Search results for: time domain analysis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13921

Search results for: time domain analysis

11371 Progressive Collapse of Hyperbolic Cooling Tower Considering the Support Inclinations

Authors: Esmaeil Asadzadeh, Mehtab Alam

Abstract:

Progressive collapse of the layered hyperbolic tower shells are studied considering the influences of changes in the supporting columns’ types and angles. 3-D time history analyses employing the finite element method are performed for the towers supported with I-type and ᴧ-type column. It is found that the inclination angle of the supporting columns is a very important parameter in optimization and safe design of the cooling towers against the progressive collapse. It is also concluded that use of Demand Capacity Ratio (DCR) criteria of the linear elastic approach recommended by GSA is un-conservative for the hyperbolic tower shells.

Keywords: Progressive collapse, cooling towers, finite element analysis, crack generation, reinforced concrete.

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11370 Bayesian Network Model for Students- Laboratory Work Performance Assessment: An Empirical Investigation of the Optimal Construction Approach

Authors: Ifeyinwa E. Achumba, Djamel Azzi, Rinat Khusainov

Abstract:

There are three approaches to complete Bayesian Network (BN) model construction: total expert-centred, total datacentred, and semi data-centred. These three approaches constitute the basis of the empirical investigation undertaken and reported in this paper. The objective is to determine, amongst these three approaches, which is the optimal approach for the construction of a BN-based model for the performance assessment of students- laboratory work in a virtual electronic laboratory environment. BN models were constructed using all three approaches, with respect to the focus domain, and compared using a set of optimality criteria. In addition, the impact of the size and source of the training, on the performance of total data-centred and semi data-centred models was investigated. The results of the investigation provide additional insight for BN model constructors and contribute to literature providing supportive evidence for the conceptual feasibility and efficiency of structure and parameter learning from data. In addition, the results highlight other interesting themes.

Keywords: Bayesian networks, model construction, parameterlearning, structure learning, performance index, model comparison.

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11369 Constraint Based Frequent Pattern Mining Technique for Solving GCS Problem

Authors: First G.M. Karthik, Second Ramachandra.V.Pujeri, Dr.

Abstract:

Generalized Center String (GCS) problem are generalized from Common Approximate Substring problem and Common substring problems. GCS are known to be NP-hard allowing the problems lies in the explosion of potential candidates. Finding longest center string without concerning the sequence that may not contain any motifs is not known in advance in any particular biological gene process. GCS solved by frequent pattern-mining techniques and known to be fixed parameter tractable based on the fixed input sequence length and symbol set size. Efficient method known as Bpriori algorithms can solve GCS with reasonable time/space complexities. Bpriori 2 and Bpriori 3-2 algorithm are been proposed of any length and any positions of all their instances in input sequences. In this paper, we reduced the time/space complexity of Bpriori algorithm by Constrained Based Frequent Pattern mining (CBFP) technique which integrates the idea of Constraint Based Mining and FP-tree mining. CBFP mining technique solves the GCS problem works for all center string of any length, but also for the positions of all their mutated copies of input sequence. CBFP mining technique construct TRIE like with FP tree to represent the mutated copies of center string of any length, along with constraints to restraint growth of the consensus tree. The complexity analysis for Constrained Based FP mining technique and Bpriori algorithm is done based on the worst case and average case approach. Algorithm's correctness compared with the Bpriori algorithm using artificial data is shown.

Keywords: Constraint Based Mining, FP tree, Data mining, GCS problem, CBFP mining technique.

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11368 Neutrosophic Multiple Criteria Decision Making Analysis Method for Selecting Stealth Fighter Aircraft

Authors: C. Ardil

Abstract:

In this paper, a neutrosophic multiple criteria decision analysis method is proposed to select stealth fighter aircraft. Neutrosophic multiple criteria decision analysis methods are used to analyze the neutrosophic environment and give results under uncertainty and incompleteness. Neutrosophic numbers are used to evaluate alternatives over a set of evaluation criteria in decision making problems. Finally, the proposed model is applied to a practical decision problem for selecting stealth fighter aircraft.

