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In 1967, Dr. René Favaloro introduced the use of reversed greater saphenous vein graft for coronary artery bypass grafting, since then a lot of efforts were made to improve the venous graft patency rate. We introduce a novel double cobra head technique of distal coronary anastomosis for better distal runoff. We expect our technique will help in difficult situations such as limited conduit availability and target vessel with bifurcation lesions. Refining our surgical techniques is essential to keep ourselves well equipped to compete with the rapidly evolving stent culture.

In the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic, the physician finds difficulty in differentiating the symptoms due to cardiac disease from that of SARS-CoV-2. We would like to present one such mystified situation (hemosiderosis versus SARS-CoV-2 pneumonia) we encountered.

In the VEST IV trial, the author concluded that external stenting of saphenous vein graft mitigates its remodeling and also significantly reduces the diffuse intimal hyperplasia and development of lumen irregularities at 4.5 years after coronary artery bypass grafting surgery. We also have valuable a suggestion in addition to external stenting that might nullify the pathology caused by the stent and might enhances graft patency.

BACKGROUND CONTEXT One of the common causes of low back pain is intervertebral disc degeneration. The pathophysiology of disc degeneration involves apoptosis of nucleus pulposes cells and degradation of extra cellular matrix (ECM). Caspase 3 plays a central role in apoptosis and the ADAMTS5 (A Disintegrin and Metalloproteinase with Thrombospondin motifs 5) gene plays a critical role in ECM degradation. Hence, we hypothesized that if one can silence these two genes, both apoptosis and ECM degradation can be prevented, thereby preventing the progression and even reverse disc degeneration. PURPOSE The purpose of this study is to demonstrate the regenerative potential of small interfering RNA (siRNA) designed against Caspase 3 and ADAMTS5 genes in an in vitro and animal model of disc degeneration. STUDY DESIGN In vitro study followed by in vivo study in a rabbit model. METHODS In vitro studies were done using the human hepatocellular carcinoma (Hep G2) cell line for validating the efficacy of liposomal siRNA in controlling the expression of genes (Caspase 3 and ADAMTS5). Later, siRNA's validation was done in a rabbit annular punctured model by administering siRNA's individually (Caspase 3 and ADAMTS5) and in combination Caspase3-ADAMTS5) for assessing their synergistic effect in down regulating the gene expression in the degenerative discs. Annular punctured intervertebral discs of the rabbit were injected with siRNA formulations (single and dual) and phosphate buffer saline, one week after initial puncture. Magnetic resonance imaging (MRI) scans were done before and after siRNA treatment (1, 4 and 8 weeks) for assessing the progression of disc degeneration. The histopathology and real time polymerase chain reaction (RT-PCR) studies were done for evaluating their efficacy. We did not receive any funding for conducting the study, and we do not have a conflict of interest with any researchers or scientific groups. RESULTS The observations made from both in vitro and in vivo studies indicate the beneficial effects of siRNA formulation in down regulating the expression of Caspase 3 and ADAMTS5 genes. The MRI and histopathological evaluation showed that the disc degeneration was progressive in phosphate buffer saline and AT5-siRNA injected discs but the discs that received Caspase 3-siRNA and dual siRNA (Cas3-AT5-siRNA) formulation showed signs of recovery and regeneration 4 and 8 weeks after injection. The efficacy of siRNA designed against Cas3 and AT5 was also assessed in both in vitro and in vivo experiments by using RT-PCR analysis and the results showed downregulation of Caspase 3 gene in Caspase 3-siRNA group, but there was no significant downregulation of ADAMTS5 gene in ADAMTS5-siRNA group (ie, indicated by fold change). Synergistic effect was observed in the group that received dual siRNA (Cas3-AT5 siRNA) formulation. CONCLUSIONS This experiment suggests that intervention by siRNA treatment significantly reduced the extent of apoptosis in the discs. CLINICAL SIGNIFICANCE Delivery of siRNA directly into spinal discs has a potential in treating disc degeneration nonsurgically.

