway fastener detection is a main task of railway maintenance. With the development of railway system, the traditional manual fastener detection method has been unable to meet the application requirements, because it is very slow, costly, and dangerous. In this paper, we propose a novel method for abnormal fastener detection based on computer vision, which can detect missing fasteners automatically. In this method, Minima Significant Region is extracted in order to improve the fastener localization accuracy. Then, fastener recognition is operated using local binary features and Support Vector Machine classifier based on the fastener sub-images which are obtained by fastener localization. The proposed method is evaluated in our own database which is obtained by railway inspection system in different environments. The experimental results have shown improved performance against the state-of-the-art algorithm.
The Research on Application of Virtual Reality Technology in Museums
Authors: Wang Bo , Liu Yue 
Published: September 2019

Abstract
The advantages of virtual reality technology become more and more obvious since the VR comes out. Il is also widely used in different social fields, such as the field of architectural design, aerospace, entertainment and so on. As well, in the field of museums, the VR technology also shows it specific advantages and is widely applied. The article mainly analyzes and studies the application of VR virtual reality technology in museums, and proposes the strategies to improve the application of VR technology used in museums.
Short-term Power Prediction of Wind Farm Power Based on BP Neural Network
Authors: Ren Yaming 
Published: September 2019

Abstract
With the proportion of wind power in the power systems increasing, consideration must be given to the fact that the randomness and volatility of wind power output will inevitably affect the stable operation of power grid. One of the effective ways to solve this problem is to forecast the output of wind power. In this paper, we employ the method of BP neural network to predict the wind power output in a period of time. To discuss the predictive performance of BP neural networks, we set different number of input variables to observe the prediction effect of BP neural network. We find that it’s not that the more input information, the better the prediction effect. The data with strong correlation can be used as input to achieve better results.
Extension Method in Case-Based Reasoning and its Application in Artillery System Design
Authors: Zhao Shubin , Xu Cheng 
Published: September 2019

Abstract
Case-Based Reasoning (CBR) is a method of designing new product configurations based on previous design case matching. Over the last couple of decades, CBR has grown from a relatively isolated research area to a comprehensive and multi-field one. Extenics is one of fields combined with it. The representation model and extension distance theory in Extenics are surveyed. Based on dependence function, an improved comprehensive evaluation of configuration schemes of a complex modularized product is proposed, considering the interface matching problem that may occur between different components. To illustrate the validity and feasibility of our method, a design case of artillery system is described. The result shows that our evaluation method can better adapt to engineering practice and provide effective and reasonable matching results.
Research on WeChat Attendance Technology Based on Geographical Location and iBeacon
Authors: Zhao Jiangsheng , Huang Xi , Wang Beizhan , Xu Zhibin 
Published: September 2019

Abstract
In the society today there are many occasions that involve attendance or sign-ins, and applications and technologies are emerging one after another. This paper focuses on the geographical location-based and iBeacon-based micro-attendance technology, and gives a concrete implementation of the two. This paper also improves the micro-attendance technology based on iBeacon. While using iBeacon positioning service, we overcome the shortcomings of “Shake” attendance and greatly optimize the user experience.
Prediction of Spontaneous Combustion Tendency Grade of Sulfide Ore Based on Decision Tree Combined Classifier
Authors: Liu Nianping , Huang Siqi , Xie Xiaojun 
Published: September 2019

Abstract
Based on the related theories of decision tree and its classifier, a decision tree combiner model for spontaneous combustion of sulfide ores was established. Based on the analysis of the influencing factors of spontaneous combustion of sulfide ore, the three most representative measured characteristics, such as oxidation rate, self-hot spot, and auto-ignition point, were selected as predictors of the decision tree classifier model. Using the actual measured data of spontaneous combustion of sulfide ore as a training sample, a decision tree model for establishing spontaneous combustion of sulfide ores was used to predict the spontaneous combustion tendency grades, and verified with other measured data that did not participate in training. The results show that the decision tree combined classifier model is simple and feasible, with high prediction accuracy and simplified data processing. It is one of the effective methods to solve the problem of predicting the spontaneous combustion grade of sulfide ore.
Genetic algorithm approach for large scale quadratic programming of probabilistic supplier selection and inventory management problem
Authors: Sutrisno  , Widowati  , Sunarsih  
Published: September 2019

