Search results for: Time series
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7086

Search results for: Time series

6666 Analyzing The Effect of Variable Round Time for Clustering Approach in Wireless Sensor Networks

Authors: Vipin Pal, Girdhari Singh, R P Yadav

Abstract:

As wireless sensor networks are energy constraint networks so energy efficiency of sensor nodes is the main design issue. Clustering of nodes is an energy efficient approach. It prolongs the lifetime of wireless sensor networks by avoiding long distance communication. Clustering algorithms operate in rounds. Performance of clustering algorithm depends upon the round time. A large round time consumes more energy of cluster heads while a small round time causes frequent re-clustering. So existing clustering algorithms apply a trade off to round time and calculate it from the initial parameters of networks. But it is not appropriate to use initial parameters based round time value throughout the network lifetime because wireless sensor networks are dynamic in nature (nodes can be added to the network or some nodes go out of energy). In this paper a variable round time approach is proposed that calculates round time depending upon the number of active nodes remaining in the field. The proposed approach makes the clustering algorithm adaptive to network dynamics. For simulation the approach is implemented with LEACH in NS-2 and the results show that there is 6% increase in network lifetime, 7% increase in 50% node death time and 5% improvement over the data units gathered at the base station.

Keywords: Wireless Sensor Network, Clustering, Energy Efficiency, Round Time.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1790
6665 Community Behaviour and Support towards Island Tourism Development

Authors: Mohd Hafiz Hanafiah, Mohamad Abdullah Hemdi

Abstract:

The tourism industry has been widely used to eradicate poverty, due to the ability to generate income, employment as well as improving the quality of life. The industry has faced rapid growth with support from local residents who were involved directly and indirectly in tourism activities. Their support and behaviour does not only facilitate in boosting tourists’ satisfaction levels, but at the same time it contributes to the word-of-mouth promotion among the visitors. In order to ensure the success of the industry, the involvement and participation of the local communities are pertinent. This paper endeavours on local community attitudes, benefit and their support toward future tourism development in Tioman Island. Through a series of descriptive and factor analyses, various useful understandings on the issues of interest revealed. The findings indicated that community with personal benefit will support future development. Meanwhile, the finding also revealed that the community with negative perception still supports future tourism development due to their over reliance on this sector as their main source of income and destination development means.

Keywords: Personal benefit, perceived impact, future attitudes.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2775
6664 Cognitive SATP for Airborne Radar Based on Slow-Time Coding

Authors: Fanqiang Kong, Jindong Zhang, Daiyin Zhu

Abstract:

Space-time adaptive processing (STAP) techniques have been motivated as a key enabling technology for advanced airborne radar applications. In this paper, the notion of cognitive radar is extended to STAP technique, and cognitive STAP is discussed. The principle for improving signal-to-clutter ratio (SCNR) based on slow-time coding is given, and the corresponding optimization algorithm based on cyclic and power-like algorithms is presented. Numerical examples show the effectiveness of the proposed method.

Keywords: Space-time adaptive processing (STAP), signal-to-clutter ratio, slow-time coding.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 856
6663 Group Invariant Solutions of Nonlinear Time-Fractional Hyperbolic Partial Differential Equation

Authors: Anupma Bansal, Rajeev Budhiraja, Manoj Pandey

Abstract:

In this paper, we have investigated the nonlinear time-fractional hyperbolic partial differential equation (PDE) for its symmetries and invariance properties. With the application of this method, we have tried to reduce it to time-fractional ordinary differential equation (ODE) which has been further studied for exact solutions.

Keywords: Nonlinear time-fractional hyperbolic PDE, Lie Classical method, exact solutions.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1390
6662 Optimal Location of the I/O Point in the Parking System

Authors: Jing Zhang, Jie Chen

Abstract:

In this paper, we deal with the optimal I/O point location in an automated parking system. In this system, the S/R machine (storage and retrieve machine) travels independently in vertical and horizontal directions. Based on the characteristics of the parking system and the basic principle of AS/RS system (Automated Storage and Retrieval System), we obtain the continuous model in units of time. For the single command cycle using the randomized storage policy, we calculate the probability density function for the system travel time and thus we develop the travel time model. And we confirm that the travel time model shows a good performance by comparing with discrete case. Finally in this part, we establish the optimal model by minimizing the expected travel time model and it is shown that the optimal location of the I/O point is located at the middle of the left-hand above corner.

