Search results for: registration algorithm

Authors: Mirjana Ruppel, Rajendra Persad, Amit Bahl, Sanja Dogramadzi, Chris Melhuish, Lyndon Smith

Abstract:

Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images ˆA, ˆB which were registered to ˜B, ˜A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph.

Keywords: Multimodal image registration, GAN, cycle consistency, deep learning.

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Authors: Hossam el-ddin Mostafa, Pavel Čičak

Abstract:

In IETF RFC 2002, Mobile-IP was developed to enable Laptobs to maintain Internet connectivity while moving between subnets. However, the packet loss that comes from switching subnets arises because network connectivity is lost while the mobile host registers with the foreign agent and this encounters large end-to-end packet delays. The criterion to initiate a simple and fast full-duplex connection between the home agent and foreign agent, to reduce the roaming duration, is a very important issue to be considered by a work in this paper. State-transition Petri-Nets of the modeling scenario-based CIA: communication inter-agents procedure as an extension to the basic Mobile-IP registration process was designed and manipulated to describe the system in discrete events. The heuristic of configuration file during practical Setup session for registration parameters, on Cisco platform Router-1760 using IOS 12.3 (15)T and TFTP server S/W is created. Finally, stand-alone performance simulations from Simulink Matlab, within each subnet and also between subnets, are illustrated for reporting better end-toend packet delays. Results verified the effectiveness of our Mathcad analytical manipulation and experimental implementation. It showed lower values of end-to-end packet delay for Mobile-IP using CIA procedure-based early registration. Furthermore, it reported packets flow between subnets to improve losses between subnets.

Keywords: Cisco configuration, handoff, Mobile-IP, packetdelay, Petri-Nets, registration process, Simulink

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Authors: Muhibul Haque Bhuyan

Abstract:

Most educational institutions were compelled to switch over to the online mode of teaching, learning, and assessment due to the lockdown when the corona pandemic started around the globe in the early part of the year 2020. However, they faced a unique set of challenges in delivering knowledge and skills to their students as well as formulating a proper assessment policy. This paper investigates whether there is an impact on the student Semester Grade Point Average (SGPA) due to the online mode of teaching and learning assessment at the Department of Electrical and Electronic Engineering (EEE) of Southeast University (SEU). Details of student assessments are discussed. Then students’ grades were analyzed to find out the impact on SGPA based on the z-test by finding the standard deviation (). It also pointed out the challenges associated with the online classes and assessment strategies to be adopted during the online assessment. The student admission, course advising, and registration statistics were also presented in several tables and analyzed based on the change in percentage to observe the impact on it due to the pandemic. In summary, it was observed that the students’ SGPAs are not affected but student course advising and registration were affected slightly by the pandemic. Finally, the paper provides some recommendations to improve the online teaching, learning, assessment, and evaluation system.

Keywords: electrical and electronic engineering students, impact on course grading and SGPA, online assessment, online teaching, student registration, semester result

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Authors: Gaohuizi Guo, Ning Zhang

Abstract:

Firefly algorithm (FA) and Sine Cosine algorithm (SCA) are two very popular and advanced metaheuristic algorithms. However, these algorithms applied to multi-objective optimization problems have some shortcomings, respectively, such as premature convergence and limited exploration capability. Combining the privileges of FA and SCA while avoiding their deficiencies may improve the accuracy and efficiency of the algorithm. This paper proposes a hybridization of FA and SCA algorithms, named multi-objective firefly-sine cosine algorithm (MFA-SCA), to develop a more efficient meta-heuristic algorithm than FA and SCA.

Keywords: Firefly algorithm, hybrid algorithm, multi-objective optimization, Sine Cosine algorithm.

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Authors: Safeer Hussain Khan

Abstract:

In this paper, we introduce a two-step iterative algorithm to prove a strong convergence result for approximating common fixed points of three contractive-like operators. Our algorithm basically generalizes an existing algorithm..Our iterative algorithm also contains two famous iterative algorithms: Mann iterative algorithm and Ishikawa iterative algorithm. Thus our result generalizes the corresponding results proved for the above three iterative algorithms to a class of more general operators. At the end, we remark that nothing prevents us to extend our result to the case of the iterative algorithm with error terms.

