Abstract
One of the major influential factors which affects the accuracy of classification rate is the selection of right features. Not all features have vital role in classification. Many of the features in the dataset may be redundant and irrelevant, which increase the computational cost and may reduce classification rate. In this paper, we used DCT(Discrete cosine transform) coefficients as features for face recognition application. The coefficients are optimally selected based on a modified PSO algorithm. In this, the choice of coefficients is done by incorporating the average of the mean normalized standard deviations of various classes and giving more weightage to the lower indexed DCT coefficients. The algorithm is tested on ORL database. A recognition rate of 97% is obtained. Average number of features selected is about 40 percent for a 10 × 10 input. The modified PSO took about 50 iterations for convergence. These performance figures are found to be better than some of the work reported in literature.
Keywords: Particle swarm optimization, Discrete cosine transform, feature extraction, feature selection, face recognition, classification rate.
BINARY SINE COSINE ALGORITHMS FOR FEATURE SELECTION FROM MEDICAL DATAacijjournal
A well-constructed classification model highly depends on input feature subsets from a dataset, which may contain redundant, irrelevant, or noisy features. This challenge can be worse while dealing with medical datasets. The main aim of feature selection as a pre-processing task is to eliminate these features and select the most effective ones. In the literature, metaheuristic algorithms show a successful performance to find optimal feature subsets. In this paper, two binary metaheuristic algorithms named S-shaped binary Sine Cosine Algorithm (SBSCA) and V-shaped binary Sine Cosine Algorithm (VBSCA) are proposed for feature selection from the medical data. In these algorithms, the search space remains continuous, while a binary position vector is generated by two transfer functions S-shaped and V-shaped for each solution. The proposed algorithms are compared with four latest binary optimization algorithms over five medical datasets from the UCI repository. The experimental results confirm that using both bSCA variants enhance the accuracy of classification on these medical datasets compared to four other algorithms.
A HYBRID COA-DEA METHOD FOR SOLVING MULTI-OBJECTIVE PROBLEMS ijcsa
The Cuckoo optimization algorithm (COA) is developed for solving single-objective problems and it cannot be used for solving multi-objective problems. So the multi-objective cuckoo optimization algorithm based on data envelopment analysis (DEA) is developed in this paper and it can gain the efficient Pareto frontiers. This algorithm is presented by the CCR model of DEA and the output-oriented approach of it.The selection criterion is higher efficiency for next iteration of the proposed hybrid method. So the profit function of the COA is replaced by the efficiency value that is obtained from DEA. This algorithm is
compared with other methods using some test problems. The results shows using COA and DEA approach for solving multi-objective problems increases the speed and the accuracy of the generated solutions.
Control chart pattern recognition using k mica clustering and neural networksISA Interchange
Automatic recognition of abnormal patterns in control charts has seen increasing demands nowadays in manufacturing processes. This paper presents a novel hybrid intelligent method (HIM) for recognition of the common types of control chart pattern (CCP). The proposed method includes two main modules: a clustering module and a classifier module. In the clustering module, the input data is first clustered by a new technique. This technique is a suitable combination of the modified imperialist competitive algorithm (MICA) and the K-means algorithm. Then the Euclidean distance of each pattern is computed from the determined clusters. The classifier module determines the membership of the patterns using the computed distance. In this module, several neural networks, such as the multilayer perceptron, probabilistic neural networks, and the radial basis function neural networks, are investigated. Using the experimental study, we choose the best classifier in order to recognize the CCPs. Simulation results show that a high recognition accuracy, about 99.65%, is achieved.
The pertinent single-attribute-based classifier for small datasets classific...IJECEIAES
Classifying a dataset using machine learning algorithms can be a big challenge when the target is a small dataset. The OneR classifier can be used for such cases due to its simplicity and efficiency. In this paper, we revealed the power of a single attribute by introducing the pertinent single-attributebased-heterogeneity-ratio classifier (SAB-HR) that used a pertinent attribute to classify small datasets. The SAB-HR’s used feature selection method, which used the Heterogeneity-Ratio (H-Ratio) measure to identify the most homogeneous attribute among the other attributes in the set. Our empirical results on 12 benchmark datasets from a UCI machine learning repository showed that the SAB-HR classifier significantly outperformed the classical OneR classifier for small datasets. In addition, using the H-Ratio as a feature selection criterion for selecting the single attribute was more effectual than other traditional criteria, such as Information Gain (IG) and Gain Ratio (GR).
BINARY SINE COSINE ALGORITHMS FOR FEATURE SELECTION FROM MEDICAL DATAacijjournal
A well-constructed classification model highly depends on input feature subsets from a dataset, which may contain redundant, irrelevant, or noisy features. This challenge can be worse while dealing with medical datasets. The main aim of feature selection as a pre-processing task is to eliminate these features and select the most effective ones. In the literature, metaheuristic algorithms show a successful performance to find optimal feature subsets. In this paper, two binary metaheuristic algorithms named S-shaped binary Sine Cosine Algorithm (SBSCA) and V-shaped binary Sine Cosine Algorithm (VBSCA) are proposed for feature selection from the medical data. In these algorithms, the search space remains continuous, while a binary position vector is generated by two transfer functions S-shaped and V-shaped for each solution. The proposed algorithms are compared with four latest binary optimization algorithms over five medical datasets from the UCI repository. The experimental results confirm that using both bSCA variants enhance the accuracy of classification on these medical datasets compared to four other algorithms.
A HYBRID COA-DEA METHOD FOR SOLVING MULTI-OBJECTIVE PROBLEMS ijcsa
The Cuckoo optimization algorithm (COA) is developed for solving single-objective problems and it cannot be used for solving multi-objective problems. So the multi-objective cuckoo optimization algorithm based on data envelopment analysis (DEA) is developed in this paper and it can gain the efficient Pareto frontiers. This algorithm is presented by the CCR model of DEA and the output-oriented approach of it.The selection criterion is higher efficiency for next iteration of the proposed hybrid method. So the profit function of the COA is replaced by the efficiency value that is obtained from DEA. This algorithm is
compared with other methods using some test problems. The results shows using COA and DEA approach for solving multi-objective problems increases the speed and the accuracy of the generated solutions.
Control chart pattern recognition using k mica clustering and neural networksISA Interchange
Automatic recognition of abnormal patterns in control charts has seen increasing demands nowadays in manufacturing processes. This paper presents a novel hybrid intelligent method (HIM) for recognition of the common types of control chart pattern (CCP). The proposed method includes two main modules: a clustering module and a classifier module. In the clustering module, the input data is first clustered by a new technique. This technique is a suitable combination of the modified imperialist competitive algorithm (MICA) and the K-means algorithm. Then the Euclidean distance of each pattern is computed from the determined clusters. The classifier module determines the membership of the patterns using the computed distance. In this module, several neural networks, such as the multilayer perceptron, probabilistic neural networks, and the radial basis function neural networks, are investigated. Using the experimental study, we choose the best classifier in order to recognize the CCPs. Simulation results show that a high recognition accuracy, about 99.65%, is achieved.
The pertinent single-attribute-based classifier for small datasets classific...IJECEIAES
Classifying a dataset using machine learning algorithms can be a big challenge when the target is a small dataset. The OneR classifier can be used for such cases due to its simplicity and efficiency. In this paper, we revealed the power of a single attribute by introducing the pertinent single-attributebased-heterogeneity-ratio classifier (SAB-HR) that used a pertinent attribute to classify small datasets. The SAB-HR’s used feature selection method, which used the Heterogeneity-Ratio (H-Ratio) measure to identify the most homogeneous attribute among the other attributes in the set. Our empirical results on 12 benchmark datasets from a UCI machine learning repository showed that the SAB-HR classifier significantly outperformed the classical OneR classifier for small datasets. In addition, using the H-Ratio as a feature selection criterion for selecting the single attribute was more effectual than other traditional criteria, such as Information Gain (IG) and Gain Ratio (GR).
Engineering Research Publication
Best International Journals, High Impact Journals,
International Journal of Engineering & Technical Research
ISSN : 2321-0869 (O) 2454-4698 (P)
www.erpublication.org
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A novel population-based local search for nurse rostering problem IJECEIAES
Population-based approaches regularly are better than single based (local search) approaches in exploring the search space. However, the drawback of population-based approaches is in exploiting the search space. Several hybrid approaches have proven their efficiency through different domains of optimization problems by incorporating and integrating the strength of population and local search approaches. Meanwhile, hybrid methods have a drawback of increasing the parameter tuning. Recently, population-based local search was proposed for a university course-timetabling problem with fewer parameters than existing approaches, the proposed approach proves its effectiveness. The proposed approach employs two operators to intensify and diversify the search space. The first operator is applied to a single solution, while the second is applied for all solutions. This paper aims to investigate the performance of population-based local search for the nurse rostering problem. The INRC2010 database with a dataset composed of 69 instances is used to test the performance of PB-LS. A comparison was made between the performance of PB-LS and other existing approaches in the literature. Results show good performances of proposed approach compared to other approaches, where population-based local search provided best results in 55 cases over 69 instances used in experiments.
Feature selection in high-dimensional datasets is
considered to be a complex and time-consuming problem. To
enhance the accuracy of classification and reduce the execution
time, Parallel Evolutionary Algorithms (PEAs) can be used. In
this paper, we make a review for the most recent works which
handle the use of PEAs for feature selection in large datasets.