Keywords: neutrosophic sets, multiple criteria decision making analysis, stealth fighter aircraft, aircraft selection, MCDMA, SVNNs

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11367 Existence of Periodic Solutions in a Food Chain Model with Holling–type II Functional Response

Authors: Zhaohui Wen

Abstract:

In this paper, a food chain model with Holling type II functional response on time scales is investigated. By using the Mawhin-s continuation theorem in coincidence degree theory, sufficient conditions for existence of periodic solutions are obtained.

Keywords: Periodic solutions, food chain model, coincidence degree, time scales.

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11366 Statistical Analysis-Driven Risk Assessment of Criteria Air Pollutants: A Sulfur Dioxide Case Study

Authors: Ehsan Bashiri

Abstract:

A 7-step method (with 25 sub-steps) to assess risk of air pollutants is introduced. These steps are: pre-considerations, sampling, statistical analysis, exposure matrix and likelihood, doseresponse matrix and likelihood, total risk evaluation, and discussion of findings. All mentioned words and expressions are wellunderstood; however, almost all steps have been modified, improved, and coupled in such a way that a comprehensive method has been prepared. Accordingly, the SADRA (Statistical Analysis-Driven Risk Assessment) emphasizes extensive and ongoing application of analytical statistics in traditional risk assessment models. A Sulfur Dioxide case study validates the claim and provides a good illustration for this method.

Keywords: Criteria air pollutants, Matrix of risk, Riskassessment, Statistical analysis.

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11365 Noise Performance of Magnetic Field Tunable Avalanche Transit Time Source

Authors: Partha Banerjee, Aritra Acharyya, Arindam Biswas, A. K. Bhattacharjee, Amit Banerjee, Hiroshi Inokawa

Abstract:

The effect of magnetic field on the noise performance of the magnetic field tunable avalanche transit time (MAGTATT) device based on Si, designed to operate at W-band (75 – 110 GHz), has been studied in this paper. A comprehensive two-dimensional (2D) model has been developed. The simulation results show that due to the presence of applied external transverse magnetic field, both the noise spectral density and noise measure of the MAGTATT device increase significantly. The noise performance of the device has been found to be further deteriorated if the magnetic field strength is further increased. Hence, in order to achieve the magnetic field tuning of the radio frequency (RF) properties of impact avalanche transit time (IMPATT) source, the noise performance of it has to be sacrificed in fair extent. Moreover, it clearly indicates that an IMPATT source must be covered with appropriate magnetic shielding material to avoid undesirable shift in operating frequency and output power and objectionable amount of deterioration in noise performance due to the presence of external magnetic field.

Keywords: 2-D model, IMPATT, MAGTATT, mm-wave, noise performance.

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11364 Prospect and Challenges of Public Bicycle Sharing System in Indian Cities

Authors: Anil Kumar

Abstract:

The Public Bicycle System (PBS), generally known as Public Bicycle Share System or Bike-Share, is a service provided to the everyday commuter, in which several cycles are available on the shared system. The concept of PBS is new to the people of India and requires more study in the fields of essential requirements, major infrastructural requirements, social acceptability and various challenges. In various Indian cities, Mass Rapid Transit System (MRTS), Bus Rapid Transit System (BRTS), Monorail and other modes of transport have been adopted for the main haul of transport. These modes take more time, space and are also expensive to implement. At the same time, the PBS system is more economical and takes less time to implement. The main benefit of the PBS system is that it is more environmentally friendly. PBS is being implemented in many Indian cities for public use, but various challenges are associated with this. The study aims to determine what are the basic infrastructural requirements for PBS in India, as well as to determine to what extent a Public Bike Sharing System can provide a quality and efficient service to passengers as a primary method of transportation.

Keywords: Public Bicycle Sharing system, sustainable transport, infrastructure, smart city.

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11363 Ignition Time Delay in Swirling Supersonic Flow Combustion

Authors: A. M. Tahsini

Abstract:

Supersonic hydrogen-air cylindrical mixing layer is numerically analyzed to investigate the effect of inlet swirl on ignition time delay in scramjets. Combustion is treated using detail chemical kinetics. One-equation turbulence model of Spalart and Allmaras is chosen to study the problem and advection upstream splitting method is used as computational scheme. The results show that swirling both fuel and oxidizer streams may drastically decrease the ignition distance in supersonic combustion, unlike using the swirl just in fuel stream which has no helpful effect.