Keywords: Contractive-like operator, iterative algorithm, fixed point, strong convergence.

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Authors: Satoshi Shimizu, Kazuaki Yamaguchi, Toshiki Saitoh, Sumio Masuda

Abstract:

Some fast exact algorithms for the maximum weight clique problem have been proposed. Östergard’s algorithm is one of them. Kumlander says his algorithm is faster than it. But we confirmed that the straightforwardly implemented Kumlander’s algorithm is slower than O¨ sterga˚rd’s algorithm. We propose some improvements on Kumlander’s algorithm.

Keywords: Maximum weight clique, exact algorithm, branch-andbound, NP-hard.

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Authors: Panpan Xu, Shulin Sui

Abstract:

The crossover probability and mutation probability are the two important factors in genetic algorithm. The adaptive genetic algorithm can improve the convergence performance of genetic algorithm, in which the crossover probability and mutation probability are adaptively designed with the changes of fitness value. We apply adaptive genetic algorithm into a function optimization problem. The numerical experiment represents that adaptive genetic algorithm improves the convergence speed and avoids local convergence.

Keywords: Genetic algorithm, Adaptive genetic algorithm, Function optimization.

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Authors: Thanapol Wisuttikul, Choochart Haruechaiyasak, Santipong Thaiprayoon

Abstract:

Thailand has evolved many unique culture and knowledge, and the leading is the Thai traditional medicine (TTM). Recently, a number of researchers have tried to save this indigenous knowledge. However, the system to do so has still been scant. To preserve this ancient knowledge, we therefore invented and integrated multi-linguistic techniques to create the system of the collected all of recipes. This application extracted the medical recipes from antique scriptures then normalized antiquarian words, primitive grammar and antiquated measurement of them to the modern ones. Then, we applied ingredient-duplication-calculation, proportion-similarity-calculation and score-ranking to examine duplicate recipes. We collected the questionnaires from registrants and people to investigate the users’ satisfaction. The satisfactory results were found. This application assists not only registrants to validating the copyright violation in TTM registration process but also people to cure their illness that aids both Thai people and all mankind to fight for intractable diseases.

Keywords: Medicine Registration, Search Engine, Text Approximation, Traditional Medicine.

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Authors: Mir Hadi Seyedafsari, Iraj Hasanzadeh

Abstract:

Like other external sorting algorithms, the presented algorithm is a two step algorithm including internal and external steps. The first part of the algorithm is like the other similar algorithms but second part of that is including a new easy implementing method which has reduced the vast number of inputoutput operations saliently. As decreasing processor operating time does not have any effect on main algorithm speed, any improvement in it should be done through decreasing the number of input-output operations. This paper propose an easy algorithm for choose the correct record location of the final list. This decreases the time complexity and makes the algorithm faster.

Keywords: External sorting algorithm, internal sortingalgorithm, fast sorting, robust algorithm.

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Authors: May-Ling Tan, Yi Su, Chi-Wan Lim, Liang Zhong, Ru-San Tan

Abstract:

This paper describes an automatic algorithm to restore the shape of three-dimensional (3D) left ventricle (LV) models created from magnetic resonance imaging (MRI) data using a geometry-driven optimization approach. Our basic premise is to restore the LV shape such that the LV epicardial surface is smooth after the restoration. A geometrical measure known as the Minimum Principle Curvature (κ2) is used to assess the smoothness of the LV. This measure is used to construct the objective function of a two-step optimization process. The objective of the optimization is to achieve a smooth epicardial shape by iterative in-plane translation of the MRI slices. Quantitatively, this yields a minimum sum in terms of the magnitude of κ 2, when κ2 is negative. A limited memory quasi-Newton algorithm, L-BFGS-B, is used to solve the optimization problem. We tested our algorithm on an in vitro theoretical LV model and 10 in vivo patient-specific models which contain significant motion artifacts. The results show that our method is able to automatically restore the shape of LV models back to smoothness without altering the general shape of the model. The magnitudes of in-plane translations are also consistent with existing registration techniques and experimental findings.