We have classified the algorithms in these papers into four main
classes (Genetic Algorithms (GA), Particle Swarm Optimization
(PSO), Scattered Search (SS), and Ant Colony Optimization
(ACO)). The accuracy is adopted as a measure to compare the
efficiency of these PEAs. It is noticeable that the Parallel Genetic
Algorithms (PGAs) are the most suitable algorithms for feature
selection in large datasets; since they achieve the highest accuracy.
On the other hand, we found that the Parallel ACO is timeconsuming
and less accurate comparing with other PEA.
Particle Swarm Optimization based K-Prototype Clustering Algorithm iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A hybrid fuzzy ann approach for software effort estimationijfcstjournal
Software development effort estimation is one of the major activities in software project management.
During the project proposal stage there is high probability of estimates being made inaccurate but later on
this inaccuracy decreases. In the field of software development there are certain matrices, based on which
the effort estimation is being made. Till date various methods has been proposed for software effort
estimation, of which the non algorithmic methods, like artificial intelligence techniques have been very
successful. A Hybrid Fuzzy-ANN model, known as Adaptive Neuro Fuzzy Inference System (ANFIS) is more
suitable in such situations. The present paper is concerned with developing software effort estimation
model based on ANFIS. The present study evaluates the efficiency of the proposed ANFIS model, for which
COCOMO81 datasets has been used. The result so obtained has been compared with Artificial Neural
Network (ANN) and Intermediate COCOCMO model developed by Boehm. The results were analyzed using
Magnitude of Relative Error (MRE) and Root Mean Square Error (RMSE). It is observed that the ANFIS
provided better results than ANN and COCOMO model.
Data Warehouses are structures with large amount of data collected from heterogeneous sources to be
used in a decision support system. Data Warehouses analysis identifies hidden patterns initially unexpected
which analysis requires great memory and computation cost. Data reduction methods were proposed to
make this analysis easier. In this paper, we present a hybrid approach based on Genetic Algorithms (GA)
as Evolutionary Algorithms and the Multiple Correspondence Analysis (MCA) as Analysis Factor Methods
to conduct this reduction. Our approach identifies reduced subset of dimensions p’ from the initial subset p
where p'<p where it is proposed to find the profile fact that is the closest to reference. Gas identify the
possible subsets and the Khi² formula of the ACM evaluates the quality of each subset. The study is based
on a distance measurement between the reference and n facts profile extracted from the warehouse.
A MULTI-POPULATION BASED FROG-MEMETIC ALGORITHM FOR JOB SHOP SCHEDULING PROBLEMacijjournal
The Job Shop Scheduling Problem (JSSP) is a well known practical planning problem in the
manufacturing sector. We have considered the JSSP with an objective of minimizing makespan. In this
paper, we develop a three-stage hybrid approach called JSFMA to solve the JSSP. In JSFMA,
considering a method similar to Shuffled Frog Leaping algorithm we divide the population in several sub
populations and then solve the problem using a Memetic algorithm. The proposed approach have been
compared with other algorithms for the Job Shop Scheduling and evaluated with satisfactory results on a
set of the JSSP instances derived from classical Job Shop Scheduling benchmarks. We have solved 20
benchmark problems from Lawrence’s datasets and compared the results obtained with the results of the
algorithms established in the literature. The experimental results show that JSFMA could gain the best
known makespan in 17 out of 20 problems.
Fiber reinforced polymer reinforcement for construction state of the art revieweSAT Journals
Abstract
Development of civil engineering is intimately connected to innovation in structural material. To full fill the requirement of advance infrastructure in India, modern technologies and innovative materials has started to makes its way. Structures with bar corrosion and other distresses requires repair, rehabilitation and retrofits for increase strength, durability and much more life span. Fiber reinforce plastic (FRP) reinforcements provides solution for such work due to its non-corrosive and non-magnetic nature also high strength and low weight ratio. Now a day FRP materials are used for internal reinforcement for RC structures worldwide.
Keywords: Fiber reinforced polymer (FRP), strength, durability, shear and flexure, fire endurance
Corrosion resistance performance of fly ash blended cement concreteseSAT Journals
Abstract Durability of reinforced concrete with respect to corrosion of reinforcement is one of the major aspects to be considered in the management of civil infrastructure systems. An accelerated laboratory test method developed at SERC where the concrete specimen containing rebar is subjected to polarization under a constant voltage in a sodium chloride solution. It is found that the current response with time follows that of a typical service life model indicating depassivation and corrosion propagation. Index terms- Materials, cement, super plasticizer, workability, compressive strength etc.
Design of the modern pasture batching system based on weighing instrumenteSAT Journals
Abstract For dairy cattle total mixed ration (TMR) feeding technology is the inevitable requirement of modern ranch, It was proposed that a ranch batching system based on weighing instrument, to achieve the production process of dairy cattle feed ingredients section of the fully automated production. Depend on the requirement of field process, the weighing instrument called ID510 is the ingredients and control core for the system, to realize the realization automated weighing ingredients for production equipment; write the PC code by using C++ Builder 6.0 to go through the human-computer interaction that used serial communication between weighing instrument and the upper computer. It could display the ingredient data by using Ethernet communication by UDP (user datagram protocol) between PC and screen monitor. It could realize management of recipes, ingredient monitoring, statistical report forms,historical data inquiry function by compiling ACCESS database. In actual batching process, the batching system running stability, friendly interface, the function indexes of the control system can satisfy the requirements of process, has obtained the good application effect. Keywords: Total mixed ration, Batching system, weighing instrument
Use of hydraulic phenomena in enhancement of dissolved oxygen concentrationeSAT Journals
Abstract
The dissolved oxygen (DO) content of water bodies is an indicator of water quality and hence a measure of ability of water to sustain aquatic life. Hydraulic phenomena such as hydraulic drops and hydraulic jumps can increase the amount of DO in the water by creating turbulent conditions. The main reason for this oxygen transfer is the air entrainment into the flow through large number of air bubbles that helps in air-water transfer. The present study investigates the effect of different weir types and hydraulic jump on their aeration efficiency. Two types of weirs namely rectangular and triangular weirs were used in the study. Also, the hydraulic jump was studied as an aeration agent. From the experimental results, it was found that the triangular weir provides greater aeration efficiency of 0.1948 as compared with rectangular weir that had aeration efficiency of 0.1012. On the other hand, the hydraulic jump showed aeration efficiency of 0.14285. As the weirs are more efficient than hydraulic jump, they are most applicable in the field. Also, weir structures are less expensive when compared with the structural arrangement required for the formation of hydraulic jump.
Keywords: Dissolved oxygen, Aeration efficiency, Weir, Hydraulic jump
Fluorescent disperse dyes reflectance spectra, relative strength and perfor...eSAT Journals
Abstract
This study attempted to focus on some important properties of regular fluorescent disperse dyes on polyester/cotton fabric. A 60/40 p/c blended woven fabric was used to dye only the polyester part in pad-thermosol dyeing process (continuous method) with different concentrations of fluorescent disperse dyes. The selected dyestuff was Terasil Flavine 10GFF belonging to coumarin class of fluorescent dye. This paper mainly aims to investigate Spectral parameters such as Reflectance curve, K/S values (with Kubelka-Munk equation) and Relative strength percentage with different concentrations of fluorescent dyes. Different color fastness properties like wash, water, rubbing, perspiration and light fastness were also assessed to evaluate performance of polyester substrate dyed with fluorescent dyes.
Keywords: Fluorescence, disperse dye, pad-thermosol dyeing, reflectance, k/s value, relative strength, color fastness.
Engineering Research Publication
Best International Journals, High Impact Journals,
International Journal of Engineering & Technical Research
ISSN : 2321-0869 (O) 2454-4698 (P)
www.erpublication.org
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A novel population-based local search for nurse rostering problem IJECEIAES
Population-based approaches regularly are better than single based (local search) approaches in exploring the search space. However, the drawback of population-based approaches is in exploiting the search space. Several hybrid approaches have proven their efficiency through different domains of optimization problems by incorporating and integrating the strength of population and local search approaches. Meanwhile, hybrid methods have a drawback of increasing the parameter tuning. Recently, population-based local search was proposed for a university course-timetabling problem with fewer parameters than existing approaches, the proposed approach proves its effectiveness. The proposed approach employs two operators to intensify and diversify the search space. The first operator is applied to a single solution, while the second is applied for all solutions. This paper aims to investigate the performance of population-based local search for the nurse rostering problem. The INRC2010 database with a dataset composed of 69 instances is used to test the performance of PB-LS. A comparison was made between the performance of PB-LS and other existing approaches in the literature. Results show good performances of proposed approach compared to other approaches, where population-based local search provided best results in 55 cases over 69 instances used in experiments.
Feature selection in high-dimensional datasets is
considered to be a complex and time-consuming problem. To
enhance the accuracy of classification and reduce the execution
time, Parallel Evolutionary Algorithms (PEAs) can be used. In
this paper, we make a review for the most recent works which
handle the use of PEAs for feature selection in large datasets.
