Search results for: high temperature exposure
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7760

Search results for: high temperature exposure

2810 Hybrid Authentication Scheme for Graphical Password Using QR Code and Integrated Sound Signature

Authors: Salim Istyaq, Mohammad Sarosh Umar

Abstract:

Today, the mankind is in the stage of development, every day comes with new proposal of technology, in order to secure these types of technology, we also prepare high yielding security modules to conserve these resources. The capacity of human brain to recognize anything is far more than any species; this is all due to our developing cycle of curiosity. In this paper, we proposed a scheme based on graphical password using QR Code which provides more security to the recent online system. It also contains a supportive sound signature. In this system, authentication is done using sequence of images in QR code form. Users select one click-point per image with the help of QR scanner or recognizer. The encoded phrase in a QR code emphasizes the minimum probability of attacking via shoulder surfing or other attacks.

Keywords: Graphical password, QR code, sound signature, image authentication, cued click point.

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2809 Navigation and Guidance System Architectures for Small Unmanned Aircraft Applications

Authors: Roberto Sabatini, Celia Bartel, Anish Kaharkar, Tesheen Shaid, Subramanian Ramasamy

Abstract:

Two multisensor system architectures for navigation and guidance of small Unmanned Aircraft (UA) are presented and compared. The main objective of our research is to design a compact, light and relatively inexpensive system capable of providing the required navigation performance in all phases of flight of small UA, with a special focus on precision approach and landing, where Vision Based Navigation (VBN) techniques can be fully exploited in a multisensor integrated architecture. Various existing techniques for VBN are compared and the Appearance-Based Navigation (ABN) approach is selected for implementation. Feature extraction and optical flow techniques are employed to estimate flight parameters such as roll angle, pitch angle, deviation from the runway centreline and body rates. Additionally, we address the possible synergies of VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU (Micro-Electromechanical System Inertial Measurement Unit) sensors, and the use of Aircraft Dynamics Model (ADM) to provide additional information suitable to compensate for the shortcomings of VBN and MEMS-IMU sensors in high-dynamics attitude determination tasks. An Extended Kalman Filter (EKF) is developed to fuse the information provided by the different sensors and to provide estimates of position, velocity and attitude of the UA platform in real-time. The key mathematical models describing the two architectures i.e., VBN-IMU-GNSS (VIG) system and VIGADM (VIGA) system are introduced. The first architecture uses VBN and GNSS to augment the MEMS-IMU. The second mode also includes the ADM to provide augmentation of the attitude channel. Simulation of these two modes is carried out and the performances of the two schemes are compared in a small UA integration scheme (i.e., AEROSONDE UA platform) exploring a representative cross-section of this UA operational flight envelope, including high dynamics manoeuvres and CAT-I to CAT-III precision approach tasks. Simulation of the first system architecture (i.e., VIG system) shows that the integrated system can reach position, velocity and attitude accuracies compatible with the Required Navigation Performance (RNP) requirements. Simulation of the VIGA system also shows promising results since the achieved attitude accuracy is higher using the VBN-IMU-ADM than using VBN-IMU only. A comparison of VIG and VIGA system is also performed and it shows that the position and attitude accuracy of the proposed VIG and VIGA systems are both compatible with the RNP specified in the various UA flight phases, including precision approach down to CAT-II.

Keywords: Global Navigation Satellite System (GNSS), Lowcost Navigation Sensors, MEMS Inertial Measurement Unit (IMU), Unmanned Aerial Vehicle, Vision Based Navigation.

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2808 A Frame Work for the Development of a Suitable Method to Find Shoot Length at Maturity of Mustard Plant Using Soft Computing Model

Authors: Satyendra Nath Mandal, J. Pal Choudhury, Dilip De, S. R. Bhadra Chaudhuri

Abstract:

