International Journal of Engineering and Manufacturing @ijem
Статьи журнала - International Journal of Engineering and Manufacturing
Все статьи: 520
Oscillatory Behavior of a Class of Second-order Nonlinear Dynamic Equations on Time Scales
Статья научная
The paper is devoted to the oscillation of a class of second-order nonlinear dynamic equations on time scales. By developing a generalized Riccati transformation technique, we establish some oscillation criteria for all solutions of the equations. Our results improve and extend some known results in the literature.
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PID Temperature Controller Design for Shell and Tube Heat Exchanger
Статья научная
Heat exchangers are one of the most important thermal devices. Shell and tube heat exchangers are the common types of heat exchangers and sustained a wide range of operating temperature and pressure. Modeling and controlling heat exchanger system is a difficult assignment because of its nonlinearity. As the flow rates changes, the gain, time delay and time constant varies, hence causing system nonlinearity. The solution for such problems is finding acceptable mathematical model and design a controller which provides better performance indices. In this paper mathematical model (experimental or empirical based) to represent the real system and design suitable controller which remove the offset and settle fast with minimum steady state error has been proposed. To this end, system model design the Proportional-Integral-Derivative controller for shell and tube heat exchanger using Ziegler Nichols method, Cohen-coon method and Chein et al. method. Since two opposing dynamic effects are existing in the system and has a problem of dynamics of inverse response and large overshoot. Therefore, Chein et al. tuning method have better performance than that of the others. In case of Chein et al. the overshoot of 2.577 % and settling time of 63.1 s.
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PID control design for second order systems
Статья научная
The Proportional Integral Derivative (PID) controllers are most commonly used in industries to compensate several numbers of practical industrial processes by the virtue of their simplicity and robustness. Several tuning methods exist for parameter tuning of PID controller. In this paper PID control design for second order system has been done with various methods. The effectiveness of tuning methods has been compared based up on time response specifications.
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Pain Expression Recognition Based on SLPP and MKSVM
Статья научная
In this paper, a novel approach is proposed for recognizing pain expression. First of all, supervised locality preserving projections (SLPP) is adopted for extracting feature of pain expression, which can solve the problem that LPP ignores the within-class local structure using adopting prior class label information, and then multiple kernels support vector machines (MKSVM) is employed for recognizing pain expression, Compared to SVM, which can improve the interpretability of decision function and classifier performance. Experimental results are shown to demonstrate the effectiveness of the proposed method.
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Parallelization of Needleman-Wunsch Algorithm Based on Software Pipelining
Статья научная
Sequence alignment is one of the most important algorithms that analyzing massive biological information. In modern bioinformatics, it plays an important role in field of serching for similar sequences, predicting sequence information of unkown sequence, looking for specific position of sequence, predicting protein structure and so on. Needleman-Wunsch algorithm is the earliest global alignment algorithm, it gets widely application with its accuracy, however, it has a high time complexity and its speed is slower. This paper adopts software pipelining technique to optimize Needleman-Wunsch algorithm with parallelization, and OpenMP which is the industrialized standard of shared memory programming is used to parallelize it. The performance of Needlelman-Wunsch algorithm can get a great improvement with the optimization.
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Parametric Optimization of Drilling Parameters in Aluminum 6061T6 Plate to Minimize the Burr
Статья научная
In the manufacturing, process a burr has been observed during the drilling through a hole in an aluminum bar. From the view of the life of a product, minimization of the burr should be significant. So in this research main aim is to identify how input parameters: drill diameter, point angle & spindle speed influenced output parameters burr height & thickness. To execute this operation a total of 27 examinations on an Aluminum 6061T6 plate is taken. Overall research performed into two stages. In first stage, Surface response methodology is used to design two objective functions for burr height & thickness with the help of input parameters and then these two objective functions combined to construct a single objective function. In next stage improved version of elephant swarm optimization (ESWSA) algorithm is applied to get the optimum input parameters. The predicted output variable after the optimization techniques (Test 2 & Test 3) further checked with experimental result to determine the accuracy of the proposed model. In a conclusion section it is seen that the average error of drill diameter, drill point angle & spindle speed are 1.72%, 3.84% & 3.89% respectively with average RMSE is 2.56 *10^-6. For further validation of effectiveness of proposed model is also compared with the state of art techniques in the field burr minimization.
