Search results for: short time window

Authors: Hun Go, Ji-Su Kim, Dong-Ho Lee

Abstract:

This study considers the problem of determining operation and maintenance schedules for a containership equipped with components during its sailing according to a pre-determined navigation schedule. The operation schedule, which specifies work time of each component, determines the due-date of each maintenance activity, and the maintenance schedule specifies the actual start time of each maintenance activity. The main constraints are component requirements, workforce availability, working time limitation, and inter-maintenance time. To represent the problem mathematically, a mixed integer programming model is developed. Then, due to the problem complexity, we suggest a heuristic for the objective of minimizing the sum of earliness and tardiness between the due-date and the starting time of each maintenance activity. Computational experiments were done on various test instances and the results are reported.

Keywords: Containerships, operation and preventive maintenance schedules, integer programming, heuristic

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Authors: Yong-Gyu Lee, Gilwon Yoon

Abstract:

Image processing for capsule endoscopy requires large memory and it takes hours for diagnosis since operation time is normally more than 8 hours. A real-time analysis algorithm of capsule images can be clinically very useful. It can differentiate abnormal tissue from health structure and provide with correlation information among the images. Bleeding is our interest in this regard and we propose a method of detecting frames with potential bleeding in real-time. Our detection algorithm is based on statistical analysis and the shapes of bleeding spots. We tested our algorithm with 30 cases of capsule endoscopy in the digestive track. Results were excellent where a sensitivity of 99% and a specificity of 97% were achieved in detecting the image frames with bleeding spots.

Keywords: bleeding, capsule endoscopy, image processing, real time analysis

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Authors: Seung Woo Lee, So Jeong Nam, Jai-Kyung Lee

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It can be said that the business sector is faced with a range of challenges–a rapidly changing business environment, an increase and diversification of customers- demands and the consequent need for quick response–for having in place flexible management and production info systems. As a matter of fact, many manufacturers have adopted production info management systems such as MES and ERP. Nevertheless, managers are having difficulties obtaining ever-changing production process information in real time, or responding quickly to any change in production related needs on the basis of such information. This is because they rely on poor production info systems which are not capable of providing real-time factory settings. If the manufacturer doesn-t have a capacity for collecting or digitalizing the 4 Ms (Man, Machine, Material, Method), which are resources for production, on a real time basis, it might to difficult to effectively maintain the information on production process. In this regard, this paper will introduce some new alternatives to the existing methods of collecting the 4 Ms in real time, which are currently comprise the production field.

Keywords: 4M, Acquisition of Data on shop-floor, Real-time machine interface

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Authors: J. Moshtagh, L. Eslami

Abstract:

Various studies have showed that about 90% of single line to ground faults occurred on High voltage transmission lines have transient nature. This type of faults is cleared by temporary outage (by the single phase auto-reclosure). The interval between opening and reclosing of the faulted phase circuit breakers is named “Dead Time” that is varying about several hundred milliseconds. For adjustment of traditional single phase auto-reclosures that usually are not intelligent, it is necessary to calculate the dead time in the off-line condition precisely. If the dead time used in adjustment of single phase auto-reclosure is less than the real dead time, the reclosing of circuit breakers threats the power systems seriously. So in this paper a novel approach for precise calculation of dead time in power transmission lines based on the network equivalencing in time domain is presented. This approach has extremely higher precision in comparison with the traditional method based on Thevenin equivalent circuit. For comparison between the proposed approach in this paper and the traditional method, a comprehensive simulation by EMTP-ATP is performed on an extensive power network.

Keywords: Dead Time, Network Equivalencing, High Voltage Transmission Lines, Single Phase Auto-Reclosure.