Keywords: Parking system, optimal location, response time, S/R machine.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 681
6661 New Delay-Dependent Stability Criteria for Neural Networks With Two Additive Time-varying Delay Components

Authors: Xingyuan Qu, Shouming Zhong

Abstract:

In this paper, the problem of stability criteria of neural networks (NNs) with two-additive time-varying delay compenents is investigated. The relationship between the time-varying delay and its lower and upper bounds is taken into account when estimating the upper bound of the derivative of Lyapunov functional. As a result, some improved delay stability criteria for NNs with two-additive time-varying delay components are proposed. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.

Keywords: Delay-dependent stability, time-varying delays, Lyapunov functional, linear matrix inequality (LMI).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1616
6660 Real-Time Defects Detection Algorithm for High-Speed Steel Bar in Coil

Authors: Se Ho Choi, Jong Pil Yun, Boyeul Seo, YoungSu Park, Sang Woo Kim

Abstract:

This paper presents a real-time defect detection algorithm for high-speed steel bar in coil. Because the target speed is very high, proposed algorithm should process quickly the large volumes of image for real-time processing. Therefore, defect detection algorithm should satisfy two conflicting requirements of reducing the processing time and improving the efficiency of defect detection. To enhance performance of detection, edge preserving method is suggested for noise reduction of target image. Finally, experiment results show that the proposed algorithm guarantees the condition of the real-time processing and accuracy of detection.

Keywords: Defect detection, edge preserving filter, real-time image processing, surface inspection.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3304
6659 Self-tuned LMS Algorithm for Sinusoidal Time Delay Tracking

Authors: Jonah Gamba

Abstract:

In this paper the problem of estimating the time delay between two spatially separated noisy sinusoidal signals by system identification modeling is addressed. The system is assumed to be perturbed by both input and output additive white Gaussian noise. The presence of input noise introduces bias in the time delay estimates. Normally the solution requires a priori knowledge of the input-output noise variance ratio. We utilize the cascade of a self-tuned filter with the time delay estimator, thus making the delay estimates robust to input noise. Simulation results are presented to confirm the superiority of the proposed approach at low input signal-to-noise ratios.

Keywords: LMS algorithm, Self-tuned filter, Systemidentification, Time delay estimation, .

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1593
6658 New Hybrid Method to Model Extreme Rainfalls

Authors: Y. Laaroussi, Z. Guennoun, A. Amar

Abstract:

Modeling and forecasting dynamics of rainfall occurrences constitute one of the major topics, which have been largely treated by statisticians, hydrologists, climatologists and many other groups of scientists. In the same issue, we propose, in the present paper, a new hybrid method, which combines Extreme Values and fractal theories. We illustrate the use of our methodology for transformed Emberger Index series, constructed basing on data recorded in Oujda (Morocco). The index is treated at first by Peaks Over Threshold (POT) approach, to identify excess observations over an optimal threshold u. In the second step, we consider the resulting excess as a fractal object included in one dimensional space of time. We identify fractal dimension by the box counting. We discuss the prospect descriptions of rainfall data sets under Generalized Pareto Distribution, assured by Extreme Values Theory (EVT). We show that, despite of the appropriateness of return periods given by POT approach, the introduction of fractal dimension provides accurate interpretation results, which can ameliorate apprehension of rainfall occurrences.

Keywords: Extreme values theory, Fractals dimensions, Peaks Over Threshold, Rainfall occurrences.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2103
6657 A General Model for Acquiring Knowledge

Authors: GuoQiang Peng, Yi Sun

Abstract:

In this paper, based on the work in [1], we further give a general model for acquiring knowledge, which first focuses on the research of how and when things involved in problems are made then describes the goals, the energy and the time to give an optimum model to decide how many related things are supposed to be involved in. Finally, we acquire knowledge from this model in which there are the attributes, actions and connections of the things involved at the time when they are born and the time in their life. This model not only improves AI theories, but also surely brings the effectiveness and accuracy for AI system because systems are given more knowledge when reasoning or computing is used to bring about results.