Keywords: Ignition delay, Supersonic combustion, Swirl, Numerical simulation, Turbulence.

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11362 Adsorption Studies on the Removal of Pesticides(Carbofuran) using Activated Carbon from Rice Straw Agricultural Waste

Authors: Ken-Lin Chang, Jun-Hong Lin, Shui-Tein Chen

Abstract:

In this study, we used a two-stage process and potassium hydroxide (KOH) to transform waste biomass (rice straw) into activated carbon and then evaluated the adsorption capacity of the waste for removing carbofuran from an aqueous solution. Activated carbon was fast and effective for the removal of carbofuran because of its high surface area. The native and carbofuran-loaded adsorbents were characterized by elemental analysis. Different adsorption parameters, such as the initial carbofuran concentration, contact time, temperature and pH for carbofuran adsorption, were studied using a batch system. This study demonstrates that rice straw can be very effective in the adsorption of carbofuran from bodies of water.

Keywords: Rice straw, Carbofuran, Activated carbon

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11361 Freighter Aircraft Selection Using Entropic Programming for Multiple Criteria Decision Making Analysis

Authors: C. Ardil

Abstract:

This paper proposes entropic programming for the freighter aircraft selection problem using the multiple criteria decision analysis method. The study aims to propose a systematic and comprehensive framework by focusing on the perspective of freighter aircraft selection. In order to achieve this goal, an integrated entropic programming approach was proposed to evaluate and rank alternatives. The decision criteria and aircraft alternatives were identified from the research data analysis. The objective criteria weights were determined by the mean weight method and the standard deviation method. The proposed entropic programming model was applied to a practical decision problem for evaluating and selecting freighter aircraft. The proposed entropic programming technique gives robust, reliable, and efficient results in modeling decision making analysis problems. As a result of entropic programming analysis, Boeing B747-8F, a freighter aircraft alternative ( a3), was chosen as the most suitable freighter aircraft candidate.   

Keywords: entropic programming, additive weighted model, multiple criteria decision making analysis, MCDMA, TOPSIS, aircraft selection, freighter aircraft, Boeing B747-8F, Boeing B777F, Airbus A350F

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11360 Shoplifting in Riyadh, Saudi Arabia

Authors: Saleh Dabil

Abstract:

the research was conducted using the self report of shoplifters who apprehended in the supermarket while stealing. 943 shoplifters in three years were interviewed right after the stealing act and before calling the police. The aim of the study is to know the shoplifting characteristics in Saudi Arabia, including the trait of shoplifters and the situation of the supermarkets where the stealing takes place. The analysis based on the written information about each thief as the documentary research method. Descriptive statistics as well as some inferential statistics were employed. The result shows that there are differences between genders, age groups, occupations, time of the day, days of the week, months, way of stealing, individual or group of thieves and other supermarket situations in the type of items stolen, total price and the count of items. The result and the recommendation will serve as a guide for retailers where, when and who to look at to prevent shoplifting.

Keywords: Shoplifting, stealing, theft, supermarket.

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11359 Sfard’s Commognitive Framework as a Method of Discourse Analysis in Mathematics

Authors: Dong-Joong Kim, Sangho Choi, Woong Lim

Abstract:

This paper discusses Sfard’s commognitive approach and provides an empirical study as an example to illustrate the theory as method. Traditionally, research in mathematics education focused on the acquisition of mathematical knowledge and the didactic process of knowledge transfer. Through attending to a distinctive form of language in mathematics, as well as mathematics as a discursive subject, alternative views of making meaning in mathematics have emerged; these views are therefore “critical,” as in critical discourse analysis. The commognitive discourse analysis method has the potential to bring more clarity to our understanding of students’ mathematical thinking and the process through which students are socialized into school mathematics.

Keywords: Commognitive framework, discourse analysis, mathematical discourse, mathematics education.