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Authors: C. Pacheco, A. Cipriano

Abstract:

A new concept of response system is proposed for filling the gap that exists in reducing vulnerability during immediate response to natural disasters. Real Time Early Response Systems (RTERSs) incorporate real time information as feedback data for closing control loop and for generating real time situation assessment. A review of the state of the art on works that fit the concept of RTERS is presented, and it is found that they are mainly focused on manmade disasters. At the same time, in response phase of natural disaster management many works are involved in creating early warning systems, but just few efforts have been put on deciding what to do once an alarm is activated. In this context a RTERS arises as a useful tool for supporting people in their decision making process during natural disasters after an event is detected, and also as an innovative context for applying well-known automation technologies and automatic control concepts and tools.

Keywords: Disaster management, emergency response system, natural disasters, real time.

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Authors: Nicola Gualandi, Luca Mantecchini, Davide Serrau

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Airport capacity has always been perceived in the traditional sense as the number of aircraft operations during a specified time corresponding to a tolerable level of average delay and it mostly depends on the airside characteristics, on the fleet mix variability and on the ATM. The adoption of the Directive 2002/30/EC in the EU countries drives the stakeholders to conceive airport capacity in a different way though. Airport capacity in this sense is fundamentally driven by environmental criteria, and since acoustical externalities represent the most important factors, those are the ones that could pose a serious threat to the growth of airports and to aviation market itself in the short-medium term. The importance of the regional airports in the deregulated market grew fast during the last decade since they represent spokes for network carriers and a preferential destination for low-fares carriers. Not only regional airports have witnessed a fast and unexpected growth in traffic but also a fast growth in the complaints for the nuisance by the people living near those airports. In this paper the results of a study conducted in cooperation with the airport of Bologna G. Marconi are presented in order to investigate airport acoustical capacity as a defacto constraint of airport growth.

Keywords: Airport acoustical capacity, airport noise, air traffic noise, sustainability of regional airports.

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Authors: Anthony Spiteri Staines

Abstract:

This paper examines and compares several of the most common real time methods. These methods are CORE, YSM, MASCOT, JSD, DARTS, RTSAD, ADARTS, CODARTS, HOOD, HRT-HOOD, ROOM, UML, UML-RT. The methods are compared using attributes like i) usability, ii) compositionality and iii) proper RT notations available. Finally some comparison results are given and discussed.

Keywords: Software Engineering Methods, MethodComparison, Real Time Analysis and Design.

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Authors: Rouhollah Ahmadi, Tatsuya Ueno, Tomio Okawa

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Bubble generation was observed using a high-speed camera in subcooled flow boiling at low void fraction. Constant heat flux was applied on one side of an upward rectangular channel to make heated test channel. Water as a working fluid from high subcooling to near saturation temperature was injected step by step to investigate bubble behavior during void development. Experiments were performed in two different pressures condition close to 2bar and 4bar. It was observed that in high subcooling when boiling was commenced, bubble after nucleation departed its origin and slid beside heated surface. In an observation window mean release frequency of bubble fb,mean, nucleation site Ns and mean bubble volume Vb,mean in each step of experiments were measured to investigate wall vaporization rate. It was found that in proximity of PNVG vaporization rate was increased significantly in compare with condensation rate which remained in low value.

Keywords: Subcooled flow boiling, Bubble dynamics, Void fraction, Sliding bubble.

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Authors: Prashant P. Bedekar, Sudhir R. Bhide, Vijay S. Kale

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Overcurrent (OC) relays are the major protection devices in a distribution system. The operating time of the OC relays are to be coordinated properly to avoid the mal-operation of the backup relays. The OC relay time coordination in ring fed distribution networks is a highly constrained optimization problem which can be stated as a linear programming problem (LPP). The purpose is to find an optimum relay setting to minimize the time of operation of relays and at the same time, to keep the relays properly coordinated to avoid the mal-operation of relays. This paper presents two phase simplex method for optimum time coordination of OC relays. The method is based on the simplex algorithm which is used to find optimum solution of LPP. The method introduces artificial variables to get an initial basic feasible solution (IBFS). Artificial variables are removed using iterative process of first phase which minimizes the auxiliary objective function. The second phase minimizes the original objective function and gives the optimum time coordination of OC relays.