The production of a plant can be measured in terms of seeds. The generation of seeds plays a critical role in our social and daily life. The fruit production which generates seeds, depends on the various parameters of the plant, such as shoot length, leaf number, root length, root number, etc When the plant is growing, some leaves may be lost and some new leaves may appear. It is very difficult to use the number of leaves of the tree to calculate the growth of the plant.. It is also cumbersome to measure the number of roots and length of growth of root in several time instances continuously after certain initial period of time, because roots grow deeper and deeper under ground in course of time. On the contrary, the shoot length of the tree grows in course of time which can be measured in different time instances. So the growth of the plant can be measured using the data of shoot length which are measured at different time instances after plantation. The environmental parameters like temperature, rain fall, humidity and pollution are also play some role in production of yield. The soil, crop and distance management are taken care to produce maximum amount of yields of plant. The data of the growth of shoot length of some mustard plant at the initial stage (7,14,21 & 28 days after plantation) is available from the statistical survey by a group of scientists under the supervision of Prof. Dilip De. In this paper, initial shoot length of Ken( one type of mustard plant) has been used as an initial data. The statistical models, the methods of fuzzy logic and neural network have been tested on this mustard plant and based on error analysis (calculation of average error) that model with minimum error has been selected and can be used for the assessment of shoot length at maturity. Finally, all these methods have been tested with other type of mustard plants and the particular soft computing model with the minimum error of all types has been selected for calculating the predicted data of growth of shoot length. The shoot length at the stage of maturity of all types of mustard plants has been calculated using the statistical method on the predicted data of shoot length.

Keywords: Fuzzy time series, neural network, forecasting error, average error.

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2807 Investigating the Process Kinetics and Nitrogen Gas Production in Anammox Hybrid Reactor with Special Emphasis on the Role of Filter Media

Authors: Swati Tomar, Sunil Kumar Gupta

Abstract:

Anammox is a novel and promising technology that has changed the traditional concept of biological nitrogen removal. The process facilitates direct oxidation of ammonical nitrogen under anaerobic conditions with nitrite as an electron acceptor without addition of external carbon sources. The present study investigated the feasibility of Anammox Hybrid Reactor (AHR) combining the dual advantages of suspended and attached growth media for biodegradation of ammonical nitrogen in wastewater. Experimental unit consisted of 4 nos. of 5L capacity AHR inoculated with mixed seed culture containing anoxic and activated sludge (1:1). The process was established by feeding the reactors with synthetic wastewater containing NH4-H and NO2-N in the ratio 1:1 at HRT (hydraulic retention time) of 1 day. The reactors were gradually acclimated to higher ammonium concentration till it attained pseudo steady state removal at a total nitrogen concentration of 1200 mg/l. During this period, the performance of the AHR was monitored at twelve different HRTs varying from 0.25-3.0 d with increasing NLR from 0.4 to 4.8 kg N/m3d. AHR demonstrated significantly higher nitrogen removal (95.1%) at optimal HRT of 1 day. Filter media in AHR contributed an additional 27.2% ammonium removal in addition to 72% reduction in the sludge washout rate. This may be attributed to the functional mechanism of filter media which acts as a mechanical sieve and reduces the sludge washout rate many folds. This enhances the biomass retention capacity of the reactor by 25%, which is the key parameter for successful operation of high rate bioreactors. The effluent nitrate concentration, which is one of the bottlenecks of anammox process was also minimised significantly (42.3-52.3 mg/L). Process kinetics was evaluated using first order and Grau-second order models. The first-order substrate removal rate constant was found as 13.0 d-1. Model validation revealed that Grau second order model was more precise and predicted effluent nitrogen concentration with least error (1.84±10%). A new mathematical model based on mass balance was developed to predict N2 gas in AHR. The mass balance model derived from total nitrogen dictated significantly higher correlation (R2=0.986) and predicted N2 gas with least error of precision (0.12±8.49%). SEM study of biomass indicated the presence of heterogeneous population of cocci and rod shaped bacteria of average diameter varying from 1.2-1.5 mm. Owing to enhanced NRE coupled with meagre production of effluent nitrate and its ability to retain high biomass, AHR proved to be the most competitive reactor configuration for dealing with nitrogen laden wastewater.

Keywords: Anammox, filter media, kinetics, nitrogen removal.

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2806 Uplink Throughput Prediction in Cellular Mobile Networks

Authors: Engin Eyceyurt, Josko Zec

Abstract:

The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: Drive test, LTE, machine learning, uplink throughput prediction.