Keywords: Time, knowledge, model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1088
6656 Deep Learning Application for Object Image Recognition and Robot Automatic Grasping

Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

Abstract:

Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: Deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1105
6655 A Linearization and Decomposition Based Approach to Minimize the Non-Productive Time in Transfer Lines

Authors: Hany Osman, M. F. Baki

Abstract:

We address the balancing problem of transfer lines in this paper to find the optimal line balancing that minimizes the nonproductive time. We focus on the tool change time and face orientation change time both of which influence the makespane. We consider machine capacity limitations and technological constraints associated with the manufacturing process of auto cylinder heads. The problem is represented by a mixed integer programming model that aims at distributing the design features to workstations and sequencing the machining processes at a minimum non-productive time. The proposed model is solved by an algorithm established using linearization schemes and Benders- decomposition approach. The experiments show the efficiency of the algorithm in reaching the exact solution of small and medium problem instances at reasonable time.

Keywords: Transfer line balancing, Benders' decomposition, Linearization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1735
6654 Experimental Investigation on Solid Concentration in Gas-Solid Circulating Fluidized Bed for Methanol-to-Olefins Process

Authors: Biao Wang, Tao Li, Qi-Wen Sun, Wei-Yong Ying, Ding-Ye Fang

Abstract:

Methanol-to-olefins coupled with transformation of coal or natural gas to methanol gives an interesting and promising way to produce ethylene and propylene. To investigate solid concentration in gas-solid fluidized bed for methanol-to-olefins process catalyzed by SAPO-34, a cold model experiment system is established in this paper. The system comprises a gas distributor in a 300mm internal diameter and 5000mm height acrylic column, the fiber optic probe system and series of cyclones. The experiments are carried out at ambient conditions and under different superficial gas velocity ranging from 0.3930m/s to 0.7860m/s and different initial bed height ranging from 600mm to 1200mm. The effects of radial distance, axial distance, superficial gas velocity, initial bed height on solid concentration in the bed are discussed. The effects of distributor shape and porosity on solid concentration are also discussed. The time-averaged solid concentration profiles under different conditions are obtained.

Keywords: Branched pipe distributor, distributor porosity, gas-solid fluidized bed, solid concentration.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1465
6653 A Finite-Time Consensus Protocol of the Multi-Agent Systems

Authors: Xin-Lei Feng, Ting-Zhu Huang

Abstract:

According to conjugate gradient algorithm, a new consensus protocol algorithm of discrete-time multi-agent systems is presented, which can achieve finite-time consensus. Finally, a numerical example is given to illustrate our theoretical result.

Keywords: Consensus protocols; Graph theory; Multi-agent systems;Conjugate gradient algorithm; Finite-time.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2147
6652 Ultrasonographic Manifestations of Periventricular Leukomalacia in Preterm Neonates at Teaching Hospital Peradeniya, Sri Lanka

Authors: P. P. Chandrasekera, P. B. Hewavithana, S. Rosario, M. H. M. N. Hearth, D. M. R. D. Mirihella

Abstract:

Periventricular Leukomalacia (PVL) is a White Matter Injury (WMI) of preterm neonatal brain. Objectives of the study were to assess the neuro-developmental outcome at one year of age and to determine a good protocol of cranial ultrasonography to detect PVL. Two hundred and sixty four preterm neonates were included in the study. Series of cranial ultrasound scans were done by using a dedicated neonatal head probe 4-10 MHz of Logic e portable ultrasound scanner. Clinical history of seizures, abnormal head growth (hydrocephalus or microcephaly) and developmental milestones were assessed and neurological examinations were done until one year of age. Among live neonates, 57% who had cystic PVL (Grades 2 and 3) manifested as cerebral palsy. In conclusion cystic PVL has permanent neurological disabilities like cerebral palsy. Good protocol of real time cranial ultrasonography to detect PVL is to perform scans at least once a week until one month and at term (40 weeks of gestation).

Keywords: Cerebral palsy, cranial ultrasonography, Periventricular Leukomalacia (PVL), preterm neonates.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2578
6651 Artificial Neural Network Model Based Setup Period Estimation for Polymer Cutting

Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

Abstract:

The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: Artificial neural network, low series manufacturing, polymer cutting, setup period estimation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 980
6650 A Parallel Architecture for the Real Time Correction of Stereoscopic Images

Authors: Zohir Irki, Michel Devy

Abstract:

In this paper, we will present an architecture for the implementation of a real time stereoscopic images correction's approach. This architecture is parallel and makes use of several memory blocs in which are memorized pre calculated data relating to the cameras used for the acquisition of images. The use of reduced images proves to be essential in the proposed approach; the suggested architecture must so be able to carry out the real time reduction of original images.