We have classified the algorithms in these papers into four main
classes (Genetic Algorithms (GA), Particle Swarm Optimization
(PSO), Scattered Search (SS), and Ant Colony Optimization
(ACO)). The accuracy is adopted as a measure to compare the
efficiency of these PEAs. It is noticeable that the Parallel Genetic
Algorithms (PGAs) are the most suitable algorithms for feature
selection in large datasets; since they achieve the highest accuracy.
On the other hand, we found that the Parallel ACO is timeconsuming
and less accurate comparing with other PEA.
Particle Swarm Optimization based K-Prototype Clustering Algorithm iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A hybrid fuzzy ann approach for software effort estimationijfcstjournal
Software development effort estimation is one of the major activities in software project management.
During the project proposal stage there is high probability of estimates being made inaccurate but later on
this inaccuracy decreases. In the field of software development there are certain matrices, based on which
the effort estimation is being made. Till date various methods has been proposed for software effort
estimation, of which the non algorithmic methods, like artificial intelligence techniques have been very
successful. A Hybrid Fuzzy-ANN model, known as Adaptive Neuro Fuzzy Inference System (ANFIS) is more
suitable in such situations. The present paper is concerned with developing software effort estimation
model based on ANFIS. The present study evaluates the efficiency of the proposed ANFIS model, for which
COCOMO81 datasets has been used. The result so obtained has been compared with Artificial Neural
Network (ANN) and Intermediate COCOCMO model developed by Boehm. The results were analyzed using
Magnitude of Relative Error (MRE) and Root Mean Square Error (RMSE). It is observed that the ANFIS
provided better results than ANN and COCOMO model.
Data Warehouses are structures with large amount of data collected from heterogeneous sources to be
used in a decision support system. Data Warehouses analysis identifies hidden patterns initially unexpected
which analysis requires great memory and computation cost. Data reduction methods were proposed to
make this analysis easier. In this paper, we present a hybrid approach based on Genetic Algorithms (GA)
as Evolutionary Algorithms and the Multiple Correspondence Analysis (MCA) as Analysis Factor Methods
to conduct this reduction. Our approach identifies reduced subset of dimensions p’ from the initial subset p
where p'<p where it is proposed to find the profile fact that is the closest to reference. Gas identify the
possible subsets and the Khi² formula of the ACM evaluates the quality of each subset. The study is based
on a distance measurement between the reference and n facts profile extracted from the warehouse.
A MULTI-POPULATION BASED FROG-MEMETIC ALGORITHM FOR JOB SHOP SCHEDULING PROBLEMacijjournal
The Job Shop Scheduling Problem (JSSP) is a well known practical planning problem in the
manufacturing sector. We have considered the JSSP with an objective of minimizing makespan. In this
paper, we develop a three-stage hybrid approach called JSFMA to solve the JSSP. In JSFMA,
considering a method similar to Shuffled Frog Leaping algorithm we divide the population in several sub
populations and then solve the problem using a Memetic algorithm. The proposed approach have been
compared with other algorithms for the Job Shop Scheduling and evaluated with satisfactory results on a
set of the JSSP instances derived from classical Job Shop Scheduling benchmarks. We have solved 20
benchmark problems from Lawrence’s datasets and compared the results obtained with the results of the
algorithms established in the literature. The experimental results show that JSFMA could gain the best
known makespan in 17 out of 20 problems.
Fiber reinforced polymer reinforcement for construction state of the art revieweSAT Journals
Abstract
Development of civil engineering is intimately connected to innovation in structural material. To full fill the requirement of advance infrastructure in India, modern technologies and innovative materials has started to makes its way. Structures with bar corrosion and other distresses requires repair, rehabilitation and retrofits for increase strength, durability and much more life span. Fiber reinforce plastic (FRP) reinforcements provides solution for such work due to its non-corrosive and non-magnetic nature also high strength and low weight ratio. Now a day FRP materials are used for internal reinforcement for RC structures worldwide.
Keywords: Fiber reinforced polymer (FRP), strength, durability, shear and flexure, fire endurance
Corrosion resistance performance of fly ash blended cement concreteseSAT Journals
Abstract Durability of reinforced concrete with respect to corrosion of reinforcement is one of the major aspects to be considered in the management of civil infrastructure systems. An accelerated laboratory test method developed at SERC where the concrete specimen containing rebar is subjected to polarization under a constant voltage in a sodium chloride solution. It is found that the current response with time follows that of a typical service life model indicating depassivation and corrosion propagation. Index terms- Materials, cement, super plasticizer, workability, compressive strength etc.
Design of the modern pasture batching system based on weighing instrumenteSAT Journals
Abstract For dairy cattle total mixed ration (TMR) feeding technology is the inevitable requirement of modern ranch, It was proposed that a ranch batching system based on weighing instrument, to achieve the production process of dairy cattle feed ingredients section of the fully automated production. Depend on the requirement of field process, the weighing instrument called ID510 is the ingredients and control core for the system, to realize the realization automated weighing ingredients for production equipment; write the PC code by using C++ Builder 6.0 to go through the human-computer interaction that used serial communication between weighing instrument and the upper computer. It could display the ingredient data by using Ethernet communication by UDP (user datagram protocol) between PC and screen monitor. It could realize management of recipes, ingredient monitoring, statistical report forms,historical data inquiry function by compiling ACCESS database. In actual batching process, the batching system running stability, friendly interface, the function indexes of the control system can satisfy the requirements of process, has obtained the good application effect. Keywords: Total mixed ration, Batching system, weighing instrument
Use of hydraulic phenomena in enhancement of dissolved oxygen concentrationeSAT Journals
Abstract
The dissolved oxygen (DO) content of water bodies is an indicator of water quality and hence a measure of ability of water to sustain aquatic life. Hydraulic phenomena such as hydraulic drops and hydraulic jumps can increase the amount of DO in the water by creating turbulent conditions. The main reason for this oxygen transfer is the air entrainment into the flow through large number of air bubbles that helps in air-water transfer. The present study investigates the effect of different weir types and hydraulic jump on their aeration efficiency. Two types of weirs namely rectangular and triangular weirs were used in the study. Also, the hydraulic jump was studied as an aeration agent. From the experimental results, it was found that the triangular weir provides greater aeration efficiency of 0.1948 as compared with rectangular weir that had aeration efficiency of 0.1012. On the other hand, the hydraulic jump showed aeration efficiency of 0.14285. As the weirs are more efficient than hydraulic jump, they are most applicable in the field. Also, weir structures are less expensive when compared with the structural arrangement required for the formation of hydraulic jump.
Keywords: Dissolved oxygen, Aeration efficiency, Weir, Hydraulic jump
Fluorescent disperse dyes reflectance spectra, relative strength and perfor...eSAT Journals
Abstract
This study attempted to focus on some important properties of regular fluorescent disperse dyes on polyester/cotton fabric. A 60/40 p/c blended woven fabric was used to dye only the polyester part in pad-thermosol dyeing process (continuous method) with different concentrations of fluorescent disperse dyes. The selected dyestuff was Terasil Flavine 10GFF belonging to coumarin class of fluorescent dye. This paper mainly aims to investigate Spectral parameters such as Reflectance curve, K/S values (with Kubelka-Munk equation) and Relative strength percentage with different concentrations of fluorescent dyes. Different color fastness properties like wash, water, rubbing, perspiration and light fastness were also assessed to evaluate performance of polyester substrate dyed with fluorescent dyes.
Keywords: Fluorescence, disperse dye, pad-thermosol dyeing, reflectance, k/s value, relative strength, color fastness.
Design and manufacture of an angle adjustable crutch with kennedy key mechanismeSAT Journals
Abstract A crutch is a mobility aid that transfers weight from the legs to the upper body. It has been observed that users of walking aids require double the energy than the normal gait. Users experience a lot of stress at underarm and wrist while using standard underarm or forearm crutches which is the primary reason for pain and various medical complications. Therefore, a new design of crutch has been developed which allows the user to apply his/her weight over a larger area along the forearm instead of wrist and underarm. The primary objective of the study is provide more comfort to the end user of the crutch. The modeling of the new crutch design has been done using CAD modeling package (Catia). Finite Element Analysis (FEA) of the design has been conducted using ANSYS to understand the stress behavior in the new model. The new crutch has been fabricated using aluminum alloy because of its properties like high strength to weight ratio and low density. The fabrication of the new crutch has been performed in such a way that it ensured the entire crutch can be disassembled easily thus making it easily transportable. The testing of the new crutch has been carried out using energy expenditure method to assess the comfort level of the user. Keywords: Finite element analysis, crutch, gait, energy expenditure method, CAD
Experimental investigation of the performance of vcr diesel engine fuelled by...eSAT Journals
Abstract
Increasing demand of fuel in everyday life and its hazards cause serious problem for this planet. Serious attention is required to see this problem. In this paper there is a research to find out the alternative for diesel fuel and efforts to increase its performance. N-butanol is blended with diesel in different volume (B5 - 5% n-butanol and 95% diesel, B10, B15, B20, B25 and B30) and its effects on various performance parameters are studied. Increasing Butanol concentration in fuel increases BSFC of the engine. Increasing butanol ratio reduces the BTE of the engine from 24% to 22% at maximum load. Exhaust gas temperature reduces with increasing butanol. Mechanical efficiency also increases with addition of n-butanol.