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2805 Nanotechnology Innovations for the Sustainable Buildings of the Future

Authors: Aysin Sev, Meltem Ezel

Abstract:

Sustainability, being the urgent issue of our time, is closely related with the innovations in technology. Nanotechnology (NT), although not a new science, can be regarded relatively a new science for buildings with brand new materials and applications. This paper tends to give a research review of current and near future applications of nanotechnology (NT) for achieving high-performance and healthy buildings for a sustainable future. In the introduction, the driving forces for the sustainability of construction industry are explained. Then, the term NT is defined, and significance of innovations in NT for a sustainable construction industry is revealed. After presenting the application areas of NT and nanomaterials for buildings with a number of cases, challenges in the adoption of this technology are put forward, and finally the impacts of nanoparticles and nanomaterials on human health and environment are discussed.

Keywords: Nanomaterial, self-healing concrete, self-cleaning sensor, nano sensor, steel, wood, aerogel, flexible solar panel.

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2804 The Use of FBC Ash for Preparation of Types of Hydraulic Binders Similar to Portland Cement

Authors: Karel Dvořák, Karel Kulísek, Radek Magrla

Abstract:

The reduction of greenhouse gases emissions is highly discussed ecological theme at present. In addition to power industry also main production sectors of binders, i.e. cement, air and hydraulic lime are very sensitive to these questions. One of the possibilities how CO2 emissions can be reduced directly at clinker burnout is represented by partial substitution of lime with a material containing limy ions at absence of carbonate group. Fluidised fly ash is one of such potential raw materials where CaO can be found free and also bound in anhydrite, CaSO4. At application of FBC (fluidized bed combustion) fly ash with approximate 20% CaO content and its dosing ratio to high percent lime 1:2, corresponding stechiometrically to the preparation of raw material powder, approximately 0,37 t CO2 per 1 ton of one-component cement would be released at clinker burnout compared to 0,46 t CO2 when orthodox raw materials are used. The reduction of CO2 emissions thus could reach even 20%.

Keywords: FBC ash, cement, hydraulic binders.

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2803 Parametric Analysis on Information Technology Adoption and Organizational Efficiency in Northern Nigeria

Authors: A. Y. Dutse, S. I. Ningi

Abstract:

The adoption and diffusion of Information Technology (IT) is one of the fastest growing trends in organizations operating within Nigeria’s economy. Public and private organizations make huge capital investments in an attempt acquire and adopt the state-of-the-art IT for improving operational efficiency. In this study the level of IT adoption is considered the primary driver of efficiency witnessed by organizations. The research gathered data on the intensity of IT usage, and resultant efficiency increase in the organizations’ operations. The data was analyzed using multiple regression analysis and reveals that high level of IT usage has enhance efficiency of private and public organizations in Northern part of Nigeria with organizations having strategic intent on IT adoption indicating higher efficiency gains.

Keywords: IT Adoption, Nigeria, Organizational efficiency.

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2802 Cardiac Biosignal and Adaptation in Confined Nuclear Submarine Patrol

Authors: B. Lefranc, C. Aufauvre-Poupon, C. Martin-Krumm, M. Trousselard

Abstract:

Isolated and confined environments (ICE) present several challenges which may adversely affect human’s psychology and physiology. Submariners in Sub-Surface Ballistic Nuclear (SSBN) mission exposed to these environmental constraints must be able to perform complex tasks as part of their normal duties, as well as during crisis periods when emergency actions are required or imminent. The operational and environmental constraints they face contribute to challenge human adaptability. The impact of such a constrained environment has yet to be explored. Establishing a knowledge framework is a determining factor, particularly in view of the next long space travels. Ensuring that the crews are maintained in optimal operational conditions is a real challenge because the success of the mission depends on them. This study focused on the evaluation of the impact of stress on mental health and sensory degradation of submariners during a mission on SSBN using cardiac biosignal (heart rate variability, HRV) clustering. This is a pragmatic exploratory study of a prospective cohort included 19 submariner volunteers. HRV was recorded at baseline to classify by clustering the submariners according to their stress level based on parasympathetic (Pa) activity. Impacts of high Pa (HPa) versus low Pa (LPa) level at baseline were assessed on emotional state and sensory perception (interoception and exteroception) as a cardiac biosignal during the patrol and at a recovery time one month after. Whatever the time, no significant difference was found in mental health between groups. There are significant differences in the interoceptive, exteroceptive and physiological functioning during the patrol and at recovery time. To sum up, compared to the LPa group, the HPa maintains a higher level in psychosensory functioning during the patrol and at recovery but exhibits a decrease in Pa level. The HPa group has less adaptable HRV characteristics, less unpredictability and flexibility of cardiac biosignals while the LPa group increases them during the patrol and at recovery time. This dissociation between psychosensory and physiological adaptation suggests two treatment modalities for ICE environments. To our best knowledge, our results are the first to highlight the impact of physiological differences in the HRV profile on the adaptability of submariners. Further studies are needed to evaluate the negative emotional and cognitive effects of ICEs based on the cardiac profile. Artificial intelligence offers a promising future for maintaining high level of operational conditions. These future perspectives will not only allow submariners to be better prepared, but also to design feasible countermeasures that will help support analog environments that bring us closer to a trip to Mars.

