Search results for: time history analysis.

Authors: Jung-Lo Park, Sung-Sik Kim, Sun-Young Choi, Ju-Hyung Kim, Jae-Jun Kim

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Sub-prime mortgage crisis which began in the US is regarded as the most economic crisis since the Great Depression in the early 20th century. Especially, hidden problems on efficient operation of a business were disclosed at a time and many financial institutions went bankrupt and filed for court receivership. The collapses of physical market lead to bankruptcy of manufacturing and construction businesses. This study is to analyze dynamic efficiency of construction businesses during the five years at the turn of the global financial crisis. By discovering the trend and stability of efficiency of a construction business, this study-s objective is to improve management efficiency of a construction business in the ever-changing construction market. Variables were selected by analyzing corporate information on top 20 construction businesses in Korea and analyzed for static efficiency in 2008 and dynamic efficiency between 2006 and 2010. Unlike other studies, this study succeeded in deducing efficiency trend and stability of a construction business for five years by using the DEA/Window model. Using the analysis result, efficient and inefficient companies could be figured out. In addition, relative efficiency among DMU was measured by comparing the relationship between input and output variables of construction businesses. This study can be used as a literature to improve management efficiency for companies with low efficiency based on efficiency analysis of construction businesses.

Keywords: Construction Company, DEA, DEA/Window, Efficiency Analysis

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Authors: Zarita Zainuddin, Ong Pauline, C. Ardil

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Diabetes Mellitus is a chronic metabolic disorder, where the improper management of the blood glucose level in the diabetic patients will lead to the risk of heart attack, kidney disease and renal failure. This paper attempts to enhance the diagnostic accuracy of the advancing blood glucose levels of the diabetic patients, by combining principal component analysis and wavelet neural network. The proposed system makes separate blood glucose prediction in the morning, afternoon, evening and night intervals, using dataset from one patient covering a period of 77 days. Comparisons of the diagnostic accuracy with other neural network models, which use the same dataset are made. The comparison results showed overall improved accuracy, which indicates the effectiveness of this proposed system.

Keywords: Diabetes Mellitus, principal component analysis, time-series, wavelet neural network.

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Authors: Jacqueline R. T. Alipo-on, Francesca I. F. Escobar, Myles J. T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases which are considered as one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis on the ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heart beat types. The dataset used in this work is the synthetic MIT-Beth Israel Hospital (MIT-BIH) Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: Heartbeat classification, convolutional neural network, electrocardiogram signals, ECG signals, generative adversarial networks, long short-term memory, LSTM, ResNet-50.

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Authors: J. R. Wang, H. C. Chen, C. Shih, S. W. Chen, J. H. Yang, Y. Chiang

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In this study, we focus on the establishment of the analysis model for Maanshan PWR nuclear power plant (NPP) by using RADTRAD and SNAP codes with the FSAR, manuals, and other data. In order to evaluate the cumulative dose at the Exclusion Area Boundary (EAB) and Low Population Zone (LPZ) outer boundary, Maanshan NPP RADTRAD/SNAP model was used to perform the analysis of the DBA LOCA case. The analysis results of RADTRAD were similar to FSAR data. These analysis results were lower than the failure criteria of 10 CFR 100.11 (a total radiation dose to the whole body, 250 mSv; a total radiation dose to the thyroid from iodine exposure, 3000 mSv).

Keywords: RADionuclide, transport, removal, and dose estimation, RADTRAD, symbolic nuclear analysis package, SNAP, dose, PWR.

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Authors: Jungho Moon, Lae-Jeong Park

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This paper introduces a signal monitoring program developed with a view to helping electrical engineering students get familiar with sensors with digital output. Because the output of digital sensors cannot be simply monitored by a measuring instrument such as an oscilloscope, students tend to have a hard time dealing with digital sensors. The monitoring program runs on a PC and communicates with an MCU that reads the output of digital sensors via an asynchronous communication interface. Receiving the sensor data from the MCU, the monitoring program shows time and/or frequency domain plots of the data in real time. In addition, the monitoring program provides a serial terminal that enables the user to exchange text information with the MCU while the received data is plotted. The user can easily observe the output of digital sensors and configure the digital sensors in real time, which helps students who do not have enough experiences with digital sensors. Though the monitoring program was programmed in the Matlab programming language, it runs without the Matlab since it was compiled as a standalone executable.