Keywords: Magnetic Resonance Imaging, Left Ventricle, ShapeRestoration, Principle Curvature, Optimization

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Authors: Amod P. Vaze

Abstract:

Genetic Algorithm has been used to solve wide range of optimization problems. Some researches conduct on applying Genetic Algorithm to analog circuit design automation. These researches show a better performance due to the nature of Genetic Algorithm. In this paper a modified Genetic Algorithm is applied for analog circuit design automation. The modifications are made to the topology of the circuit. These modifications will lead to a more computationally efficient algorithm.

Keywords: Genetic algorithm, analog circuits, design.

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Authors: Hossam el-ddin Mostafa, Pavel Čičak

Abstract:

The mobile users with Laptops need to have an efficient access to i.e. their home personal data or to the Internet from any place in the world, regardless of their location or point of attachment, especially while roaming outside the home subnet. An efficient interpretation of packet losses problem that is encountered from this roaming is to the centric of all aspects in this work, to be over-highlighted. The main previous works, such as BER-systems, Amigos, and ns-2 implementation that are considered to be in conjunction with that problem under study are reviewed and discussed. Their drawbacks and limitations, of stopping only at monitoring, and not to provide an actual solution for eliminating or even restricting these losses, are mentioned. Besides that, the framework around which we built a Triple-R sequence as a costeffective solution to eliminate the packet losses and bridge the gap between subnets, an area that until now has been largely neglected, is presented. The results show that, in addition to the high bit error rate of wireless mobile networks, mainly the low efficiency of mobile-IP registration procedure is a direct cause of these packet losses. Furthermore, the output of packet losses interpretation resulted an illustrated triangle of the registration process. This triangle should be further researched and analyzed in our future work.

Keywords: Amigos, BER-systems, ns-2 implementation, packetlosses, registration process, roaming.

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Authors: Hossam el-ddin Mostafa, Pavel Čičak

Abstract:

IETF RFC 2002 originally introduced the wireless Mobile-IP protocol to support portable IP addresses for mobile devices that often change their network access points to the Internet. The inefficiency of this protocol mainly within the handoff management produces large end-to-end packet delays, during registration process, and further degrades the system efficiency due to packet losses between subnets. The criterion to initiate a simple and fast full-duplex connection between the home agent and foreign agent, to reduce the roaming duration, is a very important issue to be considered by a work in this paper. State-transition Petri-Nets of the modeling scenario-based CIA: communication inter-agents procedure as an extension to the basic Mobile-IP registration process was designed and manipulated. The heuristic of configuration file during practical Setup session for registration parameters, on Cisco platform Router-1760 using IOS 12.3 (15)T is created. Finally, stand-alone performance simulations results from Simulink Matlab, within each subnet and also between subnets, are illustrated for reporting better end-to-end packet delays. Results verified the effectiveness of our Mathcad analytical manipulation and experimental implementation. It showed lower values of end-to-end packet delay for Mobile-IP using CIA procedure. Furthermore, it reported packets flow between subnets to improve packet losses between subnets.

Keywords: Cisco configuration, handoff, packet delay, Petri-Nets, registration process, Simulink.

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Authors: Panpan Xu, Shulin Sui, Zongjie Du

Abstract:

Genetic algorithm is widely used in optimization problems for its excellent global search capabilities and highly parallel processing capabilities; but, it converges prematurely and has a poor local optimization capability in actual operation. Simulated annealing algorithm can avoid the search process falling into local optimum. A hybrid genetic algorithm based on simulated annealing is designed by combining the advantages of genetic algorithm and simulated annealing algorithm. The numerical experiment represents the hybrid genetic algorithm can be applied to solve the function optimization problems efficiently.