Keywords: Adaptation, exteroception, HRV, ICE, interoception, SSBN.

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2801 Efficient Signal Detection Using QRD-M Based On Channel Condition in MIMO-OFDM System

Authors: Jae-Jeong Kim, Ki-Ro Kim, Hyoung-Kyu Song

Abstract:

In this paper, we propose an efficient signal detector that switches M parameter of QRD-M detection scheme is proposed for MIMO-OFDM system. The proposed detection scheme calculates the threshold by 1-norm condition number and then switches M parameter of QRD-M detection scheme according to channel information. If channel condition is bad, the parameter M is set to high value to increase the accuracy of detection. If channel condition is good, the parameter M is set to low value to reduce complexity of detection. Therefore, the proposed detection scheme has better tradeoff between BER performance and complexity than the conventional detection scheme. The simulation result shows that the complexity of proposed detection scheme is lower than QRD-M detection scheme with similar BER performance.

Keywords: MIMO-OFDM, QRD-M, Channel condition.

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2800 Effect of Speed and Torque on Statistical Parameters in Tapered Bearing Fault Detection

Authors: Sylvester A. Aye, Philippus S. Heyns

Abstract:

The effect of the rotational speed and axial torque on the diagnostics of tapered rolling element bearing defects was investigated. The accelerometer was mounted on the bearing housing and connected to Sound and Vibration Analyzer (SVAN 958) and was used to measure the accelerations from the bearing housing. The data obtained from the bearing was processed to detect damage of the bearing using statistical tools and the results were subsequently analyzed to see if bearing damage had been captured. From this study it can be seen that damage is more evident when the bearing is loaded. Also, at the incipient stage of damage the crest factor and kurtosis values are high but as time progresses the crest factors and kurtosis values decrease whereas the peak and RMS values are low at the incipient stage but increase with damage.

Keywords: crest factor, damage detection, kurtosis, RMS, tapered roller bearing.

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2799 Analysis of Physicochemical Properties on Prediction of R5, X4 and R5X4 HIV-1 Coreceptor Usage

Authors: Kai-Ti Hsu, Hui-Ling Huang, Chun-Wei Tung, Yi-Hsiung Chen, Shinn-Ying Ho

Abstract:

Bioinformatics methods for predicting the T cell coreceptor usage from the array of membrane protein of HIV-1 are investigated. In this study, we aim to propose an effective prediction method for dealing with the three-class classification problem of CXCR4 (X4), CCR5 (R5) and CCR5/CXCR4 (R5X4). We made efforts in investigating the coreceptor prediction problem as follows: 1) proposing a feature set of informative physicochemical properties which is cooperated with SVM to achieve high prediction test accuracy of 81.48%, compared with the existing method with accuracy of 70.00%; 2) establishing a large up-to-date data set by increasing the size from 159 to 1225 sequences to verify the proposed prediction method where the mean test accuracy is 88.59%, and 3) analyzing the set of 14 informative physicochemical properties to further understand the characteristics of HIV-1coreceptors.

Keywords: Coreceptor, genetic algorithm, HIV-1, SVM, physicochemical properties, prediction.

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2798 Using Interval Constrained Petri Nets for the Fuzzy Regulation of Quality: Case of Assembly Process Mechanics

Authors: Nabli L., Dhouibi H., Collart Dutilleul S., Craye E.