Data mining is the progress of instinctively find out valuable information from huge depot. In educational data mining predicting the academic performance of the student is a well-known research. The intention of the research work is to examine the classification algorithms as a hybrid classification. We used Radial Basis Function network, Multilayer Perceptron, C4.5 and Random Forest Algorithms for classification. Initially classification accuracy was computed individually by the classification algorithms. The Radial Basis Function network, Multilayer Perceptron, C4.5 and Random Forest Algorithm’s individual classification gave the accuracy of 72.9167%, 75.4167%, 75% and 73.125% vice versa. To increase more accuracy of classification algorithm the Radial Basis Function network is combined with multilayer perceptron. This hybrid algorithm provides 75.625% of classification accuracy. Then we combined C4.5 algorithm with random forest algorithm which gives 76.4583% classification accuracy. In this study we found hybrid classification algorithm gives more accuracy than individual classification algorithm.

Development in usage of internet for sharing data over internet leads to some risk on privacy, authenticity and confidentiality of information. To overcome the problem of security and authenticity, biometrics and cryptography technology are separately used due few drawbacks in both system, but because of their similar characteristics these two technologies are combined and Bio-crypto system has been designed, to satisfy the needs of user who transmit their data through internet for enhancing the security and authenticity of data and the user. In this proposed work bio-cryptosystem based on fuzzy extractor using face attributes, the user face feature points are extracted and bio code can be generated by bio hashing technique to facilitate the user to access the key that are already stored on the database server. By using face attribute for retrieving the key there is no need for the user to remember the pass code which does not corresponds to the user moreover biometric features cannot be stole and forgotten. Using bio-crypto system the user can be authenticated by enrolment and verification process and encrypt the key along with the own face attribute of the user to make the system more secure and authenticated. The robustness of the data is prevented and there is no cause of bug or intrusion occurs during the interval of data transmission. By this proposed work security, privacy, confidentiality and authenticity can be increased and provide authority only to the valid user to access the data using bio-crypto key.

The overall recognition rate of a biometric authentic system is completely depends upon the input of an image quality. Nowadays the image qualities are besmirched by some reasons such as apprehending the image of input devices, underprivileged quality of an image, large enlightenment dissimilarities of the inside and outside environments, pixel intensity level, etc. In biometrics based recognition system various physical and behavioral traits are used for recognition purpose. Here considering minor finger knuckle print trait is secondhand for authentication process. The main issue of the MinorFKP system is the quality of an image is relatively poor level and matching level of the image is difficult due to poor image quality. Therefore the CLAHE method is applied to MinorFKP image enhancement. The values of an MSE, RMSE and PSNR that the CLAHE technique considerably improves the better quality of MinorFKP images and reducing noise and artifacts.

Minutiae-based fingerprint recognition system is an important technique for person identification. Yet spurious and false minutiae are often occurred and it can be removed during the post-processing phase is passible. False minutiae will affect the accuracy of fingerprint matching process. Hence it is essential to decrease the false minutiae and increase the fingerprint authentication. Besides initially at the pre-processing the input fingerprint image is subjected to adaptive histogram equalization (AHE) followed by Gabor Filter (GF). Using Gabor filter to improve the given fingerprint in wavelet domain and restructure the fingerprint. Further the enhanced image subjected to binarization and thinning process. After successful pre-processing the minutiae set extracted by crossing number method while the existence of spurious minutiae lying on the boundaries of the fingerprint image. To overcome this problem in post-processing stage, the Graham’s Scan Algorithm (GSA) based closed hull filtering technique (CHFT) is successfully to remove the border minutiae. The studied closed hull filtering can be simply superposed to the fingerprint template, the accuracy of filtered minutiae evaluated by Goodness Index (GI) value calculated through manually. Thus the post-processing method, the Graham’s scan algorithm applied on fingerprint minutiae points(vertex) proved mathematically, The investigational results of the projected algorithm was verified on FVC2002and 2004 fingerprint database DBI.