Keywords: Image reduction, Real-time correction, Parallel architecture, Parallel treatment.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1113
6649 Changing Geomorphosites in a Changing Lake: How Environmental Changes in Urmia Lake Have Been Driving Vanishing or Creating of Geomorphosites

Authors: D. Mokhtari

Abstract:

Any variation in environmental characteristics of geomorphosites would lead to destabilisation of their geotouristic values all around the planet. The Urmia lake, with an area of approximately 5,500 km2 and a catchment area of 51,876 km2, and to which various reasons over time, especially in the last fifty years have seen a sharp decline and have decreased by about 93 % in two recent decades. These variations are not only driving significant changes in the morphology and ecology of the present lake landscape, but at the same time are shaping newly formed morphologies, which vanished some valuable geomorphosites or develop into smaller geomorphosites with significant value from a scientific and cultural point of view. This paper analyses and discusses features and evolution in several representative coastal and island geomorphosites. For this purpose, a total of 23 geomorphosites were studied in two data series (1963 and 2015) and the respective data were compared and analysed. The results showed, the total loss in geomorphosites area in a half century amounted to a loss of more than 90% of the valuable geomorphosites. Moreover, the comparison between the mean yearly value of coastal area lost over the entire period and the yearly average calculated for the shorter period (1998- 2014) clearly indicates a pattern of acceleration. This acceleration in the rate of reduction in lake area was seen in most of the southern half of the lake. In the region as well, the general water-level falling is not only causing the loss of a significant water resource, which is followed by major impact on regional ecosystems, but is also driving the most marked recent (last century) changes in the geotouristic landscapes. In fact, the disappearance of geomorphosites means the loss of tourism phenomenon. In this context attention must be paid to the question of conservation. The action needed to safeguard geomorphosites includes: 1) Preventive action, 2) Corrective action, and 3) Sharing knowledge.

Keywords: Changing lake, environmental changes, geomorphosite, northwest of Iran, Urmia lake.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1714
6648 A Reliable FPGA-based Real-time Optical-flow Estimation

Authors: M. M. Abutaleb, A. Hamdy, M. E. Abuelwafa, E. M. Saad

Abstract:

Optical flow is a research topic of interest for many years. It has, until recently, been largely inapplicable to real-time applications due to its computationally expensive nature. This paper presents a new reliable flow technique which is combined with a motion detection algorithm, from stationary camera image streams, to allow flow-based analyses of moving entities, such as rigidity, in real-time. The combination of the optical flow analysis with motion detection technique greatly reduces the expensive computation of flow vectors as compared with standard approaches, rendering the method to be applicable in real-time implementation. This paper describes also the hardware implementation of a proposed pipelined system to estimate the flow vectors from image sequences in real time. This design can process 768 x 576 images at a very high frame rate that reaches to 156 fps in a single low cost FPGA chip, which is adequate for most real-time vision applications.

Keywords: Optical flow, motion detection, real-time systems, FPGA.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1751
6647 Adaptive Discharge Time Control for Battery Operation Time Enhancement

Authors: Jong-Bae Lee, Seongsoo Lee

Abstract:

This paper proposes an adaptive discharge time control method to balance cell voltages in alternating battery cell discharging method. In the alternating battery cell discharging method, battery cells are periodically discharged in turn. Recovery effect increases battery output voltage while the given battery cell rests without discharging, thus battery operation time of target system increases. However, voltage mismatch between cells leads two problems. First, voltage difference between cells induces inter-cell current with wasted power. Second, it degrades battery operation time, since system stops when any cell reaches to the minimum system operation voltage. To solve this problem, the proposed method adaptively controls cell discharge time to equalize both cell voltages. In the proposed method, battery operation time increases about 19%, while alternating battery cell discharging method shows about 7% improvement.

Keywords: Battery, Recovery Effect, Low-Power, Alternating Battery Cell Discharging, Adaptive Discharge Time Control.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1502
6646 A Novel Source/Drain-to-Gate Non-overlap MOSFET to Reduce Gate Leakage Current in Nano Regime

Authors: Ashwani K. Rana, Narottam Chand, Vinod Kapoor

Abstract:

In this paper, gate leakage current has been mitigated by the use of novel nanoscale MOSFET with Source/Drain-to-Gate Non-overlapped and high-k spacer structure for the first time. A compact analytical model has been developed to study the gate leakage behaviour of proposed MOSFET structure. The result obtained has found good agreement with the Sentaurus Simulation. Fringing gate electric field through the dielectric spacer induces inversion layer in the non-overlap region to act as extended S/D region. It is found that optimal Source/Drain-to-Gate Non-overlapped and high-k spacer structure has reduced the gate leakage current to great extent as compared to those of an overlapped structure. Further, the proposed structure had improved off current, subthreshold slope and DIBL characteristic. It is concluded that this structure solves the problem of high leakage current without introducing the extra series resistance.