Keywords: Digital sensor, MATLAB, MCU, signal monitoring program.

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Authors: Chanin Yoopetch, Natcha Toemtemsab

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The purpose of this study was to explore the demographic differences of international tourists according to three main factors, including the value of time, shopping behavior and shopping motivation. The Chatuchak Weekend Market is known as one of the biggest weekend markets in the world. Too little academic studies had been conducted in this area of weekend market, despite its growth and continuous development. In general, both domestic visitors and international tourists are attracted to the perception of cheap and bargaining prices the weekend market. However, systematic research study can provide reliable understanding of the perception of the visitors. This study focused on the group of international tourists who visited the market and aimed to provide better insights based on the differences in their demographic factors. Findings indicated that several differences in value of time, shopping behavior, and shopping motivation were identified by gender, income and age. Research implications and directions for further studies were discussed.

Keywords: Value of Time, Shopping Behavior, Shopping Motivation, Chatuchak Weekend Market.

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Authors: Tawakal Hasnain Baluch, Adnan Masood, Javaid Iqbal, Umer Izhar, Umar Shahbaz Khan

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This paper will provide the kinematic and dynamic analysis of a lower limb exoskeleton. The forward and inverse kinematics of proposed exoskeleton is performed using Denevit and Hartenberg method. The torques required for the actuators will be calculated using Lagrangian formulation technique. This research can be used to design the control of the proposed exoskeleton.

Keywords: Dynamic Analysis, Exoskeleton, Kinematic Analysis, Lower Limb, Rehabilitation Robotics

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Authors: Gitanjali Devi, Kandarpa Kumar Sarma, Pranayee Datta, Anjana Kakoti Mahanta

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Cosmic showers, from their places of origin in space, after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of EAS and similar High Energy Particle Showers involve a plethora of experimental setups with certain constraints for which soft-computational tools like Artificial Neural Network (ANN)s can be adopted. The optimality of ANN classifiers can be enhanced further by the use of Multiple Classifier System (MCS) and certain data - dimension reduction techniques. This work describes the performance of certain data dimension reduction techniques like Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Self Organizing Map (SOM) approximators for application with an MCS formed using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN). The data inputs are obtained from an array of detectors placed in a circular arrangement resembling a practical detector grid which have a higher dimension and greater correlation among themselves. The PCA, ICA and SOM blocks reduce the correlation and generate a form suitable for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.

Keywords: EAS, Shower, Core, ANN, Location.

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

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Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: Microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks.

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Authors: Matheus Müller, Delma Vidal

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The present paper aims to expose two techniques of dewatering for sludge, analyzing its operations and dewatering processes, aiming at improving the conditions of disposal of residues with high liquid content. It describes the field tests performed on two geotextile systems, a closed geotextile tube and an open geotextile drying bed, both of which are submitted to two filling cycles. The sludge used in the filling cycles for the field trials is from the water treatment plant of the Technological Center of Aeronautics – CTA, in São José dos Campos, Brazil. Data about volume and height abatement due to the dewatering and consolidation were collected per time, until it was observed constancy. With the laboratory analysis of the sludge allied to the data collected in the field, it was possible to perform a critical comparative study between the observed and the scientific literature, in this way, this paper expresses the data obtained and compares them with the bibliography. The tests were carried out on three fronts: field tests, including the filling cycles of the systems with the sludge from CTA, taking measurements of filling time per cycle and maximum filling height per cycle, heights against the abatement by dewatering of the systems over time; tests carried out in the laboratory, including the characterization of the sludge and removal of material samples from the systems to ascertain the solids content within the systems per time and; comparing the data obtained in the field and laboratory tests with the scientific literature. Through the study, it was possible to perceive that the process of densification of the material inside a closed system, such as the geotextile tube, occurs faster than the observed in the drying bed system. This process of accelerated densification can be brought about by the pumping pressure of the sludge in its filling and by the confinement of the residue through the permeable geotextile membrane (allowing water to pass through), accelerating the process of densification and dewatering by its own weight after the filling with sludge.

