Статьи журнала - International Journal of Engineering and Manufacturing
Все статьи: 508
A Checkpointing Algorithm Based Unreliable Non-FIFO Channels
Статья научная
We propose a coordinated checkpointing algorithm based unreliable non-FIFO channel. In unreliable non-FIFO channel, the system can lose, duplicate, or reorder messages. The processes may not compute some messages because of message losses; the processes may compute some messages twice or more because of message duplicate; the processes may not compute messages according to their sending order because of message reordering. The above-mentioned problems make processes produce incorrect computation result, consequently, prevent processes from taking consistent global checkpoints. Our algorithm assigns each message a sequence number in order to resolve above-mentioned problems. During the establishing of the checkpoint, the consistency of checkpoint can be determined by the sequence number of sending and receiving messages. We can identify the lost messages, reordering messages and duplicate messages by checking the sequence number of sending and receiving messages. We resolve above-mentioned problems by resending the lost messages, buffering the reordering messages and dropping the duplicate messages. Our algorithm makes processes take consistent global checkpoints.
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A Comparative Analysis of Video Summarization Techniques
Статья научная
Video summarization special field of signal processing which includes pre-processing of video sets, their contextual segmentation, application-specific feature extraction & selection, and identification of dissimilar frame sets. Various variety of machine learning models are proposed by researchers to design such summarization methods, and each of them varies in terms of their functional nuances, application-specific advantages, deployment specific limitations, and contextual future scopes. Moreover, these models also vary in terms of quantitative & qualitative measures including accuracy of summarization, computational complexity, delay needed for summarization, precision during the summarization process, etc. Due to such a wide variation in performance levels, it is difficult for researchers to identify optimal models for their functional-specific &performance-specific use cases. Because of this, researchers and summarization-system-designers are required to validate individual models, which increases the delay & cost needed for final model deployments. To overcome these delays & reduce deployment costs, this paper initially discusses a multiple variety of video summarization models in terms of their working characteristics. Based on this discussion, researchers shall be able to identify optimum models for their functionality-specific use cases. This paper also analyzes and compares the reviewed models in terms of their performance metrics including summarization accuracy, delay, complexity, scalability and fMeasure, which will further allow readers to identify performance-specific models for their deployments. A novel Summarization Rank Metric (SRM) is calculated based on these evaluation metrics, which will assist readers to identify models that can perform optimally w.r.t. multiple evaluation parameters & different use cases. This metric is calculated by combining all the comparison metrics, which will assist in identification of models that have high accuracy, low delay, low complexity, high scalability & fMeasure levels.
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A Discriminative Statistical Model for Digital Image Forgery Detection
Статья научная
The headway of modern technology and facility to use processing software leads to tamper and implicate of digital images. This tampering is being performed without leaving any a clear effect noted with the naked eye. The discrimination between different authentic and forged images can be based on its Probability Density Functions (PDFs). This paper introduces a new model for digital image forgery detection. This framework has two main phases; training and testing. In the training phase, the peak is calculated for the derivatives histogram of the illumination components by using homomorphic filter to separate the illumination components on each image. Firstly, the derivative of illumination histogram for authentic and forged images is calculated then the PDFs are estimated for authentic and forged images, finally the threshold is determined. In the testing phase, the determined threshold is tested with realistic dataset followed by using the selected bins for feature calculation in the prediction process. In the final prediction step, a detection and decision process is performed to obtain performance of the new model. This new model is provided a very effective performance. Different color image contrast systems RGB and HIS are studied and utilized for testing our model and compare between each channel for two systems to estimate performance and obtain more sensitive channel.
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A Fuzzy Programming Technique for Solving Multi-objective Structural Problem
Статья научная
This paper proposes a new fuzzy multi-objective optimization approach to solve a multi-objective nonlinear programming problem in context of a structural design. We have been developed a multi-objective structural problem of a planar truss structural model in fuzzy environment. Here, the objectives are (i) to minimize weight of the structure and (ii) to minimize the vertical deflection at loading point. In this model, the design variables are the cross-section of the truss members and the constraints are the stresses in members. This approach is used to solve the structural model under uncertainty based on different operator. A numerical illustration is given to support our approach.