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11358 Evaluation of the Triticale Flour Blend Dough in the Mixing and Fermentation Processes

Authors: Martins Sabovics, Karina Ruse, Evita Straumite, Ruta Galoburda

Abstract:

The research was accomplished on triticale flour blend, which was made from whole grain triticale, rye, hull-less barley flour and rice, maize flour. The aim of this research was to evaluate physico-chemical and sensory properties of triticale flour blend dough in the mixing and fermentation processes. For dough making was used triticale flour blend, yeast, sugar, salt, and water. In the mixing process ware evaluated moisture, acidity, pH, and dough sensory properties (softness, viscosity, and stickiness), but in the fermentation process ware evaluated volume, moisture, acidity, and pH. During present research was established that increasing fermentation temperature and time, increase dough temperature, volume, moisture, and acidity. The mixing time and fermentation time and temperature have significant effect (p<0.05) on triticale flour blend dough physico-chemical and sensory properties.

Keywords: Dough quality, dough fermentation, dough mixing, triticale flour blend.

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11357 An Energy-Efficient Distributed Unequal Clustering Protocol for Wireless Sensor Networks

Authors: Sungju Lee, Jangsoo Lee , Hongjoong Sin, Seunghwan Yoo, Sanghyuck Lee, Jaesik Lee, Yongjun Lee, Sungchun Kim

Abstract:

The wireless sensor networks have been extensively deployed and researched. One of the major issues in wireless sensor networks is a developing energy-efficient clustering protocol. Clustering algorithm provides an effective way to prolong the lifetime of a wireless sensor networks. In the paper, we compare several clustering protocols which significantly affect a balancing of energy consumption. And we propose an Energy-Efficient Distributed Unequal Clustering (EEDUC) algorithm which provides a new way of creating distributed clusters. In EEDUC, each sensor node sets the waiting time. This waiting time is considered as a function of residual energy, number of neighborhood nodes. EEDUC uses waiting time to distribute cluster heads. We also propose an unequal clustering mechanism to solve the hot-spot problem. Simulation results show that EEDUC distributes the cluster heads, balances the energy consumption well among the cluster heads and increases the network lifetime.

Keywords: Wireless Sensor Network, Distributed UnequalClustering, Multi-hop, Lifetime.

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11356 Establishing a Probabilistic Model of Extrapolated Wind Speed Data for Wind Energy Prediction

Authors: Mussa I. Mgwatu, Reuben R. M. Kainkwa

Abstract:

Wind is among the potential energy resources which can be harnessed to generate wind energy for conversion into electrical power. Due to the variability of wind speed with time and height, it becomes difficult to predict the generated wind energy more optimally. In this paper, an attempt is made to establish a probabilistic model fitting the wind speed data recorded at Makambako site in Tanzania. Wind speeds and direction were respectively measured using anemometer (type AN1) and wind Vane (type WD1) both supplied by Delta-T-Devices at a measurement height of 2 m. Wind speeds were then extrapolated for the height of 10 m using power law equation with an exponent of 0.47. Data were analysed using MINITAB statistical software to show the variability of wind speeds with time and height, and to determine the underlying probability model of the extrapolated wind speed data. The results show that wind speeds at Makambako site vary cyclically over time; and they conform to the Weibull probability distribution. From these results, Weibull probability density function can be used to predict the wind energy.

Keywords: Probabilistic models, wind speed, wind energy

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11355 Concept, Design and Implementation of Power System Component Simulator Based on Thyristor Controlled Transformer and Power Converter

Authors: B. Kędra, R. Małkowski

Abstract:

This paper presents information on Power System Component Simulator – a device designed for LINTE^2 laboratory owned by Gdansk University of Technology in Poland. In this paper, we first provide an introductory information on the Power System Component Simulator and its capabilities. Then, the concept of the unit is presented. Requirements for the unit are described as well as proposed and introduced functions are listed. Implementation details are given. Hardware structure is presented and described. Information about used communication interface, data maintenance and storage solution, as well as used Simulink real-time features are presented. List and description of all measurements is provided. Potential of laboratory setup modifications is evaluated. Lastly, the results of experiments performed using Power System Component Simulator are presented. This includes simulation of under frequency load shedding, frequency and voltage dependent characteristics of groups of load units, time characteristics of group of different load units in a chosen area.

Keywords: Power converter, Simulink real-time, MATLAB, load, tap controller.