Keywords: Constrained optimization, LPP, Overcurrent relaycoordination, Two-phase simplex method.

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Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

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In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: Data Estimation, link data, machine learning, road network.

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Authors: Ana Vieira, Fernando Lau, João Pedro Mortágua, Luís Cruz, Rui Santos

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The air transport impact on environment is more than ever a limitative obstacle to the aeronautical industry continuous growth. Over the last decades, considerable effort has been carried out in order to obtain quieter aircraft solutions, whether by changing the original design or investigating more silent maneuvers. The noise propagated by rotating surfaces is one of the most important sources of annoyance, being present in most aerial vehicles. Bearing this is mind, CEIIA developed a new computational chain for noise prediction with in-house software tools to obtain solutions in relatively short time without using excessive computer resources. This work is based on the new acoustic tool, which aims to predict the rotor noise generated during steady and maneuvering flight, making use of the flexibility of the C language and the advantages of GPU programming in terms of velocity. The acoustic tool is based in the Formulation 1A of Farassat, capable of predicting two important types of noise: the loading and thickness noise. The present work describes the most important features of the acoustic tool, presenting its most relevant results and framework analyses for helicopters and UAV quadrotors.

Keywords: Rotor noise, acoustic tool, GPU Programming, UAV noise.

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Authors: Nuray Uçar, Mervin Ölmez, Özge Alptoğa, Nilgün K. Yavuz, Ayşen Önen

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In recent years, research on continuous graphene oxide fibers has been intensified. Therefore, many factors of production stages are being studied. In this study, the effect of exfoliation time and presence of activated carbon particle (ACP) on graphene oxide fiber’s properties has been analyzed. It has been seen that cross-sectional appearance of sample with ACP is harsh and porous because of ACP. The addition of ACP did not change the electrical conductivity. However, ACP results in an enormous decrease of mechanical properties. Longer exfoliation time results to higher crystallinity degree, C/O ratio and less d space between layers. The breaking strength and electrical conductivity of sample with less exfoliation time is some higher than sample with high exfoliation time.

Keywords: Activated carbon, coagulation by wet spinning, exfoliation, graphene oxide fiber.

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Authors: Chunshien Li, Jhao-Wun Hu, Tai-Wei Chiang, Tsunghan Wu

Abstract:

Time series forecasting is an important and widely popular topic in the research of system modeling. This paper describes how to use the hybrid PSO-RLSE neuro-fuzzy learning approach to the problem of time series forecasting. The PSO algorithm is used to update the premise parameters of the proposed prediction system, and the RLSE is used to update the consequence parameters. Thanks to the hybrid learning (HL) approach for the neuro-fuzzy system, the prediction performance is excellent and the speed of learning convergence is much faster than other compared approaches. In the experiments, we use the well-known Mackey-Glass chaos time series. According to the experimental results, the prediction performance and accuracy in time series forecasting by the proposed approach is much better than other compared approaches, as shown in Table IV. Excellent prediction performance by the proposed approach has been observed.

Keywords: forecasting, hybrid learning (HL), Neuro-FuzzySystem (NFS), particle swarm optimization (PSO), recursiveleast-squares estimator (RLSE), time series

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Authors: Ashish Saini, A.K. Saxena

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In competitive electricity markets all over the world, an adoption of suitable transmission pricing model is a problem as transmission segment still operates as a monopoly. Transmission pricing is an important tool to promote investment for various transmission services in order to provide economic, secure and reliable electricity to bulk and retail customers. The nodal pricing based on SRMC (Short Run Marginal Cost) is found extremely useful by researchers for sending correct economic signals. The marginal prices must be determined as a part of solution to optimization problem i.e. to maximize the social welfare. The need to maximize the social welfare subject to number of system operational constraints is a major challenge from computation and societal point of views. The purpose of this paper is to present a nodal transmission pricing model based on SRMC by developing new mathematical expressions of real and reactive power marginal prices using GA-Fuzzy based optimal power flow framework. The impacts of selecting different social welfare functions on power marginal prices are analyzed and verified with results reported in literature. Network revenues for two different power systems are determined using expressions derived for real and reactive power marginal prices in this paper.