Fault detection during testing can provide faster feedback on the system under test and permit software engineers begin correcting faults earlier. One application of prioritization technique involves regression testing for retesting of software following modifications. In this context, prioritization technique can take advantage of information gathered about the previous execution of test cases to obtain test case orderings. Test case prioritization techniques schedule test cases in an order that increases their effectiveness in meeting certain performance goals. Regression testing makes sure that up gradation of software in terms of adding new features or for bug fixing purposes should not hamper previously working functionalities. Whenever a software is upgraded or modified, a set of test cases are run on each of its functions to assure that the change to that function is not affecting other parts of the software that were previously running flawlessly.Our proposed regression test case prioritization research initially generates test cases. Then the generated test cases are clustered with the aid of kernel fuzzy c-means clustering technique. The KFCM will cluster relevant and irrelevant test cases later the relevant test cases are considered for test case prioritization. The goal of test case prioritization is to determine test case ordering that maximizes the probability to discover faults in source code early. Here for test case prioritization Modified Artificial Neural Network classification algorithms are used. A Whale Optimization Algorithm is used for weight optimization process.

The left internal mammary artery is the most accepted and widely used conduit in coronary artery bypass grafting. This report presents a rare case of very early bifurcation of the left internal mammary artery at the level of the third intercostal space.

MANETs consist of mobile nodes which can any time enter or exit from the network [16]. The no central admin set up of the MANET makes it more prone to attacks [5]. Sending much more secured data than any other networks is verily needed in MANETs since the mobile nodes consume a lot of energy for capturing signals and cryptanalysis of messages. Here we are presenting a security scheme that adorns selective encryption strategy and encrypts selective bit positions instead the entire data set. The scheme needs less computation capability while providing adequate security to the MANET nodes [15]. It provides better security compared to the existing selective encryption algorithms. Thus we manage safety as well energy conservation of mobile nodes.

BACKGROUND: Bioprosthetic valves are increasingly used for surgical mitral valve replacement (MVR). The long-term outcomes of bovine (BoMVR) vs porcine (PoMVR) remain an enigma regarding the durability. This study aims to examine the outcomes of BoMVR vs PoMVR. METHODS: A retrospective analysis of all bioprosthetic MVRs, with concomitant procedures, at a single tertiary referral institution from January 2005 to December 2008 was conducted. Procedures were classified as BoMVR or PoMVR. The age group was from 40 to 70 years. RESULTS: We identified 154 BoMVR patients and 120 PoMVR patients after matching the two groups with respect to age, sex, valve size and concomitant procedures. Kaplan-Meier survival analysis model was used for corresponding statistical analysis. Freedom from reoperation (all cause), freedom from non-structural valve deterioration, freedom from structural valve deterioration, freedom from heart failure and freedom from infective endocarditis were 96.4 ± 0.08, 97.1 ± 0.07, 96.4 ± 0.08%, 98.2 ± 0.07, and 98.6 ± 0.06% in PoMVR, respectively, and 92.6 ± 0.09, 91.6 ± 0.08, 90.6 ± 0.09, 94 ± 0.08, and 92.8 ± 0.08% in BoMVR groups, respectively, at the end of 10-year follow-up (mean follow up of 6.2 ± 2.3 years). Overall, 20 (12.9%) patients were lost to follow-up in the BoMVR and 15(12.5%) patients in the PoMVR groups for a global follow-up of 87.1%. CONCLUSIONS: For patients undergoing MVR with a bioprosthetic valve, the choice of PoMVR vs BoMVR favours more in favour of PoMVR as evidenced by the outcome results. Probably long-term follow-up with more patients might throw further light on the debatable topic.

Mobile ad hoc network is a group of mobile nodes which have no centralized administrator. MANETs have dynamic topology since the nodes are moving. For this reason it is more prone to attacks that any node may be a misbehaving node. Every node acts as a router thereby it may lead the network with wrong routing. For these reasons MANETs have to be more protected than the wired networks. The mobile nodes will lavishly consume energy and so a security scheme that consumes less energy still provides ample protection to the messages have to be introduced. Here we propose an encryption scheme for the messages passing through MANET. The security scheme is based on selective encryption that is very robust, simple and with less computational capability.

