Search results for: business data type
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9756

Search results for: business data type

6486 Electricity Price Forecasting: A Comparative Analysis with Shallow-ANN and DNN

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: Deep learning, artificial neural networks, energy price forecasting, Turkey.

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6485 The Implementation of the Multi-Agent Classification System (MACS) in Compliance with FIPA Specifications

Authors: Mohamed R. Mhereeg

Abstract:

The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). The Microsoft's .NET widows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.

Keywords: MACS, Implementation, Multi-Agent, SOA, Autonomous, WCF.

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6484 A Car Parking Monitoring System Using Wireless Sensor Networks

Authors: Jung-Ho Moon, Tae Kwon Ha

Abstract:

This paper presents a car parking monitoring system using wireless sensor networks. Multiple sensor nodes and a sink node, a gateway, and a server constitute a wireless network for monitoring a parking lot. Each of the sensor nodes is equipped with a 3-axis AMR sensor and deployed in the center of a parking space. Each sensor node reads its sensor values periodically and transmits the data to the sink node if the current and immediate past sensor values show a difference exceeding a threshold value. The sensor nodes and sink node use the 448 MHz band for wireless communication. Since RF transmission only occurs when sensor values show abrupt changes, the number of RF transmission operations is reduced and battery power can be conserved. The data from the sensor nodes reach the server via the sink node and gateway. The server determines which parking spaces are taken by cars based upon the received sensor data and reference values. The reference values are average sensor values measured by each sensor node when the corresponding parking spot is not occupied by a vehicle. Because the decision making is done by the server, the computational burden of the sensor node is relieved, which helps reduce the duty cycle of the sensor node.

Keywords: Car parking monitoring, magnetometer, sensor node, wireless sensor network.

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6483 Computer Aided Diagnosis of Polycystic Kidney Disease Using ANN

Authors: Anjan Babu G, Sumana G, Rajasekhar M

Abstract:

Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multilayered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Further, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: Dialysis, Hereditary, Transplantation, Polycystic, Pathogenesis.

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6482 Numerical Analysis of Laminar Mixed Convection within a Complex Geometry

Authors: Y. Lasbet, A. L. Boukhalkhal, K. Loubar

Abstract:

The study of mixed convection is, usually, focused on the straight channels in which the onset of the mixed convection is well defined as function of the ratio between Grashof number and Reynolds number, Gr/Re. This is not the case for a complex channel wherein the mixed convection is not sufficiently examined in the literature. Our paper focuses on the study of the mixed convection in a complex geometry in which our main contribution reveals that the critical value of the ratio Gr/Re for the onset of the mixed convection increases highly in the type of geometry contrary to the straight channel. Furthermore, the accentuated secondary flow in this geometry prevents the thermal stratification in the flow and consequently the buoyancy driven becomes negligible. To perform these objectives, a numerical study in complex geometry for several values of the ratio Gr/Re with prescribed wall heat flux (H2), was realized by using the CFD code.

Keywords: Complex geometry, heat transfer, laminar flow, mixed convection, Nusselt number.

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6481 Comparison of Multi-User Detectors of DS-CDMA System

Authors: Kavita Khairnar, Shikha Nema

Abstract:

DS-CDMA system is well known wireless technology. This system suffers from MAI (Multiple Access Interference) caused by Direct Sequence users. Multi-User Detection schemes were introduced to detect the users- data in presence of MAI. This paper focuses on linear multi-user detection schemes used for data demodulation. Simulation results depict the performance of three detectors viz-conventional detector, Decorrelating detector and Subspace MMSE (Minimum Mean Square Error) detector. It is seen that the performance of these detectors depends on the number of paths and the length of Gold code used.

Keywords: Cross Correlation Matrix, MAI, Multi-UserDetection, Multipath Effect.

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6480 A Small-Scale Knowledge Management System for a Service-Oriented Department

Authors: Eliza Mazmee Mazlan, K.S. Savita, Amir Hamzah Zalfakhar

Abstract:

This paper demonstrates an effort of a serviceoriented engineering department in improving the sharing and transfer of knowledge. Although the department consist of only six employees, but it provides services in various chemical application in an oil and gas business. The services provided span across Asia Pacific region mainly Indonesia, Myanmar, Vietnam, Brunei, Thailand and Singapore. Currently there are no effective tools or integrated systems that support the sharing or transfer and maintenance of knowledge so the department has considered preserving this valuable knowledge by developing a Knowledge Management System (KMS). This paper presents the development of a KMS to support the sharing of knowledge in a service-oriented engineering department of an oil and gas company. The embedded features in the KMS like blog and forum will encourage iterative process of knowledge sharing among the employees in the department. The information and knowledge being shared, discussed and communicated will be then achieved for future re-use. The re-use of the knowledge allows the department to reduce redundant efforts in providing consistent, up-to-date and cost effective of the best solution to the its clients.