Abstract:

The indistinctness of the manufacturing processes makes that a parts cannot be realized in an absolutely exact way towards the specifications on the dimensions. It is thus necessary to assume that the effectively realized product has to belong in a very strict way to compatible intervals with a correct functioning of the parts. In this paper we present an approach based on mixing tow different characteristics theories, the fuzzy system and Petri net system. This tool has been proposed to model and control the quality in an assembly system. A robust command of a mechanical assembly process is presented as an application. This command will then have to maintain the specifications interval of parts in front of the variations. It also illustrates how the technique reacts when the product quality is high, medium, or low.

Keywords: Petri nets, production rate, performance evaluation, tolerant system, fuzzy sets.

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2797 Towards Achieving Energy Efficiency in Kazakhstan

Authors: Aigerim Uyzbayeva, Valeriya Tyo, Nurlan Ibrayev

Abstract:

Kazakhstan is currently one of the dynamically developing states in its region. The stable growth in all sectors of the economy leads to a corresponding increase in energy consumption. Thus country consumes significant amount of energy due to the high level of industrialisation and the presence of energy-intensive manufacturing such as mining and metallurgy which in turn leads to low energy efficiency. With allowance for this the Government has set several priorities to adopt a transition of Republic of Kazakhstan to a “green economy”. This article provides an overview of Kazakhstan’s energy efficiency situation in for the period of 1991- 2014. First, the dynamics of production and consumption of conventional energy resources are given. Second, the potential of renewable energy sources is summarised followed by the description of GHG emissions trends in the country. Third, Kazakhstan’ national initiatives, policies and locally implemented projects in the field of energy efficiency are described.

Keywords: Energy efficiency in Kazakhstan, greenhouse gases, renewable energy, sustainable development.

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2796 Visual Hull with Imprecise Input

Authors: Peng He

Abstract:

Imprecision is a long-standing problem in CAD design and high accuracy image-based reconstruction applications. The visual hull which is the closed silhouette equivalent shape of the objects of interest is an important concept in image-based reconstruction. We extend the domain-theoretic framework, which is a robust and imprecision capturing geometric model, to analyze the imprecision in the output shape when the input vertices are given with imprecision. Under this framework, we show an efficient algorithm to generate the 2D partial visual hull which represents the exact information of the visual hull with only basic imprecision assumptions. We also show how the visual hull from polyhedra problem can be efficiently solved in the context of imprecise input.

Keywords: Geometric Domain, Computer Vision, Computational Geometry, Visual Hull, Image-Based reconstruction, Imprecise Input, CAD object

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2795 Patents Analysis and Design Suggestions for the Mandibular Advancement Devices

Authors: Tsung-yin Lin, Yi-yu Lee

Abstract:

Snoring is prevalent and is the most significant feature of sleep-disordered breathing (SDB). Ignore the therapies of SDB will lead to serious problems in health. Based on the research of mechanisms, diagnosis, and treatments of snoring, oral appliances are ensured in therapeutic effect and compliance, especially the mandibular advancement devices (MADs). Market survey includes commercial product reviews and patent analyses. Due to pay more attention to the sleep medicine, the oral appliances are considered as a standard treatment of snoring that promoted by American Academy of Sleep Medicine (AASM). There are more and more adjustable MADs developed since 1995. According to the patent analyses, there are many drawbacks existed in the present design, such as uncomfortable, high cost, bulky volume, and complex adjustment. In this study, several new designs of the MAD are proposed.

Keywords: mandibular advancement device, mechanism design, patent review

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2794 Water End-Use Classification with Contemporaneous Water-Energy Data and Deep Learning Network

Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

Abstract:

‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: Deep learning network, smart metering, water end use, water-energy data.

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2793 Design of a Permanent Magnet Synchronous Machine for the Hybrid Electric Vehicle

Authors: Arash Hassanpour Isfahani, Siavash Sadeghi

Abstract:

Permanent magnet synchronous machines are known as a good candidate for hybrid electric vehicles due to their unique merits. However they have two major drawbacks i.e. high cost and small speed range. In this paper an optimal design of a permanent magnet machine is presented. A reduction of permanent magnet material for a constant torque and an extension in speed and torque ranges are chosen as the optimization aims. For this purpose the analytical model of the permanent magnet synchronous machine is derived and the appropriate design algorithm is devised. The genetic algorithm is then employed to optimize some machine specifications. Finally the finite element method is used to validate the designed machine.