Minutiae-based fingerprint recognition is a challenging problem, mostly due poor quality of the sensing image, large nonlinear distortion among dissimilar impressions of similar fingerprint and several common transactions. Those problems make poor feature extraction and matching. Most of the fingerprint matching system is constructed on minutiae-based feature vector. The minutiae position, size and direction of the fingerprint impression must be invariant to scaling and rotation. Such distortion problems are generated by the image capturing devices; in this study the scanned fingerprint image is subjected to feature extraction and minutiae evaluation. In the feature extracting stage image pre-processing, minutiae extraction is accomplished and in the minutiae evaluation stage the original minutiae was evaluated. The scope of this work is to attain invariance by extracting the characteristics based on the spatial connection between minutiae points. We suggest four minutiae based structural local feature vectors, at the same time it is expected to fulfill at least two necessary feature vector properties. These feature vector descriptions support in solving the spurious and missing minutiae problems and hence help us develop a robust person authentication system. The performance improvement of the proposed system is evaluated by Goodness of Index (GI) GI values. These techniques achieve effectiveness with the help of FVC databases.

One of the most difficult tasks in networking is to provide security to data during transmission, the main issue using network is lack of security. Various techniques and methods had been introduced to satisfy the needs to enhance the firmness of the data while transmitting over internet. Due to several reasons and intruders the mechanism of providing security becomes a tedious task. At first conventional passwords are used to provide security to data while storing and transmitting but remembering the password quite confusing and difficult for the user to access the data. After that cryptography methodology is introduced to protect the data from the intruders by converting readable form of data into unreadable data by encryption process. Then the data is processed and received the receiver can access the original data by the reverse process of encryption called decryption. The processes of encoding have broken by intruders using various combinations of keys. In this proposed work strong encryption key can be generated by combining biometric and cryptography methods for enhancing firmness of data. Here biometric face image is pre-processed at initial stage then facial features are extracted to generate biometric-cryptographic key. After generating bio-crypto key data can be encrypted along with newly produced key with 0's or 1's bit combination and stored in the database. By generating bio-crypto key and using them for transmitting or storing the data the privacy and firmness of the data can be enhanced and by using own biometrics as key the process of hacking and interfere of intruders to access the data can be minimized.

Biometrics means an authentication of the person's Physiological and Behavioral Characteristics. One of the key steps in biometric based authentication is verification and identification. In physiological and behavioral based authentications are carried out using different traits such as fingerprint, finger vein, finger knuckle, iris, voice, handwriting, keystrokes, ear, EEG, ECG signals, etc. In these traits Minor finger knuckle print means backside of the finger surface and its very cheapest and easiest one for authentication system. First and second minor finger knuckle images has lot of thin lines and creases but it is not easily visible to the system for substantiation process. To overcome the above drawback image pre - processing step is very essential. Image preprocessing step segmentation is a one of the important portion. Edge detection is a pre-step of segmentation which is directly cut all the significant edges from the image correctly. In this proposed work to cut the first and second minor finger knuckle print image edges using diverse edge detection techniques. The second order derivatives are yields better results compare than first order derivatives and it's suitable for noisy Images. The output of the edge detection results are measured by various parameters such as MSE, RMSE and PSNR. According to the measurement parameters second order derivatives which give better results comparing with other datasets.

INTRODUCTION: During valve replacement, appropriate valve size will be chosen based on many factors, neglecting the potential of the patient for gaining weight. We aimed at evaluating the weight gain potential and its effect on hemodynamics in post mitral valve replacement (MVR) patients. MATERIAL AND METHODS: In 118 post-MVR patients, demographic and echocardiographic data at the time of discharge and follow-up were obtained and analyzed. Primary aim of study is to analyze the hemodynamics of patients based on weight gain/loss. Secondary aim is to evaluate the same in patient-prosthesis mismatch (PPM) subgroup and to evaluate the study population for the potential to gain/loss weight. RESULTS: Among 118 patients, 87 patients (73.7%) gained weight. In 87 weight gained patients, left atrial (LA) size (p = 0.011) and pulmonary artery systolic (PA) pressure (p = 0.028) at follow-up were significantly elevated than the discharge values. Among 53 PPM patients (incidence, 44.9%), 34 patients gained weight and their PA pressure was found to be elevated at follow-up (p = 0.021) whereas weight lost group does not show any significant difference (p = 0.972). Frequency of weight gain was more among patients who weighed