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A General Simulation Framework Based on CAN Bus for Satellite Design
Статья научная
The running status of a satellite can be imitated realistically through the use of an interactive simulation system, in which actual hardware can join for testing and validation. To solve the problem of interfaces and communications between different members in a satellite simulation system, an on-board interactive simulation system based on CAN bus is established. Several simulation members are built according to the composition of real system. Interfaces of drivers included in simulation members are packaged into a uniform interface, thus the on-board simulation system is established with the foundation of CAN bus simulation framework. Uniform communication interface of each simulation member is designed and realized, the framework of simulation flow is established, and foundation of intercommunion and operation between simulation members is laid. Experiment results prove that the framework can work stably with great efficiency and high flexibility, and expected effect is achieved.
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A Heterogeneous Agent-based Asset Pricing Model and Simulation
Статья научная
Behavioral finance models can help to explain several stylized facts in financial markets. As one of the behavioral financial theory, prospect theory describes how ‘irrational investors’ making decisions under uncertainty. In this paper, we present a heterogeneous agent-based asset pricing model, where parts of investors determine their demand for risky asset using prospect theory utility function. Time series generated from simulation show many stylized facts that can be observed in actual financial markets, such as abnormal distribution of asset returns, volatility clustering and equity premium. We also find that positive correlation between investors’ performance and their market share, negative correlation between investors’ performance and the loss aversion coefficient under certain market condition.
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A Hybrid Approach for Real-time Vehicle Monitoring System
Статья научная
In today's modern era, with the significant increase in the number of vehicles on the roads, there is a pressing need for an advanced and efficient system to monitor them effectively. Such a system not only helps minimize the chances of any faults but also facilitates human intervention when required. Our proposed method focuses on detecting vehicles through background subtraction, which leverages the benefits of various techniques to create a comprehensive vehicle monitoring solution. In general, when it comes to surveillance and monitoring moving objects, the initial step involves detecting and tracking these objects. For vehicle segmentation, we employ background subtraction, a technique that distinguishes foreground objects from the background. To target the most prominent regions in video sequences, our method utilizes a combination of morphological techniques. The advancements in vision-related technologies have proven to be instrumental in object detection and image classification, making them valuable tools for monitoring moving vehicles. Methods based on moving object detection play a vital role in real-time extraction of vehicles from surveillance videos captured by street cameras. These methods also involve the removal of background information while filtering out noisy data. In our study, we employ background subtraction-based techniques that continuously update the background image to ensure efficient output. By adopting this approach, we enhance the overall performance of vehicle detection and monitoring.
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A LL Subband Based Digital Watermarking in DWT
Статья научная
Digital watermarking is a technique which allows an individual to add hidden copyright notices or other verification messages to digital audio, video, image and documents in such a way that the watermark cannot be removed against different attacks. Digital Watermarking is a process to prevent the unauthorized access and modification of data. It ensures that the communication between two parties' remains secure. Digital watermarking can be performed in spatial and frequency domain. In the spatial domain, the watermark is embedded in the very existence of the pixel. In frequency domain, the transformation of any kind is applied and then information is embedded. In this paper, we proposed an approach to watermarking in frequency domain using DWT technique. The gray scale host image is divided into four sub bands: LL, HL, LH, HH and the watermark are inserted in the LL sub band using DWT technique. As the image is divided into four sub bands, a watermark of equal size of the LL sub band is inserted and the results are analyzed on the bases of different parameters such as PSNR and MSE. LL represents the average component of the host image which contains the maximum information of the image. In this approach the watermark is inserted in LL sub band using XOR operation. As the table IV shows, the imperceptibility of this method is quite good. Also, it shows good results when compared with existing methods.
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Статья научная
The research is concerned with the development of a mathematical model for estimating Intelligent Quotient of human above 65years. The model was optimized to know whether we have maximum or minimum human IQ level. However, the optimization result showed a saddled point which indicates that there is no minimum or maximum human IQ in life. This result implies that there is no particular IQ level that any human above 65years cannot attain when there is an enabling environment for adult education and other adult related trainings geared towards sharpening IQ skills of our retired and aged people. Similarly the IQ model was also validated with data from real life. And the outcome of the validation gave a correlation coefficient of 0.990405. This implies that our model is approximately 99% in agreement with real life data used, thus shows that the model is a standard measure for estimating IQ of human above 65years.