Keywords: Knowledge management, knowledge managementsystem, knowledge barrier, knowledge sharing.

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6479 Initialization Method of Reference Vectors for Improvement of Recognition Accuracy in LVQ

Authors: Yuji Mizuno, Hiroshi Mabuchi

Abstract:

Initial values of reference vectors have significant influence on recognition accuracy in LVQ. There are several existing techniques, such as SOM and k-means, for setting initial values of reference vectors, each of which has provided some positive results. However, those results are not sufficient for the improvement of recognition accuracy. This study proposes an ACO-used method for initializing reference vectors with an aim to achieve recognition accuracy higher than those obtained through conventional methods. Moreover, we will demonstrate the effectiveness of the proposed method by applying it to the wine data and English vowel data and comparing its results with those of conventional methods.

Keywords: Clustering, LVQ, ACO, SOM, k-means.

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6478 Consolidating Service Engineering Ontologies Building Service Ontology from SOA Modeling Language (SoaML)

Authors: Purnomo Yustianto, Robin Doss, Suhardi, Novianto Budi Kurniawan

Abstract:

As a term for characterizing a process of devising a service system, the term ‘service engineering’ is still regarded as an ‘open’ research challenge due to unspecified details and conflicting perspectives. This paper presents consolidated service engineering ontologies in collecting, specifying and defining relationship between components pertinent within the context of service engineering. The ontologies are built by way of literature surveys from the collected conceptual works by collating various concepts into an integrated ontology. Two ontologies are produced: general service ontology and software service ontology. The software-service ontology is drawn from the informatics domain, while the generalized ontology of a service system is built from both a business management and the information system perspective. The produced ontologies are verified by exercising conceptual operationalizations of the ontologies in adopting several service orientation features and service system patterns. The proposed ontologies are demonstrated to be sufficient to serve as a basis for a service engineering framework.

Keywords: Engineering, ontology, service, SoaML.

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6477 Image Processing Approach for Detection of Three-Dimensional Tree-Rings from X-Ray Computed Tomography

Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

Abstract:

Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: Ring recognition, edge detection, X-ray computed tomography, dendrochronology.

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6476 Ion- Acoustic Solitary Waves in a Self- Gravitating Dusty Plasma Having Two-Temperature Electrons

Authors: S.N.Paul, G.Pakira, B.Paul, B.Ghosh

Abstract:

Nonlinear propagation of ion-acoustic waves in a selfgravitating dusty plasma consisting of warm positive ions, isothermal two-temperature electrons and negatively charged dust particles having charge fluctuations is studied using the reductive perturbation method. It is shown that the nonlinear propagation of ion-acoustic waves in such plasma can be described by an uncoupled third order partial differential equation which is a modified form of the usual Korteweg-deVries (KdV) equation. From this nonlinear equation, a new type of solution for the ion-acoustic wave is obtained. The effects of two-temperature electrons, gravity and dust charge fluctuations on the ion-acoustic solitary waves are discussed with possible applications.

Keywords: Charge fluctuations, gravitating dusty plasma, Ionacoustic solitary wave, Two-temperature electrons

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6475 Identifying the Best Global Solar Radiation Model for Hutat Suder, Saudi Arabia

Authors: H. Al-Sholigom, Z. Al-Mostafa

Abstract:

Many associations and experimental models have been developed to estimate solar radiation around the world. The duration of sunshine is the most commonly used parameter for estimating global solar radiation because it can be easily and reliably measured. To estimate the global monthly solar average on horizontal surfaces, we used 52 models with widely available data in Hutat Suder, Saudi Arabia. After testing the models, some were not suitable for use in this area, while others differed in performance. The best models have been identified.

Keywords: Earth, Global solar radiation, Hutat Suder, Saudi Arabia, sunshine, measured data.