OBJECTIVE: To compare the outcomes of isolated coronary artery bypass grafting (CABG) versus surgical ventricular restoration (SVR) with or without CABG for patients with ischemic cardiomyopathy (ICM). METHODS: Retrospectively, 49 patients with ICM and severe LV dysfunction (LVEF

We report the successful treatment of a rare case of chronic intrapericardial hematoma which presented with congestive cardiac failure 20 months after aortic valve replacement surgery for severe calcific aortic stenosis. Chest roentgenograph demonstrated paracardiac mass over lower left ventricle border, left pleural effusion and pulmonary venous hypertension. An echocardiographic study demonstrated intrapericardial mass posterolateral to left ventricle compressing left ventricular cavity both during systole and diastole causing septum to bulge into right ventricle. Computed tomography showed a loculated pericardial mass in left heart margin, left pleural effusion, bilateral axillary and mediastinal lymphadenopathy. Surgical resection was planned to relieve the symptoms and to confirm the diagnosis of the mass. The mass was completely resected through left anterolateral thoracotomy and histopathology findings confirmed the diagnosis of hematoma with cystic degeneration. Postoperative course was uneventful, and his symptoms improved markedly.

Cluster headache is a primary neurovascular unilateral headache associated with autonomic symptoms. The sphenopalatine ganglion plays an important role in the pathogenesis of this disorder. Although medications are the first line of treatment, percutaneous, and surgical interventions have been proposed to treat cluster headache. An attractive option is the radiofrequency ablation of the sphenopalatine ganglion for the treatment of cluster headache due to its relative safety and simplicity compared with other procedures.

Mobile ad-hoc network security problems are the subject of in depth analysis. A group of mobile nodes area unit connected to a set wired backbone. In MANET, the node themselves implement the network management in a very cooperative fashion. All the nodes area unit accountable to create a constellation that is dynamically, modification it and conjointly the absence of any clear network boundaries. We tend to project a completely unique intrusion detection model for mobile ad-hoc network victimization. CP-KNN (Conformal Prediction K-Nearest Neighbor) algorithmic rule is to classify the audit knowledge for anomaly detection. The non-conformity score worth is employed to cut back the classification period of time for multi level iteration. It is effectively notice anomalies with high true positive rate, low false positive rate and high confidence that the progressive of assorted anomaly detection ways. Additionally it is interfered by “noisy” knowledge (unclean data), the projected technique is strong, effective and conjointly it retains its smart detection performance and to avoid the abnormal activity.

Service Oriented Architecture has gained significant attention as programming model for heterogeneous wireless sensor networks. Its key idea is to exploit the decoupling of service providers and consumers to enable platform independent applications that are dynamically bound to platform specific services. The promise of service oriented architecture is to enable the composition of new distributed applications/solutions: when no available service can satisfy a client request, available services can be composed in order to satisfy such a request. In this paper we explore a simple approach to create service graph on-demand for service composition in service oriented wireless sensor network based on input/output dependency between services. The proposed algorithm ASSG (Automatic Service Graph Generation) discovers abstract services that satisfies user constraints and identifies the relationship between these services. Based on this service graph is generated. The application of this method is discussed with an example. Simulation results prove that our proposed algorithm increases success ratio and reduces service composition time.

Mobile ad hoc networks are becoming an important concept of modern communication technologies and services. It provides some advantages to this communication world such as self-organizing and decentralization. In this paper, we are going to design a cluster-based multi source multicast routing protocol with new cluster head election, path construction and maintenance techniques. The main objective of this work to compute the maximum performance of proposed routing protocol in various environments, and also it has been compared with Multicast Ad-hoc On-Demand Distance Vector (MAODV) and On-Demand Multicast Routing Protocol (ODMRP) to prove the performance of delivery ratio, control overhead and forwarding efficiency.

