Search results for: cigarette filters rods

Authors: Mark Harmon, Abdolghani Ebrahimi, Patrick Lucey, Diego Klabjan

Abstract:

In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories. To approach this problem, we present a convolutional neural network (CNN) approach where we initially represent the multiagent behavior as an image. To encode the adversarial nature of basketball, we use a multichannel image which we then feed into a CNN. Additionally, to capture the temporal aspect of the trajectories we use “fading.” We find that this approach is superior to a traditional FFN model. By using gradient ascent, we were able to discover what the CNN filters look for during training. Last, we find that a combined FFN+CNN is the best performing network with an error rate of 39%.

Keywords: basketball, computer vision, image processing, convolutional neural network

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Authors: Young-Seok Choi

Abstract:

We present a new subband adaptive filter (R-SAF) which is robust against impulsive noise in system identification. To address the vulnerability of adaptive filters based on the L2-norm optimization criterion against impulsive noise, the R-SAF comes from the L1-norm optimization criterion with a constraint on the energy of the weight update. Minimizing L1-norm of the a posteriori error in each subband with a constraint on minimum disturbance gives rise to the robustness against the impulsive noise and the capable convergence performance. Experimental results clearly demonstrate that the proposed R-SAF outperforms the classical adaptive filtering algorithms when impulsive noise as well as background noise exist.

Keywords: Subband adaptive filter, L1-norm, system identification, robustness, impulsive interference.

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Authors: Anatoli Torokhti, Stanley Miklavcic

Abstract:

Suppose KY and KX are large sets of observed and reference signals, respectively, each containing N signals. Is it possible to construct a filter F : KY → KX that requires a priori information only on few signals, p  N, from KX but performs better than the known filters based on a priori information on every reference signal from KX? It is shown that the positive answer is achievable under quite unrestrictive assumptions. The device behind the proposed method is based on a special extension of the piecewise linear interpolation technique to the case of random signal sets. The proposed technique provides a single filter to process any signal from the arbitrarily large signal set. The filter is determined in terms of pseudo-inverse matrices so that it always exists.

Keywords: Wiener filter, filtering of stochastic signals.

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Authors: František Šebek, Petr Kubík, Jindřich Petruška, Jiří Hůlka

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Present study is aimed on the cutting process of circular cross-section rods where the fracture is used to separate one rod into two pieces. Incorporating the phenomenological ductile fracture model into the explicit formulation of finite element method, the process can be analyzed without the necessity of realizing too many real experiments which could be expensive in case of repetitive testing in different conditions. In the present paper, the steel AISI 1045 was examined and the tensile tests of smooth and notched cylindrical bars were conducted together with biaxial testing of the notched tube specimens to calibrate material constants of selected phenomenological ductile fracture models. These were implemented into the Abaqus/Explicit through user subroutine VUMAT and used for cutting process simulation. As the calibration process is based on variables which cannot be obtained directly from experiments, numerical simulations of fracture tests are inevitable part of the calibration. Finally, experiments regarding the cutting process were carried out and predictive capability of selected fracture models is discussed. Concluding remarks then make the summary of gained experience both with the calibration and application of particular ductile fracture criteria.

Keywords: Ductile fracture, phenomenological criteria, cutting process, explicit formulation, AISI 1045 steel.

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Authors: Madhav V. Chitturi, Anshu Manik, Kasthurirangan Gopalakrishnan

Abstract:

The dynamic or complex modulus test is considered to be a mechanistically based laboratory test to reliably characterize the strength and load-resistance of Hot-Mix Asphalt (HMA) mixes used in the construction of roads. The most common observation is that the data collected from these tests are often noisy and somewhat non-sinusoidal. This hampers accurate analysis of the data to obtain engineering insight. The goal of the work presented in this paper is to develop and compare automated evolutionary computational techniques to filter test noise in the collection of data for the HMA complex modulus test. The results showed that the Covariance Matrix Adaptation-Evolutionary Strategy (CMA-ES) approach is computationally efficient for filtering data obtained from the HMA complex modulus test.