Keywords: Design, Finite Element, Hybrid electric vehicle, Optimization, Permanent magnet synchronous machine.

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2792 Physiological and Psychological Influence on Office Workers during Demand Response

Authors: Megumi Nishida, Naoya Motegi, Takurou Kikuchi, Tomoko Tokumura

Abstract:

In recent years, the power system has been changed and a flexible power pricing system such as demand response has been sought in Japan. The demand response system works simply in the household sector and the owner as the decision-maker, can benefit from power saving. On the other hand, the execution of demand response in the office building is more complex than in the household because various people such as owners, building administrators and occupants are involved in the decision-making process. While the owners benefit from demand saving, the occupants are exposed to restricted benefits of a demand-saved environment. One of the reasons is that building systems are usually under centralized management and each occupant cannot choose freely whether to participate in demand response or not. In addition, it is unclear whether incentives give occupants the motivation to participate. However, the recent development of IT and building systems enables the personalized control of the office environment where each occupant can control the lighting level or temperature individually. Therefore, it can be possible to have a system which each occupant can make a decision of whether or not to participate in demand response in the office building. This study investigates personal responses to demand response requests, under the condition where each occupant can adjust their brightness individually in their workspace. Once workers participate in the demand response, their desk-lights are automatically turned off. The participation rates in the demand response events are compared among four groups, which are divided by different motivation, the presence, or absence of incentives and the method of participation. The result shows that there are significant differences of participation rates in demand response event between four groups. The method of participation has a large effect on the participation rate. The “Opt-out” groups where the occupants are automatically enrolled in a demand response event if they do not express non-participation have the highest participation rate in the four groups. Incentives also have an effect on the participation rate. This study also reports on the impact of low illumination office environment on the occupants, such as stress or fatigue. The electrocardiogram and the questionnaire are used to investigate the autonomic nervous activity and subjective fatigue symptoms of the occupants. There is no big difference between dim workspace during demand response event and bright workspace in autonomic nervous activity and fatigue.

Keywords: Demand response, illumination, questionnaire, electrocardiograph.

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2791 Normalizing Logarithms of Realized Volatility in an ARFIMA Model

Authors: G. L. C. Yap

Abstract:

Modelling realized volatility with high-frequency returns is popular as it is an unbiased and efficient estimator of return volatility. A computationally simple model is fitting the logarithms of the realized volatilities with a fractionally integrated long-memory Gaussian process. The Gaussianity assumption simplifies the parameter estimation using the Whittle approximation. Nonetheless, this assumption may not be met in the finite samples and there may be a need to normalize the financial series. Based on the empirical indices S&P500 and DAX, this paper examines the performance of the linear volatility model pre-treated with normalization compared to its existing counterpart. The empirical results show that by including normalization as a pre-treatment procedure, the forecast performance outperforms the existing model in terms of statistical and economic evaluations.

Keywords: Long-memory, Gaussian process, Whittle estimator, normalization, volatility, value-at-risk.

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2790 A Comparison Study of Inspector's Performance between Regular and Complex Tasks

Authors: Santirat Nansaarng, Sittichai Kaewkuekool, Supreeya Siripattanakunkajorn

Abstract:

This research was to study a comparison of inspector-s performance between regular and complex visual inspection task. Visual task was simulated on DVD read control circuit. Inspection task was performed by using computer. Subjects were 10 undergraduate randomly selected and test for 20/20. Then, subjects were divided into two groups, five for regular inspection (control group) and five for complex inspection (treatment group) tasks. Result was showed that performance on regular and complex inspectors was significantly difference at the level of 0.05. Inspector performance on regular inspection was showed high percentage on defects detected by using equal time to complex inspection. This would be indicated that inspector performance was affected by visual inspection task.

Keywords: Visual inspection task, regular and complex task.

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2789 Micropower Fuzzy Linguistic-Hedges Circuit in Current-Mode Approach

Authors: E. Farshidi

Abstract:

In this paper, based on a novel synthesis, a set of new simplified circuit design to implement the linguistic-hedge operations for adjusting the fuzzy membership function set is presented. The circuits work in current-mode and employ floating-gate MOS (FGMOS) transistors that operate in weak inversion region. Compared to the other proposed circuits, these circuits feature severe reduction of the elements number, low supply voltage (0.7V), low power consumption (<200nW), immunity from body effect and wide input dynamic range (>60dB). In this paper, a set of fuzzy linguistic hedge circuits, including absolutely, very, much more, more, plus minus, more or less and slightly, has been implemented in 0.18 mm CMOS process. Simulation results by Hspice confirm the validity of the proposed design technique and show high performance of the circuits.