Keywords: N-butanol, BSFC, BTE
An efficient image compression algorithm using dct biorthogonal wavelet trans...eSAT Journals
Abstract
Recently the digital imaging applications is increasing significantly and it leads the requirement of effective image compression techniques. Image compression removes the redundant information from an image. By using it we can able to store only the necessary information which helps to reduce the transmission bandwidth, transmission time and storage size of image. This paper proposed a new image compression technique using DCT-Biorthogonal Wavelet Transform with arithmetic coding for improvement the visual quality of an image. It is a simple technique for getting better compression results. In this new algorithm firstly Biorthogonal wavelet transform is applied and then 2D DCT-Biorthogonal wavelet transform is applied on each block of the low frequency sub band. Finally, split all values from each transformed block and arithmetic coding is applied for image compression.
Keywords: Arithmetic coding, Biorthogonal wavelet Transform, DCT, Image Compression.
Data preprocessing for efficient external sortingeSAT Journals
Abstract Paper presents external sorting using data preprocessing. Generally, huge data of any organization possess data redundancy, noise and data inconsistency. To eliminate, Data preprocessing should be performed on raw data, then sorting technique is applied on it. Data preprocessing includes many methods such as data cleaning, data integration, data transformation and data reduction. Depending on the complexity of given data, these methods are taken and applied on raw data in order to produce quality of data. Then, external sorting is applied. The external sorting now takes the number of passes less than actual passes log B (N/M) + 1 for B – way external merge sorting, and number of Input / Outputs less than 2*N* (log B (N/M) + 1) of Input / Outputs and also involve least number of runs compared to actual basic external sorting. Keywords: data preprocessing, external sorting, Data cleaning, passes, Inputs / Outputs, and runs.
A novel cryptographic technique that emphasis visual quality and efficieny by...eSAT Journals
Abstract Visual cryptography is a cryptographic technique which allows visual information to be encrypted in such a way that decryption becomes a mechanical operation that does not require a computer. The original image can be split into shares, where unauthorized person cannot get the data which we hide within that share images. By stacking the two shares, the secret data can be revealed. The highlighted issue in VC is, the size and quality of the reconstructed image should be same as the original image. In this paper, a novel k out of k extended visual cryptography scheme (EVCS) is used, to improve security and to produce meaningful shares. Halftone visual cryptography (VC) encodes a secret image into k halftone meaningful image shares through Floyd Steinberg error diffusion algorithm. The algorithm achieves dithering using error diffusion, meaning it pushes (adds) the residual quantization error of a pixel onto its neighboring pixels, to be dealt with later. This algorithm takes a substantial time for encryption and decryption in a considerably calmer manner. Comparisons with previous approaches show the superior performance of the new method.
Keywords: k out of k, extended visual cryptography, halftone visual cryptography, Floyd Steinberg error diffusion algorithm.
Study of mechanical and morphological properties of glass fiber reinforced mo...eSAT Journals
Abstract Polymethylmethacrylate and Poly (acrylonitrile-co-butadiene) rubber were used to modify Diglycidyl ether of bisphenol A (DGEBA) type epoxy resin and cured with stoichiometric quantities of the hardener 4,4’ diamino dipheny methane. This modified epoxy resin was used as the matrix for the preparation of glass fiber reinforced composites. E- Glass fiber was used as fiber reinforcement. The morphology and mechanical properties of the composite analysed. Morphological analysis of the fractured surface of the composites indicated good adhesion between the matrix polymer and the glass fibers. Hence an enhancement in mechanical properties of the composite such as tensile, flexural, impact and fracture toughness has been observed as there has been an effective transfer of the load from the matrix to the fiber. Hence these composites which exhibit high toughness, strength and dimensional stability can be envisaged to provide valuable contribution to high performance structural applications. Keywords: Glass composites, mechanical properties, modified epoxy matrix, morphology and ternary blend
The compensatation of unbalanced 3 phase currents in transmission systems on ...eSAT Journals
Abstract It is self-possessed of the Distributed Power Flow Controller is a new device within the family of FACTS. Power Quality is becoming an important issue for both electric utilities and end users. So the paper concentrate on one of the issue of power quality that is voltage sag compensation. My paper deals with the operation principle of a Practical Design and Implementation Procedure of Utilize Distributed Power Flow Controller (DPFC) to Compensate Unbalanced 3-phase Currents in Transmissions Systems. The series converters of the DPFC are single phase, the DPFC can compensate both active and reactive, zero and negative sequence unbalanced currents. To compensate the unbalance, two additional current controllers are supplemented to control the zero and negative sequence current respectively. FACTS devices can be employed to compensate the unbalanced currents and voltages in transmission systems. Unfortunately, it is found that the capability of most of FACTS devices to compensating unbalance is limited. Series and shunt FACTS device can only provide compensation of unbalanced reactive currents and the most powerful device – the UPFC cannot compensate zero-sequence unbalance current, because of the converter topology. My paper will show that the so-called DPFC can compensate both active and reactive, zero and negative sequence unbalanced currents. My paper consists of both active and reactive variations, using MATLAB/SIMULINK is simulated and its effects on the transmission lines observed. The simulated results are analyzed and validated with the real time results for the system considered Index Terms: AC–DC power conversion, filters, load flow control, power electronics, power-transmission control, power semiconductor devices, Power system control V-I measurements
Study of protein content and effect of p h variation on solubility of seed pr...eSAT Journals
Abstract Protein utilization in the different food systems principally depend on their functional properties. The solubility behavior of the seed protein is of great importance from the several points of view. It determines their utility for many industrial purposes. Solubility is a critical functional property, since a protein generally has to be in solution in order to exert its other desirable functional characteristics. Nitrogen Solubility Index and Protein Dispersibility Index (PDI) are the two most common methods of evaluating solubility characteristics. Hence in this study seeds of Eleusine coracana (variety DFM-1 and HR-374) minor millet were studied for protein solubility at wide range of pH from 0.5 to 13.5. Keywords: Protein solubility, Protein Dispersibility Index, Nitrogen Solubility Index, Minor millet Seeds, Variety of Eleusine coracana.
Design of c slotted microstrip antenna using artificial neural network modeleSAT Journals
Abstract In this paper, neural network model has been used to estimation of resonance frequency of a coaxial feed C-slotted Microstrip Antenna. The Multi-Layer Perceptron Feed forward back Propagation (MLPFFBP) and Radial basis function Artificial Neural Network (RBFANN) have been used to implement the neural network model. A relative performance analysis of the proposed neural network for different training algorithms. Number of neurons and number of hidden layer is also carried out for estimating the resonance frequency. The method of moment (MOM) based IE3D software was used to generate data dictionary for training and validation set of ANN. The results obtain using ANN are compared with simulation feeding and found quite satisfactory and also it is concluded that RBFANN network is more accurate and fast compared to MLPFFBP network algorithm. Index Terms: Artificial Neural Network, C slot, Microstrip Antenna, Multilayer Feed Forward Networks, Radial basis function Artificial Neural Network, Resonance frequency.
Design and simulation of a tunable frequency microstrip patch antennaeSAT Journals
Abstract This paper presents an evaluation of frequency reconfigurable patch antennas for X-band, using PIN diode as a switch. A pin diode is incorporated in the slot etched on rectangular patch antenna. The frequency band selectivity can be achieved by controlling the state of switch inserted in the antenna. We are using IE3D simulation software for designing and analysis. We have discussed and analyzed the performance of unslotted Rectangular Microstrip patch antenna and slotted rectangular patch antenna with PIN diode in ON and OFF states. Keyword: Microstrip Antenna, Return Loss, Radiation pattern, IE3D.
Design and development of aperture coupled rectangular microstrip antenna for...eSAT Journals
Abstract This paper presents the experimental investigations carried out for obtaining wide band operation of rectangular microstrip antenna by using aperture coupled feeding technique. By incorporating U-slots with stubs on the radiating element, antenna resonates for single wideband with an impedance bandwidth of 45.61%. The antenna has two resonant peaks f1 and f2 which occurs at 12.1 GHz and 14.38 GHz with minimum return loss of −32.46 dB and −46.12 dB respectively. The lower resonant frequency f1 is closer to the fundamental resonance of the rectangular patch. The second resonant frequency f2 is due to current along the edges of U-slots and stubs of aperture coupled U-slot and stub rectangular microstrip antenna (AUSRMSA). This technique also enhances the gain to 9.96 dB which is 1.89 times more than the gain of conventional rectangular microstrip antenna (CRMA). The enhancement of impedance bandwidth and gain does not affect the nature of broadside radiation characteristics. The design concepts of antennas are presented and experimental results are discussed. Keywords: Microstrip, wide band, Aperture coupled, Slots.