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6474 Electricity Consumption Prediction Model using Neuro-Fuzzy System

Authors: Rahib Abiyev, Vasif H. Abiyev, C. Ardil

Abstract:

In this paper the development of neural network based fuzzy inference system for electricity consumption prediction is considered. The electricity consumption depends on number of factors, such as number of customers, seasons, type-s of customers, number of plants, etc. It is nonlinear process and can be described by chaotic time-series. The structure and algorithms of neuro-fuzzy system for predicting future values of electricity consumption is described. To determine the unknown coefficients of the system, the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The developed system is applied for predicting future values of electricity consumption of Northern Cyprus. The simulation of neuro-fuzzy system has been performed.

Keywords: Fuzzy logic, neural network, neuro-fuzzy system, neuro-fuzzy prediction.

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6473 Intrabody Communication Using Different Ground Configurations in Digital Door Lock

Authors: Daewook Kim, Gilwon Yoon

Abstract:

Intrabody communication (IBC) is a new way of transferring data using human body as a medium. Minute current can travel though human body without any harm. IBC can remove electrical wires for human area network. IBC can be also a secure communication network system unlike wireless networks which can be accessed by anyone with bad intentions. One of the IBC systems is based on frequency shift keying modulation where individual data are transmitted to the external devices for the purpose of secure access such as digital door lock. It was found that the quality of IBC data transmission was heavily dependent on ground configurations of electronic circuits. Reliable IBC transmissions were not possible when both of the transmitter and receiver used batteries as circuit power source. Transmission was reliable when power supplies were used as power source for both transmitting and receiving sites because the common ground was established through the grounds of instruments such as power supply and oscilloscope. This was due to transmission dipole size and the ground effects of floor and AC power line. If one site used battery as power source and the other site used the AC power as circuit power source, transmission was possible.

Keywords: Frequency shift keying, Ground, Intrabody, Communication, door lock.

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6472 Surface Roughness Effects in Pure Sliding EHL Line Contacts with Carreau-Type Shear-Thinning Lubricants

Authors: Punit Kumar, Niraj Kumar

Abstract:

The influence of transverse surface roughness on EHL characteristics has been investigated numerically using an extensive set of full EHL line contact simulations for shear-thinning lubricants under pure sliding condition. The shear-thinning behavior of lubricant is modeled using Carreau viscosity equation along with Doolittle-Tait equation for lubricant compressibility. The surface roughness is assumed to be sinusoidal and it is present on the stationary surface. It is found that surface roughness causes sharp pressure peaks along with reduction in central and minimum film thickness. With increasing amplitude of surface roughness, the minimum film thickness decreases much more rapidly as compared to the central film thickness.

Keywords: EHL, Carreau, Shear-thinning, Surface Roughness, Amplitude, Wavelength.

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6471 Cognitive Weighted Polymorphism Factor: A Comprehension Augmented Complexity Metric

Authors: T. Francis Thamburaj, A. Aloysius

Abstract:

Polymorphism is one of the main pillars of objectoriented paradigm. It induces hidden forms of class dependencies which may impact software quality, resulting in higher cost factor for comprehending, debugging, testing, and maintaining the software. In this paper, a new cognitive complexity metric called Cognitive Weighted Polymorphism Factor (CWPF) is proposed. Apart from the software structural complexity, it includes the cognitive complexity on the basis of type. The cognitive weights are calibrated based on 27 empirical studies with 120 persons. A case study and experimentation of the new software metric shows positive results. Further, a comparative study is made and the correlation test has proved that CWPF complexity metric is a better, more comprehensive, and more realistic indicator of the software complexity than Abreu’s Polymorphism Factor (PF) complexity metric.

Keywords: Cognitive complexity metric, cognitive weighted polymorphism factor, object-oriented metrics, polymorphism factor, software metrics.

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6470 Effect of Nanofluids on the Saturated Pool Film Boiling

Authors: Dogan Ciloglu, Abdurrahim Bolukbasi, Kemal Comakli

Abstract:

In this study, the effect of nanofluids on the pool film boiling was experimentally investigated at saturated condition under atmospheric pressure. For this purpose, four different water-based nanofluids (Al2O3, SiO2, TiO2 and CuO) with 0.1% particle volume fraction were prepared. To investigate the boiling heat transfer, a cylindrical rod with high temperature was used. The rod heated up to high temperatures was immersed into nanofluids. The center temperature of rod during the cooling process was recorded by using a K-type thermocouple. The quenching curves showed that the pool boiling heat transfer was strongly dependent on the nanoparticle materials. During the repetitive quenching tests, the cooling time decreased and thus, the film boiling vanished. Consequently, the primary reason of this was the change of the surface characteristics due to the nanoparticles deposition on the rod-s surface.

