Search results for: noise pollution

Authors: Vladimír Frišták, Martin Pipíška, Juraj Lesný

Abstract:

Alginate has been evaluated as an efficient pollution control material. In this paper, alginate from maar Pinciná (SR) for removal of Cd2+ ions from aqueous solution was studied. The potential sorbent was characterized by X-Ray Fluorescence Analysis (RFA) analysis, Fourier Transform Infrared Spectral Analysis (FT-IR) and Specific Surface Area (SSA) was also determined. The sorption process was optimized from the point of initial cadmium concentration effect and effect of pH value. The Freundlich and Langmuir models were used to interpret the sorption behaviour of Cd2+ ions, and the results showed that experimental data were well fitted by the Langmuir equation. Alginate maximal sorption capacity (QMAX) for Cd2+ ions calculated from Langmuir isotherm was 34 mg/g. Sorption process was significantly affected by initial pH value in the range from 4.0-7.0. Alginate is a comparable sorbent with other materials for toxic metals removal.

Keywords: alginates, Cd2+, sorption, QMAX

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Authors: Mahdi Shamsi, Tohid Yousefi Rezaii, Siavash Eftekharifar

Abstract:

Compressed sensing (CS) is a new powerful mathematical theory concentrating on sparse signals which is widely used in signal processing. The main idea is to sense sparse signals by far fewer measurements than the Nyquist sampling rate, but the reconstruction process becomes nonlinear and more complicated. Common dilemma in sparse signal recovery in CS is the lack of knowledge about sparsity order of the signal, which can be viewed as model order selection procedure. In this paper, we address the problem of sparsity order estimation in sparse signal recovery. This is of main interest in situations where the signal sparsity is unknown or the signal to be recovered is approximately sparse. It is shown that the proposed method also leads to some kind of signal denoising, where the observations are contaminated with noise. Finally, the performance of the proposed approach is evaluated in different scenarios and compared to an existing method, which shows the effectiveness of the proposed method in terms of order selection as well as denoising.

Keywords: compressed sensing, data denoising, model order selection, sparse representation

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Authors: Mehmet Karahan, Nevin Karahan

Abstract:

Water and air permeability and thermal resistance of fabrics are the important attributes which strongly influence the thermo-physiological comfort properties of sportswear fabrics in different environmental conditions. In this work, terry and fleece fabrics were developed by varying the fiber content and areal density of fabrics. Further, the thermo-physical properties, including air permeability, water vapor permeability, and thermal resistance, of the developed fabrics were analyzed before and after washing. The multi-response optimization of thermo-physiological comfort properties was done by using principal component analysis (PCA) and Taguchi signal to noise ratio (PCA-S/N ratio) for optimal properties. It was found that the selected parameters resulted in a significant effect on thermo-physiological comfort properties of knitted fabrics. The PCA analysis showed that before wash, 100% cotton fabric with an aerial weight of 220 g.m⁻² gave optimum values of thermo-physiological comfort.

Keywords: thermo-physiological comfort, fleece knitted fabric, air permeability, water vapor transmission, cotton/polyester

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Authors: Osiris Terry, Kenneth Hopkinson, Laura Humphrey

Abstract:

Systematic resampling is the most popularly used resampling method in particle filters. This paper seeks to further the understanding of systematic resampling by defining a formula made up of variables from the sampling equation and the particle weights. The formula is then verified via SPARK, a software verification language. The verified systematic resampling formula states that the minimum/maximum number of possible samples taken of a particle is equal to the floor/ceiling value of particle weight divided by the sampling interval, respectively. This allows for the creation of a randomness spectrum that each resampling method can fall within. Methods on the lower end, e.g., systematic resampling, have less randomness and, thus, are quicker to reach an estimate. Although lower randomness allows for error by having a larger bias towards the size of the weight, having this bias creates vulnerabilities to the noise in the environment, e.g., jamming. Conclusively, this is the first step in characterizing each resampling method. This will allow target-tracking engineers to pick the best resampling method for their environment instead of choosing the most popularly used one.

Keywords: SPARK, software verification, resampling, systematic resampling, particle filter, tracking

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Authors: Abraham Terán Salcedo, Didier Samayoa Ochoa

Abstract:

This work presents a numerical implementation of a method for estimating the box-counting dimension of self-avoiding curves on a planar space, fractal objects captured on digital images; this method is named fractioning estimator. Classical methods of digital image processing, such as noise filtering, contrast manipulation, and thresholding, among others, are used in order to obtain binary images that are suitable for performing the necessary computations of the fractioning estimator. A user interface is developed for performing the image processing operations and testing the fractioning estimator on different captured images of real-life fractal objects. To analyze the results, the estimations obtained through the fractioning estimator are compared to the results obtained through other methods that are already implemented on different available software for computing and estimating the box-counting dimension.