Effects of shape on the wind instigate response of high rise buildingseSAT Journals
Abstract A large number of structures that are being constructed at present tend to be wind-sensitive because of their slenderness, shapes, size, lightness and flexibility. With the ever increase in the vertical growth of urban cities, high rise buildings are being constructed in large numbers. In this study, analytical investigation of different shapes of buildings are taken as an example and various analytical approaches are performed on the building. These plans are modeled and wind loads are found out according to I.S 875(part 3)-1987 by taking gust factor and without taking gust factor. These models are compared in different aspects such as storey drift, storey displacement, storey shear, etc. for different shapes of buildings by using finite element software package ETAB’s 13.1.1v. Among these results, which shape of building provide sound wind loading to the structure as well as the structural efficiency would be selected. Key Words: Storey displacement, Storey drift, Storey shear, Gust, Wind load
Effects of welding current and arc voltage on fcaw weld bead geometryeSAT Journals
Abstract Flux cored arc welding(FCAW) process is characterized with its high deposition rate and productivity. Control of the operating parameters in FCAW is essential to obtain high production rates and good quality welds. Bead on plate welds were carried out on mild steel plates to study the influence of welding current and arc voltage on weld bead geometry parameters. The weld bead coss-sections were metallographically investigated. The effects of these welding parameters were evaluated by measuring penetration depth, reinforcement height, bead width, wetting angle, electrod deposit area and plate fusion area. The bead cross-section area and the weld shape factor were calculated from the measured results. The effects of welding parameters on weld bead geometry have been presented by histograms. Key Words: Flux cored arc welding, arc welding parameters, weld bead geometry, weld shape factor
Application of optimization algorithms for classification problemIJECEIAES
The work presented in this paper investigates the use of metaheuristic optimization algorithms for the face recognition problem. In the first setup, a face recognition system is implemented using particle swarm optimization (PSO) and firefly optimization algorithms, separately. PSO and firefly are used for forming the feature vectors in the feature selection stage. These feature vectors serve as the new representation for the face images that will be fed to the classifier. In the second setup, selected features from both PSO and firefly algorithms are fused to form one single feature vector for each face image before the classification stage. Extensive simulations are conducted using Poznan University of Technology (PUT) and face recognition technology (FERET) face databases. Optimal values for population size and maximum iterations number were selected before conducting the experiments. The effect of using different numbers of selected features on the performance is investigated for feature selection using PSO, firefly, and feature fusion of both.
Gesture Recognition using Principle Component Analysis & Viola-Jones AlgorithmIJMER
Gesture recognition pertains to recognizing meaningful expressions of motion by a human,
involving the hands, arms, face, head, and/or body. It is of utmost importance in designing an intelligent
and efficient human–computer interface. The applications of gesture recognition are manifold, ranging
from sign language through medical rehabilitation to virtual reality. In this paper, we provide a survey on
gesture recognition with particular emphasis on hand gestures and facial expressions. Applications
involving wavelet transform and principal component analysis for face and hand gesture recognition on
digital images
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Comparison Analysis of Gait Classification for Human Motion Identification Us...IJECEIAES
In this paper, it will be discussed about comparison between two kinds of classification methods in order to improve security system based of human gait. Gait is one of biometric methods which can be used to identify person. K-Nearest Neighbour has parallelly implemented with Support Vector Machine for classifying human gait in same basic system. Generally, system has been built using Histogram and Principal Component Analysis for gait detection and its feature extraction. Then, the result of the simulation showed that K-Nearest Neighbour is slower in processing and less accurate than Support Vector Machine in gait classification.
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Mechanical properties of hybrid fiber reinforced concrete for pavementseSAT Journals
Abstract
The effect of addition of mono fibers and hybrid fibers on the mechanical properties of concrete mixture is studied in the present
investigation. Steel fibers of 1% and polypropylene fibers 0.036% were added individually to the concrete mixture as mono fibers and
then they were added together to form a hybrid fiber reinforced concrete. Mechanical properties such as compressive, split tensile and
flexural strength were determined. The results show that hybrid fibers improve the compressive strength marginally as compared to
mono fibers. Whereas, hybridization improves split tensile strength and flexural strength noticeably.
Keywords:-Hybridization, mono fibers, steel fiber, polypropylene fiber, Improvement in mechanical properties.
Material management in construction – a case studyeSAT Journals
Abstract
The objective of the present study is to understand about all the problems occurring in the company because of improper application
of material management. In construction project operation, often there is a project cost variance in terms of the material, equipments,
manpower, subcontractor, overhead cost, and general condition. Material is the main component in construction projects. Therefore,
if the material management is not properly managed it will create a project cost variance. Project cost can be controlled by taking
corrective actions towards the cost variance. Therefore a methodology is used to diagnose and evaluate the procurement process
involved in material management and launch a continuous improvement was developed and applied. A thorough study was carried
out along with study of cases, surveys and interviews to professionals involved in this area. As a result, a methodology for diagnosis
and improvement was proposed and tested in selected projects. The results obtained show that the main problem of procurement is
related to schedule delays and lack of specified quality for the project. To prevent this situation it is often necessary to dedicate
important resources like money, personnel, time, etc. To monitor and control the process. A great potential for improvement was
detected if state of the art technologies such as, electronic mail, electronic data interchange (EDI), and analysis were applied to the
procurement process. These helped to eliminate the root causes for many types of problems that were detected.
Managing drought short term strategies in semi arid regions a case studyeSAT Journals
Abstract
Drought management needs multidisciplinary action. Interdisciplinary efforts among the experts in various fields of the droughts
prone areas are helpful to achieve tangible and permanent solution for this recurring problem. The Gulbarga district having the total
area around 16, 240 sq.km, and accounts 8.45 per cent of the Karnataka state area. The district has been situated with latitude 17º 19'
60" North and longitude of 76 º 49' 60" east. The district is situated entirely on the Deccan plateau positioned at a height of 300 to
750 m above MSL. Sub-tropical, semi-arid type is one among the drought prone districts of Karnataka State. The drought
management is very important for a district like Gulbarga. In this paper various short term strategies are discussed to mitigate the
drought condition in the district.
Keywords: Drought, South-West monsoon, Semi-Arid, Rainfall, Strategies etc.
Life cycle cost analysis of overlay for an urban road in bangaloreeSAT Journals
Abstract
Pavements are subjected to severe condition of stresses and weathering effects from the day they are constructed and opened to traffic
mainly due to its fatigue behavior and environmental effects. Therefore, pavement rehabilitation is one of the most important
components of entire road systems. This paper highlights the design of concrete pavement with added mono fibers like polypropylene,
steel and hybrid fibres for a widened portion of existing concrete pavement and various overlay alternatives for an existing
bituminous pavement in an urban road in Bangalore. Along with this, Life cycle cost analyses at these sections are done by Net
Present Value (NPV) method to identify the most feasible option. The results show that though the initial cost of construction of
concrete overlay is high, over a period of time it prove to be better than the bituminous overlay considering the whole life cycle cost.
The economic analysis also indicates that, out of the three fibre options, hybrid reinforced concrete would be economical without
compromising the performance of the pavement.
Keywords: - Fatigue, Life cycle cost analysis, Net Present Value method, Overlay, Rehabilitation
Laboratory studies of dense bituminous mixes ii with reclaimed asphalt materialseSAT Journals
Abstract
The issue of growing demand on our nation’s roadways over that past couple of decades, decreasing budgetary funds, and the need to
provide a safe, efficient, and cost effective roadway system has led to a dramatic increase in the need to rehabilitate our existing
pavements and the issue of building sustainable road infrastructure in India. With these emergency of the mentioned needs and this
are today’s burning issue and has become the purpose of the study.
In the present study, the samples of existing bituminous layer materials were collected from NH-48(Devahalli to Hassan) site.The
mixtures were designed by Marshall Method as per Asphalt institute (MS-II) at 20% and 30% Reclaimed Asphalt Pavement (RAP).
RAP material was blended with virgin aggregate such that all specimens tested for the, Dense Bituminous Macadam-II (DBM-II)
gradation as per Ministry of Roads, Transport, and Highways (MoRT&H) and cost analysis were carried out to know the economics.
Laboratory results and analysis showed the use of recycled materials showed significant variability in Marshall Stability, and the
variability increased with the increase in RAP content. The saving can be realized from utilization of recycled materials as per the
methodology, the reduction in the total cost is 19%, 30%, comparing with the virgin mixes.
Keywords: Reclaimed Asphalt Pavement, Marshall Stability, MS-II, Dense Bituminous Macadam-II
Laboratory investigation of expansive soil stabilized with natural inorganic ...eSAT Journals
Abstract
Soil stabilization has proven to be one of the oldest techniques to improve the soil properties. Literature review conducted revealed
that uses of natural inorganic stabilizers are found to be one of the best options for soil stabilization. In this regard an attempt has
been made to evaluate the influence of RBI-81 stabilizer on properties of black cotton soil through laboratory investigations. Black
cotton soil with varying percentages of RBI-81 viz., 0, 0.5, 1, 1.5, 2, and 2.5 percent were studied for moisture density relationships
and strength behaviour of soils. Also the effect of curing period was evaluated as literature review clearly emphasized the strength
gain of soils stabilized with RBI-81 over a period of time. The results obtained shows that the unconfined compressive strength of
specimens treated with RBI-81 increased approximately by 250% for a curing period of 28 days as compared to virgin soil. Further
the CBR value improved approximately by 400%. The studies indicated an increasing trend for soil strength behaviour with
increasing percentage of RBI-81 suggesting its potential applications in soil stabilization.