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Parametric optimization of Liquid Flow Process by ANOVA Optimized DE, PSO & GA Algorithms
Статья научная
Control of liquid level & flow are the most interest domain in process control industry. Generally process parameter of the liquid flow system is varied frequently during the operation. So the selection of the level of process parameters i.e. input variables seems to be important for achieving the optimum flow rate. In the present work focus is given on the identification of the proper combination of the input parameters in liquid flow rate process. Flow sensor output, pipe diameter, liquid conductivity & viscosity have been taken as input parameter; flow rate obtained from test is taken as response parameter. Till now several researchers have been performed various optimization methods for optimized the parameters of the process plant. But still computational time & convergence speed of the applied optimization techniques for the modelling of the nonlinear process system is still an open challenge for the modern research. In this research we proposed three evolutionary algorithms are used to optimize the process parameters of the nonlinear model implemented by ANOVA to mitigate the unbalance, convergence speed and reduce the total computational time. Overall research performed into three stage, in first phase nonlinear equation ANOVA has been used for mathematical model for the process, In second stage three evolutionary algorithms: GA, PSO & DE are applied for parametric optimization of liquid flow process to maximize the response parameter & in last phase comparative study performed on simulated results based on confirmed test & validated our proposed methodology.
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Particle Swarm Optimization With Adaptive Parameters and Boundary Constraints
Статья научная
The core idea of PSO is that each particle searches the best solution of optimization problems according to “information sharing” between surrounding particles and itself. PSO has fast convergence speed and high global search capability. For low accuracy and divergent results of elementary PSO, this paper proposes a kind of PSO with adaptive parameters and boundary constraints. Inertia weight and learning factors increase or decrease linearly with iterative process, in order that the particles search the global space in early period of the algorithm and converge towards the global optimum later. At the same time, the author sets particle boundary constraints to ensure the optimization accuracy. Theoretical analysis and numerical simulation results show the efficiency and high optimization accuracy of the designed method.
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Performance Analysis of Image Processing Algorithms using Matlab for Biomedical Applications
Статья научная
Image processing is used in every sphere of life such as agriculture, remote sensing, wireless, medical etc. Bi-omedical imaging plays a vital role in the detection of diseases. Without image processing, it is not possible to detect diseases such as cancer, tumors etc. Medical equipment such as ultrasound, MRI, CT scan machine is totally dependent on image processing algorithms. Radiologists utilize these image processing algorithms to detect diseases and abnormalities. Matlab is a proprietary tool which is used by image architects in order to design these algorithms. Image processing algorithms designed using Matlab provides efficiency, accuracy, flexibility and timing constraints. The present paper addresses various image processing algorithms designed using Matlab. The performance of these algorithms is also analyzed visually as well as statistically in order to check the quality of images.
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Статья научная
This paper proposes a new MATLAB built-in function, mathematical and simulink models, all to be simultaneously simple, user–friendly and to be used to face the two top challenges in developing mechatronic motion control systems, particularly, the early identifying system level problems and ensuring that all design requirements are met, as well as, to simplify and accelerate Mechatronics motion control design process including; performance analysis and verification of a given electric DC system, proper controller selection and verification for desired output speed or angle. The proposed models and function are intended for research purposes, application in educational process, and to be used by the mechatronics students and engineers for selection, design and verification purposes.