Keywords: HMA, dynamic modulus, GA, evolutionarycomputation.

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Authors: Yong-JuJeon, Doo-chul Choi, Jong Pil Yun, Changhyun Park, Homoon Bae, Sang Woo Kim

Abstract:

This paper presents an automated inspection algorithm for a thick plate. Thick plates typically have various types of surface defects, such as scabs, scratches, and roller marks. These defects have individual characteristics including brightness and shape. Therefore, it is not simple to detect all the defects. In order to solve these problems and to detect defects more effectively, we propose a dual light switching lighting method and a defect detection algorithm based on Gabor filters.

Keywords: Thick plate, Defect, Inspection, Gabor filter, Dual Light Switching.

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Authors: Pablo Barrera, Jose M. Canas, Vicente Matellan

Abstract:

This paper addresses the problem of determining the current 3D location of a moving object and robustly tracking it from a sequence of camera images. The approach presented here uses a particle filter and does not perform any explicit triangulation. Only the color of the object to be tracked is required, but not any precisemotion model. The observation model we have developed avoids the color filtering of the entire image. That and the Monte Carlotechniques inside the particle filter provide real time performance.Experiments with two real cameras are presented and lessons learned are commented. The approach scales easily to more than two cameras and new sensor cues.

Keywords: Monte Carlo sampling, multiple view, particle filters, visual tracking.

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Authors: Al-Amin Bhuiyan, Chang Hong Liu

Abstract:

Gabor-based face representation has achieved enormous success in face recognition. This paper addresses a novel algorithm for face recognition using neural networks trained by Gabor features. The system is commenced on convolving a face image with a series of Gabor filter coefficients at different scales and orientations. Two novel contributions of this paper are: scaling of rms contrast and introduction of fuzzily skewed filter. The neural network employed for face recognition is based on the multilayer perceptron (MLP) architecture with backpropagation algorithm and incorporates the convolution filter response of Gabor jet. The effectiveness of the algorithm has been justified over a face database with images captured at different illumination conditions.

Keywords: Fuzzily skewed filter, Gabor filter, rms contrast, neural network.

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Authors: Shu-Mei Liu, Feng-Chuan Pan

Abstract:

According to the governmental data, the cases of oral cancers doubled in the past 10 years. This had brought heavy burden to the patients- family, the society, and the country. The literature generally evidenced the betel nut contained particular chemicals that can cause oral cancers. Research in Taiwan had also proofed that 90 percent of oral cancer patients had experience of betel nut chewing. It is thus important to educate the betel-nut hobbyists to cease such a hazardous behavior. A program was then organized to establish several training classes across different areas specific to help ceasing this particular habit. Purpose of this research was to explore the attitude and intention toward ceasing betel-nut chewing before and after attending the training classes. 50 samples were taken from a ceasing class with average age at 45 years old with high school education (54%). 74% of the respondents were male in service or agricultural industries. Experiences in betel-nut chewing were 5-20 years with a dose of 1-20 pieces per day. The data had shown that 60% of the respondents had cigarette smoking habit, and 30% of the respondents were concurrently alcoholic dependent. Research results indicated that the attitude, intentions, and the knowledge on oral cancers were found significant different between before and after attendance. This provided evidence for the effectiveness of the training class. However, we do not perform follow-up after the class. Noteworthy is the test result also shown that participants who were drivers as occupation, or habitual smokers or alcoholic dependents would be less willing to quit the betel-nut chewing. The test results indicated as well that the educational levels and the type of occupation may have significant impacts on an individual-s decisions in taking betel-nut or substance abuse.

Keywords: Oral cancer, betel-nut ceasing class, attitude, intention

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Authors: Young-Seok Choi

Abstract:

This paper presents a subband adaptive filter (SAF) for a system identification where an impulse response is sparse and disturbed with an impulsive noise. Benefiting from the uses of l1-norm optimization and l0-norm penalty of the weight vector in the cost function, the proposed l0-norm sign SAF (l0-SSAF) achieves both robustness against impulsive noise and much improved convergence behavior than the classical adaptive filters. Simulation results in the system identification scenario confirm that the proposed l0-norm SSAF is not only more robust but also faster and more accurate than its counterparts in the sparse system identification in the presence of impulsive noise.