Keywords: Heat transfer, nanofluid, nanoparticles, pool film boiling

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6469 The Impact of Parent Involvement in Preschool Disabled Children

Authors: Sheng-Min Cheng

Abstract:

The purpose of this study was to investigate the relationship between parent involvement and preschool disabled children’s development. Parents of 3 year old disabled children (N=440) and 5 year old disabled children (N=937) participating in the Special Needs Education Longitudinal Study were interviewed or answered the web design questionnaire about their actions in parenting their disabled children. These children’s developments were also evaluated by their teachers. Data were analyzed using Structural Equation Modeling. Results were showed by tables and figures. Based on the results, the researcher made some suggestions for future studies.

Keywords: Child development, longitudinal data analysis, parent involvement, preschool disabled children.

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6468 Enabling Automated Deployment for Cluster Computing in Distributed PC Classrooms

Authors: Shuen-Tai Wang, Ying-Chuan Chen, Hsi-Ya Chang

Abstract:

The rapid improvement of the microprocessor and network has made it possible for the PC cluster to compete with conventional supercomputers. Lots of high throughput type of applications can be satisfied by using the current desktop PCs, especially for those in PC classrooms, and leave the supercomputers for the demands from large scale high performance parallel computations. This paper presents our development on enabling an automated deployment mechanism for cluster computing to utilize the computing power of PCs such as reside in PC classroom. After well deployment, these PCs can be transformed into a pre-configured cluster computing resource immediately without touching the existing education/training environment installed on these PCs. Thus, the training activities will not be affected by this additional activity to harvest idle computing cycles. The time and manpower required to build and manage a computing platform in geographically distributed PC classrooms also can be reduced by this development.

Keywords: PC cluster, automated deployment, cluster computing, PC classroom.

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6467 Endometrial Cancer Recognition via EEG Dependent upon 14-3-3 Protein Leading to an Ontological Diagnosis

Authors: Marios Poulos, Eirini Maliagani, Minas Paschopoulos, George Bokos

Abstract:

The purpose of my research proposal is to demonstrate that there is a relationship between EEG and endometrial cancer. The above relationship is based on an Aristotelian Syllogism; since it is known that the 14-3-3 protein is related to the electrical activity of the brain via control of the flow of Na+ and K+ ions and since it is also known that many types of cancer are associated with 14-3-3 protein, it is possible that there is a relationship between EEG and cancer. This research will be carried out by well-defined diagnostic indicators, obtained via the EEG, using signal processing procedures and pattern recognition tools such as neural networks in order to recognize the endometrial cancer type. The current research shall compare the findings from EEG and hysteroscopy performed on women of a wide age range. Moreover, this practice could be expanded to other types of cancer. The implementation of this methodology will be completed with the creation of an ontology. This ontology shall define the concepts existing in this research-s domain and the relationships between them. It will represent the types of relationships between hysteroscopy and EEG findings.

Keywords: Bioinformatics, Protein 14-3-3, EEG, Endometrial cancer, Ontology.

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6466 The Impact of the Number of Neurons in the Hidden Layer on the Performance of MLP Neural Network: Application to the Fast Identification of Toxic Gases

Authors: Slimane Ouhmad, Abdellah Halimi

Abstract:

In this work, neural networks methods MLP type were applied to a database from an array of six sensors for the detection of three toxic gases. The choice of the number of hidden layers and the weight values are influential on the convergence of the learning algorithm. We proposed, in this article, a mathematical formula to determine the optimal number of hidden layers and good weight values based on the method of back propagation of errors. The results of this modeling have improved discrimination of these gases and optimized the computation time. The model presented here has proven to be an effective application for the fast identification of toxic gases.

Keywords: Back-propagation, Computing time, Fast identification, MLP neural network, Number of neurons in the hidden layer.

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6465 A New Approach to Design Policies for the Adoption of Alternative Fuel-Technology Powertrains

Authors: Reza Fazeli, Vitor Leal, Jorge Pinho de Sousa

Abstract:

Planning the transition period for the adoption of alternative fuel-technology powertrains is a challenging task that requires sophisticated analysis tools. In this study, a system dynamic approach was applied to analyze the bi-directional interaction between the development of the refueling station network and vehicle sales. Besides, the developed model was used to estimate the transition cost to reach a predefined target (share of alternative fuel vehicles) in different scenarios. Several scenarios have been analyzed to investigate the effectiveness and cost of incentives on the initial price of vehicles, and on the evolution of fuel and refueling stations. Obtained results show that a combined set of incentives will be more effective than just a single specific type of incentives.