Keywords: Deregulation, electricity markets, nodal pricing, social welfare function, short run marginal cost.

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Authors: Sotirios Raptis

Abstract:

Health and Social care (HSc) services planning and scheduling are facing unprecedented challenges, due to the pandemic pressure and also suffer from unplanned spending that is negatively impacted by the global financial crisis. Data-driven approaches can help to improve policies, plan and design services provision schedules using algorithms that assist healthcare managers to face unexpected demands using fewer resources. The paper discusses services packing using statistical significance tests and machine learning (ML) to evaluate demands similarity and coupling. This is achieved by predicting the range of the demand (class) using ML methods such as Classification and Regression Trees (CART), Random Forests (RF), and Logistic Regression (LGR). The significance tests Chi-Squared and Student’s test are used on data over a 39 years span for which data exist for services delivered in Scotland. The demands are associated using probabilities and are parts of statistical hypotheses. These hypotheses, as their NULL part, assume that the target demand is statistically dependent on other services’ demands. This linking is checked using the data. In addition, ML methods are used to linearly predict the above target demands from the statistically found associations and extend the linear dependence of the target’s demand to independent demands forming, thus, groups of services. Statistical tests confirmed ML coupling and made the prediction statistically meaningful and proved that a target service can be matched reliably to other services while ML showed that such marked relationships can also be linear ones. Zero padding was used for missing years records and illustrated better such relationships both for limited years and for the entire span offering long-term data visualizations while limited years periods explained how well patients numbers can be related in short periods of time or that they can change over time as opposed to behaviours across more years. The prediction performance of the associations were measured using metrics such as Receiver Operating Characteristic (ROC), Area Under Curve (AUC) and Accuracy (ACC) as well as the statistical tests Chi-Squared and Student. Co-plots and comparison tables for the RF, CART, and LGR methods as well as the p-value from tests and Information Exchange (IE/MIE) measures are provided showing the relative performance of ML methods and of the statistical tests as well as the behaviour using different learning ratios. The impact of k-neighbours classification (k-NN), Cross-Correlation (CC) and C-Means (CM) first groupings was also studied over limited years and for the entire span. It was found that CART was generally behind RF and LGR but in some interesting cases, LGR reached an AUC = 0 falling below CART, while the ACC was as high as 0.912 showing that ML methods can be confused by zero-padding or by data’s irregularities or by the outliers. On average, 3 linear predictors were sufficient, LGR was found competing well RF and CART followed with the same performance at higher learning ratios. Services were packed only when a significance level (p-value) of their association coefficient was more than 0.05. Social factors relationships were observed between home care services and treatment of old people, low birth weights, alcoholism, drug abuse, and emergency admissions. The work found  that different HSc services can be well packed as plans of limited duration, across various services sectors, learning configurations, as confirmed by using statistical hypotheses.

Keywords: Class, cohorts, data frames, grouping, prediction, probabilities, services.

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Authors: Chao Wang, Yongkun Li

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In this paper, the discrete-time fuzzy BAM neural network with delays and impulses is studied. Sufficient conditions are obtained for the existence and global stability of a unique equilibrium of this class of fuzzy BAM neural networks with Lipschitzian activation functions without assuming their boundedness, monotonicity or differentiability and subjected to impulsive state displacements at fixed instants of time. Some numerical examples are given to demonstrate the effectiveness of the obtained results.

Keywords: Discrete-time fuzzy BAM neural networks, ımpulses, global exponential stability, global asymptotical stability, equilibrium point.