Keywords: Subband adaptive filter, l0-norm, sparse system, robustness, impulsive interference.

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Authors: S. Usha, S. Arumugam

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Cancer affects people globally with breast cancer being a leading killer. Breast cancer is due to the uncontrollable multiplication of cells resulting in a tumour or neoplasm. Tumours are called ‘benign’ when cancerous cells do not ravage other body tissues and ‘malignant’ if they do so. As mammography is an effective breast cancer detection tool at an early stage which is the most treatable stage it is the primary imaging modality for screening and diagnosis of this cancer type. This paper presents an automatic mammogram classification technique using wavelet and Gabor filter. Correlation feature selection is used to reduce the feature set and selected features are classified using different decision trees.

Keywords: Breast Cancer, Mammogram, Symlet Wavelets, Gabor Filters, Decision Trees

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Authors: Weitao Lin

Abstract:

To quickly extract adequate information from large-scale unstructured text data, this paper studies the representation of events in Chinese scenarios and performs the regularized abstraction. It proposes a Chinese event detection technique based on dependency parsing and rule matching. The method first performs dependency parsing on the original utterance, then performs pattern matching at the word or phrase granularity based on the results of dependent syntactic analysis, filters out the utterances with prominent non-event characteristics, and obtains the final results. The experimental results show the effectiveness of the method.

Keywords: Natural Language Processing, Chinese event detection, rules matching, dependency parsing.

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Authors: T. Alghamdi, G. Alaghband

Abstract:

In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution neural network, edges, face recognition, support vector machine.

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Authors: H. Madi, L. Mouzai, M. Bouhadef

Abstract:

The purpose of this article is to study the effects of plants cover on overland flow and, therefore, its influences on the amount of eroded and transported soil. In this investigation, all the experiments were conducted in the LEGHYD laboratory using a rainfall simulator and a soil tray. The experiments were conducted using an experimental plot (soil tray) which is 2m long, 0.5 m wide and 0.15 m deep. The soil used is an agricultural sandy soil (62,08% coarse sand, 19,14% fine sand, 11,57% silt and 7,21% clay). Plastic rods (4 mm in diameter) were used to simulate the plants at different densities: 0 stem/m2 (bared soil), 126 stems/m², 203 stems/m², 461 stems/m² and 2500 stems/m²). The used rainfall intensity is 73mm/h and the soil tray slope is fixed to 3°. The results have shown that the overland flow velocities decreased with increasing stems density, and the density cover has a great effect on sediment concentration. Darcy–Weisbach and Manning friction coefficients of overland flow increased when the stems density increased. Froude and Reynolds numbers decreased with increasing stems density and, consequently, the flow regime of all treatments was laminar and subcritical. From these findings, we conclude that increasing the plants cover can efficiently reduce soil loss and avoid denuding the roots plants.

Keywords: Soil erosion, vegetation, stems density, overland flow.

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Authors: Al-Amin Bhuiyan, Chang Hong Liu

Abstract:

This paper addresses the development of an intelligent vision system for human-robot interaction. The two novel contributions of this paper are 1) Detection of human faces and 2) Localizing the eye. The method is based on visual attributes of human skin colors and geometrical analysis of face skeleton. This paper introduces a spatial domain filtering method named ?Fuzzily skewed filter' which incorporates Fuzzy rules for deciding the gray level of pixels in the image in their neighborhoods and takes advantages of both the median and averaging filters. The effectiveness of the method has been justified over implementing the eye tracking commands to an entertainment robot, named ''AIBO''.

Keywords: Fuzzily skewed filter, human-robot interface, rmscontrast, skin color segmentation.