Abstract
This paper is focused on the effectiveness of existing metaheuristic optimization method, genetic algorithm (GA), in providing solutions to a large-scale integer quadratic programming of a probabilistic supplier selection and inventory management problem. The term “probabilistic” in this case refers to any problem that involves some uncertain parameters, approached by random variables (probabilistic parameter). We used the existing mathematical model of probabilistic supplier selection problem and inventory management provided in our previous works. This was done for optimization problem in a small-scale, which could be solved efficiently either by analytical or numerical method. We resolved this model with an extensive number of decision variable, indicated by the number of supplier and time period sufficient to use GA, conducted to analyse if the solution of decision variable, is reliable or not for application to the larger problem. We generated some random data to simulate the problem and the results, running over hundreds of computational experiments. The results showed that the decision obtained by the genetic algorithm was significantly different from the global optimal solution generated by the generalized reduced gradient (GRG) performed in LINGO 18.0. In conclusion, GA is not preferred in solving large-scale problems as regards supplier selection and inventory management.
The adsorption kinetics and isoterm of activated carbon from Water Hyacinth Leaves (Eichhornia crassipes) on Co(II)
Authors: Riyanto C A , Prabalaras E 
Published: September 2019

Abstract
Heavy metal waste can endanger human health and can accumulate in rivers or land. Heavy metals such as Co(II) can be removed or minimized using adsorbents such as activated carbon. The use of activated carbon from water hyacinth leaves (Eichhornia crassipes) has the potential to reduce the concentration of heavy metals in the environment as water hyacinth leaves (WHL) have the ability to adsorp both organic and inorganic compounds. This study aims to determine the appropriate adsorption kinetics and isotherm models in the process of Co(II) adsorption using activated carbon from water hyacinth leaves (ACWHL). The ACWHL can be produced from the carbonization process at 400°C for an hour and two-stage activation process (physical and chemical activation) with 30% H3PO4 as an activator and the impregnation ratio of 1:4 (w/w) for 24 hours and then activated at 600°C for 60 minutes. The analytical method used in this study was using a UV-Vis spectrophotometer. The results of the study showed that the ability of ACWHL to adsorp Co(II) followed the pseudo second-order kinetic model with R2 = 0.3086 and the Elovich isotherm with R2 = 0.664 with a maximum adsorption capacity of 140.725 mg/g. Fulfillment of this model can be assumed if the adsorption process of Co(II) on the surface of ACWHL occurs in multilayer.
Adsorption of cadmium using teak leaves powder (Tectona grandis sp.): embedding Mahaffy’s tetrahedral concept in undergraduate chemical engineering capstone lab project
Authors: Muryanto S , Firyanto R , Nurkholik  
Published: September 2019

Abstract
Chemical engineering education can be aptly structured on four central components: macroscopic, particulate, symbolic, and human element domains; known as the Mahaffy’s tetrahedral concept. This paper discusses the application of the concept of undergraduate chemical engineering capstone projects. The capstone was carried out as an undergraduate final laboratory project to investigate the adsorption of heavy metal, namely cadmium (Cd), using powder of teak leaves (Tectona grandis sp.). The lab experiment was environmentally safe, completed at ambient temperatures and that the experimental data collection was easy. It was actively guided by lecturers in a way to encourage meaningful lab experience as proposed in the Mahaffy’s tetrahedral idea. Three experimental variables were investigated: initial pH solution, adsorbent dosage, and initial concentration of Cd. The results were analyzed to determine the diffusion mechanism and kinetics through Weber-and-Morris intra-particle diffusion model. The experimental results agreed with most published literature which gave satisfaction on both students and lecturers. To assess learning outcomes, pre- and post-evaluations in regard the Mahaffy’s tetrahedral idea was employed. The post-test scores were significantly higher than those of the pre-test indicating that the learning outcomes were achieved. The lab project was also found to increase the student’s writing and presentation skills.
The effect of project based learning on learning environment and learning outcomes in vocational high school students
Authors: Rismawati  , Sunarno W , Sarwanto  
Published: September 2019