Keywords: box-counting, digital image processing, fractal dimension, numerical method

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Authors: Sara Bahariderakhshan, Morteza Ahmadifar

Abstract:

Leakage is one of the most important problems that water distribution networks face which first reason is high-pressure existence. There are many approaches to control this excess pressure, which using pressure reducing valves (PRVs) or reducing pipe diameter are ones. In the other hand, Pumps are using electricity or fossil fuels to supply needed pressure in distribution networks but excess pressure are made in some branches due to topology problems and water networks’ variables therefore using pressure valves will be inevitable. Although using PRVs is inevitable but it leads to waste electricity or fuels used by pumps because PRVs just waste excess hydraulic pressure to lower it. Pumps working in reverse or Pumps as Turbine (called PaT in this article) are easily available and also effective sources of reducing the equipment cost in small hydropower plants. Urban areas of developing countries are facing increasing in area and maybe water scarcity in near future. These cities need wider water networks which make it hard to predict, control and have a better operation in the urban water cycle. Using more energy and, therefore, more pollution, slower repairing services, more user dissatisfaction and more leakage are these networks’ serious problems. Therefore, more effective systems are needed to monitor and act in these complicated networks than what is used now. In this article a new approach is proposed and evaluated: Using PAT to produce enough energy for remote valves and sensors in the water network. These sensors can be used to determine the discharge, pressure, water quality and other important network characteristics. With the help of remote valves pipeline discharge can be controlled so Instead of wasting excess hydraulic pressure which may be destructive in some cases, obtaining extra pressure from pipeline and producing clean electricity used by remote instruments is this articles’ goal. Furthermore due to increasing the area of the network there is unwanted high pressure in some critical points which is not destructive but lowering the pressure results to longer lifetime for pipeline networks without users’ dissatisfaction. This strategy proposed in this article, leads to use PaT widely for pressure containment and producing energy needed for remote valves and sensors like what happens in supervisory control and data acquisition (SCADA) systems which make it easy for us to monitor, receive data from urban water cycle and make any needed changes in discharge and pressure of pipelines easily and remotely. This is a clean project of energy production without significant environmental impacts and can be used in urban drinking water networks, without any problem for consumers which leads to a stable and dynamic network which lowers leakage and pollution.

Keywords: new energies, pump as turbine, drinking water, distribution network, remote control equipments

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Authors: Hossam Hassan Elborombaly, Nader Y. Azab

Abstract:

The Middle East region is rich with its architecture and urban settings. This makes it viable for exploring and applying different strategies that deal with conservation. Current context characterized by pollution, socioeconomic issues, behavioral problems, etc. affects architectural and urban heritage –literally- in all Middle Eastern countries. Although there have been numerous strategies in place to preserve and/ or rehabilitate heritage, all has been designed and implemented following political more than technical or methodical processes. This only resulted in more deterioration of the targeted areas. This paper explores different approaches in some selected Arab countries and relies on comparative analysis with some successful European experiences. The aim is to establish some solid basis for dealing with heritage areas; an approach that respects heritage and traditions without compromising sustainability or socioeconomic opportunities.

Keywords: rehabilitation, socioeconomic, urban conservation, urban strategy

Procedia PDF Downloads 543

Authors: Morteza Ahmadifar, Sarah Bahari Derakhshan

Abstract:

