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, CAC
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 and Hamid Abubakar Adamu3,1 Adamawa State Polytechnic, Nigeria,2Adamawa 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. Sumathi1, T. Santhanam2, and M. Mahadevi1 1SDNB Vaishnav College for Women, India and 2DG 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
Facial 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 validation activity.
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 :
hhttp://airccse.org/journal/ijcses/currentissue.html