Abstract
The aimed of this study was to determine the effect of Project Based Learning Models on students’ learning environment and learning outcome in vocational High School. Samples were taken using cluster random sampling technique. This study used quasi-experimental method and involving a population of 142 students in the first year in automotive class from one of State Vocational High School in Surakarta. The sample was taken using cluster random sampling. Automotive class A with 36 students was used as the experimental class and automotive class B with 35 students as the control class. Data was collected using questionnaire, interview and test in the topic of rectilinear motion and circular motion. Data were analysed using descriptive and inferential analysis techniques using ANOVA. The results of this study showed that there was significant effect of project based learning model on students’ learning environment and outcomes. The project-based learning and learning environment has an interaction to determine the students learning outcome. Students tend to have better learning outcomes in good learning environment. Project-based learning successfully increases the learning environment significantly on indicators teacher-student relationships and Student-student relationships.
The Wayfinding Technology Application Dependability and its influential factors on Millennials
Authors: Jalil Emy Ezura A. , Ee Lim Kiong , Loo Wong Wai , Phok Yang Boon 
Published: September 2019

Abstract
The use of navigational applications is getting famous among riders. With the development of the internet, routes information is easily at the fingertips. From a fundamental perspective, routing could not be completed without navigational applications. The performance of navigational applications can be considered as one of the determinants that influence dependability on navigational applications. This paper presents the factors that influence the dependability of technology application in way-finding. In this study, three factors influence the dependability of navigational applications in way-finding which consists of social influence; accurateness and system reliability have been adopted. Using a quantitative approach via online survey design; about with 406 usable data derived from the population sample and they were identified to be dependent on navigational apps in their wayfinding needs. As a result, the findings indicated that all of the independent variables such as social influence, accurateness and system reliability have a significant relationship with dependability on navigational applications.
Kinetics Modelling of Batch Anaerobic Co-digestion of Domestic Primary Sewage Sludge and Food Waste in a Stirred Reactor
Authors: Mariam Sulaiman Siti , Seswoya Roslinda 
Published: September 2019

Abstract
Anaerobic digestion was conventionally applied for treating sewage sludge. However, the accumulation of solid waste particularly food waste has reach the critical levels worldwide. In practice, the food waste was dumped into the landfill for ultimate disposal. However, the greenhouse gases produced in the landfill makes this is no longer a preferable option. Anaerobic digestion was seen as an alternative for managing the food waste in a sustainable way. Methane, a renewable energy is potentially in replacing fossil fuel. However, the methane yield from the digestion of food waste inefficient. Therefore, a study of the co-digestion of sewage sludge and food waste was conducted to investigate the improvement of the methane yield. This study was conducted by using a mixture of domestic primary sewage sludge and food waste as a co-substrate for the anaerobic digester. The kinetics modified Gompertz modelling was applied to describe the anaerobic digestion process. A series of batch biochemical methane potential (BMP) assay was prepared using Automatic Methane Potential Test System (AMPTS II) to investigate the anaerobic digestibility of the mixture of domestic primary sewage sludge and food waste. The BMP assay showed that the co-digestion improved the ultimate methane yield by 32.6% higher than domestic primary sewage sludge alone, indicated that the co-substrate characteristics influencing the methane yield. Besides that, the greater VS/TS ratio of the substrate also resulted in the greater methane yield. The kinetics parameter from the modelling analysis were slightly lower as compared to the laboratory data.
Assessment of Cause and Effect Factors of Poor Communication in Construction Industry
Authors: Abdul Rahman Ismail , Gamil Yaser 
Published: September 2019