Keywords: Consolidation, dewatering, geotextile drying bed, geotextile tube.

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Authors: Luísa P. Cruz-Lopes, Hugo Costa e Silva, Idalina Domingos, José Ferreira, Luís Teixeira de Lemos, Bruno Esteves

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The liquefaction process of cork based tree barks has led to an increase of interest due to its potential innovation in the lumber and wood industries. In this particular study the bark of Quercus cerris (Turkish oak) is used due to its appreciable amount of cork tissue, although of inferior quality when compared to the cork provided by other Quercus trees. This study aims to optimize alkaline catalysis liquefaction conditions, regarding several parameters. To better comprehend the possible chemical characteristics of the bark of Quercus cerris, a complete chemical analysis was performed. The liquefaction process was performed in a double-jacket reactor heated with oil, using glycerol and a mixture of glycerol/ethylene glycol as solvents, potassium hydroxide as a catalyst, and varying the temperature, liquefaction time and granulometry. Due to low liquefaction efficiency resulting from the first experimental procedures a study was made regarding different washing techniques after the filtration process using methanol and methanol/water. The chemical analysis stated that the bark of Quercus cerris is mostly composed by suberin (ca. 30%) and lignin (ca. 24%) as well as insolvent hemicelluloses in hot water (ca. 23%). On the liquefaction stage, the results that led to higher yields were: using a mixture of methanol/ethylene glycol as reagents and a time and temperature of 120 minutes and 200 ºC, respectively. It is concluded that using a granulometry of <80 mesh leads to better results, even if this parameter barely influences the liquefaction efficiency. Regarding the filtration stage, washing the residue with methanol and then distilled water leads to a considerable increase on final liquefaction percentages, which proves that this procedure is effective at liquefying suberin content and lignocellulose fraction.

Keywords: Liquefaction, alkaline catalysis, optimization, Quercus cerris bark.

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Authors: Zarabizan Zakaria, Syuhaida Ismail, Aminah Md. Yusof

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Delay can be defined as time overrun or extension of time to complete the project. There are high possibilities that delay issues in final account closing cannot be avoided especially in construction project in Malaysia which is unique and dynamic in the terms of nature of design and technical skill. Delay in final account closing is a situation when the actual planning (time and budget allocation) of a construction project exceeds the planned schedule or on the other hand, final account closing exceeds the time and other provisions specified in the contract. The causes of delay discussed in this paper are appraised from the literature review. There are two main types of delay: excusable delay and non-excusable delay. The literature reviews on the delay in final account closing which is then translated into a theoretical framework are summarized in the context of construction players and academician perspective. It is anticipated that the finding reported in this paper could assist the planning of future strategies and guidelines of final account closing for the betterment of construction projects in Malaysia.

Keywords: Construction industry, construction contract, final account closing, delay.

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Authors: Ali W. Alattabi, Khalid S. Hashim, Hassnen M. Jafer, Ali Alzeyadi

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This study was performed to optimise the react time (RT) and study its effects on the removal rates of nitrogen compounds in a sequencing batch reactor (SBR) treating synthetic industrial wastewater. The results showed that increasing the RT from 4 h to 10, 16 and 22 h significantly improved the nitrogen compounds’ removal efficiency, it was increased from 69.5% to 95%, 75.7 to 97% and from 54.2 to 80.1% for NH₃-N, NO₃-N and NO₂-N respectively. The results obtained from this study showed that the RT of 22 h was the optimum for nitrogen compounds removal efficiency.

Keywords: Ammonia-nitrogen, retention time, nitrate, nitrite, sequencing batch reactor, sludge characteristics.

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Authors: Satadal Das, Parthasarathi Sengupta

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With millions of livestock wealth in India including cattle, and buffaloes, the National Animal Disease Control Program targeted a massive Brucella vaccination program. As a part of it in the state of West Bengal Veterinary healthcare assistants participated in the program in 2021. The aim of this study was to elucidate the burden of brucellosis in those healthcare assistants and to pinpoint the main causes of such infection. We contacted the healthcare assistants to find out whether they were infected during the vaccination program. Our findings indicated many Veterinary healthcare assistants who participated in the program developed symptoms and signs suggestive of brucellosis. Laboratory tests indicated many confirmed Brucellosis cases. However, this may not include many asymptomatic cases. Detailed analysis revealed that in most of them there was a history of needle prick injury about a month back during the vaccination program, which was mainly due to ferocious or disturbed animals. Few also complained that they were not properly trained or proper personal protective types of equipment were not provided. All of them were treated in referral hospitals following a standard protocol of the Government Health Department and now they are followed up. Thus we conclude that proper care during the vaccination of animals should be followed, prophylactic treatment for needle prick injuries should be given, and training and supply of personal protective equipment should be monitored.