Leakage is one of the most important problems that water distribution networks face which first reason is high-pressure existence. There are many approaches to control this excess pressure, which using pressure reducing valves (PRVs) or reducing pipe diameter are ones. On the other hand, Pumps are using electricity or fossil fuels to supply needed pressure in distribution networks but excess pressure are made in some branches due to topology problems and water networks’ variables, therefore using pressure valves will be inevitable. Although using PRVs is inevitable but it leads to waste electricity or fuels used by pumps because PRVs just waste excess hydraulic pressure to lower it. Pumps working in reverse or Pumps as Turbine (called PAT in this article) are easily available and also effective sources of reducing the equipment cost in small hydropower plants. Urban areas of developing countries are facing increasing in area and maybe water scarcity in near future. These cities need wider water networks which make it hard to predict, control and have a better operation in the urban water cycle. Using more energy and therefore more pollution, slower repairing services, more user dissatisfaction and more leakage are these networks’ serious problems. Therefore, more effective systems are needed to monitor and act in these complicated networks than what is used now. In this article a new approach is proposed and evaluated: Using PAT to produce enough energy for remote valves and sensors in the water network. These sensors can be used to determine the discharge, pressure, water quality and other important network characteristics. With the help of remote valves pipeline discharge can be controlled so Instead of wasting excess hydraulic pressure which may be destructive in some cases, obtaining extra pressure from pipeline and producing clean electricity used by remote instruments is this articles’ goal. Furthermore, due to increasing the area of network there is unwanted high pressure in some critical points which is not destructive but lowering the pressure results to longer lifetime for pipeline networks without users’ dissatisfaction. This strategy proposed in this article, leads to use PAT widely for pressure containment and producing energy needed for remote valves and sensors like what happens in supervisory control and data acquisition (SCADA) systems which make it easy for us to monitor, receive data from urban water cycle and make any needed changes in discharge and pressure of pipelines easily and remotely. This is a clean project of energy production without significant environmental impacts and can be used in urban drinking water networks, without any problem for consumers which leads to a stable and dynamic network which lowers leakage and pollution.

Keywords: clean energies, pump as turbine, remote control, urban water distribution network

Procedia PDF Downloads 392

Authors: Zaffar Hayat Nawaz Khan

Abstract:

In the face of growing environmental concerns, the need for sustainable practices has become increasingly urgent. This paper aims to explore the path towards a greener and more resilient future by examining key strategies and initiatives that address environmental challenges. The paper begins by analyzing the current state of the environment, highlighting the various concerns such as climate change, deforestation, pollution, and depletion of natural resources. It emphasizes the need for immediate action and proposes a comprehensive approach to tackle these issues. Furthermore, the paper delves into the concept of resilience and its importance in creating a sustainable future. It discusses the need to build resilient systems and communities that can withstand and adapt to environmental shocks and stresses. The paper highlights the role of innovation, technology, and policy frameworks in promoting resilience and fostering a greener and more sustainable future.

Keywords: environmental concerns, ustainable development, greener future, energy, waste management

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Authors: Mandeep Kumar, Hari Singh

Abstract:

The effective optimization of machining process parameters affects dramatically the cost and production time of machined components as well as the quality of the final products. This paper presents the optimization aspects of a Wire Electrical Discharge Machining operation using Inconel X-750 as work material. The objective considered in this study is minimization of the dimensional deviation. Six input process parameters of WEDM namely spark gap voltage, pulse-on time, pulse-off time, wire feed rate, peak current and wire tension, were chosen as variables to study the process performance. Taguchi's design of experiments methodology has been used for planning and designing the experiments. The analysis of variance was carried out for raw data as well as for signal to noise ratio. Four input parameters and one two-factor interaction have been found to be statistically significant for their effects on the response of interest. The confirmation experiments were also performed for validating the predicted results.

Keywords: ANOVA, DOE, inconel, machining, optimization

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Authors: Bouchra Wassate, Younes Karhat, Khadija El Falaki

Abstract:

Leachate is a source of surface water and groundwater contamination if it has not been pretreated. Indeed, due to its complex structure and its pollution load make its treatment extremely difficult to achieve the standard limits required. The objective of this work is to show the interest of advanced oxidation processes on leachate treatment of urban waste containing high concentrations of organic pollutants. The efficiency of Fenton (Fe2+ +H2O2 + H+) reagent for young leachate recovered from collection trucks household waste in the city of Casablanca, Morocco, was evaluated with the objectives of chemical oxygen demand (COD) and discoloration reductions. The optimization of certain physicochemical parameters (initial pH value, reaction time, and [Fe2+], [H2O2]/ [Fe2+] ratio) has yielded good results in terms of reduction of COD and discoloration of the leachate.