Abstract
Effective communication in construction industry is a core competency element to the success of the project. But it has been always a challenging mission to perform the communication effectively because the industry itself is characterized as fragmented, dynamic, and comprises of many parties (client, consultant, contractor, authorities) which leads to the presence of poor communication. There has been no publication to address the poor communication in a broad context especially identifying and assessing the causative factors and effects to this issue in the construction industry. However, this article aimed to identify and assess the significance of these factors through ranked them individually based on its level of significance/severity. Quantitative approach was adopted to conduct this study using structured questionnaire survey. A 5-point Likert’s type scale was used to assess the factors gradually based on their significance. Descriptive analysis was used to analyse the data collected from the survey. Average index (AI) and standard deviation were used to rank the importance of the factors in descending order. The study found that, the most dominant cause factors of poor communication is fear to communicate in the project space however the most dominant effect factor is high stress in workplace. The findings of this study serve best to draw a platform for construction practitioners to introduce strategies and plans to avoid the cause and diminish the effect of poor communication in construction industry.
Strategizing contractor firms to deliver green construction projects: conceptual framework
Authors: Powmya Ayisha , Zainul Abidin Nazirah , Sakina Mokhtar Azizi Nurul 
Published: September 2019

Abstract
Delivering green construction (GC) projects is not an easy task for inefficient or inexperienced contractor due to added requirements. This paper conceptualizes firm strategies in delivering green projects by focusing on enhancing firm resources. Journal articles with keywords such as ‘green construction’, ‘green project’, ‘sustainable construction’, ‘resources and capabilities’, ‘contractor strategies’, and so forth in the title, abstract or keywords of the publications were reviewed. Articles published from 2000 to 2018 in Scopus database were selected. The current literature on firm resources mainly focused on four assets (personal, financial, technological and organizational) and four capabilities (technical, innovative, managerial competency and collaborative). These assets and capabilities are necessary for contractor firms to survive in the industry. Capitalizing on these resources, this paper proposes seven strategies: human resource strategy, innovation strategy, financial strategy, smart collaboration strategy, environmental pro-activeness strategy, management enhancement strategy and information and communication strategy, for contractor to effectively deliver green project. Using Resource Based View (RBV) and Resource Mobilisation Theory (RMT), a conceptual framework is produced connecting firm resources and Resource Mobilisation Strategies (RMS). This paper shall benefit contractors and academician as it extended the knowledge on firms’ resources and recommend ways to strategize green delivery.
Experimental study on the out-of-plane strengthening of unreinforced masonry walls using cement-based fiber composites
Authors: Altoubat Salah , Maalej Mohamed , Leblouba Moussa , Saboor Karzad Abdul 
Published: September 2019

Abstract
This paper presents results from an ongoing research that is intended to study the behavior of URM walls for out-of-plane action. The effect of fiber reinforced shotcrete (FRS) as a strengthening method for the URM walls is examined. Eight URM walls were built inside a precast reinforced concrete boundary frame and strengthened with cement-based shotcrete mixes reinforced with different types of fibers. The masonry wall is 1.2x 1.2 m, and the masonry units were hollow concrete blocks (10 x 20 x 40 cm). Conventional fiber reinforced concrete (FRC) and engineered cementitious composite (ECC) were used as the strengthening layers sprayed on the surface of masonry walls. Control walls with plain shotcrete and conventional plastering mortar were also examined. Synthetic macro-fibers at dosage rate of 6 kg/m3 in FRC mix and Polyethylene micro-fibers at a dosage rate of 16 kg/m3 in ECC mix were considered in this study. The walls were placed in a carefully designed set up and tested under static central load using a hydraulic actuator with a capacity of 500 kN. The parameters recorded during testing were the applied load and out-of-plane displacement of the walls. Cracking pattern and failure modes were also monitored. The reported test results demonstrate that FRC and ECC mixes can significantly increase the out of plane strength and ductility of the URM walls.