Report
Share
Recommended
Energy saving Wireless Sensor Networks using Kerberos
The wireless sensor network is an networking field that combines sensing, computation, and communication into a single
tiny device. As sensor networks frame closer towards well-known deployment, security issues become a vital concern. So far, much
work has focused on making sensor networks realistic and useful, but still security in sensor network data communication is big issue
for research. This paper proposed the idea of having different Kerberos authentication architecture for the different clusters in sensor
network to save energy factor of the sensor nodes and to save time for data communication between the sensor nodes in the network
Recommended
Energy saving Wireless Sensor Networks using Kerberos
The wireless sensor network is an networking field that combines sensing, computation, and communication into a single
tiny device. As sensor networks frame closer towards well-known deployment, security issues become a vital concern. So far, much
work has focused on making sensor networks realistic and useful, but still security in sensor network data communication is big issue
for research. This paper proposed the idea of having different Kerberos authentication architecture for the different clusters in sensor
network to save energy factor of the sensor nodes and to save time for data communication between the sensor nodes in the network
Challenges, Issues and Research directions in Optical Burst Switching
Optical Burst Switching architecture (OBS) is based on buffer-less WDM network that provides unbelievably huge
bandwidth for communication. A brief review on OBS architecture along with its supporting protocols is studied here. This
architecture suffers from various issues and these complications along with the future research directions are reviewed here.
Quest Trail: An Effective Approach for Construction of Personalized Search En...
Personalized search refers to search experiences that are tailored specifically to an individual's interests by incorporating information about the individual beyond specific query provided. Especially people working in a software development organization (analysts, developers, testers, maintenance team members), find it increasingly difficult to get relevant results to their searches. We propose methods to personalize searches by resolving the ambiguity of query terms, and increase the relevance of search results in order to match the user’s interests. Difficulty in web searches has given rise to the need for development of personalized search engines. Personalized search engines create user profiles to capture the users’ personal preferences and as such identify the actual goal of the input query. Since users are usually reluctant to explicitly provide their preferences due to the extra manual effort involved, the search engine faces the entire burden of predicting the user’s preferences and intentions behind a query in order to yield more relevant search results. In this paper we define a QUEST to be the objective of user’s search; here we combine quest level analysis of user’s search logs and semantic analysis of the user’s query in order to personalize user’s search results. Most personalization methods focus on the creation of one single profile for a user and apply the same profile to all of the user’s queries. Hence we propose a personalized search for a software development organization by creating QUEST or domain based profile rather than individual user based profile.
Intuitionistic Fuzzy Semipre Generalized Connected Spaces
In this paper, we introduce the notion of intuitionistic fuzzy semipre generalized connected space, intuitionistic fuzzy semipre generalized super connected space and intuitionistic fuzzy semipre generalized extremally disconnected spaces. We investigate some of their properties.
Adaptive Neural Fuzzy Inference System for Employability Assessment
Employability is potential of a person for gaining and maintains employment. Employability is measure through the
education, personal development and understanding power. Employability is not the similar as ahead a graduate job, moderately it
implies something almost the capacity of the graduate to function in an employment and be capable to move between jobs, therefore
remaining employable through their life. This paper introduced a new adaptive neural fuzzy inference system for assessment of
employability with the help of some neuro fuzzy rules. The purpose and scope of this research is to examine the level of employability.
The concern research use both fuzzy inference systems and artificial neural network which is known as neuro fuzzy technique for
solve the problem of employability assessment. This paper use three employability skills as input and find a crisp value as output
which indicates the glassy of employee. It uses twenty seven neuro fuzzy rules, with the help of Sugeno type inference in Mat-lab and
finds single value output. The proposed system is named as Adaptive Neural Fuzzy Inference System for Employability Assessment
(ANFISEA).
More Related Content
Viewers also liked
Challenges, Issues and Research directions in Optical Burst Switching
Optical Burst Switching architecture (OBS) is based on buffer-less WDM network that provides unbelievably huge
bandwidth for communication. A brief review on OBS architecture along with its supporting protocols is studied here. This
architecture suffers from various issues and these complications along with the future research directions are reviewed here.
Quest Trail: An Effective Approach for Construction of Personalized Search En...
Personalized search refers to search experiences that are tailored specifically to an individual's interests by incorporating information about the individual beyond specific query provided. Especially people working in a software development organization (analysts, developers, testers, maintenance team members), find it increasingly difficult to get relevant results to their searches. We propose methods to personalize searches by resolving the ambiguity of query terms, and increase the relevance of search results in order to match the user’s interests. Difficulty in web searches has given rise to the need for development of personalized search engines. Personalized search engines create user profiles to capture the users’ personal preferences and as such identify the actual goal of the input query. Since users are usually reluctant to explicitly provide their preferences due to the extra manual effort involved, the search engine faces the entire burden of predicting the user’s preferences and intentions behind a query in order to yield more relevant search results. In this paper we define a QUEST to be the objective of user’s search; here we combine quest level analysis of user’s search logs and semantic analysis of the user’s query in order to personalize user’s search results. Most personalization methods focus on the creation of one single profile for a user and apply the same profile to all of the user’s queries. Hence we propose a personalized search for a software development organization by creating QUEST or domain based profile rather than individual user based profile.
Intuitionistic Fuzzy Semipre Generalized Connected Spaces
In this paper, we introduce the notion of intuitionistic fuzzy semipre generalized connected space, intuitionistic fuzzy semipre generalized super connected space and intuitionistic fuzzy semipre generalized extremally disconnected spaces. We investigate some of their properties.
Adaptive Neural Fuzzy Inference System for Employability Assessment
Employability is potential of a person for gaining and maintains employment. Employability is measure through the
education, personal development and understanding power. Employability is not the similar as ahead a graduate job, moderately it
implies something almost the capacity of the graduate to function in an employment and be capable to move between jobs, therefore
remaining employable through their life. This paper introduced a new adaptive neural fuzzy inference system for assessment of
employability with the help of some neuro fuzzy rules. The purpose and scope of this research is to examine the level of employability.
The concern research use both fuzzy inference systems and artificial neural network which is known as neuro fuzzy technique for
solve the problem of employability assessment. This paper use three employability skills as input and find a crisp value as output
which indicates the glassy of employee. It uses twenty seven neuro fuzzy rules, with the help of Sugeno type inference in Mat-lab and
finds single value output. The proposed system is named as Adaptive Neural Fuzzy Inference System for Employability Assessment
(ANFISEA).
Viewers also liked (13)
Challenges, Issues and Research directions in Optical Burst Switching
Challenges, Issues and Research directions in Optical Burst Switching
Quest Trail: An Effective Approach for Construction of Personalized Search En...
Quest Trail: An Effective Approach for Construction of Personalized Search En...
Intuitionistic Fuzzy Semipre Generalized Connected Spaces
Intuitionistic Fuzzy Semipre Generalized Connected Spaces
Adaptive Neural Fuzzy Inference System for Employability Assessment
Adaptive Neural Fuzzy Inference System for Employability Assessment