Keywords: Current-mode, Linguistic-Hedge, Fuzzy Logic, lowpower

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2788 High Performance of Hollow Fiber Supported Liquid Membrane to Separate Silver Ions from Medicinal Wastewater

Authors: Thidarat Wongsawa, Ura Pancharoen, Anchaleeporn Waritswat Lothongkum

Abstract:

The separation of silver ions from medicinal wastewater via hollow fiber supported liquid membrane (HFSLM) was examined to promote the performance of this technique. The wastewater consisting of 30mg/L silver ions and 120mg/L ferric ions was used as the feed solution. LIX84I dissolving in kerosene and sodium thiosulfate pentahydrate solution were used as the liquid membrane and stripping solution, respectively. In order to access the highest performance of HFSLM, the optimum condition was investigated via several influential variables. Final concentration of silver ions in feed solution was obtained 0.2mg/L which was lower than the discharge limit of Thailand’s mandatory.

Keywords: Hollow fiber, Liquid membrane, Separation, Silver ions.

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2787 Slice Bispectrogram Analysis-Based Classification of Environmental Sounds Using Convolutional Neural Network

Authors: Katsumi Hirata

Abstract:

Certain systems can function well only if they recognize the sound environment as humans do. In this research, we focus on sound classification by adopting a convolutional neural network and aim to develop a method that automatically classifies various environmental sounds. Although the neural network is a powerful technique, the performance depends on the type of input data. Therefore, we propose an approach via a slice bispectrogram, which is a third-order spectrogram and is a slice version of the amplitude for the short-time bispectrum. This paper explains the slice bispectrogram and discusses the effectiveness of the derived method by evaluating the experimental results using the ESC‑50 sound dataset. As a result, the proposed scheme gives high accuracy and stability. Furthermore, some relationship between the accuracy and non-Gaussianity of sound signals was confirmed.

Keywords: Bispectrum, convolutional neural network, environmental sound, slice bispectrogram, spectrogram.

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2786 A Fixed Band Hysteresis Current Controller for Voltage Source AC Chopper

Authors: K. Derradji Belloum, A. Moussi

Abstract:

Most high-performance ac drives utilize a current controller. The controller switches a voltage source inverter (VSI) such that the motor current follows a set of reference current waveforms. Fixed-band hysteresis (FBH) current control has been widely used for the PWM inverter. We want to apply the same controller for the PWM AC chopper. The aims of the controller is to optimize the harmonic content at both input and output sides, while maintaining acceptable losses in the ac chopper and to control in wide range the fundamental output voltage. Fixed band controller has been simulated and analyzed for a single-phase AC chopper and are easily extended to three-phase systems. Simulation confirmed the advantages and the excellent performance of the modulation method applied for the AC chopper.

Keywords: AC chopper, Current controller, Distortion factor, Hysteresis, Input Power Factor, PWM.

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2785 Linguistic Competence Analysis and the Development of Speaking Instructional Material

Authors: Felipa M. Rico

Abstract:

