Data deduplication is widely used in cloud computing to eliminate the redundant data storage with... more Data deduplication is widely used in cloud computing to eliminate the redundant data storage with intelligent compression process. Hybrid cloud is composed with the private cloud and public cloud utilization. The latest trends of cloud storage are enriched with the end-to-end encryption mechanism. Combining deduplication process with end-to-end encryption mechanism are costly. Providing semantic security with cost effectiveness is the high task for the research scholars. In this paper a high security authentication mechanism is introduced in association with the deduplication process in Hybrid Cloud Storage. In this paper we proposed a prototype model to show the intelligent compression with high security authentication system for performing any storage operations. The experimental results have replicated the concept of providing security and duplicate check scheme while storing in the Hybrid Cloud.
Karbala International Journal of Modern Science, 2019
Traditional search mechanisms are based on the keyword search, which does not consider the semant... more Traditional search mechanisms are based on the keyword search, which does not consider the semantic links between different concepts. This leads to the loss of relevant documents due to inaccurate query formulation or using contextually close words and concepts in the query. To solve the problems of formulating user queries and interdisciplinarity of concepts, it is suggested to use semantic search. The proposed method for implementing semantic search is applicable to large scopes of text data and is based on using a genetic algorithm. Unlike standard methods for information search, the suggested method allows us to consider the semantics of interrelationships between concepts and to handle interdisciplinary concepts correctly. By the aid of semantic tagging, documents contain concepts that are not present in the user's initial query but are semantically close to the requested concepts. Semantic tagging is performed for each document separately, which provides parallel tagging in several subject areas. By the time of the document ontological profile formation is completed, all semantic distances between pairs of distinguished concepts are calculated. Concepts are considered contextually close if their semantic proximity value is above a certain threshold value that is specified in the search parameters. Building a document ontological profile is a multicriteria task, since it depends on a lot of characteristics, so genetic algorithms can be used to solve it effectively. The developed genetic algorithm is intended for more accurate distribution of weight coefficients and estimation of semantic proximity of concepts.
The coronavirus disease of 2019 (COVID-19), a unique Coronavirus strain, has created a chaotic si... more The coronavirus disease of 2019 (COVID-19), a unique Coronavirus strain, has created a chaotic situation, negatively impacting the number of deaths and people's lives globally. The daily increase in COVID-19 instances is due to a lack of and restricted availability of detection techniques for determining the disease's presence. Therefore, detecting positive results as soon as feasible is important to preventing the spread of this epidemic and treating infected people as soon as possible. As a result of these constraints, the demand for clinical decision-making systems based on predictive algorithms has increased. The article describes a recurrent neural network (RNN) for identifying Coronavirus (COVID-19) and tries to improve the detection method. Different machine learning methodologies, such as Support Vector Machines (SVMs), were used to create a detection system with a deep learning algorithm called Long Short Term Memory (LSTM). The research describes a method for detec...
Data deduplication is widely used in cloud computing to eliminate the redundant data storage with... more Data deduplication is widely used in cloud computing to eliminate the redundant data storage with intelligent compression process. Hybrid cloud is composed with the private cloud and public cloud utilization. The latest trends of cloud storage are enriched with the end-to-end encryption mechanism. Combining deduplication process with end-to-end encryption mechanism are costly. Providing semantic security with cost effectiveness is the high task for the research scholars. In this paper a high security authentication mechanism is introduced in association with the deduplication process in Hybrid Cloud Storage. In this paper we proposed a prototype model to show the intelligent compression with high security authentication system for performing any storage operations. The experimental results have replicated the concept of providing security and duplicate check scheme while storing in the Hybrid Cloud.
Karbala International Journal of Modern Science, 2019
Traditional search mechanisms are based on the keyword search, which does not consider the semant... more Traditional search mechanisms are based on the keyword search, which does not consider the semantic links between different concepts. This leads to the loss of relevant documents due to inaccurate query formulation or using contextually close words and concepts in the query. To solve the problems of formulating user queries and interdisciplinarity of concepts, it is suggested to use semantic search. The proposed method for implementing semantic search is applicable to large scopes of text data and is based on using a genetic algorithm. Unlike standard methods for information search, the suggested method allows us to consider the semantics of interrelationships between concepts and to handle interdisciplinary concepts correctly. By the aid of semantic tagging, documents contain concepts that are not present in the user's initial query but are semantically close to the requested concepts. Semantic tagging is performed for each document separately, which provides parallel tagging in several subject areas. By the time of the document ontological profile formation is completed, all semantic distances between pairs of distinguished concepts are calculated. Concepts are considered contextually close if their semantic proximity value is above a certain threshold value that is specified in the search parameters. Building a document ontological profile is a multicriteria task, since it depends on a lot of characteristics, so genetic algorithms can be used to solve it effectively. The developed genetic algorithm is intended for more accurate distribution of weight coefficients and estimation of semantic proximity of concepts.
The coronavirus disease of 2019 (COVID-19), a unique Coronavirus strain, has created a chaotic si... more The coronavirus disease of 2019 (COVID-19), a unique Coronavirus strain, has created a chaotic situation, negatively impacting the number of deaths and people's lives globally. The daily increase in COVID-19 instances is due to a lack of and restricted availability of detection techniques for determining the disease's presence. Therefore, detecting positive results as soon as feasible is important to preventing the spread of this epidemic and treating infected people as soon as possible. As a result of these constraints, the demand for clinical decision-making systems based on predictive algorithms has increased. The article describes a recurrent neural network (RNN) for identifying Coronavirus (COVID-19) and tries to improve the detection method. Different machine learning methodologies, such as Support Vector Machines (SVMs), were used to create a detection system with a deep learning algorithm called Long Short Term Memory (LSTM). The research describes a method for detec...
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Papers by jamal challab