Keywords: Occupational brucellosis, needle prick injury, brucella vaccination, personal protective equipment.

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Authors: Thaniya Kaosol, Narumol Sohgrathok

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In this research, an anaerobic co-digestion using decanter cake from palm oil mill industry to improve the biogas production from frozen seafood wastewater is studied using Continuously Stirred Tank Reactor (CSTR) process. The experiments were conducted in laboratory-scale. The suitable Hydraulic Retention Time (HRT) was observed in CSTR experiments with 24 hours of mixing time using the mechanical mixer. The HRT of CSTR process impacts on the efficiency of biogas production. The best performance for biogas production using CSTR process was the anaerobic codigestion for 20 days of HRT with the maximum methane production rate of 1.86 l/d and the average maximum methane production of 64.6%. The result can be concluded that the decanter cake can improve biogas productivity of frozen seafood wastewater.

Keywords: anaerobic co-digestion, frozen seafood wastewater, decanter cake, biogas, hydraulic retention time

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Authors: Hemant I. Joshi, Vivek J. Pandya

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This paper discusses the simulation and experimental work of small Smart Grid containing ten consumers. Smart Grid is characterized by a two-way flow of real-time information and energy. RTP (Real Time Pricing) based tariff is implemented in this work to reduce peak demand, PAR (peak to average ratio) and cost of energy consumed. In the experimental work described here, working of Smart Plug, HEC (Home Energy Controller), HAN (Home Area Network) and communication link between consumers and utility server are explained. Algorithms for Smart Plug, HEC, and utility server are presented and explained in this work. After receiving the Real Time Price for different time slots of the day, HEC interacts automatically by running an algorithm which is based on Linear Programming Problem (LPP) method to find the optimal energy consumption schedule. Algorithm made for utility server can handle more than one off-peak time period during the day. Simulation and experimental work are carried out for different cases. At the end of this work, comparison between simulation results and experimental results are presented to show the effectiveness of the minimization method adopted.

Keywords: Smart Grid, Real Time Pricing, Peak to Average Ratio, Home Area Network, Home Energy Controller, Smart Plug, Utility Server, Linear Programming Problem.

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Authors: Liu Yi, Bao Liyong

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Aiming at the problem of low efficiency of pipelined scheduling in periodic query-qualified service, this paper proposes a system service resource scheduling strategy with parallel optimized qualified service polling control. The paper constructs the polling queuing system and its mathematical model; firstly, the first-order and second-order characteristic parameter equations are obtained by partial derivation of the probability mother function of the system state variables, and the complete mathematical, analytical expressions of each system parameter are deduced after the joint solution. The simulation experimental results are consistent with the theoretical calculated values. The system performance analysis shows that the average captain and average period of the system have been greatly improved, which can better adapt to the service demand of delay-sensitive data in the dense data environment.

Keywords: Polling, parallel scheduling, mean queue length, average cycle time.

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Authors: Letizia Marchetti, Federica Annunzi, Federico Fiorini, Cristiano Nicolella

