DETECTING BRAIN TUMOUR FROM MRIIMAGE USING MATLAB GUI PROGRAMME
Esmail Hassan1 and Abobakr Aboshgifa, 1Higher Institute of Medical Professions – Tripoli Libya2High technical center for training and production. Tripoli Libya
Engineers have been actively developing tools to detect tumors and to process medical images. Medical image segmentation is a powerful tool that is often used to detect tumors. Many scientists and researchers are working to develop and add more features to this tool. This project is about detecting Brain tumors from MRI images using an interface of GUI in Matlab. Using the GUI, this program can use various combinations of segmentation, filters, and other image processing algorithms to achieve the best results. We start with filtering the image using Prewitt horizontal edge-emphasizing filter. The next step for detecting tumor is "watershed pixels." The most important part of this project is that all the Matlab programs work with GUI “Matlab guide”. This allows us to use various combinations of filters, and other image processing techniques to arrive at the best result that can help us detect brain tumors in their early stages.
Matlab program, GUI program, Tumors, Medical image .
For More Details :
https://aircconline.com/ijcses/V6N6/6615ijcses04.pdf
Volume Link :
https://airccse.org/journal/ijcses/current2015.html
ROLE OF MIDDLEWARE FOR INTERNET OF THINGS: A STUDY
Soma Bandyopadhyay, Munmun Sengupta, Souvik Maiti and Subhajit Dutta , Innovation Lab, TATA Consultancy Services Ltd. Kolkata, India
Internet of Things (IoT) has been recognized as a part of future internet and ubiquitous computing. It creates a true ubiquitous or smart environment. It demands a complex distributed architecture with numerous diverse components, including the end devices and application and association with their context. This article provides the significance of middleware system for (IoT). The middleware for IoT acts as a bond joining the heterogeneous domains of applications communicating over heterogeneous interfaces. First, to enable the better understanding of the current gap and future directions in this field a comprehensive review of the existing middleware systems for IoT is provided here. Second, fundamental functional blocks are proposed for this middleware system, and based on that feature wise classification is performed on the existing IoT-middleware. Third, open issues are analyzed and our vision on the research scope in this area is presented.
Internet of Things, middleware, semantic model, context-awareness, ubiquitous computing.
For More Details :
https://airccse.org/journal/ijcses/papers/0811cses07.pdf
Volume Link :
https://airccse.org/journal/ijcses/current2011.html
A SURVEY ON CALL ADMISSION CONTROL SCHEMES IN LTE
Solomon Orduen Yese, Abdulhakeem Abdulazeez, Aminu Mohammed, Maniru Malami Umar and Zaharadden Yusuf Yeldu,Department of Mathematics, Usmanu Danfodiyo University, Sokoto, Nigeria,
The growing number of mobile users with diverse applications such as VoIP, video, internet surfing etc. has made LTE networks to adopt a CAC strategy in order to ensure the quality of service (QoS) requirements of these applications. Over the years, several CAC schemes have been proposed to either accept or reject service requests. This paper presents a survey of these schemes under four different classes. The classes are: Bandwidth Reservation (BR), Bandwidth Degradation (BD), BR and BD and Non-BR and Non-BD (NBR-NBD). In each of the classification, the operation procedure, strengths and weaknesses of each scheme has been discussed. Furthermore, a comparative analysis of these schemes is also presented. The analysis provides insight into the challenges in the design of CAC by highlighting open research issues for future directions.
Call Admission Control, LTE, bandwidth degradation, bandwidth reservation, survey, CA.
For More Details :
http://aircconline.com/ijcses/V10N5/10519ijcses01.pdf
Volume Link :
http://airccse.org/journal/ijcses/current2019.html
REVIEW AND ANALYSIS ON TELECOMMUNICATION NETWORKS INFRASTRUCTURE IN THE NORTHWEST PROVINCE OF NIGERIA FOR OPTIMISATION: PROBLEMS AND SOLUTIONS
Sanusi Mohammed Bunu1 Murtala Muhammad2 Hamid Abubakar Adamu3,1Adamawa State Polytechnic, Nigeria.2Adamawa State University Mubi, Nigeria and 3Adamawa State University Mubi, Nigeria.Adamawa State University Mubi, Nigeria and 3Adamawa State University Mubi, Nigeria
Telecommunication network infrastructure determines the strength of a country for successful communication with other parts of the world. Due to the rapid increase of internet usage and mobile communication in every part of the world, specifically the third world countries, Nigeria is among the countries that is advancing in the used of telecommunication contraptions. The Nigerian Telecommunication Industries play a vital role in boosting the social and economic infrastructure of the country. This paper is aimed at investigating the Telecommunication Network infrastructure in the Northwestern part of Nigerian and propose some technologies that increase data bandwidth and internet penetration in the region. Problems and future solutions to the existing network infrastructure in the province were discussed and basic analysis is conducted to justify the importance of the study. Mobile market analysis, current infrastructure, parameters evaluation and the way forward to the problems are discussed. Comparative analysis between the existing network infrastructure that is 3G networks and the proffer solution to the existing standard which is 4G network is also conducted. This paper also conducts an analysis on the existing Network providers in the region with their draw backs and the quality of services they provide to the customers within the region. The paper concludes with a future plan of coming up with an analytical solution in order to study the implementation process of a full 4G network in the Northwest region of Nigeria and to use a simulated environment to test the proposed model for viability.