Keywords: Gate tunneling current, analytical model, spacer dielectrics, DIBL, subthreshold slope.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2608
6645 Forecasting Unemployment Rate in Selected European Countries Using Smoothing Methods

Authors: Ksenija Dumičić, Anita Čeh Časni, Berislav Žmuk

Abstract:

The aim of this paper is to select the most accurate forecasting method for predicting the future values of the unemployment rate in selected European countries. In order to do so, several forecasting techniques adequate for forecasting time series with trend component, were selected, namely: double exponential smoothing (also known as Holt`s method) and Holt-Winters` method which accounts for trend and seasonality. The results of the empirical analysis showed that the optimal model for forecasting unemployment rate in Greece was Holt-Winters` additive method. In the case of Spain, according to MAPE, the optimal model was double exponential smoothing model. Furthermore, for Croatia and Italy the best forecasting model for unemployment rate was Holt-Winters` multiplicative model, whereas in the case of Portugal the best model to forecast unemployment rate was Double exponential smoothing model. Our findings are in line with European Commission unemployment rate estimates.

Keywords: European Union countries, exponential smoothing methods, forecast accuracy unemployment rate.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3787
6644 Assessment of Thermal Comfort at Manual Car Body Assembly Workstation

Authors: A. R. Ismail, N. Jusoh, M. Z. Nuawi, B. M. Deros, N. K. Makhtar, M. N. A. Rahman

Abstract:

The objective of this study is to determine the thermal comfort among worker at Malaysian automotive industry. One critical manual assembly workstation had been chosen as a subject for the study. The human subjects for the study constitute operators at Body Assembly Station of the factory. The environment examined was the Relative Humidity (%), Airflow (m/s), Air Temperature (°C) and Radiant Temperature (°C) of the surrounding workstation area. The environmental factors were measured using Babuc apparatus, which is capable to measure simultaneously those mentioned environmental factors. The time series data of fluctuating level of factors were plotted to identify the significant changes of factors. Then thermal comfort of the workers were assessed by using ISO Standard 7730 Thermal sensation scale by using Predicted Mean Vote (PMV). Further Predicted percentage dissatisfied (PPD) is used to estimate the thermal comfort satisfaction of the occupant. Finally the PPD versus PMV were plotted to present the thermal comfort scenario of workers involved in related workstation. The result of PMV at the related industry is between 1.8 and 2.3, where PPD at that building is between 60% to 84%. The survey result indicated that the temperature more influenced comfort to the occupants

Keywords: Thermal, Comfort, Temperature, PPD, PMV

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1901
6643 Effects of Proactive Coping on Workplace Adaptation After Transition from College to Workplace

Authors: YiHui Cai, Takaya Kohyama

Abstract:

Proactive coping directed at an upcoming as opposed to an ongoing stressor, is a new focus in positive psychology. The present study explored the proactive coping-s effect on the workplace adaptation after transition from college to workplace. In order to demonstrate the influence process between them, we constructed the model of proactive coping style effecting the actual positive coping efforts and outcomes by mediating proactive competence during one year after the transition. Participants (n = 100) started to work right after graduating from college completed all the four time-s surveys --one month before (Time 0), one month after (Time 1), three months after (Time 2), and one year after (Time 3) the transition. Time 0 survey included the measurement of proactive coping style and competence. Time 1, 2, 3 surveys included the measurement of the challenge cognitive appraisal, problem solving coping strategy, and subjective workplace adaptation. The result indicated that proactive coping style effected newcomers- actual coping efforts and outcomes by mediating proactive coping competence. The result also showed that proactive coping competence directly promoted Time1-s actual positive coping efforts and outcomes, and indirectly promoted Time 2-s and Time 3-s.