Keywords: Genetic algorithm, Simulated annealing, Hybrid genetic algorithm, Function optimization.

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Authors: Chenxue Yang, Mao Ye, Zijian Liu, Tao Li, Jiao Bao

Abstract:

Non-negative matrix factorization (NMF) is a useful computational method to find basis information of multivariate nonnegative data. A popular approach to solve the NMF problem is the multiplicative update (MU) algorithm. But, it has some defects. So the columnwisely alternating gradient (cAG) algorithm was proposed. In this paper, we analyze convergence of the cAG algorithm and show advantages over the MU algorithm. The stability of the equilibrium point is used to prove the convergence of the cAG algorithm. A classic model is used to obtain the equilibrium point and the invariant sets are constructed to guarantee the integrity of the stability. Finally, the convergence conditions of the cAG algorithm are obtained, which help reducing the evaluation time and is confirmed in the experiments. By using the same method, the MU algorithm has zero divisor and is convergent at zero has been verified. In addition, the convergence conditions of the MU algorithm at zero are similar to that of the cAG algorithm at non-zero. However, it is meaningless to discuss the convergence at zero, which is not always the result that we want for NMF. Thus, we theoretically illustrate the advantages of the cAG algorithm.

Keywords: Non-negative matrix factorizations, convergence, cAG algorithm, equilibrium point, stability.

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Authors: S. M. Khalessizadeh, R. Zaefarian, S.H. Nasseri, E. Ardil

Abstract:

Today, Genetic Algorithm has been used to solve wide range of optimization problems. Some researches conduct on applying Genetic Algorithm to text classification, summarization and information retrieval system in text mining process. This researches show a better performance due to the nature of Genetic Algorithm. In this paper a new algorithm for using Genetic Algorithm in concept weighting and topic identification, based on concept standard deviation will be explored.

Keywords: Genetic Algorithm, Text Mining, Term Weighting, Concept Extraction, Concept Distribution.

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Authors: Keonwoo Kim, Dowon Hong, Kyoil Chung

Abstract:

This paper proposes the authentication method using ESA algorithm instead of using CAVE algorithm in the CDMA mobile communication systems including IS-95 and CDMA2000 1x. And, we analyze to apply ESA mechanism on behalf of CAVE mechanism without the change of message format and air interface in the existing CDMA systems. If ESA algorithm can be used as the substitution of CAVE algorithm, security strength of authentication algorithm is intensified without protocol change. An algorithm replacement proposed in this paper is not to change an authentication mechanism, but to configure input of ESA algorithm and to produce output. Therefore, our proposal can be the compatible to the existing systems.

Keywords: ESA, CAVE, CDMA, authentication, mobilecommunication.

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Authors: Razagh Hafezi, Ahmad Keshavarz, Vida Moshfegh

Abstract:

This paper presents a novel algorithm of stereo correspondence with rank transform. In this algorithm we used the genetic algorithm to achieve the accurate disparity map. Genetic algorithms are efficient search methods based on principles of population genetic, i.e. mating, chromosome crossover, gene mutation, and natural selection. Finally morphology is employed to remove the errors and discontinuities.

Keywords: genetic algorithm, morphology, rank transform, stereo correspondence

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Authors: Ali Nourollah, Mohsen Movahedinejad

Abstract:

In this paper a new algorithm to generate random simple polygons from a given set of points in a two dimensional plane is designed. The proposed algorithm uses a genetic algorithm to generate polygons with few vertices. A new merge algorithm is presented which converts any two polygons into a simple polygon. This algorithm at first changes two polygons into a polygonal chain and then the polygonal chain is converted into a simple polygon. The process of converting a polygonal chain into a simple polygon is based on the removal of intersecting edges. The experiments results show that the proposed algorithm has the ability to generate a great number of different simple polygons and has better performance in comparison to celebrated algorithms such as space partitioning and steady growth.

Keywords: Divide and conquer, genetic algorithm, merge polygons, Random simple polygon generation.