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Authors: Wael M. El-Mamlouk, Metwally A. El-Sharkawy, Hossam. E. Mostafa

Abstract:

In this paper, we analyze and test a scheme for the estimation of electrical fundamental frequency signals from the harmonic load current and voltage signals. The scheme was based on using two different Multi Layer Artificial Neural Networks (ML-ANN) one for the current and the other for the voltage. This study also analyzes and tests the effect of choosing the optimum artificial neural networks- sizes which determine the quality and accuracy of the estimation of electrical fundamental frequency signals. The simulink tool box of the Matlab program for the simulation of the test system and the test of the neural networks has been used.

Keywords: Harmonics, Neural Networks, Modeling, Simulation, Active filters, electric Networks.

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Authors: Rasmus Engholm, Eva B. Vedel Jensen, Henrik Karstoft

Abstract:

In this paper we present a noise reduction filter for video processing. It is based on the recently proposed two dimensional steering kernel, extended to three dimensions and further augmented to suit the spatial-temporal domain of video processing. Two alternative filters are proposed - the time symmetric kernel and the time asymmetric kernel. The first reduces the noise on single sequences, but to handle the problems at scene shift the asymmetric kernel is introduced. The performance of both are tested on simulated data and on a real video sequence together with the existing steering kernel. The proposed kernels improves the Rooted Mean Squared Error (RMSE) compared to the original steering kernel method on video material.

Keywords: Adaptive image filtering, noise reduction, kernel methods, video processing.

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Authors: Z. Salehi Dehyagani, A. L. Yusoff

Abstract:

BEAMnrc was used to calculate the spectrum and HVL for X-ray Beam during low energy X-ray radiation using tube model: SRO 33/100 /ROT 350 Philips. The results of BEAMnrc simulation and measurements were compared to the IPEM report number 78 and SpekCalc software. Three energies 127, 103 and 84 Kv were used. In these simulation a tungsten anode with 1.2 mm for Be window were used as source. HVLs were calculated from BEAMnrc spectrum with air Kerma method for four different filters. For BEAMnrc one billion particles were used as original particles for all simulations. The results show that for 127 kV, there was maximum 5.2 % difference between BEAMnrc and Measurements and minimum was 0.7% .the maximum 9.1% difference between BEAMnrc and IPEM and minimum was 2.3% .The maximum difference was 3.2% between BEAMnrc and SpekCal and minimum was 2.8%. The result show BEAMnrc was able to satisfactory predict the quantities of Low energy Beam as well as high energy X-ray radiation.

Keywords: BEAMnr , Monte Carlo , HVL

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Authors: Roman Knizek, Denisa Karhankova, Ludmila Fridrichova

Abstract:

For their exceptional properties nanofibers, respectively, nanofiber layers are achieving an increasingly wider range of uses. Nowadays nanofibers are used mainly in the field of air filtration where they are removing submicron particles, bacteria, and viruses. Their efficiency is not changed in time, and the power consumption is much lower than that of electrically charged filters. Nanofibers are primarily used for converting and storage of energy in both air and liquid filtration, in food and packaging, protecting the environment, but also in health care which is made possible by their newly discovered properties. However, a major problem of the nanofiber layer is practically zero abrasion resistance; it is, therefore, necessary to laminate the nanofiber layer with another suitable material. Unfortunately, lamination of nanofiber layers is a major problem since the nanofiber layer contains small pores through which it is very difficult for adhesion to pass through. Therefore, there is still only a small percentage of products with these unique fibers 5.

Keywords: Nanofiber layer, nanomembrane, lamination, electrospinning.

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Authors: Rami A. Maher, Ibraheem K. Ibraheem

Abstract:

This work presents a comparison study between the state-space and polynomial methods for the design of the robust governor for load frequency control of steam turbine power systems. The robust governor is synthesized using the two approaches and the comparison is extended to include time and frequency domains performance, controller order, and uncertainty representation, weighting filters, optimality and sub-optimality. The obtained results are represented through tables and curves with reasons of similarities and dissimilarities.

Keywords: Robust control, load frequency control, steam turbine, H∞-norm, system uncertainty, load disturbance.