Keywords: COD removal, color removal, Fenton process, oxidation process, leachate

Procedia PDF Downloads 285

Authors: Hyun-Woo Cho

Abstract:

Unexpected operational events or abnormalities of industrial processes have a serious impact on the quality of final product of interest. In terms of statistical process control, fault detection and diagnosis of processes is one of the essential tasks needed to run the process safely. In this work, nonlinear representation of process measurement data is presented and evaluated using a simulation process. The effect of using different representation methods on the diagnosis performance is tested in terms of computational efficiency and data handling. The results have shown that the nonlinear representation technique produced more reliable diagnosis results and outperforms linear methods. The use of data filtering step improved computational speed and diagnosis performance for test data sets. The presented scheme is different from existing ones in that it attempts to extract the fault pattern in the reduced space, not in the original process variable space. Thus this scheme helps to reduce the sensitivity of empirical models to noise.

Keywords: fault diagnosis, nonlinear technique, process data, reduced spaces

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Authors: Kim Lytle, Tim Talty, Alan Michaels, Jeff Reed

Abstract:

Implantable medical devices (IMDs) are medically necessary devices embedded in the human body that monitor chronic disorders or automatically deliver therapies. Most IMDs have wireless capabilities that allow them to share data with an offboard programming device to help medical providers monitor the patient’s health while giving the patient more insight into their condition. However, serious security concerns have arisen as researchers demonstrated these devices could be hacked to obtain sensitive information or harm the patient. Cooperative jamming can be used to prevent privileged information leaks by maintaining an adequate signal-to-noise ratio at the intended receiver while minimizing signal power elsewhere. This paper uses ray tracing to demonstrate how a low number of friendly nodes abiding by Bluetooth Low Energy (BLE) transmission regulations can enhance IMD communication security in an office environment, which in turn may inform how companies and individuals can protect their proprietary and personal information.

Keywords: implantable biomedical devices, communication system security, array signal processing, ray tracing

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Authors: S. Zouainia, R. Djebar, H. Berrebah, A. Sayeb

Abstract:

This work focused on the study of physiological and biochemical changes observed in tadpoles exposed to fungicide Rana saharica Artea 330ec recently introduced in Algeria. For this, we tested the effect of xenobiotics on growth and development of tadpoles; among the studied parameters: total protein, glutathione and respiratory activity. The study of physiological parameters showed that the tadpoles change perfectly in the absence of toxic and in favorable conditions (pH, temperature). Our results showed an increased rate of protein and GSH in the presence of the fungicide Artea 330ec. The latter causes uninhibited very highly significant respiratory activity of tadpoles treated. The presence of xenobiotics in the breeding tadpoles water causes disturbances in behavior and food metabolism.

Keywords: amphibians, fungicides, pesticides, pollution

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Authors: Yushuai Wang, Feng Xu, Junbo Tan, Xueqian Wang, Bin Liang

Abstract:

In this paper, a sensor fault-tolerant control (FTC) scheme using robust model predictive control (RMPC) and set theoretic fault detection and isolation (FDI) is extended to linear parameter varying (LPV) systems. First, a group of set-valued observers are designed for passive fault detection (FD) and the observer gains are obtained through minimizing the size of invariant set of state estimation-error dynamics. Second, an input set for fault isolation (FI) is designed offline through set theory for actively isolating faults after FD. Third, an RMPC controller based on state estimation for LPV systems is designed to control the system in the presence of disturbance and measurement noise and tolerate faults. Besides, an FTC algorithm is proposed to maintain the plant operate in the corresponding mode when the fault occurs. Finally, a numerical example is used to show the effectiveness of the proposed results.

Keywords: fault detection, linear parameter varying, model predictive control, set theory

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Authors: Mohamed Hafid, Marcel Lacroix

Abstract:

This study presents an inverse analysis for predicting the thermal conductivities and the heat flux of a high-temperature metallurgical reactor simultaneously. Once these thermal parameters are predicted, the time-varying thickness of the protective phase-change bank that covers the inside surface of the brick walls of a metallurgical reactor can be calculated. The enthalpy method is used to solve the melting/solidification process of the protective bank. The inverse model rests on the Levenberg-Marquardt Method (LMM) combined with the Broyden method (BM). A statistical analysis for the thermal parameter estimation is carried out. The effect of the position of the temperature sensors, total number of measurements and measurement noise on the accuracy of inverse predictions is investigated. Recommendations are made concerning the location of temperature sensors.