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Performance Study on the System of Real-Time VBR Service with Shared Cache
Статья научная
In this paper, we study a system that adopts complete sharing admission policy to multiple broadband real-time variable bit rate (VBR) service sharing a common buffer or cache. Under joint connection-level and packet-level analysis, we utilize shared cache queue model with multiple ON-OFF sources to analyze the probability distribution of the number of packets and then obtain the formulas of calculating packet loss rate and average delay. Through numerical calculation, the results compared with the non-caching system indicate that the packet loss rate has decreased, but the average delay has increased. Taking into account the delay sensitive nature of real-time VBR service, this paper puts forward a call admission control (CAC) algorithm that gives consideration to both packet-level performance parameters and connection-level performance parameters. The algorithm optimizes the average delay of the system with constraints on call blocking probabilities for each kind of VBR service and a common packet loss rate for all services. Numerical examples exhibit the nature of such systems.
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Performance optimization of codec in VOIP using Raspberry Pi
Статья научная
This paper aims in design and implementation of Voice over Internet Protocol (VoIP) system with a high compression rate. The system uses a Raspberry Pi B+ ARM 11 microcontroller which is faster in processing the audio signal by means of CODEC2 software. An Audio Adapter (CM-108 or 109) is interfaced with the Raspberry Pi, which acts as a bridge in providing the processed voice signal to Raspberry Pi in its required PCM format. The setup is implemented in Local Area Network (LAN) in which the data transmission occurs. During the transmission of the data, the wireshark software was used to analyze the data in the network. A detailed analysis of the comparison results of different CODECs for compression rate and the estimated frame sizes are given. From the results, it is proved that the use of CODEC2 is an efficient system for VoIP. For secure communication, the AES encryption protocol with static private key was implemented. The 3.2Kbps compression technique is suitable for VoIP system as it has high compression rate and less delay compared to the other systems.
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Perspective directions of development of innovative structures on the basis of modern technologies
Статья научная
The article analyzes the need to create innovative manufacturing enterprises in modern conditions, and justifies their role in the development of society. The principles, priorities and strategic requirements to the innovative manufacturing enterprises in the process of economic development are analyzed. International, regional and local recommendations for the formation of innovative enterprises structures are generalized. Perspective applications of components of the fourth industrial revolution are considered. Ways of improving the innovation infrastructure and environment are examined from the scientific and theoretical and methodological point of view. Priorities, mechanisms, elements of communication, the parameters and criteria for the management of innovative manufacturing enterprises structures are identified.
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Positive Crankcase Ventilation System
Статья научная
In this paper, we have studied the traditional Positive Crankcase Ventilation (PCV) valve equipment. Then we have improved the system by adding ventilation equipment. We have applied this kind of connection equipment on gas engine which has no PCV. This can determine the engine fuel-air ratio and make the engine get the best power performance, economical efficiency and emission behavior. Because emission amount is based on input air amount, so how to control the input air amount is the basis of the whole system. On the basis of traditional inlet manifold MVEM, we have considered the affection of PCV system, and we have simulated the actual input air process by getting improved module’s input air amount and inlet manifold pressure parameters. So the fuel-air ratio precision can be increased greatly. We also have prompted some improving directions about traditional inlet manifold. So we can ensure that engine can get a compact structure and good response on the all operation states.
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Статья научная
A model of post-craniectomy intracranial pressure dynamics is proposed in this article. Defining the craniectomy distensible volume the original Monro-Kellie principle is generalized. A craniectomy compartment is added to traditional intracranial system including blood, cerebrospinal fluid, and brain parenchyma. The system equation of generalized Monro-Kellie principle is solved with 4th order runge-kutta method. Volume of the new compartment is calculated with deflection solution. The model verifies that abnormal morphology of intracranial pressure (systolic value-21mmHg and diastolic value-13mmHg) in hypertension can be reduced to a normal range (systolic value-14.5mmHg and diastolic value-13mmHg) with decompressive craniectomy. Additionally the ICP-DC Size curve provides an effective interval (about 80-200 square centimeters) of craniectomy size for practice of decompressive craniectomy.