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Automotive shredder residue (ASR) is a mixture of waste that makes up 20-25% of end-of-life vehicles. For many years, ASR was commonly disposed of in landfills or incinerated, causing serious environmental problems. Nowadays, thermochemical treatments are a promising alternative, although the heterogeneity of ASR still poses some challenges. One of the emerging thermochemical treatments for ASR is pyrolysis, which promotes the decomposition of long polymeric chains by providing heat in the absence of an oxidizing agent. In this way, pyrolysis promotes the conversion of ASR into solid, liquid, and gaseous phases. This work aims to improve the performance of a two-step pyrolysis process. After the characterization of the analysed ASR, the focus is on determining the effects of residence time on product yields and gas composition. A batch experimental setup that reproduces the entire process was used. The setup consists of three sections: the pyrolysis section (made of two reactors), the separation section, and the analysis section. Two different residence times were investigated to find suitable conditions for the first sample of ASR. These first tests showed that the products obtained were more sensitive to residence time in the second reactor. Indeed, slightly increasing residence time in the second reactor managed to raise the yield of gas and carbon residue and decrease the yield of liquid fraction. Then, to test the versatility of the setup, the same conditions were applied to a different sample of ASR coming from a different chemical plant. The comparison between the two ASR samples shows that similar product yields and compositions are obtained using the same setup.

Keywords: Automotive shredder residue, experimental tests, heterogeneity, product yields, two-step pyrolysis.

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Authors: Dong-Eun Lee

Abstract:

To calculate the temperature distribution of the slab in a hot rolled reheating furnace a mathematical model has been developed by considering the thermal radiation in the furnace and transient conduction in the slab. The furnace is modeled as radiating medium with spatially varying temperature. Radiative heat flux within the furnace including the effect of furnace walls, combustion gases, skid beams and buttons is calculated using the FVM and is applied as the boundary condition of the transient conduction equation of the slab. After determining the slab emissivity by comparison between simulation and experimental work, variation of heating characteristics in the slab is investigated in the case of changing furnace temperature with various time and the slab residence time is optimized with this evaluation.

Keywords: Reheating Furnace, Thermal Radiation, ResidenceTime, FVM for Radiation

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Authors: Kisik Song, Sungjoo Lee

Abstract:

Recent years have seen an increasing number of patent disputes due to excessive competition in the global market and a reduced technology life-cycle; this has increased the risk of investment in technology development. While many global companies have started developing a methodology to identify promising technologies and assess for decisions, the existing methodology still has some limitations. Post hoc assessments of the new technology are not being performed, especially to determine whether the suggested technologies turned out to be promising. For example, in existing quantitative patent analysis, a patent’s citation information has served as an important metric for quality assessment, but this analysis cannot be applied to recently registered patents because such information accumulates over time. Therefore, we propose a new technology assessment model that can replace citation information and positively affect technological development based on post hoc analysis of the patents for promising technologies. Additionally, we collect customer reviews on a target technology to extract keywords that show the customers’ needs, and we determine how many keywords are covered in the new technology. Finally, we construct a portfolio (based on a technology assessment from patent information) and a customer-based marketability assessment (based on review data), and we use them to visualize the characteristics of the new technologies.

Keywords: Technology assessment, patents, citation information, opinion mining.

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Authors: Kejun Zhuang, Zhaohui Wen

Abstract:

The main purpose of this paper is to investigate a discrete time three–species food chain system with ratio dependence. By employing coincidence degree theory and analysis techniques, sufficient conditions for existence of periodic solutions are established.

Keywords: Food chain, ratio–dependent, coincidence degree, periodic solutions.

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Authors: Wang Xu, Yao Yangyang, Lin Ying, Wang Zhenzhen

Abstract:

Intelligent Transportation System integrates various modern advanced technologies into the ground transportation system, and it will be the goal of urban transport system in the future because of its comprehensive effects. However, it also brings some problems, such as project performance assessment, fairness of benefiting groups, fund management, which are directly related to its operation and implementation. Wuhan has difficulties in organizing transportation because of its nature feature (river and lake), therefore, calling Service of Taxi plays an important role in transportation. This paper researches on calling Service of Taxi in Wuhan, based on quantitative and qualitative analysis. It analyzes its operations management systematically, including business model, finance, usage analysis and users evaluation. As for business model, it is that the government leads the operation at the initial stage, and the third part dominates the operation at the mature stage, which not only eases the pressure of the third part and benefits the spread of the calling service at the initial stage, but also alleviates financial pressure of government and improve the efficiency of the operation at the mature stage. As for finance, it draws that this service will bring heavy financial burden of equipments, but it will be alleviated in the future because of its spread. As for usage analysis, through data comparison, this service can bring some benefits for taxi drivers, and time and spatial distribution of usage have certain features. As for user evaluation, it analyzes using group and the reason why choosing it. At last, according to the analysis above, the paper puts forward the potentials, limitations, and future development strategies for it.