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Authors: V. Murugan, R. Balasubramanian

Abstract:

Image enhancement is a challenging issue in many applications. In the last two decades, there are various filters developed. This paper proposes a novel method which removes Gaussian noise from the gray scale images. The proposed technique is compared with Enhanced Fuzzy Peer Group Filter (EFPGF) for various noise levels. Experimental results proved that the proposed filter achieves better Peak-Signal-to-Noise-Ratio PSNR than the existing techniques. The proposed technique achieves 1.736dB gain in PSNR than the EFPGF technique.

Keywords: Gaussian noise, adaptive bilateral filter, fuzzy peer group filter, switching bilateral filter, PSNR

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Authors: Min Wang , Shuyuan Yang

Abstract:

The paper presents a method of designing ultrawide band (UWB) pulse array beamformer in the case of nearfield. Firstly the principle of space-time processing of UWB pulse array is discussed. The radical beampattern transform based on spherical coordinates is employed to solve the nearfield beamforming of UWB pulse array. The frequency invariant technology is considered for the frequency dependent beampattern of UWB pulse array. We use a multirate bank scheme of to implement the FI beamformer of UWB pulse array. By using multirate filters in each element channel, it can make the response of the UWB array to avoid distortion in the whole band. The simulation resultes are given to prove the efficiency and feasibility of this method.

Keywords: UWB pulse array, frequency invariant, multiratebank, nearfield beamformer, radical transform

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Authors: Abhijit Mitra

Abstract:

we propose a new normalized LMS (NLMS) algorithm, which gives satisfactory performance in certain applications in comaprison with con-ventional NLMS recursion. This new algorithm can be treated as a block based simplification of NLMS algorithm with significantly reduced number of multi¬ply and accumulate as well as division operations. It is also shown that such a recursion can be easily implemented in block floating point (BFP) arithmetic, treating the implementational issues much efficiently. In particular, the core challenges of a BFP realization to such adaptive filters are mainly considered in this regard. A global upper bound on the step size control parameter of the new algorithm due to BFP implementation is also proposed to prevent overflow in filtering as well as weight updating operations jointly.

Keywords: Adaptive algorithm, Block floating point arithmetic, Implementation issues, Normalized least mean square methods

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Authors: Ruchika, Munish Vashisht, S. Qamar

Abstract:

Detection of small ship is crucial task in many automatic surveillance systems which are employed for security of maritime boundaries of a country. To address this problem, image de-noising is technique to identify the target ship in between many other ships in the sea. Image de-noising technique needs to extract the ship’s image from sea background for the analysis as the ship’s image may submerge in the background and flooding waves. In this paper, a noise filter is presented that is based on fuzzy linguistic ‘most’ quantifier. Ordered weighted averaging (OWA) function is used to remove salt-pepper noise of ship’s image. Results obtained are in line with the results available by other well-known median filters and OWA based approach shows better performance.

Keywords: Linguistic quantifier, impulse noise, OWA filter, median filter.

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Authors: Asmaa Amehraye, Dominique Pastor, Ahmed Tamtaoui, Driss Aboutajdine

Abstract:

A new analysis of perceptual speech enhancement is presented. It focuses on the fact that if only noise above the masking threshold is filtered, then noise below the masking threshold, but above the absolute threshold of hearing, can become audible after the masker filtering. This particular drawback of some perceptual filters, hereafter called the maskee-to-audible-noise (MAN) phenomenon, favours the emergence of isolated tonals that increase musical noise. Two filtering techniques that avoid or correct the MAN phenomenon are proposed to effectively suppress background noise without introducing much distortion. Experimental results, including objective and subjective measurements, show that these techniques improve the enhanced speech quality and the gain they bring emphasizes the importance of the MAN phenomenon.

Keywords: Perceptual speech filtering, maskee to audible noise, distorsion, musical noise.

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Authors: Somkait Udomhunsakul

Abstract:

In this paper, a novel road extraction method using Stationary Wavelet Transform is proposed. To detect road features from color aerial satellite imagery, Mexican hat Wavelet filters are used by applying the Stationary Wavelet Transform in a multiresolution, multi-scale, sense and forming the products of Wavelet coefficients at a different scales to locate and identify road features at a few scales. In addition, the shifting of road features locations is considered through multiple scales for robust road extraction in the asymmetry road feature profiles. From the experimental results, the proposed method leads to a useful technique to form the basis of road feature extraction. Also, the method is general and can be applied to other features in imagery.