Influence of reinforcement on the behavior of hollow concrete block masonry p...eSAT Journals
Abstract
Reinforced masonry was developed to exploit the strength potential of masonry and to solve its lack of tensile strength. Experimental
and analytical studies have been carried out to investigate the effect of reinforcement on the behavior of hollow concrete block
masonry prisms under compression and to predict ultimate failure compressive strength. In the numerical program, three dimensional
non-linear finite elements (FE) model based on the micro-modeling approach is developed for both unreinforced and reinforced
masonry prisms using ANSYS (14.5). The proposed FE model uses multi-linear stress-strain relationships to model the non-linear
behavior of hollow concrete block, mortar, and grout. Willam-Warnke’s five parameter failure theory has been adopted to model the
failure of masonry materials. The comparison of the numerical and experimental results indicates that the FE models can successfully
capture the highly nonlinear behavior of the physical specimens and accurately predict their strength and failure mechanisms.
Keywords: Structural masonry, Hollow concrete block prism, grout, Compression failure, Finite element method,
Numerical modeling.
Influence of compaction energy on soil stabilized with chemical stabilizereSAT Journals
Abstract
Increase in traffic along with heavier magnitude of wheel loads cause rapid deterioration in pavements. There is a need to improve
density, strength of soil subgrade and other pavement layers. In this study an attempt is made to improve the properties of locally
available loamy soil using twin approaches viz., i) increasing the compaction of soil and ii) treating the soil with chemical stabilizer.
Laboratory studies are carried out on both untreated and treated soil samples compacted by different compaction efforts. Studies
show that increase in compaction effort results in increase in density of soil. However in soil treated with chemical stabilizer, rate of
increase in density is not significant. The soil treated with chemical stabilizer exhibits improvement in both strength and performance
properties.
Keywords: compaction, density, subgradestabilization, resilient modulus
Geographical information system (gis) for water resources managementeSAT Journals
Abstract
Water resources projects are inherited with overlapping and at times conflicting objectives. These projects are often of varied sizes
ranging from major projects with command areas of millions of hectares to very small projects implemented at the local level. Thus,
in all these projects there is seldom proper coordination which is essential for ensuring collective sustainability.
Integrated watershed development and management is the accepted answer but in turn requires a comprehensive framework that can
enable planning process involving all the stakeholders at different levels and scales is compulsory. Such a unified hydrological
framework is essential to evaluate the cause and effect of all the proposed actions within the drainage basins.
The present paper describes a hydrological framework developed in the form of a Hydrologic Information System (HIS) which is
intended to meet the specific information needs of the various line departments of a typical State connected with water related aspects.
The HIS consist of a hydrologic information database coupled with tools for collating primary and secondary data and tools for
analyzing and visualizing the data and information. The HIS also incorporates hydrological model base for indirect assessment of
various entities of water balance in space and time. The framework would be maintained and updated to reflect fully the most
accurate ground truth data and the infrastructure requirements for planning and management.
Keywords: Hydrological Information System (HIS); WebGIS; Data Model; Web Mapping Services
Forest type mapping of bidar forest division, karnataka using geoinformatics ...eSAT Journals
Abstract
The study demonstrate the potentiality of satellite remote sensing technique for the generation of baseline information on forest types
including tree plantation details in Bidar forest division, Karnataka covering an area of 5814.60Sq.Kms. The Total Area of Bidar
forest division is 5814Sq.Kms analysis of the satellite data in the study area reveals that about 84% of the total area is Covered by
crop land, 1.778% of the area is covered by dry deciduous forest, 1.38 % of mixed plantation, which is very threatening to the
environmental stability of the forest, future plantation site has been mapped. With the use of latest Geo-informatics technology proper
and exact condition of the trees can be observed and necessary precautions can be taken for future plantation works in an appropriate
manner
Keywords:-RS, GIS, GPS, Forest Type, Tree Plantation
Factors influencing compressive strength of geopolymer concreteeSAT Journals
Abstract
To study effects of several factors on the properties of fly ash based geopolymer concrete on the compressive strength and also the
cost comparison with the normal concrete. The test variables were molarities of sodium hydroxide(NaOH) 8M,14M and 16M, ratio of
NaOH to sodium silicate (Na2SiO3) 1, 1.5, 2 and 2.5, alkaline liquid to fly ash ratio 0.35 and 0.40 and replacement of water in
Na2SiO3 solution by 10%, 20% and 30% were used in the present study. The test results indicated that the highest compressive
strength 54 MPa was observed for 16M of NaOH, ratio of NaOH to Na2SiO3 2.5 and alkaline liquid to fly ash ratio of 0.35. Lowest
compressive strength of 27 MPa was observed for 8M of NaOH, ratio of NaOH to Na2SiO3 is 1 and alkaline liquid to fly ash ratio of
0.40. Alkaline liquid to fly ash ratio of 0.35, water replacement of 10% and 30% for 8 and 16 molarity of NaOH and has resulted in
compressive strength of 36 MPa and 20 MPa respectively. Superplasticiser dosage of 2 % by weight of fly ash has given higher
strength in all cases.
Keywords: compressive strength, alkaline liquid, fly ash
Experimental investigation on circular hollow steel columns in filled with li...eSAT Journals
Abstract
Composite Circular hollow Steel tubes with and without GFRP infill for three different grades of Light weight concrete are tested for
ultimate load capacity and axial shortening , under Cyclic loading. Steel tubes are compared for different lengths, cross sections and
thickness. Specimens were tested separately after adopting Taguchi’s L9 (Latin Squares) Orthogonal array in order to save the initial
experimental cost on number of specimens and experimental duration. Analysis was carried out using ANN (Artificial Neural
Network) technique with the assistance of Mini Tab- a statistical soft tool. Comparison for predicted, experimental & ANN output is
obtained from linear regression plots. From this research study, it can be concluded that *Cross sectional area of steel tube has most
significant effect on ultimate load carrying capacity, *as length of steel tube increased- load carrying capacity decreased & *ANN
modeling predicted acceptable results. Thus ANN tool can be utilized for predicting ultimate load carrying capacity for composite
columns.
Keywords: Light weight concrete, GFRP, Artificial Neural Network, Linear Regression, Back propagation, orthogonal
Array, Latin Squares
Experimental behavior of circular hsscfrc filled steel tubular columns under ...eSAT Journals
Abstract
This paper presents an outlook on experimental behavior and a comparison with predicted formula on the behaviour of circular
concentrically loaded self-consolidating fibre reinforced concrete filled steel tube columns (HSSCFRC). Forty-five specimens were
tested. The main parameters varied in the tests are: (1) percentage of fiber (2) tube diameter or width to wall thickness ratio (D/t
from 15 to 25) (3) L/d ratio from 2.97 to 7.04 the results from these predictions were compared with the experimental data. The
experimental results) were also validated in this study.
Keywords: Self-compacting concrete; Concrete-filled steel tube; axial load behavior; Ultimate capacity.
Evaluation of punching shear in flat slabseSAT Journals
Abstract
Flat-slab construction has been widely used in construction today because of many advantages that it offers. The basic philosophy in
the design of flat slab is to consider only gravity forces; this method ignores the effect of punching shear due to unbalanced moments
at the slab column junction which is critical. An attempt has been made to generate generalized design sheets which accounts both
punching shear due to gravity loads and unbalanced moments for cases (a) interior column; (b) edge column (bending perpendicular
to shorter edge); (c) edge column (bending parallel to shorter edge); (d) corner column. These design sheets are prepared as per
codal provisions of IS 456-2000. These design sheets will be helpful in calculating the shear reinforcement to be provided at the
critical section which is ignored in many design offices. Apart from its usefulness in evaluating punching shear and the necessary
shear reinforcement, the design sheets developed will enable the designer to fix the depth of flat slab during the initial phase of the
design.
Keywords: Flat slabs, punching shear, unbalanced moment.
Evaluation of performance of intake tower dam for recent earthquake in indiaeSAT Journals
Abstract
Intake towers are typically tall, hollow, reinforced concrete structures and form entrance to reservoir outlet works. A parametric
study on dynamic behavior of circular cylindrical towers can be carried out to study the effect of depth of submergence, wall thickness
and slenderness ratio, and also effect on tower considering dynamic analysis for time history function of different soil condition and
by Goyal and Chopra accounting interaction effects of added hydrodynamic mass of surrounding and inside water in intake tower of
dam
Key words: Hydrodynamic mass, Depth of submergence, Reservoir, Time history analysis,
Evaluation of operational efficiency of urban road network using travel time ...eSAT Journals
Abstract
Efficiency of the road network system is analyzed by travel time reliability measures. The study overlooks on an important measure of
travel time reliability and prioritizing Tiruchirappalli road network. Traffic volume and travel time were collected using license plate
matching method. Travel time measures were estimated from average travel time and 95th travel time. Effect of non-motorized vehicle
on efficiency of road system was evaluated. Relation between buffer time index and traffic volume was created. Travel time model has
been developed and travel time measure was validated. Then service quality of road sections in network were graded based on
travel time reliability measures.
Keywords: Buffer Time Index (BTI); Average Travel Time (ATT); Travel Time Reliability (TTR); Buffer Time (BT).