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Authors: Luciano Nieddu, Giuseppe Manfredi

Abstract:

In this paper a Pattern Recognition algorithm based on a constrained version of the k-means clustering algorithm will be presented. The proposed algorithm is a non parametric supervised statistical pattern recognition algorithm, i.e. it works under very mild assumptions on the dataset. The performance of the algorithm will be tested, togheter with a feature extraction technique that captures the information on the closed two-dimensional contour of an image, on images of industrial mineral ores.

Keywords: K-means, Industrial ores classification, Invariant Features, Supervised Classification.

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Authors: M. A. Sharbafi, M. Shakiba Herfeh, Caro Lucas, A. Mohammadi Nejad

Abstract:

Several researchers have proposed methods about combination of Genetic Algorithm (GA) and Fuzzy Logic (the use of GA to obtain fuzzy rules and application of fuzzy logic in optimization of GA). In this paper, we suggest a new method in which fuzzy decision making is used to improve the performance of genetic algorithm. In the suggested method, we determine the alleles that enhance the fitness of chromosomes and try to insert them to the next generation. In this algorithm we try to present an innovative vaccination in the process of reproduction in genetic algorithm, with considering the trade off between exploration and exploitation.

Keywords: Genetic Algorithm, Fuzzy Decision Making.

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Authors: M. Sankari, R. Bremananth, C.Meena

Abstract:

Localization and Recognition of License registration characters from the moving vehicle is a computationally complex task in the field of machine vision and is of substantial interest because of its diverse applications such as cross border security, law enforcement and various other intelligent transportation applications. Previous research used the plate specific details such as aspect ratio, character style, color or dimensions of the plate in the complex task of plate localization. In this paper, license registration character is localized by Enhanced Weight based density map (EWBDM) method, which is independent of such constraints. In connection with our previous method, this paper proposes a method that relaxes constraints in lighting conditions, different fonts of character occurred in the plate and plates with hand-drawn characters in various aspect quotients. The robustness of this method is well suited for applications where the appearance of plates seems to be varied widely. Experimental results show that this approach is suited for recognizing license plates in different external environments. 

Keywords: Character segmentation, Connectivity checking, Edge detection, Image analysis, license plate localization, license number recognition, Quality frame selection

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Authors: Branislav Vuksanović, Dragana Nikolić

Abstract:

This paper describes the implementation and testing of a multichannel active noise control system (ANCS) based on the filtered-inverse LMS (FILMS) algorithm. The FILMS algorithm is derived from the well-known filtered-x LMS (FXLMS) algorithm with the aim to improve the rate of convergence of the multichannel FXLMS algorithm and to reduce its computational load. Laboratory setup and techniques used to implement this system efficiently are described in this paper. Experiments performed in order to test the performance of the FILMS algorithm are discussed and the obtained results presented.

Keywords: Active noise control, adaptive filters, inverse filters, LMS algorithm, FILMS algorithm.

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Authors: Mahmud Hesain ALdwaik, Omar Hsiain Eldwaik

Abstract:

This paper deals with tracking and estimating time delay between two signals. The simulation of this algorithm accomplished by using Mathcad package is carried out. The algorithm we will present adaptively controls and tracking the delay, so as to minimize the mean square of this error. Thus the algorithm in this case has task not only of seeking the minimum point of error but also of tracking the change of position, leading to a significant improving of performance. The flowchart of the algorithm is presented as well as several tests of different cases are carried out.

Keywords: Tracking time delay, Algorithm simulation, Mathcad, MSE

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Authors: Moth'd Belal. Al-Daoud

Abstract:

Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the k-means algorithm. Solutions obtained from this technique are dependent on the initialization of cluster centers. In this article we propose a new algorithm to initialize the clusters. The proposed algorithm is based on finding a set of medians extracted from a dimension with maximum variance. The algorithm has been applied to different data sets and good results are obtained.

Keywords: clustering, k-means, data mining.