Keywords: Road extraction, Multiresolution, Stationary Wavelet Transform, Multi-scale analysis

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Authors: S. Bokka

Abstract:

Fiber filter membranes have a high surface area-to-volume ratio and high porosity making them ideal for various filtration and separation applications. Using the conventional filter membrane, a filtration efficiency of > 95% can be achieved. Specific applications such as air and fuel filtration require nearly 100% filtration efficiency, which is harder to achieve using conventional filter membranes. To achieve high filtration efficiencies additional costs are incurred due to increasing the cost of membrane and operating cost. Due to the simultaneous electrostatic attraction and mechanical capture, the electret filters have shown nearly 100% filtration efficiency. This article presents an overview of the charged filter membrane, its applications, and a discussion on factors contributing to increasing charge.

Keywords: Charged fiber membrane, piezoelectric materials, filtration, polymeric materials.

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Authors: X. Z. Gao, S. J. Ovaska, X. Wang

Abstract:

Prediction of sinusoidal signals with time-varying frequencies has been an important research topic in power electronics systems. To solve this problem, we propose a new fuzzy predictive filtering scheme, which is based on a Finite Impulse Response (FIR) filter bank. Fuzzy logic is introduced here to provide appropriate interpolation of individual filter outputs. Therefore, instead of regular 'hard' switching, our method has the advantageous 'soft' switching among different filters. Simulation comparisons between the fuzzy predictive filtering and conventional filter bank-based approach are made to demonstrate that the new scheme can achieve an enhanced prediction performance for slowly changing sinusoidal input signals.

Keywords: Predictive filtering, fuzzy logic, sinusoidal signals, time-varying frequencies.

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Authors: R. K. D. G. Kaluarachchi

Abstract:

The generation of solid waste and its effective management are debated topics in Sri Lanka as well as in the global environment. It was estimated that the most of the waste generated in global was originated from construction and demolition of buildings. Thus, the proportion of construction waste in solid waste generation cannot be underestimated. The construction waste, which is the by-product generated and removed from work sites is collected in direct and indirect processes. Hence, the objectives of this research are to identify the proportion of construction waste which can be reused and identify the methods to reduce the waste generation without reducing the quality of the process. A 6-storey building construction site was selected for this research. The site was divided into six zones depending on the process. Ten waste materials were identified by considering the adverse effects on safety and health of people and the economic value of them. The generated construction waste in each zone was recorded per week for a period of five months. The data revealed that sand, cement, wood used for form work and rusted steel rods were the generated waste which has higher economic value in all zones. Structured interviews were conducted to gather information on how the materials are categorized as waste and the capability of reducing, reusing and recycling the waste. It was identified that waste is generated in following processes; ineffective storage of material for a longer time and improper handling of material during the work process. Further, the alteration of scheduled activities of construction work also yielded more waste. Finally, a proper management of construction waste is suggested to reduce and reuse waste.

Keywords: Construction waste, effective management, reduce, reuse.

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Authors: P. Nammalvar, P. Meganathan, A. Balamuguran

Abstract:

Among various active filters, shunt active filter is a viable solution for reactive power and harmonics compensation. In this paper, the SRF plan is used to generate current reference for compensation and conventional PI controllers were used as the controller to compensate the reactive power. The design of the closed loop controllers is reserved simple by modeling them as first order systems. Computationally uncomplicated and efficient SVM system is used in the present work for better utilization of dc bus voltage. The rating of shunt active filter has been finalized based on the reactive power demand of the selected reactive load. The proposed control and SVM technique are validated by simulating in MATLAB software.

Keywords: Shunt Active Filter, Space vector pulse width modulation, Voltage Source Converter, Reactive Power, Synchronous Reference Frame, Point of common coupling.

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