Keywords: adoption of Alternative Fuel Vehicles, System Dynamic Analysis, Plug-in Hybrid Vehicles

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6464 Data Envelopment Analysis with Partially Perfect Objects

Authors: Alexander Y. Vaninsky

Abstract:

This paper presents a simplified version of Data Envelopment Analysis (DEA) - a conventional approach to evaluating the performance and ranking of competitive objects characterized by two groups of factors acting in opposite directions: inputs and outputs. DEA with a Perfect Object (DEA PO) augments the group of actual objects with a virtual Perfect Object - the one having greatest outputs and smallest inputs. It allows for obtaining an explicit analytical solution and making a step to an absolute efficiency. This paper develops this approach further and introduces a DEA model with Partially Perfect Objects. DEA PPO consecutively eliminates the smallest relative inputs or greatest relative outputs, and applies DEA PO to the reduced collections of indicators. The partial efficiency scores are combined to get the weighted efficiency score. The computational scheme remains simple, like that of DEA PO, but the advantage of the DEA PPO is taking into account all of the inputs and outputs for each actual object. Firm evaluation is considered as an example.

Keywords: Data Envelopment Analysis, Perfect object, Partially perfect object, Partial efficiency, Explicit solution, Simplified algorithm.

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6463 Chemical Reaction Algorithm for Expectation Maximization Clustering

Authors: Li Ni, Pen ManMan, Li KenLi

Abstract:

Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: Chemical reaction optimization, expectation maximization, initial, objective function clustering.

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6462 The Direct Updating of Damping and Gyroscopic Matrices using Incomplete Complex Test Data

Authors: Jiashang Jiang, Yongxin Yuan

Abstract:

In this paper we develop an efficient numerical method for the finite-element model updating of damped gyroscopic systems based on incomplete complex modal measured data. It is assumed that the analytical mass and stiffness matrices are correct and only the damping and gyroscopic matrices need to be updated. By solving a constrained optimization problem, the optimal corrected symmetric damping matrix and skew-symmetric gyroscopic matrix complied with the required eigenvalue equation are found under a weighted Frobenius norm sense.

Keywords: Model updating, damped gyroscopic system, partially prescribed spectral information.

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6461 A Low-Power Two-Stage Seismic Sensor Scheme for Earthquake Early Warning System

Authors: Arvind Srivastav, Tarun Kanti Bhattacharyya

Abstract:

The north-eastern, Himalayan, and Eastern Ghats Belt of India comprise of earthquake-prone, remote, and hilly terrains. Earthquakes have caused enormous damages in these regions in the past. A wireless sensor network based earthquake early warning system (EEWS) is being developed to mitigate the damages caused by earthquakes. It consists of sensor nodes, distributed over the region, that perform majority voting of the output of the seismic sensors in the vicinity, and relay a message to a base station to alert the residents when an earthquake is detected. At the heart of the EEWS is a low-power two-stage seismic sensor that continuously tracks seismic events from incoming three-axis accelerometer signal at the first-stage, and, in the presence of a seismic event, triggers the second-stage P-wave detector that detects the onset of P-wave in an earthquake event. The parameters of the P-wave detector have been optimized for minimizing detection time and maximizing the accuracy of detection.Working of the sensor scheme has been verified with seven earthquakes data retrieved from IRIS. In all test cases, the scheme detected the onset of P-wave accurately. Also, it has been established that the P-wave onset detection time reduces linearly with the sampling rate. It has been verified with test data; the detection time for data sampled at 10Hz was around 2 seconds which reduced to 0.3 second for the data sampled at 100Hz.

Keywords: Earthquake early warning system, EEWS, STA/LTA, polarization, wavelet, event detector, P-wave detector.

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6460 Liquid-Liquid Equilibrium Data for Butan-2-ol - Ethanol - Water, Pentan-1-ol - Ethanol - Water and Toluene - Acetone - Water Systems

Authors: Tinuade Jolaade Afolabi, Theresa Ibibia Edewor

Abstract:

Experimental liquid-liquid equilibra of butan-2-ol - ethanol -water; pentan-1-ol - ethanol - water and toluene - acetone - water ternary systems were investigated at (25oC). The reliability of the experimental tie-line data was ascertained by using Othmer-Tobias and Hand plots. The distribution coefficients (D) and separation factors (S) of the immiscibility region were evaluated for the three systems.