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Authors: Le Xuan Cau

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Flash flood is occurred in short time rainfall interval: from 1 hour to 12 hours in small and medium basins. Flash floods typically have two characteristics: large water flow and big flow velocity. Flash flood is occurred at hill valley site (strip of lowland of terrain) in a catchment with large enough distribution area, steep basin slope, and heavy rainfall. The risk of flash floods is determined through Gridded Basin Flash Flood Potential Index (GBFFPI). Flash Flood Potential Index (FFPI) is determined through terrain slope flash flood index, soil erosion flash flood index, land cover flash floods index, land use flash flood index, rainfall flash flood index. Determining GBFFPI, each cell in a map can be considered as outlet of a water accumulation basin. GBFFPI of the cell is determined as basin average value of FFPI of the corresponding water accumulation basin. Based on GIS, a tool is developed to compute GBFFPI using ArcObjects SDK for .NET. The maps of GBFFPI are built in two types: GBFFPI including rainfall flash flood index (real time flash flood warning) or GBFFPI excluding rainfall flash flood index. GBFFPI Tool can be used to determine a high flash flood potential site in a large region as quick as possible. The GBFFPI is improved from conventional FFPI. The advantage of GBFFPI is that GBFFPI is taking into account the basin response (interaction of cells) and determines more true flash flood site (strip of lowland of terrain) while conventional FFPI is taking into account single cell and does not consider the interaction between cells. The GBFFPI Map of QuangNam, QuangNgai, DaNang, Hue is built and exported to Google Earth. The obtained map proves scientific basis of GBFFPI.

Keywords: ArcObjects SDK for .NET, Basin average value of FFPI, Gridded basin flash flood potential index, GBFFPI map.

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Authors: M. Keshavarzi

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Grasslands of Iran are encountered with a vast desertification and destruction. Some legumes are plants of forage importance with high palatability. Studied legumes in this project are Onobrychis, Medicago sativa (alfalfa) and Trifolium repens. Seeds were cultivated in research field of Kaboutarabad (33 km East of Isfahan, Iran) with an average 80 mm. annual rainfall. Plants were cultivated in a split plot design with 3 replicate and two water treatments (weekly irrigation, and under stress with same amount per 15 days interval). Water entrance to each plots were measured by Partial flow. This project lasted 20 weeks. Destructive samplings (1m2 each time) were done weekly. At each sampling plants were gathered and weighed separately for each vegetative parts. An Area Meter (Vista) was used to measure root surface and leaf area. Total shoot and root fresh and dry weight, leaf area index and soil coverage were evaluated too. Dry weight was achieved in 750c oven after 24 hours. Statgraphic and Harvard Graphic software were used to formulate and demonstrate the parameters curves due to time. Our results show that Trifolium repens has affected 60 % and Medicago sativa 18% by water stress. Onobrychis total fresh weight was reduced 45%. Dry weight or Biomass in alfalfa is not so affected by water shortage. This means that in alfalfa fields we can decrease the irrigation amount and have some how same amount of Biomass. Onobrychis show a drastic decrease in Biomass. The increases in total dry matter due to time in studied plants are formulated. For Trifolium repens if removal or cattle entrance to meadows do not occurred at perfect time, it will decrease the palatability and water content of the shoots. Water stress in a short period could develop the root system in Trifolium repens, but if it last more than this other ecological and soil factors will affect the growth of this plant. Low level of soil water is not so important for studied legume forges. But water shortage affect palatability and water content of aerial parts. Leaf area due to time in studied legumes is formulated. In fact leaf area is decreased by shortage in available water. Higher leaf area means higher forage and biomass production. Medicago and Onobrychis reach to the maximum leaf area sooner than Trifolium and are able to produce an optimum soil cover and inhibit the transpiration of soil water of meadows. Correlation of root surface to Total biomass in studied plants is formulated. Medicago under water stress show a 40% decrease in crown cover while at optimum condition this amount reach to 100%. In order to produce forage in areas without soil erosion Medicago is the best choice even with a shortage in water resources. It is tried to represent the growth simulation of three famous Forage Legumes. By growth simulation farmers and range managers could better decide to choose best plant adapted to water availability without designing different time and labor consuming field experiments.

Keywords: Ecological parameters, Medicago, Onobrychis, Trifolium.