Keywords: Assessment, Calling service of taxi, Operations management, Strategies, Using groups.

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Authors: D. S. Fardhyanti, A. Damayanti

Abstract:

Coal tar is a liquid by-product of coal pyrolysis processes. This liquid oil mixture contains various kinds of useful compounds such as benzoic aromatic compounds and phenolic compounds. These compounds are widely used as raw material for insecticides, dyes, medicines, perfumes, coloring matters, and many others. The coal tar was collected by pyrolysis process of coal obtained from PT Kaltim Prima Coal and Arutmin-Kalimantan. The experiments typically occurred at the atmospheric pressure in a laboratory furnace at temperatures ranging from 300 to 550oC with a heating rate of 10oC/min and a holding time of 1 hour at the pyrolysis temperature. The Gas Chromatography-Mass Spectroscopy (GC-MS) was used to analyze the coal tar components. The obtained coal tar has the viscosity of 3.12 cp, the density of 2.78 g/cm3, the calorific value of 11,048.44 cal/g, and the molecular weight of 222.67. The analysis result showed that the coal tar contained more than 78 chemical compounds such as benzene, cresol, phenol, xylene, naphtalene, etc. The total phenolic compounds contained in coal tar are 33.25% (PT KPC) and 17.58% (Arutmin-Kalimantan). The total naphtalene compounds contained in coal tar is 14.15% (PT KPC) and 17.13% (Arutmin-Kalimantan).

Keywords: Coal tar, pyrolysis, gas chromatography-mass spectroscopy.

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Authors: Asok Adak, Debabrata Mazumder, Pratip Bandyopadhyay

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Anaerobic Digestion has become a promising technology for biological transformation of organic fraction of the municipal solid wastes (MSW). In order to represent the kinetic behavior of such biological process and thereby to design a reactor system, development of a mathematical model is essential. Addressing this issue, a simplistic mathematical model has been developed for anaerobic digestion of MSW in a continuous flow reactor unit under homogeneous steady state condition. Upon simulated hydrolysis, the kinetics of biomass growth and substrate utilization rate are assumed to follow first order reaction kinetics. Simulation of this model has been conducted by studying sensitivity of various process variables. The model was simulated using typical kinetic data of anaerobic digestion MSW and typical MSW characteristics of Kolkata. The hydraulic retention time (HRT) and solid retention time (SRT) time were mainly estimated by varying different model parameters like efficiency of reactor, influent substrate concentration and biomass concentration. Consequently, design table and charts have also been prepared for ready use in the actual plant operation.

Keywords: Anaerobic digestion, municipal solid waste (MSW), process design model, simulation study, hydraulic retention time(HRT), solid retention time (SRT).

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Authors: Seiyed Hamid Zareh, Atabak Sarrafan, Kambiz Ghaemi Osgouie

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This paper will first describe predictor controllers when the proportional-integral-derivative (PID) controllers are inactive for procedures that have large delay time (LDT) in transfer stage. Therefore in those states, the predictor controllers are better than the PID controllers, then compares three types of predictor controllers. The value of these controller-s parameters are obtained by trial and error method, so here an effort has been made to obtain these parameters by Ziegler-Nichols method. Eventually in this paper Ziegler-Nichols method has been described and finally, a PIP controller has been designed for a thermal system, which circulates hot air to keep the temperature of a chamber constant.

Keywords: Proportional-integral-predictive controller, Transferfunction, Delay time, Transport-lag.

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Authors: K. Paisal

Abstract:

The purposes of this research were (1) to create a learning activity for constructivism, (2) study the Mathematical Analysis courses learning achievement, and (3) study students’ attitude toward the learning activity for constructivism. The samples in this study were divided into 2 parts including 3 Mathematical Analysis courses instructors of Suan Sunandha Rajabhat University who provided basic information and attended the seminar and 17 Mathematical Analysis courses students who were studying in the academic and engaging in the learning activity for constructivism. The research instruments were lesson plans constructivism, subjective Mathematical Analysis courses achievement test with reliability index of 0.8119, and an attitude test concerning the students’ attitude toward the Mathematical Analysis courses learning activity for constructivism. The result of the research show that the efficiency of the Mathematical Analysis courses learning activity for constructivism is 73.05/72.16, which is more than expected criteria of 70/70. The research additionally find that the average score of learning achievement of students who engaged in the learning activities for constructivism are equal to 70% and the students’ attitude toward the learning activity for constructivism are at the medium level.