Wireless sensor networks (WSN) present a challenging programming environment because of their limited resources, heterogeneity and highly dynamic nature. Service oriented computing (SOC) can simplify application development by hiding platform-specific capabilities behind services. Their services are dynamically discovered and used at run time, enabling application to be platform independent and adapt to network dynamics. While service-oriented computing is widely used on the internet, adapting it to WSNs is non-trivial due to the extremely limited resource available. The selection of which service provider to use and how to adapt as provider change significantly impacts application and network performance. In this paper, we present a global QoS optimizing and multiobjective service composition algorithm based on the construction of convex hull. Simulation experiments were conducted to show the efficiency of the proposed algorithm.

In a large sensor network, in-network data aggregation is inherently used as a communication paradigm which reduces the number of packets transmitted and hence the energy consumed. However the unattended and hostile operation of sensor network makes the system vulnerable to node compromise attack. The compromised nodes can inject false data in to the network which deteriorates the accuracy of the aggregate data. So the research on resilient data aggregation with a focus on data integrity and accuracy becomes a major issue. In this paper, we propose a statistical based robust estimate to design a resilient in-network aggregation scheme which detects and isolates the outliers from computed aggregate value. Simulation results demonstrate that our approach provides a powerful mechanism for detecting outliers even in the presence of multiple compromised nodes.

The changes that occur during the software development process is rapid. Hence software has to undergo modification frequently. Due to this modification,the cost for testing increases due to repetitive retesting. This retesting process is called as the regression testing. Modification made in the single test case will make the side effect in all other related test cases. In order to overcome this problem all the test cases have to be retested again and again whenever the changes are incorporated in the software. But testing all the test cases is time consuming and will also increase the cost of testing. To address this problem, this work focuses on providing priority to the test cases. Test case which had more effect to changes is assigned with higher priority and the test case which had the less effect to changes is assigned lower priority. For test case prioritization, we employ m-ACO (Modified Ant colony optimization) method.Test case prioritization is done in two ways namely “Triangle classification problem” and “Quadratic Equation Problem”. Flow of the data in the test case is done by Genetic Algorithm. This identifies the changed code in the program under test. It identifies both indirectly and directly affected def-use association in the modified part of the software by using forward walk algorithm and backward walk algorithm.

Safe operating environment is essential for all complex industrial processes. The safety issues in steel rolling mill when the hot strip passes through consecutive mill stands have been considered in this paper. Formation of sag in strip is a common problem in the rolling process. The excessive sag can lead to scrap runs and damage to machinery. Conventional controllers for mill actuation system are based on a rolling model. The factors like rise in temperature, aging, wear and tear are not taken into account while designing a conventional controller. Therefore, the conventional controller cannot yield a requisite controlled output. In this paper, a new Genetic-neuro-fuzzy hybrid controller without tension sensor has been proposed to optimize the quantum of excessive sag and reduce it. The performance of the proposed controller has been compared with the performance of fuzzy logic controller, Neuro-fuzzy controller and conventional controller with the help of data collected from the plant. The simulation results depict that the proposed controller has superior performance than the other controllers.

Traditional intrusion detection have a trouble dealing with lack of secure boundaries, threats from compromised nodes, lack of centralized management facility, restricted power supply and scalability. Due to these issues, we are motivated to propose efficient IDS, which involve a new technique to identify the anomalous activities in mobile ad-hoc networks. During this paper, we propose a Genetic based feature selection and rule evaluation process for anomaly detection. This process is effectively classified with new rules and also increases with high positive rate alarm. The new findings of our proposed work is effectively notice the anomalies with low false positive rate, high detection rate and attain the upper detection accuracy.

This paper presents a new; cluster based multicast routing protocol with some upgrading features such as multiple sources, less redundancy in packet delivery and better forwarding efficiency in mobile ad hoc networks. In this proposed work we have used the differential evolution algorithm for the cluster and hence cluster heads optimization. To prove the proposed routing protocol performance which has been simulated in NS2 and that results are proved that better delivery ratio, control overhead and forwarding efficiency as the function of increasing multicast sources and destinations.