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Authors: Vishnu Pratap Singh Kirar

Abstract:

Artificial Neural Network (ANN) can be trained using back propagation (BP). It is the most widely used algorithm for supervised learning with multi-layered feed-forward networks. Efficient learning by the BP algorithm is required for many practical applications. The BP algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a twoterm algorithm consisting of a learning rate (LR) and a momentum factor (MF). The major drawbacks of the two-term BP learning algorithm are the problems of local minima and slow convergence speeds, which limit the scope for real-time applications. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and criteria for evaluating convergence are required to facilitate the application of the three terms BP algorithm. Although these two seem to be closely related, as described later, we summarize various improvements to overcome the drawbacks. Here we compare the different methods of convergence of the new three-term BP algorithm.

Keywords: Neural Network, Backpropagation, Local Minima, Fast Convergence Rate.

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Authors: B.Bahmani Firouzi, T. Niknam, M. Nayeripour

Abstract:

Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the kmeans algorithm. Solutions obtained from this technique depend on the initialization of cluster centers and the final solution converges to local minima. In order to overcome K-means algorithm shortcomings, this paper proposes a hybrid evolutionary algorithm based on the combination of PSO, SA and K-means algorithms, called PSO-SA-K, which can find better cluster partition. The performance is evaluated through several benchmark data sets. The simulation results show that the proposed algorithm outperforms previous approaches, such as PSO, SA and K-means for partitional clustering problem.

Keywords: Data clustering, Hybrid evolutionary optimization algorithm, K-means algorithm, Simulated Annealing (SA), Particle Swarm Optimization (PSO).

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Authors: B. Arun Kumar, T. Ravichandran

Abstract:

Workflow scheduling is an important part of cloud computing and based on different criteria it decides cost, execution time, and performances. A cloud workflow system is a platform service facilitating automation of distributed applications based on new cloud infrastructure. An aspect which differentiates cloud workflow system from others is market-oriented business model, an innovation which challenges conventional workflow scheduling strategies. Time and Cost optimization algorithm for scheduling Hybrid Clouds (TCHC) algorithm decides which resource should be chartered from public providers is combined with a new De-De algorithm considering that every instance of single and multiple workflows work without deadlocks. To offset this, two new concepts - De-De Dodging Algorithm and Priority Based Decisive Algorithm - combine with conventional deadlock avoidance issues by proposing one algorithm that maximizes active (not just allocated) resource use and reduces Makespan.

Keywords: Workflow Scheduling, cloud workflow, TCHC algorithm, De-De Dodging Algorithm, Priority Based Decisive Algorithm (PBD), Makespan.

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Authors: Xiangbin Zhu

Abstract:

EDF (Early Deadline First) algorithm is a very important scheduling algorithm for real- time systems . The EDF algorithm assigns priorities to each job according to their absolute deadlines and has good performance when the real-time system is not overloaded. When the real-time system is overloaded, many misdeadlines will be produced. But these misdeadlines are not uniformly distributed, which usually focus on some tasks. In this paper, we present an adaptive fuzzy control scheduling based on EDF algorithm. The improved algorithm can have a rectangular distribution of misdeadline ratios among all real-time tasks when the system is overloaded. To evaluate the effectiveness of the improved algorithm, we have done extensive simulation studies. The simulation results show that the new algorithm is superior to the old algorithm.

Keywords: Fuzzy control, real-time systems, EDF, misdeadline ratio.

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Authors: Safa Adi

Abstract:

This paper will consider the problem of sequential mining patterns embedded in a database by handling the time constraints as defined in the GSP algorithm (level wise algorithms). We will compare two previous approaches GTC and PSP, that resumes the general principles of GSP. Furthermore this paper will discuss PG-hybrid algorithm, that using PSP and GTC. The results show that PSP and GTC are more efficient than GSP. On the other hand, the GTC algorithm performs better than PSP. The PG-hybrid algorithm use PSP algorithm for the two first passes on the database, and GTC approach for the following scans. Experiments show that the hybrid approach is very efficient for short, frequent sequences.

Keywords: Database, GTC algorithm, PSP algorithm, sequential patterns, time constraints.

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