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11354 Normalization Discriminant Independent Component Analysis

Authors: Liew Yee Ping, Pang Ying Han, Lau Siong Hoe, Ooi Shih Yin, Housam Khalifa Bashier Babiker

Abstract:

In face recognition, feature extraction techniques attempts to search for appropriate representation of the data. However, when the feature dimension is larger than the samples size, it brings performance degradation. Hence, we propose a method called Normalization Discriminant Independent Component Analysis (NDICA). The input data will be regularized to obtain the most reliable features from the data and processed using Independent Component Analysis (ICA). The proposed method is evaluated on three face databases, Olivetti Research Ltd (ORL), Face Recognition Technology (FERET) and Face Recognition Grand Challenge (FRGC). NDICA showed it effectiveness compared with other unsupervised and supervised techniques.

Keywords: Face recognition, small sample size, regularization, independent component analysis.

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11353 Removal of a Reactive Dye by Adsorption Utilizing Waste Aluminium Hydroxide Sludge as an Adsorbent

Authors: R. Songur, E. Bayraktar, U. Mehmetoglu

Abstract:

Removal of a reactive dye (Reactive blue 4) by adsorption utilizing waste aluminium hydroxide sludge as an adsorbent was investigated. The removal of the dye was optimized using response surface methodology (RSM). In the RSM experiments; initial dye concentration, adsorbent concentration and contact time were critical parameters. RSM experiments were performed at the range of initial dye concentration 31.82-368.18 mg/L, adsorbent concentration 3.18-36.82 g/L, contact time 15.82- 56.18 h. Optimum initial dye concentration, adsorbent concentration and contact time were obtained as 108.83 mg/L, 29.36 g/L and 33.57 h respectively. At these conditions, maximum removal of the dye was obtained as 95%. The experiments were performed at the optimum conditions to verify these results and the same results were obtained.

Keywords: Adsorption, Reactive blue 4, Response surface methodology (RSM), Waste aluminium hydroxide sludge

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11352 Low Cost Real Time Robust Identification of Impulsive Signals

Authors: R. Biondi, G. Dys, G. Ferone, T. Renard, M. Zysman

Abstract:

This paper describes an automated implementable system for impulsive signals detection and recognition. The system uses a Digital Signal Processing device for the detection and identification process. Here the system analyses the signals in real time in order to produce a particular response if needed. The system analyses the signals in real time in order to produce a specific output if needed. Detection is achieved through normalizing the inputs and comparing the read signals to a dynamic threshold and thus avoiding detections linked to loud or fluctuating environing noise. Identification is done through neuronal network algorithms. As a setup our system can receive signals to “learn” certain patterns. Through “learning” the system can recognize signals faster, inducing flexibility to new patterns similar to those known. Sound is captured through a simple jack input, and could be changed for an enhanced recording surface such as a wide-area recorder. Furthermore a communication module can be added to the apparatus to send alerts to another interface if needed.

Keywords: Sound Detection, Impulsive Signal, Background Noise, Neural Network.

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11351 Reduction of Linear Time-Invariant Systems Using Routh-Approximation and PSO

Authors: S. Panda, S. K. Tomar, R. Prasad, C. Ardil

Abstract:

Order reduction of linear-time invariant systems employing two methods; one using the advantages of Routh approximation and other by an evolutionary technique is presented in this paper. In Routh approximation method the denominator of the reduced order model is obtained using Routh approximation while the numerator of the reduced order model is determined using the indirect approach of retaining the time moments and/or Markov parameters of original system. By this method the reduced order model guarantees stability if the original high order model is stable. In the second method Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical examples.

Keywords: Model Order Reduction, Markov Parameters, Routh Approximation, Particle Swarm Optimization, Integral Squared Error, Steady State Stability.