Keywords: Distribution coefficient, Liquid-liquid equilibrium, separation factors, thermodynamic models

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6459 Estimation of Methane from Hydrocarbon Exploration and Production in India

Authors: A. K. Pathak, K. Ojha

Abstract:

Methane is the second most important greenhouse gas (GHG) after carbon dioxide. Amount of methane emission from energy sector is increasing day by day with various activities. In present work, various sources of methane emission from upstream, middle stream and downstream of oil & gas sectors are identified and categorised as per IPCC-2006 guidelines. Data were collected from various oil & gas sector like (i) exploration & production of oil & gas (ii) supply through pipelines (iii) refinery throughput & production (iv) storage & transportation (v) usage. Methane emission factors for various categories were determined applying Tier-II and Tier-I approach using the collected data. Total methane emission from Indian Oil & Gas sectors was thus estimated for the year 1990 to 2007.

Keywords: Carbon credit, Climate change, Methane emission, Oil & Gas production

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6458 Rainfall and Flood Forecast Models for Better Flood Relief Plan of the Mae Sot Municipality

Authors: S. Chuenchooklin, S. Taweepong, U. Pangnakorn

Abstract:

This research was conducted in the Mae Sot Watershed where located in the Moei River Basin at the Upper Salween River Basin in Tak Province, Thailand. The Mae Sot Municipality is the largest urban area in Tak Province and situated in the midstream of the Mae Sot Watershed. It usually faces flash flood problem after heavy rain due to poor flood management has been reported since economic rapidly bloom up in recent years. Its catchment can be classified as ungauged basin with lack of rainfall data and no any stream gaging station was reported. It was attached by most severely flood events in 2013 as the worst studied case for all those communities in this municipality. Moreover, other problems are also faced in this watershed, such shortage water supply for domestic consumption and agriculture utilizations including a deterioration of water quality and landslide as well. The research aimed to increase capability building and strengthening the participation of those local community leaders and related agencies to conduct better water management in urban area was started by mean of the data collection and illustration of the appropriated application of some short period rainfall forecasting model as they aim for better flood relief plan and management through the hydrologic model system and river analysis system programs. The authors intended to apply the global rainfall data via the integrated data viewer (IDV) program from the Unidata with the aim for rainfall forecasting in a short period of 7-10 days in advance during rainy season instead of real time record. The IDV product can be present in an advance period of rainfall with time step of 3-6 hours was introduced to the communities. The result can be used as input data to the hydrologic modeling system model (HEC-HMS) for synthesizing flood hydrographs and use for flood forecasting as well. The authors applied the river analysis system model (HEC-RAS) to present flood flow behaviors in the reach of the Mae Sot stream via the downtown of the Mae Sot City as flood extents as the water surface level at every cross-sectional profiles of the stream. Both models of HMS and RAS were tested in 2013 with observed rainfall and inflow-outflow data from the Mae Sot Dam. The result of HMS showed fit to the observed data at the dam and applied at upstream boundary discharge to RAS in order to simulate flood extents and tested in the field, and the result found satisfying. The product of rainfall from IDV was fair while compared with observed data. However, it is an appropriate tool to use in the ungauged catchment to use with flood hydrograph and river analysis models for future efficient flood relief plan and management.

Keywords: Global rainfall, flood forecasting, hydrologic modeling system, river analysis system.

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6457 Flexible Development and Calculation of Contract Logistics Services

Authors: T. Spiegel, J. Siegmann, C. F. Durach

Abstract:

Challenges resulting from an international and dynamic business environment are increasingly being passed on from manufacturing companies to external service providers. Especially providers of complex, customer-specific industry services have to cope with continuously changing requirements. This is particularly true for contract logistics service providers. They are forced to develop efficient and highly flexible structures and strategies to meet their customer’s needs. One core element they have to focus on is the reorganization of their service development and sales process. Based on an action research approach, this study develops and tests a concept to streamline tender management for contract logistics service providers. The concept of modularized service architecture is deployed in order to derive a practice-oriented approach for the modularization of complex service portfolios and the design of customized quotes. These findings are evaluated regarding their applicability in other service sectors and practical recommendations are given.

Keywords: Contract Logistics, Modularization, Service Development, Tender Management.

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