Linguistic oral competence plays a vital role in attaining effective communication. Since the English language is considered as universally used language and has a high demand skill needed in the work-place, mastery is the expected output from learners. To achieve this, learners should be given integrated differentiated tasks which help them develop and strengthen the expected skills. This study aimed to develop speaking instructional supplementary material to enhance the English linguistic competence of Grade 9 students in areas of pronunciation, intonation and stress, voice projection, diction and fluency. A descriptive analysis was utilized to analyze the speaking level of performance of the students in order to employ appropriate strategies. There were two sets of respondents: 178 Grade 9 students selected through a stratified sampling and chosen at random. The other set comprised English teachers who evaluated the usefulness of the devised teaching materials. A teacher conducted a speaking test and activities were employed to analyze the speaking needs of students. Observation and recordings were also used to evaluate the students’ performance. The findings revealed that the English pronunciation of the students was slightly unclear at times, but generally fair. There were lapses but generally they rated moderate in intonation and stress, because of other language interference. In terms of voice projection, students have erratic high volume pitch. For diction, the students’ ability to produce comprehensible language is limited, and as to fluency, the choice of vocabulary and use of structure were severely limited. Based on the students’ speaking needs analyses, the supplementary material devised was based on Nunan’s IM model, incorporating context of daily life and global work settings, considering the principle that language is best learned in the actual meaningful situation. To widen the mastery of skill, a rich learning environment, filled with a variety instructional material tends to foster faster acquisition of the requisite skills for sustained learning and development. The role of IM is to encourage information to stick in the learners’ mind, as what is seen is understood more than what is heard. Teachers say they found the IM “very useful.” This implied that English teachers could adopt the materials to improve the speaking skills of students. Further, teachers should provide varied opportunities for students to get involved in real life situations where they could take turns in asking and answering questions and share information related to the activities. This would minimize anxiety among students in the use of the English language.

Keywords: Fluency, intonation, instructional materials, linguistic competence, pronunciation.

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2784 Effect of Particle Size on Alkali-Activation of Slag

Authors: E. Petrakis, V. Karmali, K. Komnitsas

Abstract:

In this study grinding experiments were performed in a laboratory ball mill using Polish ferronickel slag in order to study the effect of the particle size on alkali activation and the properties of the produced alkali activated materials (AAMs). In this regard, the particle size distribution and the specific surface area of the grinding products in relation to grinding time were assessed. The experimental results show that products with high compressive strength, e.g. higher than 60 MPa, can be produced when the slag median size decreased from 39.9 μm to 11.9 μm. Also, finer fractions are characterized by higher reactivity and result in the production of AAMs with lower porosity and better mechanical properties.

Keywords: Alkali activated materials, compressive strength, particle size distribution, slag.

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2783 Time Series Forecasting Using Independent Component Analysis

Authors: Theodor D. Popescu

Abstract:

The paper presents a method for multivariate time series forecasting using Independent Component Analysis (ICA), as a preprocessing tool. The idea of this approach is to do the forecasting in the space of independent components (sources), and then to transform back the results to the original time series space. The forecasting can be done separately and with a different method for each component, depending on its time structure. The paper gives also a review of the main algorithms for independent component analysis in the case of instantaneous mixture models, using second and high-order statistics. The method has been applied in simulation to an artificial multivariate time series with five components, generated from three sources and a mixing matrix, randomly generated.

Keywords: Independent Component Analysis, second order statistics, simulation, time series forecasting

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2782 The Influence of Interest, Beliefs, and Identity with Mathematics on Achievement

Authors: Asma Alzahrani, Elizabeth Stojanovski

Abstract:

This study investigated factors that influence mathematics achievement based on a sample of ninth-grade students (N  =  21,444) from the High School Longitudinal Study of 2009 (HSLS09). Key aspects studied included efficacy in mathematics, interest and enjoyment of mathematics, identity with mathematics and future utility beliefs and how these influence mathematics achievement. The predictability of mathematics achievement based on these factors was assessed using correlation coefficients and multiple linear regression. Spearman rank correlations and multiple regression analyses indicated positive and statistically significant relationships between the explanatory variables: mathematics efficacy, identity with mathematics, interest in and future utility beliefs with the response variable, achievement in mathematics.

Keywords: Mathematics achievement, math efficacy, mathematics interest, identity.

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2781 An Amalgam Approach for DICOM Image Classification and Recognition

Authors: J. Umamaheswari, G. Radhamani

Abstract:

This paper describes about the process of recognition and classification of brain images such as normal and abnormal based on PSO-SVM. Image Classification is becoming more important for medical diagnosis process. In medical area especially for diagnosis the abnormality of the patient is classified, which plays a great role for the doctors to diagnosis the patient according to the severeness of the diseases. In case of DICOM images it is very tough for optimal recognition and early detection of diseases. Our work focuses on recognition and classification of DICOM image based on collective approach of digital image processing. For optimal recognition and classification Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Support Vector Machine (SVM) are used. The collective approach by using PSO-SVM gives high approximation capability and much faster convergence.

Keywords: Recognition, classification, Relaxed Median Filter, Adaptive thresholding, clustering and Neural Networks

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