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Authors: Armando Cartenì, Ilaria Henke

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The perceived public transport quality is an important driver that influences both customer satisfaction and mobility choices. The competition among transport operators needs to improve the quality of the services and identify which attributes are perceived as relevant by passengers. Among the “traditional” public transport quality attributes there are, for example: travel and waiting time, regularity of the services, and ticket price. By contrast, there are some “non-conventional” attributes that could significantly influence customer satisfaction jointly with the “traditional” ones. Among these, the beauty/aesthetics of the transport terminals (e.g. rail station and bus terminal) is probably one of the most impacting on user perception. Starting from these considerations, the point stressed in this paper was if (and how munch) the travel experience of the overall travel (e.g. how long is the travel, how many transport modes must be used) influences the perception of the public transport quality. The aim of this paper was to investigate the weight of the terminal quality (e.g. aesthetic, comfort and service offered) within the overall travel experience. The case study was the extra-urban Italian bus network. The passengers of the major Italian terminal bus were interviewed and the analysis of the results shows that about the 75% of the travelers, are available to pay up to 30% more for the ticket price for having a high quality terminal. A travel experience effect was observed: the average perceived transport quality varies with the characteristic of the overall trip. The passengers that have a “long trip” (travel time greater than 2 hours) perceived as “low” the overall quality of the trip even if they pass through a high quality terminal. The opposite occurs for the “short trip” passengers. This means that if a traveler passes through a high quality station, the overall perception of that terminal could be significantly reduced if he is tired from a long trip. This result is important and if confirmed through other case studies, will allow to conclude that the “travel experience impact" must be considered as an explicit design variable for public transport services and planning.

Keywords: Transportation planning, sustainable mobility, decision support system, discrete choice model, design problem.

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Authors: Yananda Siraphatthada

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The current study was the succession of a previous study on value added of recycling business management. Its aims are to 1) explore conditions on how to increasing value add of Thai recycling business, and 2) exam the implementation of the 3-staged plan (short, medium, and long term), suggested by the former study, to increase value added of the recycling business as immediate mechanisms to accelerate government operation. Quantitative and qualitative methods were utilized in this research. A qualitative research consisted of in-depth interviews and focus group discussions. Responses were obtained from owners of the waste separation plants, and recycle shops, as well as officers in relevant governmental agencies. They were randomly selected via Quota Sampling. Data was analyzed via content analysis. The sample used for quantitative method consisted of 1,274 licensed recycling operators in eight provinces. The operators were randomly stratified via sampling method. Data were analyzed via descriptive statistics frequency, percentage, average (Mean) and standard deviation.The study recommended three-staged plan: short, medium, and long terms. The plan included the development of logistics, the provision of quality market/plants, the amendment of recycling rules/regulation, the restructuring recycling business, the establishment of green-purchasing recycling center, support for the campaigns run by the International Green Purchasing Network (IGPN), conferences/workshops as a public forum to share insights among experts/concern people.

Keywords: Strategies, Value Added, Recycle Business.

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Authors: Kuljit Kaur, Parminder Kaur, Jaspreet Bedi, Hardeep Singh

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Software crisis refers to the situation in which the developers are not able to complete the projects within time and budget constraints and moreover these overscheduled and over budget projects are of low quality as well. Several methodologies have been adopted form time to time to overcome this situation and now in the focus is component based software engineering. In this approach, emphasis is on reuse of already existing software artifacts. But the results can not be achieved just by preaching the principles; they need to be practiced as well. This paper highlights some of the very basic elements of this approach, which has to be in place to get the desired goals of high quality, low cost with shorter time-to-market software products.

Keywords: Component Model, Software Components, SoftwareRepository, Process Models.