Keywords: inverse heat transfer, phase change, metallurgical reactor, Levenberg–Marquardt method, Broyden method, bank thickness

Procedia PDF Downloads 332

Authors: Md Al Masum Bhuiyan, Maria C. Mariani, Osei K. Tweneboah

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In the present work, we develop a technique for estimating the volatility of financial time series by using stochastic differential equation. Taking the daily closing prices from developed and emergent stock markets as the basis, we argue that the incorporation of stochastic volatility into the time-varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. While using the technique, we see the long-memory behavior of data sets and one-step-ahead-predicted log-volatility with ±2 standard errors despite the variation of the observed noise from a Normal mixture distribution, because the financial data studied is not fully Gaussian. Also, the Ornstein-Uhlenbeck process followed in this work simulates well the financial time series, which aligns our estimation algorithm with large data sets due to the fact that this algorithm has good convergence properties.

Keywords: financial time series, maximum likelihood estimation, Ornstein-Uhlenbeck type models, stochastic volatility model

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Authors: Boudjema Nouara, Mameri Nabil

Abstract:

Bacteria have played an important role in water contamination as a consequence of organic pollution. In this study, an electrocoagulation process was adopted to remove fecal contamination and pathogenic bacteria from waste water. The effect of anode/cathodes materials as well as operating conditions for bacteria removal from water, such as current intensity and initial pH and temperature. The results indicated that the complete removal was achevied when using aluminium anode as anode at current intensity of 3A, initial pH of 7-8 and electrolysis time of 30 minutes. This process showed a bactericidal effect of 95 to 99% for the total and fecal coliforms and 99% to 100% for Eschercichia coli and fecal Streptococci. A decrease of 72% was recorded for sulphite-reducing Clostridia. Thus, this process has the potential to be one the options for treatment where high amount of bacteria in wastewater river.

Keywords: bacteria, el Harrach river, electrocoagulation, wastewater, treatment

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Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

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Authors: Adebayo Emmanuel Layi

Abstract:

Library and Information Science Education is about six (6) decades old in Nigeria. The first Library School was established in 1962 at the University of Ibadan, and since then, several institutions have been running the programme under various certifications, providing the manpower needs of professionals for libraries. As at June 2023, Nigeria has close to a thousand (1000) tertiary institutions and all needing the services of librarians. Apart from the tertiary institutions, several libraries exit in various establishments, both government, private and non-governmental organisations. These has underscored the enormous need for trained librarians for the libraries in these places. The Nexus between LIS Education training and Practice is like a puzzle of egg and chick, which one came first and against this background, this paper examined the roles of the colonial masters in educational development in Africa and vis-à-vis the influence of great library educators such as Melvil Dewey and other educators and the journey through Nigeria institutions. Despite the sound footing of LIS Education, Noise which seems to be a major obstacle on the practice as well as mending the broken link were all examined in the paper. Strategies and the way forward for overall development are suggested.

Keywords: nexus, education, training, synergy

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Authors: Fabiana Franceschi, Martha Cobo, Manuel Figueredo

Abstract:

Bogotá, the capital of Colombia, is its largest city and one of the most polluted in Latin America due to the fast economic growth over the last ten years. Bogotá has been affected by high pollution events which led to the high concentration of PM10 and NO2, exceeding the local 24-hour legal limits (100 and 150 g/m3 each). The most important pollutants in the city are PM10 and PM2.5 (which are associated with respiratory and cardiovascular problems) and it is known that their concentrations in the atmosphere depend on the local meteorological factors. Therefore, it is necessary to establish a relationship between the meteorological variables and the concentrations of the atmospheric pollutants such as PM10, PM2.5, CO, SO2, NO2 and O3. This study aims to determine the interrelations between meteorological variables and air pollutants in Bogotá, using data mining techniques. Data from 13 monitoring stations were collected from the Bogotá Air Quality Monitoring Network within the period 2010-2015. The Principal Component Analysis (PCA) algorithm was applied to obtain primary relations between all the parameters, and afterwards, the K-means clustering technique was implemented to corroborate those relations found previously and to find patterns in the data. PCA was also used on a per shift basis (morning, afternoon, night and early morning) to validate possible variation of the previous trends and a per year basis to verify that the identified trends have remained throughout the study time. Results demonstrated that wind speed, wind direction, temperature, and NO2 are the most influencing factors on PM10 concentrations. Furthermore, it was confirmed that high humidity episodes increased PM2,5 levels. It was also found that there are direct proportional relationships between O3 levels and wind speed and radiation, while there is an inverse relationship between O3 levels and humidity. Concentrations of SO2 increases with the presence of PM10 and decreases with the wind speed and wind direction. They proved as well that there is a decreasing trend of pollutant concentrations over the last five years. Also, in rainy periods (March-June and September-December) some trends regarding precipitations were stronger. Results obtained with K-means demonstrated that it was possible to find patterns on the data, and they also showed similar conditions and data distribution among Carvajal, Tunal and Puente Aranda stations, and also between Parque Simon Bolivar and las Ferias. It was verified that the aforementioned trends prevailed during the study period by applying the same technique per year. It was concluded that PCA algorithm is useful to establish preliminary relationships among variables, and K-means clustering to find patterns in the data and understanding its distribution. The discovery of patterns in the data allows using these clusters as an input to an Artificial Neural Network prediction model.