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11350 Design and Manufacture of Non-Contact Moving Load for Experimental Analysis of Beams

Authors: FiroozBakhtiari-Nejad, Hamidreza Rostami, MeysamMirzaee, Mona Zandbaf

Abstract:

Dynamic tests are an important step of the design of engineering structures, because the accuracy of predictions of theoretical–numerical procedures can be assessed. In experimental test of moving loads that is one of the major research topics, the load is modeled as a simple moving mass or a small vehicle. This paper deals with the applicability of Non-contact Moving Load (NML) for vibration analysis. For this purpose, an experimental set-up is designed to generate the different types of NML including constant and harmonic. The proposed method relies on pressurized air which is useful, especially when dealing with fragile or sensitive structures. To demonstrate the performance of this system, the set-up is employedfor a modal analysis of a beam and detecting crack of the beam.The obtained results indicate that the experimental set-up for NML can be an attractive alternative to the moving load problems.

Keywords: Experimental analysis, Moving load, Non-contact excitation.

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11349 A Continuous Real-Time Analytic for Predicting Instability in Acute Care Rapid Response Team Activations

Authors: Ashwin Belle, Bryce Benson, Mark Salamango, Fadi Islim, Rodney Daniels, Kevin Ward

Abstract:

A reliable, real-time, and non-invasive system that can identify patients at risk for hemodynamic instability is needed to aid clinicians in their efforts to anticipate patient deterioration and initiate early interventions. The purpose of this pilot study was to explore the clinical capabilities of a real-time analytic from a single lead of an electrocardiograph to correctly distinguish between rapid response team (RRT) activations due to hemodynamic (H-RRT) and non-hemodynamic (NH-RRT) causes, as well as predict H-RRT cases with actionable lead times. The study consisted of a single center, retrospective cohort of 21 patients with RRT activations from step-down and telemetry units. Through electronic health record review and blinded to the analytic’s output, each patient was categorized by clinicians into H-RRT and NH-RRT cases. The analytic output and the categorization were compared. The prediction lead time prior to the RRT call was calculated. The analytic correctly distinguished between H-RRT and NH-RRT cases with 100% accuracy, demonstrating 100% positive and negative predictive values, and 100% sensitivity and specificity. In H-RRT cases, the analytic detected hemodynamic deterioration with a median lead time of 9.5 hours prior to the RRT call (range 14 minutes to 52 hours). The study demonstrates that an electrocardiogram (ECG) based analytic has the potential for providing clinical decision and monitoring support for caregivers to identify at risk patients within a clinically relevant timeframe allowing for increased vigilance and early interventional support to reduce the chances of continued patient deterioration.

Keywords: Critical care, early warning systems, emergency medicine, heart rate variability, hemodynamic instability, rapid response team.

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11348 Effectiveness of Cellular Phone with Active RFID Tag for Evacuation - The Case of Evacuation from the Underground Shopping Mall of Tenjin

Authors: Masatora Daito, Noriyuki Tanida

Abstract:

The underground shopping mall has the constructional problem of the fire evacuation. Also, the people sometimes lose their direction and information of current time in the mall. If the emergencies such as terrorist explosions or gas explosions are happened, they have to go out soon. Under such circumstances, inside of the mall has high risk for life. In this research, the authors propose a way that he/she can go out from the underground shopping mall quickly. If the narrow exits are discovered by using active RFID (Radio Frequency Identification) tags and using cellular phones, they can evacuate as soon as possible. To verify this hypothesis, the authors design the model and carry out the agent-based simulation. They treat, as a case study, the Tenjin mall in Fukuoka Prefecture in Japan. The result of the simulation is that the case of the pedestrian with using active RFID tags and cellular phones reduced the amount of time to spend on the evacuation. Even if the diffusion of RFID tags and cellular phones was not perfect, they could show the effectiveness of reducing the time of evacuation.

Keywords: Evacuation, active RFID tag and cellular phone, underground shopping mall, agent-based simulation.

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11347 Automatic Thresholding for Data Gap Detection for a Set of Sensors in Instrumented Buildings

Authors: Houda Najeh, Stéphane Ploix, Mahendra Pratap Singh, Karim Chabir, Mohamed Naceur Abdelkrim

Abstract:

Building systems are highly vulnerable to different kinds of faults and failures. In fact, various faults, failures and human behaviors could affect the building performance. This paper tackles the detection of unreliable sensors in buildings. Different literature surveys on diagnosis techniques for sensor grids in buildings have been published but all of them treat only bias and outliers. Occurences of data gaps have also not been given an adequate span of attention in the academia. The proposed methodology comprises the automatic thresholding for data gap detection for a set of heterogeneous sensors in instrumented buildings. Sensor measurements are considered to be regular time series. However, in reality, sensor values are not uniformly sampled. So, the issue to solve is from which delay each sensor become faulty? The use of time series is required for detection of abnormalities on the delays. The efficiency of the method is evaluated on measurements obtained from a real power plant: an office at Grenoble Institute of technology equipped by 30 sensors.