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Authors: Arnab Majumdar, Srimani Sen

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In this paper, a vivid simulated study has been made on 35 GHz Ka-band window frequency in order to judge and compare the DC and high frequency properties of cubic ZnB-GaN with the existing hexagonal 4H-SiC. A flat profile p⁺pnn⁺ DDR structure of impatt is chosen and is optimized at a particular bias current density with respect to efficiency and output power taking into consideration the effect of mobile space charge also. The simulated results obtained reveals the strong potentiality of impatts based on both cubic ZnB-GaN and hexagonal 4H-SiC. The DC-to-millimeter wave conversion efficiency for cubic ZnB-GaN impatt obtained is 50% with an estimated output power of 2.83 W at an optimized bias current density of 2.5×10⁸ A/m². The conversion efficiency and estimated output power in case of hexagonal 4H-SiC impatt obtained is 22.34% and 40 W respectively at an optimum bias current density of 0.06×10⁸ A/m².

Keywords: Cubic ZnB-GaN, hexagonal 4H-SiC, Double drift impatt diode, millimeter wave, optimized bias current density, wide band gap semiconductor.

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Authors: Chris K. Y. Lo, Andy C. L. Yeung, T. C. Edwin Cheng

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ISO 9000 is the most popular and widely adopted meta-standard for quality and operational improvements. However, only limited empirical research has been conducted to examine the impact of ISO 9000 on operational performance based on objective and longitudinal data. To reveal any causal relationship between the adoption of ISO 9000 and operational performance, we examined the timing and magnitude of change in time-based performance as a result of ISO 9000 adoption. We analyzed the changes in operating cycle, inventory days, and account receivable days prior and after the implementation of ISO 9000 in 695 publicly listed manufacturing firms. We found that ISO 9000 certified firms shortened their operating cycle time by 5.28 days one year after the implementation of ISO 9000. In the long-run (3 years after certification), certified firms showed continuous improvement in time-based efficiency, and experienced a shorter operating cycle time of 11 days than that of non-certified firms. There was an average of 6.5% improvement in operating cycle time for ISO 9000 certified firms. Both inventory days and account receivable days showed similar significant improvements after the implementation of ISO 9000, too.

Keywords: ISO 9000, Operating Cycle, Time-based efficiency.

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Authors: Katleho D. Makatjane, Kalebe M. Kalebe

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The present paper used time-varying parameters which are based on the score function of a probability density at time t to model volatility of saving rate. We used a scaled likelihood function to update the parameters of the model overtime. Our results revealed high diligence of time-varying since the location parameter is greater than zero. Furthermore, we discovered a leptokurtic condition on saving rate’s distribution. Kapetanios, Shin-Shell Nonlinear Augmented Dickey-Fuller (KSS-NADF) test showed that the saving rate has a nonlinear unit root; therefore, it can be modeled by a generalised autoregressive score (GAS) model. Additionally, value at risk (VaR) and conditional tail expectation (CTE) indicate that 99% of the time people in Lesotho are saving more than spending. This puts the economy in high risk of not expanding. Therefore, the monetary policy committee (MPC) of Lesotho should revise their monetary policies towards this high saving rates risk.

Keywords: Generalized autoregressive score, time-varying, saving rate, Lesotho.

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Authors: Aws Al-azawi, John Soraghan

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There is a growing interest in the use of ultrasonic speckle tracking for biomedical image formation of tissue deformation. Speckle tracking is angle independent and has an ability to differentiate soft tissue into benign and malignant regions. In this paper a simulation model for dynamic ultrasound scatterer is presented. The model composes Field-II ultrasonic scatterers and FEM (ANSYS-11) nodes as a regional tissue deformation. A performance evaluation is presented on axial displacement and strain fields estimation of a uniformly elastic model, using speckle tracking based 1D cross-correlation of optimally segmented pre and post-deformation frames. Optimum correlation window length is investigated in terms of highest signal-to-noise ratio (SNR) for a selected region of interest of a smoothed displacement field. Finally, gradient based strain field of both smoothed and non-smoothed displacement fields are compared. Simulation results from the model are shown to compare favorably with FEM results.

Keywords: Speckle tracking, tissue deformation, ultrasonic simulation.