Keywords: Proactive coping style, proactive coping competence, transition form college to workplace, workplace adaptation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2323
6642 Design and Implementation of a Neural Network for Real-Time Object Tracking

Authors: Javed Ahmed, M. N. Jafri, J. Ahmad, Muhammad I. Khan

Abstract:

Real-time object tracking is a problem which involves extraction of critical information from complex and uncertain imagedata. In this paper, we present a comprehensive methodology to design an artificial neural network (ANN) for a real-time object tracking application. The object, which is tracked for the purpose of demonstration, is a specific airplane. However, the proposed ANN can be trained to track any other object of interest. The ANN has been simulated and tested on the training and testing datasets, as well as on a real-time streaming video. The tracking error is analyzed with post-regression analysis tool, which finds the correlation among the calculated coordinates and the correct coordinates of the object in the image. The encouraging results from the computer simulation and analysis show that the proposed ANN architecture is a good candidate solution to a real-time object tracking problem.

Keywords: Image processing, machine vision, neural networks, real-time object tracking.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3514
6641 Operating Room Capacity Planning Decisions

Authors: Abdulrahim Shamayleh, John Fowler, Muhong Zhang

Abstract:

Operating rooms are important assets for hospitals as they generate the largest revenue and, at the same time, produce the largest cost for hospitals. The model presented in this paper helps make capacity planning decisions on the combination of open operating rooms (ORs) and estimated overtime to satisfy the allocated OR time to each specialty. The model combines both decisions on determining the amount of OR time to open and to allocate to different surgical specialties. The decisions made are based on OR costs, overutilization and underutilization costs, and contribution margins from allocating OR time. The results show the importance of having a good estimate of specialty usage of OR time to determine the amount of needed capacity and highlighted the tradeoff that the OR manager faces between opening more ORs versus extending the working time of the ORs already in use.

Keywords: capacity planning, contribution margins, operating room, overutilization

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2726
6640 Speaker Identification by Atomic Decomposition of Learned Features Using Computational Auditory Scene Analysis Principals in Noisy Environments

Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

Abstract:

Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: Time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1573
6639 Various Speech Processing Techniques For Speech Compression And Recognition

Authors: Jalal Karam

Abstract:

Years of extensive research in the field of speech processing for compression and recognition in the last five decades, resulted in a severe competition among the various methods and paradigms introduced. In this paper we include the different representations of speech in the time-frequency and time-scale domains for the purpose of compression and recognition. The examination of these representations in a variety of related work is accomplished. In particular, we emphasize methods related to Fourier analysis paradigms and wavelet based ones along with the advantages and disadvantages of both approaches.

Keywords: Time-Scale, Wavelets, Time-Frequency, Compression, Recognition.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2336
6638 Price Quoting Method for Contract Manufacturer

Authors: S. Homrossukon, W. Parinyasart

Abstract:

This is an applied research to propose the method for price quotation for a contract electronics manufacturer. It has had a precise price quoting method but such method could not quickly provide a result as the customer required. This reduces the ability of company to compete in this kind of business. In this case, the cause of long time quotation process was analyzed. A lot of product features have been demanded by customer. By checking routine processes, it was found that high fraction of quoting time was used for production time estimating which has effected to the manufacturing or production cost. Then the historical data of products including types, number of components, assembling method, and their assembling time were used to analyze the key components affecting to production time. The price quoting model then was proposed. The implementation of proposed model was able to remarkably reduce quoting time with an acceptable required precision.

Keywords: Price quoting, Contract manufacturer, Stepwise technique, Best subset technique.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4434
6637 Statistical and Land Planning Study of Tourist Arrivals in Greece during 2005-2016

Authors: Dimitra Alexiou

Abstract:

During the last 10 years, in spite of the economic crisis, the number of tourists arriving in Greece has increased, particularly during the tourist season from April to October. In this paper, the number of annual tourist arrivals is studied to explore their preferences with regard to the month of travel, the selected destinations, as well the amount of money spent. The collected data are processed with statistical methods, yielding numerical and graphical results. From the computation of statistical parameters and the forecasting with exponential smoothing, useful conclusions are arrived at that can be used by the Greek tourism authorities, as well as by tourist organizations, for planning purposes for the coming years. The results of this paper and the computed forecast can also be used for decision making by private tourist enterprises that are investing in Greece. With regard to the statistical methods, the method of Simple Exponential Smoothing of time series of data is employed. The search for a best forecast for 2017 and 2018 provides the value of the smoothing coefficient. For all statistical computations and graphics Microsoft Excel is used.

Keywords: Tourism, statistical methods, exponential smoothing, land spatial planning, economy, Microsoft Excel.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 714