Recent technology in wireless communication has enabled the development of low-cost sensor networks. Sensors at different locations can generate streaming data, which can be analyzed in real-time to identify events of interest. Wireless sensor networks (WSNs) usually have limited energy and transmission capacity, which cannot match the transmission of a large number of data collected by sensor nodes. So, it is necessary to perform in-network data aggregation in the WSN which is performed by aggregator node. Since, the nodes in WSN are vulnerable to malicious attackers and physical impairment; the data collected in WSNs may be unreliable. So, in this paper, we propose an efficient model based technique to detect the unreliable data. Data model is designed using the sound statistical multivariate technique called Principal Component Analysis (PCA). But as a drawback, it is not robust to outliers. Hence, if the input data is corrupted, an arbitrarily wrong representation is obtained. To overcome this problem, we propose two approaches namely Minimum Volume Ellipsoid (MVE) and Minimum Covariance Determinant (MCD) to design robust PCA which aids in design of a noise-free data model. The performance of proposed approach is evaluated and compared with previous approaches and found that our approach is effective and efficient.

Ad hoc networks are wireless, infrastructureless, multi-hop and dynamic networks, established by a collection of mobile nodes which provide envisioned applications and features to the modern communication technologies and services. Multicast is a type of routing scheme, which transmit datagram's to a set of desirable destinations identified by a single address which can efficiently support a variety of applications and services. Most of existing multicast routing protocols in MANETs consider only one source in a multicast group and become extended to multi-source multicasting. In this paper, we proposed a cluster-based multicast routing protocol with the use of genetic algorithm to provide efficient multicasting for ad hoc networks in multicast environment. The simulation composed with 200 mobile nodes with both single active multicast cluster and multiple active multicast clusters. This proposed cluster-based routing preserve forwarding efficiency as well as robustness due to this cluster structure and maintenance. Moreover, to prove the proposed approach performance which has compared with ODMRP routing protocol for delivery ratio, control overhead and forwarding efficiency in the different multicast effects such as increasing number of sources and receivers in the network.

Mobile ad hoc networks are becoming an important concept of modern communication technologies and services. It provides some advantages to this communication world such as self-organizing and decentralization. In this paper, we are going to design a cluster-based multi source multicast routing protocol with new cluster head election, path construction and maintenance techniques. The main objective of this work to compute the maximum performance of proposed routing protocol in various environments, and also it has been compared with On-Demand Multicast Routing Protocol (ODMRP) to prove the better performance of delivery ratio, control overhead and forwarding efficiency.

Strip tension control is crucial in the tandem finishing mills for its safe operation. Most of the industrial applications are of nonlinear. Fuzzy logic controller is the most useful approach to achieve the adaptive ness in the case of nonlinear system. Since fuzzy logic control provides a systematic method of incorporating human expertise and implementing nonlinear system. Neural networks are integrated with fuzzy logic which forms a neuro fuzzy system. To get a desired solution from the vagueness of the problem, an ant colony system (ACS) is implemented. The nature of search of food by the real antpsilas colony to find the food from its source (i.e. nest), to its destination (i.e. food) is known as ACS. The same foraging behavior of ants can be used to determine the optimal solution for the membership functions of FLC and hence form the hybrid intelligent controller (HIC). This paper demonstrates the effectiveness of HIC in optimizing the looper height in steel rolling mills compared with conventional controllers, FLC. The simulation result depicts that HIC quickly restore the speed of the main drive and hence looper height is quickly reduced to its optimal (zero) value which intern ensures the safety working condition of steel rolling mills.

Strip tension control is crucial in the tandem finishing mills for its safe operation. Most of the industrial applications are of nonlinear. Fuzzy logic controller is the most useful approach to achieve the adaptive ness in the case of nonlinear system. Since fuzzy logic control provides a systematic method of incorporating human expertise and implementing non-linear system. Neural networks are integrated with fuzzy logic which forms a neuro fuzzy system. Genetic algorithm is used to search optimal fuzzy rules and membership functions of neuro fuzzy system in order to give optimal output and hence form the hybrid intelligent controller (HIC). This paper demonstrates the effectiveness of HIC in optimizing the looper height in steel rolling mills compared with conventional controllers, FLC. The simulation result depicts that HIC quickly restore the speed of the main drive and hence looper height is quickly reduced to its optimal (zero) value which intern ensures the safety working condition of steel rolling mills.