Estimation of surface runoff in nallur amanikere watershed using scs cn methodeSAT Journals
Abstract
The development of watershed aims at productive utilization of all the available natural resources in the entire area extending from
ridge line to stream outlet. The per capita availability of land for cultivation has been decreasing over the years. Therefore, water and
the related land resources must be developed, utilized and managed in an integrated and comprehensive manner. Remote sensing and
GIS techniques are being increasingly used for planning, management and development of natural resources. The study area, Nallur
Amanikere watershed geographically lies between 110 38’ and 110 52’ N latitude and 760 30’ and 760 50’ E longitude with an area of
415.68 Sq. km. The thematic layers such as land use/land cover and soil maps were derived from remotely sensed data and overlayed
through ArcGIS software to assign the curve number on polygon wise. The daily rainfall data of six rain gauge stations in and around
the watershed (2001-2011) was used to estimate the daily runoff from the watershed using Soil Conservation Service - Curve Number
(SCS-CN) method. The runoff estimated from the SCS-CN model was then used to know the variation of runoff potential with different
land use/land cover and with different soil conditions.
Keywords: Watershed, Nallur watershed, Surface runoff, Rainfall-Runoff, SCS-CN, Remote Sensing, GIS.
Estimation of morphometric parameters and runoff using rs & gis techniqueseSAT Journals
Abstract
Land and water are the two vital natural resources, the optimal management of these resources with minimum adverse environmental
impact are essential not only for sustainable development but also for human survival. Satellite remote sensing with geographic
information system has a pragmatic approach to map and generate spatial input layers of predicting response behavior and yield of
watershed. Hence, in the present study an attempt has been made to understand the hydrological process of the catchment at the
watershed level by drawing the inferences from moprhometric analysis and runoff. The study area chosen for the present study is
Yagachi catchment situated in Chickamaglur and Hassan district lies geographically at a longitude 75⁰52’08.77”E and
13⁰10’50.77”N latitude. It covers an area of 559.493 Sq.km. Morphometric analysis is carried out to estimate morphometric
parameters at Micro-watershed to understand the hydrological response of the catchment at the Micro-watershed level. Daily runoff
is estimated using USDA SCS curve number model for a period of 10 years from 2001 to 2010. The rainfall runoff relationship of the
study shows there is a positive correlation.
Keywords: morphometric analysis, runoff, remote sensing and GIS, SCS - method
-
Effect of variation of plastic hinge length on the results of non linear anal...eSAT Journals
Abstract The nonlinear Static procedure also well known as pushover analysis is method where in monotonically increasing loads are applied to the structure till the structure is unable to resist any further load. It is a popular tool for seismic performance evaluation of existing and new structures. In literature lot of research has been carried out on conventional pushover analysis and after knowing deficiency efforts have been made to improve it. But actual test results to verify the analytically obtained pushover results are rarely available. It has been found that some amount of variation is always expected to exist in seismic demand prediction of pushover analysis. Initial study is carried out by considering user defined hinge properties and default hinge length. Attempt is being made to assess the variation of pushover analysis results by considering user defined hinge properties and various hinge length formulations available in literature and results compared with experimentally obtained results based on test carried out on a G+2 storied RCC framed structure. For the present study two geometric models viz bare frame and rigid frame model is considered and it is found that the results of pushover analysis are very sensitive to geometric model and hinge length adopted. Keywords: Pushover analysis, Base shear, Displacement, hinge length, moment curvature analysis
Effect of use of recycled materials on indirect tensile strength of asphalt c...eSAT Journals
Abstract
Depletion of natural resources and aggregate quarries for the road construction is a serious problem to procure materials. Hence
recycling or reuse of material is beneficial. On emphasizing development in sustainable construction in the present era, recycling of
asphalt pavements is one of the effective and proven rehabilitation processes. For the laboratory investigations reclaimed asphalt
pavement (RAP) from NH-4 and crumb rubber modified binder (CRMB-55) was used. Foundry waste was used as a replacement to
conventional filler. Laboratory tests were conducted on asphalt concrete mixes with 30, 40, 50, and 60 percent replacement with RAP.
These test results were compared with conventional mixes and asphalt concrete mixes with complete binder extracted RAP
aggregates. Mix design was carried out by Marshall Method. The Marshall Tests indicated highest stability values for asphalt
concrete (AC) mixes with 60% RAP. The optimum binder content (OBC) decreased with increased in RAP in AC mixes. The Indirect
Tensile Strength (ITS) for AC mixes with RAP also was found to be higher when compared to conventional AC mixes at 300C.
Keywords: Reclaimed asphalt pavement, Foundry waste, Recycling, Marshall Stability, Indirect tensile strength.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
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Feature selection using modified particle swarm optimisation for face recognition
1. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
_______________________________________________________________________________________
Volume: 04 Issue: 02 | Feb-2015, Available @ http://www.ijret.org 679
FEATURE SELECTION USING MODIFIED PARTICLE SWARM
OPTIMISATION FOR FACE RECOGNITION
Hemalatha Gayatri L1
, Govindan V.K2
1
PG scholar, Department of Computer science & engineering, National Institute of Technology Calicut, Kerala, India.
2
Professor, Department of Computer science & engineering, National Institute of Technology Calicut, Kerala, India.
Abstract
One of the major influential factors which affects the accuracy of classification rate is the selection of right features. Not all
features have vital role in classification. Many of the features in the dataset may be redundant and irrelevant, which increase the
computational cost and may reduce classification rate. In this paper, we used DCT(Discrete cosine transform) coefficients as
features for face recognition application. The coefficients are optimally selected based on a modified PSO algorithm. In this, the
choice of coefficients is done by incorporating the average of the mean normalized standard deviations of various classes and
giving more weightage to the lower indexed DCT coefficients. The algorithm is tested on ORL database. A recognition rate of
97% is obtained. Average number of features selected is about 40 percent for a 10 × 10 input. The modified PSO took about 50
iterations for convergence. These performance figures are found to be better than some of the work reported in literature.
Keywords: Particle swarm optimization, Discrete cosine transform, feature extraction, feature selection, face
recognition, classification rate.
--------------------------------------------------------------------***----------------------------------------------------------------------
1. INTRODUCTION
Humans have the ability to recognize faces easily and
effortlessly but in the area of image analysis and computer
vision it remained as a difficult problem on which many
years of research is going on. A complete review of
techniques for face recognition can be found in [1]. An
unknown digital image is identified from a database of
known images in face identification whereas in face
recognition the person’s identity is confirmed by the system
from a stored database of faces. To verify or identify a
person in the digital image, features extracted from the
digital image are compared with features of the images in
the facial database. Face recognition has applications in
legacy systems such as voter registration, passports and
driver’s licenses, crowd surveillance, human-computer
interaction, multimedia management, smart cards, access
control and authentication. Occlusion, pose variation and
illumination problems are still challenging for face
recognition. Face recognition as a biometric has an
advantage that it requires no co-operation of the person
unlike other biometrics.
A problem called as curse of dimensionality exists because
of large number of features. The search space is explored by
the feature selection algorithm to find the optimal feature
subset.Feature selection algorithms can be broadly
classified into wrappers and filters [2], which are
distinguished based on the choice of evaluation metric. A
learning algorithm is used as a part of evaluation function in
the search process of wrapper approaches whereas filters
methods are independent of learning algorithm. Wrapper
methods tend to provide better results and are
computationally intensive than filter methods.
Optimal feature selection (FS) is to find the minimal set of
features from original feature set that can represent the
whole set. Redundant and irrelevant features which have
insignificant effect on the output are removed. Redundant
features are those which doesn’t provide any extra
information than the present and irrelevant features doesn’t
provide any useful information. Feature Selection has
significant role in many applications like biometrics,
machine learning, computer vision, and medical imaging.
Exhaustive search can be done on all combinations possible
with input features to obtain the optimal feature subset but it
is computationally very expensive. With increase in the
dimension of feature space, cost associated for search of
optimal feature subset becomes exponentially high. PSO and
GA are some of the evolutionary computation techniques
which are applicable to the feature selection problems
because of their global search ability.
1.1 Feature Extraction
In face recognition, the first step is feature extraction from
the images. In this paper, feature extraction technique used
is DCT. Information about feature extraction by DCT for
face recognition can be found in [3], [4], [5]. DCT has
strong energy compaction property [6]. DCT can represent
effective features of input image with few coefficients in the
upper left corner of the matrix. Image can be roughly
constructed using these few DCT coefficients.
1.2 Particle Swarm Optimization
Swarm intelligence is a discipline that deals with a system
that is composed of many individuals, that are
homogeneous, self-organized and are coordinated using
decentralized control. The behaviour of the system depends
upon interactions among the individuals and with their
environment.
2. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 04 Issue: 02 | Feb-2015, Available @ http://www.ijret.org 680
PSO is inspired by collective behaviour of social models
such as flock of birds and school of fishes, designed by
Kennedy and Eberhart in 1995. Implementation of PSO is
easier, it has few parameters, it is computationally
inexpensive, and the convergence rate is quicker when
compared with genetic algorithm and genetic programming
[7].PSO possesses the search ability for the best solutions
for optimization problems because of its intelligent
properties like adaptation and self-organizing [8]. Only
primitive mathematical operators are used in PSO. PSO has
an advantage because it is computationally inexpensive and
has low memory requirements [9].