Keywords: air pollution, air quality modelling, data mining, particulate matter

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Authors: Ci Lin, Tet Yeap, Iluju Kiringa

Abstract:

This paper introduces the subspace rotation algorithm (SRA) to train the Restricted Hopfield Network (RHN) as an auto-associative memory. Subspace rotation algorithm is a gradient-free subspace tracking approach based on the singular value decomposition (SVD). In comparison with Backpropagation Through Time (BPTT) on training RHN, it is observed that SRA could always converge to the optimal solution and BPTT could not achieve the same performance when the model becomes complex, and the number of patterns is large. The AUTS case study showed that the RHN model trained by SRA could achieve a better structure of attraction basin with larger radius(in general) than the Hopfield Network(HNN) model trained by Hebbian learning rule. Through learning 10000 patterns from MNIST dataset with RHN models with different number of hidden nodes, it is observed that an several components could be adjusted to achieve a balance between recovery accuracy and noise resistance.

Keywords: hopfield neural network, restricted hopfield network, subspace rotation algorithm, hebbian learning rule

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Authors: Yakup Sahin, Naim Suleyman Ting, Ismail Aksoy

Abstract:

In this paper, an improved active snubber cell is proposed on account of soft switching (SS) family of pulse width modulation (PWM) DC-DC converters. The improved snubber cell provides zero-voltage transition (ZVT) turn on and zero-current transition (ZCT) turn off for main switch. The snubber cell decreases EMI noise and operates with SS in a wide range of line and load voltages. Besides, all of the semiconductor devices in the converter operate with SS. There is no additional voltage and current stress on the main devices. Additionally, extra voltage stress does not occur on the auxiliary switch and its current stress is acceptable value. The improved converter has a low cost and simple structure. The theoretical analysis of converter is clarified and the operating states are given in detail. The experimental results of converter are obtained by prototype of 500 W and 100 kHz. It is observed that the experimental results and theoretical analysis of converter are suitable with each other perfectly.

Keywords: active snubber cells, DC-DC converters, zero-voltage transition, zero-current transition

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Authors: Syed Ali Shahbaz Shah

Abstract:

In the last few years, Bituminous Asphaltic roads are becoming popular day by day in the world. Plenty of research has been carried out to identify many advantages like safety, environmental effects, and comfort. Some other benefits are minimal noise and skid resistance enhancement. Besides the benefits of asphaltic roads, the permeable structure of the road also causes some distress, and raveling is one of the crucial defects. The main reason behind this distress is the failure of adhesion between bitumen mortar, specifically due to excessive load from heavy traffic. The main focus of this study is to identify the root cause and propose both the long-term and the short-term solutions of raveling on a specific road section depicting the overall road situation from the bridge of Kahuta road towards the intersection of the Islamabad express highway. The methodology adopted for this purpose is visual inspections in-situ. It was noted that there were chunks of debris on the road surface, which indicates that the asphalt binder is aged the most probably. Further laboratory testing would confirm that either asphalt binder is aged or inadequate compaction was adept during cold weather paving.

Keywords: asphaltic roads, asphalt binder, distress, raveling

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Authors: Selda Uzal Seyfi

Abstract:

Goat and sheep milk is quite significant in human nutrition. It is considered as more important day by day. This study was carried out in order to determine applied manure management system and their possibilities of improvement in goat and sheep farm in between 2012 and 2013 years. In the study, it was investigated manure management systems of 25 pieces of sheep and goat farms. It was analyzed the manure collecting, storage and treatment features of farms and whether or not they are suitable for animal breeding. As a result of the study, it was determined that the applied manure management systems in the farm were insufficient. Planning the manure management systems in goat and sheep breeding is appropriate technical criteria is useful in respect of the animal welfare, animal health, the health of workers in the barn and environmental pollution.