Telecommunication, 3G networks, 4G Networks, Northwest Nigeria.
For More Details :
http://aircconline.com/ijcses/V10N1/10119ijcses01.pdf
Volume Link :
http://airccse.org/journal/ijcses/current2019.html
Automatic Facial Expression Analysis A Survey
C. P. Sumathi1T. Santhanam and M. Mahadevi21SDNB Vaishnav College for Women, India and2DG Vaishnav College for Men,India
The Automatic Facial Expression Recognition has been one of the latest research topic since 1990’s.There have been recent advances in detecting face, facial expression recognition and classification. There are multiple methods devised for facial feature extraction which helps in identifying face and facial expressions. This paper surveys some of the published work since 2003 till date. Various methods are analysed to identify the Facial expression. The Paper also discusses about the facial parameterization using Facial Action Coding System(FACS) action units and the methods which recognizes the action units parameters using facial expression data that are extracted. Various kinds of facial expressions are present in human face which can be identified based on their geometric features, appearance features and hybrid features . The two basic concepts of extracting features are based on facial deformation and facial motion. This article also identifies the techniques based on the characteristics of expressions and classifies the suitable methods that can be implemented.
acial Expression, FACS, Geometric Features, Appearance Features, Deformation, Facial Motion.
For More Details :
http://airccse.org/journal/ijcses/papers/3612ijcses04.pdf
Volume Link :
http://airccse.org/journal/ijcses/current2012.html
The Implication of Statistical Analysis and Feature Engineering for Model Building Using Machine Learning Algorithms
Swayanshu Shanti Pragnya and Shashwat Priyadarshi, Accenture, India
Scrutiny for presage is the era of advance statistics where accuracy matter the most. Commensurate between algorithms with statistical implementation provides better consequence in terms of accurate prediction by using data sets. Prolific usage of algorithms lead towards the simplification of mathematical models, which provide less manual calculations. Presage is the essence of data science and machine learning requisitions that impart control over situations. Implementation of any dogmas require proper feature extraction which helps in the proper model building that assist in precision. This paper is predominantly based on different statistical analysis which includes correlation significance and proper categorical data distribution using feature engineering technique that unravel accuracy of different models of machine learning algorithms.
Correlation, Feature engineering, Feature selection, PCA, K nearest neighbour, logistic regression, RFE.
For More Details :
http://aircconline.com/ijcses/V10N3/10319ijcses01.pdf
Volume Link :
http://airccse.org/journal/ijcses/current2019.html
A Survey on Internal Validity Measure for Cluster Validation
L.Jegatha Deborah, R.Baskaran and A.Kannan , Anna University – Chennai
Data Clustering is a technique of finding similar characteristics among the data set which are always hidden in nature and grouping them into groups, called as clusters. Different clustering algorithms exhibit different results, since they are very sensitive to the characteristics of original data set especially noise and dimension. The quality of such clustering process determines the purity of cluster and hence it is very important to evaluate the results of the clustering algorithm. Due to this, Cluster validation activity had been a major and challenging task. The major factor which influences cluster validation is the internal cluster validity measure of choosing the optimal number of clusters. The main objective of this article is to present a detailed description of the mathematical working of few cluster validity indices and not all, to classify these indices and to explore the ideas for the future promotion of the work in the domain of cluster validation. In addition to this, a maximization objective function is defined assuming to provide a cluster validationactivity.
Data clustering, cluster, cluster purity, cluster analysis, cluster validation, cluster validity indices.
For More Details :
http://airccse.org/journal/ijcses/papers/1110ijcses07.pdf
Volume Link :
http://airccse.org/journal/ijcses/currentissue.html