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A Measurable Approach for Access and Control Modeling in SOA
Статья научная
Service oriented architects (SOA) is considered as an extensible, robust and platform independent web application architect. However, problems in security guard for service access remains unresolved especially for the measurable one. we proposed a novel access control model, which we called SACM: Service Access Control Model, specially for SOA. Our model is mainly based on the role access policy, extended with trust authority transition and integration mechanism, to fulfill an extensive and measurable access control modeling approach with Crypto-CCS.
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A Methodical Study for Time-Frequency Analysis Model with Experimental Case Study on Chirp Signal
Статья научная
In this paper, we are reporting on the comprehensive model design for time-frequency analysis system using Short-Time Fourier Transform (STFT) and Wigner-Ville Distribution (WVD) methods. As a case study, both STFT and WVD based time-frequency transforms have been developed via MATLAB platform and applied for both Chirp and Sunspot signals. The developed model considers the use of hamming moving window of length L=50 with 90% overlapping between the current and previous window positions. The simulation results showed that WVD is more accurate method for time and frequency analysis than STFT since it can provide simultaneous localization in both time and frequency with higher resolution than STFT which can only provide localization in either time or frequency at the same time. Also, the applied techniques provide an adequate distribution of time-frequency analysis only if they used with a non-stationary signal such as Chirp signal.
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Статья научная
Aiming at the spatial shape analysis of complex geological bodies in stereoscopic quantitative prediction of concealed ore bodies, a three-dimensional morphological analysis method for geological bodies based on 3-dimensional raster model under visualization environment was put forward by combining mathematical morphology with Euclidean distance transform theory. Firstly, the 3-dimensional visualization models for geological bodies were constructed on the basis of the 3-dimensional geological modeling (3DGM) technology; Secondly, the algorithm for extracting the surface shape trend of geological body with the 3-dimensional raster model was proposed by using mathematical morphology filtering. By the combination of morphological filtering, global set operation and three-dimensional Euclidean distance transform, the models for the quantitative analysis and extraction of the shape undulance were established. Lastly, as a case study, the three-dimensional morphological analysis method was applied in analyzing quantitatively the Xinwuli magmatic body in Fenghuangshan ore field in Tongling, Anhui Province. By means of the calculation model of Euclidean distance field, the quantitative extraction of the shape trend and shape undulance as the quantitative indexes of geological ore-controlling factors were achieved after building the 3D raster models of the magmatic body. The results show that the morphological analysis method is feasible to calculate various morphological parameters of complex geological bodies and extract quantitative indexes of geological ore-controlling factors successfully for stereoscopic quantitative predication of concealed ore bodies.
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A New Automatic Generation Control with Heterogeneous Networks for Smart Grid
Статья научная
Current sensor can measure DC current signal for high frequency (MHz magnitude), which has a very wide frequency range. And its affluent magneto resistance system can meet the needs of all kinds of electric current in the power system monitoring. In this paper, the former measure the performance levels of the network through objective point of view, the latter base on the former to join the subjective demand of distribution communication service, and to compromise subjective and objective decision result which make the business’s decision for choice of network access result more reasonable and more In favor the meet business needs of Cos.
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A New Method of Signature Verification Based on Biomimetic Pattern Recognition Theory
Статья научная
Aim at the difficulty and low recognition rate of signature verification, this paper introduces biomimetic pattern recognition theory and applies it to the problem. According to the features of the signature samples, the coverage in the high-dimension feature space is built, one class of samples are all covered with a super-sausage neuron chain. As the radius selection of the super-sausage neurons maybe unreasonable, unwanted area may be covered and correct recognition rate will reduce. So this paper uses the relationship of the distance between the two training samples and the average distance of all the neurons to adjust the radius of the super-sausage neuron automatically. Finally, the experiments show that compared to traditional pattern recognition method, biomimetic pattern recognition theory used in signature verification have a better recognition result and is more effective.