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Authors: Zhongzhen Luo, Saeid Habibi, Martin v. Mohrenschildt

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Self-driving vehicle require a high level of situational awareness in order to maneuver safely when driving in real world condition. This paper presents a LiDAR based real time perception system that is able to process sensor raw data for multiple target detection and tracking in dynamic environment. The proposed algorithm is nonparametric and deterministic that is no assumptions and priori knowledge are needed from the input data and no initializations are required. Additionally, the proposed method is working on the three-dimensional data directly generated by LiDAR while not scarifying the rich information contained in the domain of 3D. Moreover, a fast and efficient for real time clustering algorithm is applied based on a radially bounded nearest neighbor (RBNN). Hungarian algorithm procedure and adaptive Kalman filtering are used for data association and tracking algorithm. The proposed algorithm is able to run in real time with average run time of 70ms per frame.

Keywords: LiDAR, real-time system, clustering, tracking, data association.

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Authors: Long Jye Sheu, Horng-Shing Chiou, Wei Ching Chen

Abstract:

We propose a new perspective on speech communication using blind source separation. The original speech is mixed with key signals which consist of the mixing matrix, chaotic signals and a random noise. However, parts of the keys (the mixing matrix and the random noise) are not necessary in decryption. In practice implement, one can encrypt the speech by changing the noise signal every time. Hence, the present scheme obtains the advantages of a One Time Pad encryption while avoiding its drawbacks in key exchange. It is demonstrated that the proposed scheme is immune against traditional attacks.

Keywords: one time pad, blind source separation, independentcomponent analysis, speech encryption.

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Authors: Zhang Xiaodong, Tang Zixin, Liu Xin

Abstract:

In order to avoid self-collision of space manipulators during operation process, a real-time detection method is proposed in this paper. The manipulator is fitted into a cylinder-enveloping surface, and then, a kind of detection algorithm of collision between cylinders is analyzed. The collision model of space manipulator self-links can be detected by using this algorithm in real-time detection during the operation process. To ensure security of the operation, a safety threshold is designed. The simulation and experiment results verify the effectiveness of the proposed algorithm for a 7-DOF space manipulator.

Keywords: Space manipulator, Collision detection, Self-collision, the real-time collision detection.

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Authors: Udeni Jayasinghe, Anuja Dharmaratne

Abstract:

Each year many people are reported missing in most of the countries in the world owing to various reasons. Arrangements have to be made to find these people after some time. So the investigating agencies are compelled to make out these people by using manpower. But in many cases, the investigations carried out to find out an absconding for a long time may not be successful. At a time like that it may be difficult to identify these people by examining their old photographs, because their facial appearance might have changed mainly due to the natural aging process. On some occasions in forensic medicine if a dead body is found, investigations should be held to make sure that this corpse belongs to the same person disappeared some time ago. With the passage of time the face of the person might have changed and there should be a mechanism to reveal the person-s identity. In order to make this process easy, we must guess and decide as to how he will look like by now. To address this problem this paper presents a way of synthesizing a facial image with the aging effects.

Keywords: Cranio-facial growth model, eigenfaces, eigenvectors, Face Anthropometry.

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Authors: Holger Keitel

Abstract:

The prediction of long-term deformations of concrete and reinforced concrete structures has been a field of extensive research and several different creep models have been developed so far. Most of the models were developed for constant concrete stresses, thus, in case of varying stresses a specific superposition principle or time-integration, respectively, is necessary. Nowadays, when modeling concrete creep the engineering focus is rather on the application of sophisticated time-integration methods than choosing the more appropriate creep model. For this reason, this paper presents a method to quantify the uncertainties of creep prediction originating from the selection of creep models or from the time-integration methods. By adapting variance based global sensitivity analysis, a methodology is developed to quantify the influence of creep model selection or choice of time-integration method. Applying the developed method, general recommendations how to model creep behavior for varying stresses are given.

Keywords: Concrete creep models, time-integration methods, sensitivity analysis, prediction uncertainty.

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