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Power Quality Analysis of ANFIS based Distributed Generation System with UPQC
Статья научная
This paper presents a comprehensive analysis of power quality in a distributed generation (DG) system utilizing an Adaptive Neuro-Fuzzy Inference System (ANFIS) and a Unified Power Quality Conditioner (UPQC). The integration of distributed generation resources, such as solar and wind power, into the electrical grid has posed significant challenges related to power quality, including voltage sags, swells, harmonics, and reactive power issues. To address these challenges, the proposed system employs ANFIS for adaptive and precise control, enhancing the performance and stability of the DG system. The UPQC is integrated to mitigate power quality disturbances by simultaneously compensating for voltage and current harmonics and providing voltage regulation. Detailed simulations are conducted to evaluate the effectiveness of the ANFIS-based control strategy and the performance of the UPQC in various operating conditions. The results demonstrate significant improvements in power quality metrics, highlighting the potential of this approach for efficient and reliable integration of distributed generation into modern power systems. The simulation findings are thoroughly examined across multiple operational scenarios and compared to Fuzzy logic control. Furthermore, the proposed system's efficacy is validated in accordance with the IEEE 1547 and IEEE 519 standards, demonstrating its performance and compliance with industrial needs.
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Power-Time Efficient Hybrid Adder Design Based on LP with Optimal Bit-Width Generation
Статья научная
This paper presents a systematic method for a hybrid adder design through allocating the optimal bit-widths and types of classical adders constituting a hybrid adder. The proposed optimization scheme considers two aspects design delay and power. It is based on a mathematical modeling of the proposed hybrid adder architecture following the principle of LP (Linear Programming). Two models, delay optimization under power constraint and power optimization under delay constraint, are introduced. Various experiments are presented to demonstrate the effectiveness and applicability of the proposed design scheme. The results indicate that the proposed scheme successfully allocates simultaneously and in a systematic way the optimal bit-widths of the sub-adders constituting a hybrid adder; providing an improvement in (power x delay) performance reaching 71.6%. The results obtained also indicate that the proposed design scheme introduces a high flexibility in making a compromise between delay and power of the adder design.
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Prediction of Protein Subcellular Localization Using EDA based Ensemble Classifiers
Статья научная
The function of protein is closely correlated with its subcellular locations. New composed proteins can perform normal biological function only after they are translocated to correct subcellular locations. In this paper, a new selective ensemble classifiers based on EDA algorithm has been proposed. In the method, pseudo amino acid composition was firstly applied to form the protein feature sets, then 10 neural networks is generated to learn the subsets which are re-sampling from feature subsets with PSO algorithm. At last, appropriate classifiers are selected to construct the prediction committee with EDA algorithm. Experiment shows that the proposed method produces the best prediction accuracy than the other methods on SNL6 database.
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Present Situation of Tech Startups in Bangladesh: A Case Study
Статья научная
In contemporary times startup is a very popular and growing entity, especially for the software industry as the technology field continues to grow. However, the failure rate of software startups is extremely high, and many reasons are behind this failure. There are many different variables behind the success or failure of a company. The purpose of this study is to mainly identify the possible reasons behind why the startups can’t reach the promise they are presumed to reach. To identify the reasons, company and employees of the company data were collected and analyzed using sentiment analysis and statistical correlation. Based on the analysis, some constructive suggestions were proposed accordingly. The discussion will enable the company employees and employers to bring out a transparent relation to ensure productive and satisfactory work environment. All the collected data for the study and the codes that were used to analyses the findings are attached below [28].
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Статья научная
The Detection of rare variants responsible for human complex diseases has been receiving more and more attentions. However, most existing computational methods for this purpose require the selection of functional variants before statistical analysis. Based on the assumption that nonsynonymous single nucleotide polymor-phisms (nsSNPs) associated with specific diseases should be similar in their properties, we propose a method that utilize conservation scores of nsSNPs and the guilt-by-association principle to prioritize the candi-date nsSNPs for specific diseases. Systematic validation demonstrates that our approach is effective in recovering the relationship between nsSNPs and diseases, with the Manhattan distance measure achieving the most pre-cise prediction results.
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