Keywords: Building system, time series, diagnosis, outliers, delay, data gap.

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11346 The Analysis of Two-Phase Jet in Pneumatic Powder Injection into Liquid Alloys

Authors: J. Jezierski, K. Janerka

Abstract:

The results of the two-phase gas-solid jet in pneumatic powder injection process analysis were presented in the paper. The researches were conducted on model set-up with high speed camera jet movement recording. Then the recorded material was analyzed to estimate main particles movement parameters. The values obtained from this direct measurement were compared to those calculated with the use of the well-known formulas for the two-phase flows (pneumatic conveying). Moreover, they were compared to experimental results previously achieved by authors. The analysis led to conclusions which to some extent changed the assumptions used even by authors, regarding the two-phase jet in pneumatic powder injection process. Additionally, the visual analysis of the recorded clips supplied data to make a more complete evaluation of the jet behavior in the lance outlet than before.

Keywords: injection lance, liquid metal, powder injection, slip velocity, two-phase jet

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11345 The Role of Social and Technical Lean Implementation in Improving Operational Performance: Insights from the Pharmaceutical Industry

Authors: M. Bernasconi, M. Grothkopp, T. Friedli

Abstract:

The objective of this paper is to examine the relationships between technical and social lean bundles as well as operational performance in the context of the pharmaceutical industry. We investigate the direct and mediating effects of the lean bundles Total Productive Maintenance (TPM), Total Quality Management (TQM), Just-In-Time (JIT), and Human Resource Management (HRM) on operational performance. Our analysis relies on 113 manufacturing facilities from the St.Gallen OPEX benchmarking database. The results show that HRM has a positive indirect effect on operational performance mediated by the technical lean bundles.

Keywords: Human resource management, operational performance, pharmaceutical industry, technical lean practices.

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11344 Comparison of Machine Learning and Deep Learning Algorithms for Automatic Classification of 80 Different Pollen Species

Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinié

Abstract:

Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. In this context, the automation of this task is urgent. In this work, we compare classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN and Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches.

Keywords: Image segmentation, stuck particles separation, Sobel operator, thresholding.

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11343 Characterization of Banana (Musa spp.) Pseudo-Stem and Fruit-Bunch-Stem as a Potential Renewable Energy Resource

Authors: Nurhayati Abdullah, Fauziah Sulaiman, Muhamad Azman Miskam, Rahmad Mohd Taib

Abstract:

Banana pseudo-stem and fruit-bunch-stem are agricultural residues that can be used for conversion to bio-char, biooil, and gases by using thermochemical process. The aim of this work is to characterize banana pseudo-stem and banana fruit-bunch-stem through proximate analysis, elemental analysis, chemical analysis, thermo-gravimetric analysis, and heating calorific value. The ash contents of the banana pseudo-stem and banana fruit-bunch-stem are 11.0 mf wt.% and 20.6 mf wt.%; while the carbon content of banana pseudo-stem and fruit-bunch-stem are 37.9 mf wt.% and 35.58 mf wt.% respectively. The molecular formulas for banana stem and banana fruit-bunch-stem are C24H33NO26 and C19H29NO33 respectively. The measured higher heating values of banana pseudostem and banana fruit-bunch-stem are 15.5MJ/kg and 12.7 MJ/kg respectively. By chemical analysis, the lignin, cellulose, and hemicellulose contents in the samples will also be presented. The feasibility of the banana wastes to be a feedstock for thermochemical process in comparison with other biomass will be discussed in this paper.

Keywords: Banana Waste, Biomass, Renewable Energy, Thermo-chemical Characteristics.

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11342 General Purpose Graphic Processing Units Based Real Time Video Tracking System

Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai

Abstract:

Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.

Keywords: Connected components, Embrace threads, Local weighted kernel, Structuring element.

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