1.2.1 PSO Algorithm
In PSO, a group of particles explores the solution space to
find the best solution. In particle swarm optimization, each
solution is treated as an individual bird in the swarm, i.e., a
particle in the search space. Position of ith
particle is denoted
by Xi = (x1,x2,..,xd) and velocity Vi be (v1,v2,..,vd) in the D
dimensional search space. Each particle uses its individual
experience and its neighbouring particles experience to
move in the search space, that is, every particle has
knowledge about its best position it has found so far and the
best position found by swarm .We denote, PBi as the best
position (pbest) of ith
particle, and gbest as the best position
found by the swarm so far. Every particle is given random
initial position and random initial velocity. Fitness function
evaluates every particle in the search space. It determines
the quality of the particle. Particles are attracted towards
best particles in their search space which have best fitness
values. The velocity and position of particles are updated
according the equation.
(1)
where, i= , N represents the swarm size, rand1 and
rand2 are two random numbers uniformly distributed in the
range 0 and 1, and c1 and c2 are constants. Velocity is
updated based on the inertia of previous velocity, experience
of the particle itself and the experience of the neighboring
particles. Particle position is updated by:
(2)
In every iteration, fitness of every particle is evaluated.
Velocity is updated based on pbest and gbest values and
parameters like c1, c2 and w. Position is updated based on
velocity. This process is repeated until maximum iterations
or error criterion is reached.
1.2.2 Fitness Function
Fitness is a measure that determines the quality or goodness
of a particle. In each iteration every particle is evaluated for
fitness value .The particles quality is evaluated by its ability
to increase class separation. Position vector is represented
by binary values 0’s and 1’s. Let c1.c2,…,cL denote the
classes and N1,N2,…,NL denotes the number of images in
different classes. L be the total number of classes. N is the
total number of images. Let, M1,M2,…ML be the mean of
each class and M0 be the global mean, i.e., mean of all
classes. They are calculated as below.
(3)
(4)
Fitness function is calculated as:
(5)
Pseudo code of PSO algorithm
Initialise Parameters w, c1,c2;
For every particle i
Initialise VelocityVectorVi ;
Initialise PositionVector Xi ;
end
Do until maximum number of iterations
For every particle i
f=fitness(Xi);
If fitness(PBi) < f
PBi=Xi ;
end
If f >fitness(gbest) ;
gbest= Xi;
end
Update Vi;
Update Xi;
end
end
2. RELATED WORK
Some of the recent publications in this topic of research are
briefly reviewed in the following.
Ramadan and Kader [10] has presented a feature selection
algorithm using PSO for face recognition. PSO is applied on
the coefficients (features) of Discrete Cosine Transform
(DCT) and Discrete Wavelet Transform (DWT) to select
the optimum features of image. The optimum subset of
features are selected by PSO based on the fitness function.
ORL database is used for testing the performance. Face
recognition is carried out based on Euclidean distance
between features of unknown face and the features of faces
in the database. The proposed algorithm has better
performance when compared to GA-based feature selection
algorithms in terms of number of features selected and
classification accuracy rate.
Yun et al. [11] proposed feature selection methods using
algorithms like Genetic algorithm and Particle Swarm
Optimisation. An algorithm which makes use of relevance
of features is also proposed. A measure known as minimum
redundancy and maximum relevance (MRMR) is used to
select features, using which redundancy of features is
3. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 04 Issue: 02 | Feb-2015, Available @ http://www.ijret.org 681
minimised and relevance of features is maximised. This
method, when used with genetic algorithm and PSO,
provided quality feature set and achieved better accuracy
rate.
Bing Xue et al. [12] has proposed a binary particle swarm
optimization (BPSO) with two new fitness functions to
minimise the number of features selected and to maximise
the classification accuracy rate. First one linearly changes
weights of fitness function and the other one uses two-stage
fitness function. Experiment results have shown that the
BPSO with the two new fitness functions provides better
results compared to classification performance used as
fitness function.
Unlerand Murat [13] has proposed a modified discrete PSO
algorithm for feature selection. In this approach, the
relevance and dependence of features to be included in the
feature sub-set is dynamically decided by using an adaptive
feature selection algorithm proposed by them. Experimental
results show that it is computationally less expensive and
provides improved recognition rate .
Yuanning Liu et al. [14] has proposed a modified
multiswarm PSO (MSPSO). The particles are split into set
of subsets called sub swarms. Sub swarms are controlled
and monitored by a scheduler. They introduced a
mechanism to decide the survival of sub swarm called as
survival of the fittest. An improved feature selection method
(IFS) has also been designed. The proposed algorithm gave
better results when compared to standard PSO, GA and grid
search in terms of classification accuracy rate.
Liam Cervante et al. [15] has developed two new feature
selection approaches based BPSO. The relevance and
redundancy in the feature subsets is measure by mutual
information and entropy. The two new algorithms are
applied on training data from the dataset and the feature
subset is selected. The subsets’ classification performance is
evaluated by a learning algorithm. The resulting feature set
is found to have less number of features and achieved same
or higher classification rate.
Bing Xue et al.[16] has proposed a new approach for feature
selection based on PSO. In this approach, an external
archive is introduced which stores solutions which are later
used to determine gbest of particles. Particles gbest is
chosen from the solutions in archive using selection
methods such as random selection and roulette wheel
selection. The proposed approaches perform better than the
standard PSO. They select less number of features and have
same or higher classification rate.
From the review given above, it can be concluded that there
is scope for further reduction in feature dimensionality using
new rules for updating the position in PSO algorithm. The
use of features selected by such a modified algorithm is
expected to provide faster computation and improved
recognition performances.
3. MODIFIED PSO ALGORITHM
A modified PSO algorithm has been proposed for feature
selection. Feature selection becomes complex with the
increase in number of features in dataset. Dataset contains
all kinds of features that may be relevant or irrelevant and
redundant. Redundant features decrease the quality of
feature set. With increase in feature number in the dataset,
computational complexity also increases. Optimal features
set is the minimal set of features that provides the optimal
performance. Optimal feature selection using PSO is
proposed to improve the quality of the feature set by
eliminating insignificant features which have very less or
no contribution to outcome, thereby, reducing the number of
features and decreasing computational cost and/or
increasing accuracy of classification rate.
The update mechanism for the position of particle in binary
PSO algorithm is modified to minimize the number of
features and maximize the recognition rate. In the modified
approach, the choice of coefficients is done by incorporating
the average of the mean normalized standard deviations of
various classes and giving more weightage to the lower
indexed DCT coefficients.
Standard deviation for each class is computed as below.
(6)
where n is the number of training images in each class and µ
denotes the mean value of DCT coefficients of training
images in each class and xi denotes DCT coefficients of
each of the training images.
Average of the mean normalized standard deviations of
various classes is calculated as:
(7)
(8)
(10)
where i=1,2,…L. L is the number of classes, total mean is
the sum of all classmeans. Classmean is computed as in
equation 3.
The position of the particle in Modified Binary PSO is
updated by the following equation.
and( , S < median ) (11)
where g,h are matrix indexes, then Xi
t+1
=1 else Xi
t+1
= 0
4. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 04 Issue: 02 | Feb-2015, Available @ http://www.ijret.org 682
The procedure is briefly described in the following:
1. Feature Extraction: DCT coefficients are used as
features.. DCT coefficients on the left upper corner
have significant information. So, only few
coefficients are used in this approach. A 10 × 10
matrix is given as input to BPSO algorithm.
2. Apply Binary PSO algorithm to the subsets of DCT
coefficients obtained from the images in database.
3. Features of the input images which are more
effective are selected. Features which have no
significant contribution to classification accuracy are
removed.
4. Euclidean distance is used for identifying the
images . Face image corresponding to lowest
Euclidean distance is considered as result in this
approach.
Fig-1: Face recognition using PSO
4. EXPERIMENTAL RESULTS
The 2D DCT is applied on input images. DCT coefficients
are used as features. Modified Binary PSO algorithm is
applied to the 10×10 matrix of DCT coefficients obtained
from the images in database. Optimal Feature Set is
obtained based on the fitness function after specified
number of iterations.
Table-1: PSO Parameters
Swarm size 30
w 0.6
c1 2
c2 2
For performance analysis, ORL database is used which
contains 400 images. It contains 10 images for 40 distinct
persons. 4 out of 10 images for each person are used for
training and the rest are used for testing. Each image
resolution is 92 ×112 , with 256 grey levels per pixel.
Table-2: comparison of modified algorithm with [10]
Modified PSO
algorithm
[10]
Number of
training images
240 240
Number of test
images
260 260
Recognition rate 97% 94.8%
Number of
Iterations
50 100
Input Matrix size 10 × 10 50 × 50
Average features
selected
40% 50%
5. CONCLUSION
Optimal feature selection (FS) is to find the minimal subset
of features from original feature set that can represent the
whole set. PSO algorithm explores entire feature set and
finds optimal feature subset. There are many important
factors in PSO, such as the initialization strategy and the
updating mechanisms which can be further analyzed to
improve the performance and increase classification
accuracy rate. .In the modified algorithm, while updating the
position vector , the average of the mean normalized
standard deviations of various classes is considered and
more weightage is given to the lower indexed DCT
coefficients. The modified algorithm when tested on ORL
database has classification accuracy rate of 97% and the
average number of features selected are 40 for a 10 * 10
input matrix.
5. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 04 Issue: 02 | Feb-2015, Available @ http://www.ijret.org 683
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