Keywords: goat farm, sheep farm, manure storage, manure management

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Authors: Kensho Takahashi, Ko Watanabe, Takashi Kaburagi, Hiroshi Tanaka, Kajiro Watanabe, Yosuke Kurihara

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Near-infrared spectroscopy (NIRS) has been widely used as a non-invasive method to measure brain activity, but it is corrupted by baseline drift noise. Here we present a method to measure regional cerebral blood flow as a derivative of NIRS output. We investigate whether, when listening to languages, blood flow can reasonably localize and represent regional brain activity or not. The prefrontal blood flow distribution pattern when advanced second-language listeners listened to a second language (L2) was most similar to that when listening to their first language (L1) among the patterns of mean and standard deviation. In experiments with 25 healthy subjects, the maximum blood flow was localized to the left BA46 of advanced listeners. The blood flow presented is robust to baseline drift and stably localizes regional brain activity.

Keywords: NIRS, oxy-hemoglobin, baseline drift, blood flow, working memory, BA46, first language, second language

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Authors: Hyun-Woo Cho

Abstract:

The monitoring of industrial production quality has to be implemented to alarm early warning for unusual operating conditions. Furthermore, identification of their assignable causes is necessary for a quality control purpose. For such tasks many multivariate statistical techniques have been applied and shown to be quite effective tools. This work presents a process data-based monitoring scheme for production processes. For more reliable results some additional steps of noise filtering and preprocessing are considered. It may lead to enhanced performance by eliminating unwanted variation of the data. The performance evaluation is executed using data sets from test processes. The proposed method is shown to provide reliable quality control results, and thus is more effective in quality monitoring in the example. For practical implementation of the method, an on-line data system must be available to gather historical and on-line data. Recently large amounts of data are collected on-line in most processes and implementation of the current scheme is feasible and does not give additional burdens to users.

Keywords: detection, filtering, monitoring, process data

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Authors: Emil Mathew

Abstract:

Liberalisation policies adopted by a large number of countries, implementation of technological innovations with development in communication networks and continuous reduction in transport costs contributed towards the growth of international transportation of goods over the last 50 to 60 years. The present paper examines the environmental externalities of maritime transportation, that is, externalities associated with the movement of cargoes, as distinct from those emanate from production and consumption of goods. Though shipping is less polluting compared to other modes of transportation, considering the huge volume of goods transported and future growth prospects, it is important to examine environmental externalities of maritime transportation. It focuses on varied types of environmental externalities of maritime transportation and suggests that appropriate policies may be adopted by international agencies to address this issue without adversely affecting the course of international trade and also its possibility to get diverted to alternate modes of transportation.

Keywords: externalities of globalisation, maritime environment, maritime externality, transportation externality

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Authors: M. A. Alavianmehr, A. Tashk, A. Sodagaran

Abstract:

Modeling background and moving objects are significant techniques for video surveillance and other video processing applications. This paper presents a foreground detection algorithm that is robust against illumination changes and noise based on adaptive mixture Gaussian model (GMM), and provides a novel and practical choice for intelligent video surveillance systems using static cameras. In the previous methods, the image of still objects (background image) is not significant. On the contrary, this method is based on forming a meticulous background image and exploiting it for separating moving objects from their background. The background image is specified either manually, by taking an image without vehicles, or is detected in real-time by forming a mathematical or exponential average of successive images. The proposed scheme can offer low image degradation. The simulation results demonstrate high degree of performance for the proposed method.

Keywords: image processing, background models, video surveillance, foreground detection, Gaussian mixture model

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Authors: Sonia Ben Hamza, Sabra Habli, Nejla Mahjoub Saïd, Hervé Bournot, Georges Le Palec

Abstract:

This paper spots light on the effect of a point source pollution on streams, stemming out from intentional release caused by unconscious facts. The consequences of such contamination on ecosystems are very serious. Accordingly, effective tools are highly demanded in this respect, which enable us to come across an accurate progress of pollutant and anticipate different measures to be applied in order to limit the degradation of the environmental surrounding. In this context, we are eager to model a pollutant dispersion of a free surface flow which is ejected by an outfall sewer of an urban sewerage network in coastal water taking into account the influence of climatic parameters on the spread of pollutant. Numerical results showed that pollutant dispersion is merely due to the presence of vortices and turbulence. Hence, it was realized that the pollutant spread in seawater is strongly correlated with climatic conditions in this region.

Keywords: coastal waters, numerical simulation, pollutant dispersion, turbulent flows

Procedia PDF Downloads 512