Keywords: Constructivism, learning management, Mathematical Analysis courses.

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Authors: J. Grira, Y. Bédard, S. Roche

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The aim of this research is to design a collaborative framework that integrates risk analysis activities into the geospatial database design (GDD) process. Risk analysis is rarely undertaken iteratively as part of the present GDD methods in conformance to requirement engineering (RE) guidelines and risk standards. Accordingly, when risk analysis is performed during the GDD, some foreseeable risks may be overlooked and not reach the output specifications especially when user intentions are not systematically collected. This may lead to ill-defined requirements and ultimately in higher risks of geospatial data misuse. The adopted approach consists of 1) reviewing risk analysis process within the scope of RE and GDD, 2) analyzing the challenges of risk analysis within the context of GDD, and 3) presenting the components of a risk-based collaborative framework that improves the collection of the intended/forbidden usages of the data and helps geo-IT experts to discover implicit requirements and risks.

Keywords: Collaborative risk analysis, intention of use, Geospatial database design, Geospatial data misuse.

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Authors: Oscar Javier Herrera, Manuel Ángel Camacho

Abstract:

This paper addresses a cutting edge method of business demand forecasting, based on an empirical probability function when the historical behavior of the data is random. Additionally, it presents error determination based on the numerical method technique ‘propagation of errors.’ The methodology was conducted characterization and process diagnostics demand planning as part of the production management, then new ways to predict its value through techniques of probability and to calculate their mistake investigated, it was tools used numerical methods. All this based on the behavior of the data. This analysis was determined considering the specific business circumstances of a company in the sector of communications, located in the city of Bogota, Colombia. In conclusion, using this application it was possible to obtain the adequate stock of the products required by the company to provide its services, helping the company reduce its service time, increase the client satisfaction rate, reduce stock which has not been in rotation for a long time, code its inventory, and plan reorder points for the replenishment of stock.

Keywords: Demand Forecasting, Empirical Distribution, Propagation of Error.

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Authors: Romain Ben Taleb, Aurélie Montarnal, Matthieu Lauras, Mathieu Dahan, Romain Miclo

Abstract:

To be competitive and sustainable, any company has to maximize its value. However, unlike listed companies that can assess their values based on market shares, most Small and Medium Enterprises (SMEs) which are non-listed cannot have direct and live access to this critical information. Traditional accounting reports only give limited insights to SME decision-makers about the real impact of their day-to-day decisions on the company’s performance and value. Most of the time, an SME’s financial valuation is made one time a year as the associated process is time and resource-consuming, requiring several months and external expertise to be completed. To solve this issue, we propose in this paper a value-oriented metamodel that enables real-time and dynamic assessment of the SME’s value based on the large definition of their assets. These assets cover a wider scope of resources of the company and better account for immaterial assets. The proposal, which is illustrated in a case study, discusses the benefits of incorporating assets in the SME valuation.

Keywords: SME, metamodel, decision support system, financial valuation.

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Authors: Colette Malyack, Pius Egbelu

Abstract:

Business-to-Customer (B2C) delivery options have improved to meet increased demand in recent years. The change in end users has forced logistics networks to focus on customer service and sentiment that would have previously been the priority of the company or organization of origin. This has led to increased pressure on logistics companies to extend traditional B2B networks into a B2C solution while accommodating additional costs, roadblocks, and customer sentiment; the result has been the creation of the omnichannel delivery network encompassing a number of traditional and modern methods of package delivery. In this paper the many solutions within the omnichannel delivery network are defined and discussed. It can be seen through this analysis that the omnichannel delivery network can be applied to reduce the complexity of package delivery and provide customers with more options. Applied correctly the result is a reduction in cost to the logistics company over time, even with an initial increase in cost to obtain the technology.

Keywords: Network planning, Last Mile Delivery, LMD, omnichannel delivery network, omnichannel logistics.

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