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A New Support Vector Machine Optimized by Simulated Annealing for Global Optimization
Статья научная
SA-SVM model was proposed in which parameters were optimized by simulated annealing. Parameter (the kernel function) and C (the error discipline) are the key factors to the precision of SVM. Simulated annealing was used to optimize the key parameters of SVM to make enhancement on the forecasting effect of SVM. By applying this proposed model for several function optimizations, results of which demonstrate the improvement of SA-SVM on the high model accuracy in the optimization searching, and it can overcome the blindness of the model parameters.
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A Novel Genetic Operator for Genetic Folding Algorithm: A Refolding Operator and a New Genotype
Статья научная
Genetic Folding algorithm uses linear chromosomes composed of organized genes in floating-numbers manner, in which each genes chain fold back on themselves to form the final GF chromosome. In this paper, a novel genotype representation and a novel genetic operator were proposed. The paper was applied using MATLAB code to illustrate the beneficiary, flexibility and powerful of the Genetic Folding algorithm solving Santa Fe Trail problem. The problem of programming an artificial ant to follow the Santa Fe Trail is used as an example of program search space. To evaluate the efficiency and feasibility of the proposed methods, a comparison was held between the various types and sizes through the Santa Fe Trail problem. Several test functions along with various levels of difficulty were also conducted. Results of this proposal clearly show significant results of the proposed genotype and the genetic operator also.
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A Novel Hand Prosthesis Control Scheme Implementing a Tongue Control System
Статья научная
This paper presents a novel control scheme for new advanced hand prostheses implementing multiple pinches and grasps. The control signals for the hand are determined by myoelectric signals from the arm and volitionally generated signals by tongue through an inductive interface with a mouth piece. The feasibility tests have been performed on an able-bodied subject who controller a virtual reality hand. Results suggest that this hybrid control scheme works well, it is intuitive and the subject learned fast to use it, and what is most important provides many more control channel to advanced hand prostheses. This research is being continued in healthy subjects with the intention to translate the results to patients.
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Статья научная
Accurate registration of PET and CT images is an important component in oncology, so we aim to develop an automated registration algorithm for PET and CT images acquired by different system. These two modalities offer affluent complementary information: CT provides specificity to anatomic findings, and PET provides precise localization of metabolic activity. In this paper, we proposed an improved registration method that can accurately align PET and CT images. This registration algorithm includes two stages. The first stage is to deform PET image based on B-Spline Free Form Deformations (FFD). It is consists of three independent steps. After the feature points of PET and CT images have been extracted in the preprocessing step. As a next step, the PET image is deformed by B-Spline Free Form Deformations (FFD) with feature points of CT images. The second stage is to register PET and CT images based on Mutual Information (MI) of feature points combined with Particle Swarm Optimization (PSO) algorithm and Powell algorithm that are used to search the optimal registration parameters.
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Статья научная
One of the main goals for designing database is minimize the data redundancy. Literature shows that there is several approach have been used to minimize the data redundancy, such as converting an Entity Relational Diagram (ERD) scheme according to steps of an algorithm for ER-to-relational mapping, and applying the normalization rules. These techniques have improved the database design quality, reduced the data redundancy, and omitted from a large proportion of repetition. However, there are still a big proportion of duplicated values especially for the huge database as some attribute are related to each other and may have the same data, such as the attributes of first_name, middle_name, and family_name. These attributes cannot be called as the multivalued attribute as these values belong to variety of entities or relations. Therefore, we propose a novel normalization forms for relational database design that match the related data attribute. This proposed approach called Matching Related Data Attribute Normal Form (MRDANF). A civil registration database system is used as a case study to validate the proposed approach. The results show that using our proposed approach has the positive impact on database quality and performance as the data redundancy will be reduced.
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A Novel Spiking Cortical Model based Filter for Impulse Noise Removal
Статья научная
A novel spiking cortical model based switching mean filter for removing impulse noise is presented. In the proposed filter, the noise detector using spiking cortical model is first adopted to identify the pixels that are likely to be corrupted by impulse noise. Then the detected impulses are removed by the weighted mean filter while the noise-free pixels are left unaltered. Extensive simulations show that the proposed filter outperforms a number of existing decision-based filters due to its excellent performance in terms of effectiveness in image restoration. Because of its outstanding restoration performance, the proposed filter can be used for noise removal in numerous consumer electronics products such as digital camera and digital television.
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