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DRUS: A New Proposed Interoperable DRM Solution
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DRUS: A New Proposed Interoperable DRM Solution ab 59 € als Taschenbuch: A novel Hardware-Software solution for the DRM interoperability problem. Aus dem Bereich: Bücher, Wissenschaft, Technik,

Anbieter: hugendubel
Stand: 06.08.2020
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Soft Computing Techniques for Type-2 Diabetes D...
31,43 € *
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Diabetes Mellitus (DM, commonly referred to as diabetes, is a metabolic disorder in which there are high blood sugar levels over a prolonged period. Lack of sufficient insulin causes presence of excess sugar levels in the blood. As a result the glucose levels in diabetic patients are more than normal ones. It has symptoms like frequent urination, increased hunger, increase thirst and high blood sugar. There are mainly three types of diabetes namely type-1, type-2 and gestational diabetes. Type-1 DM occurs due to immune system mistakenly attacks and destroys the beta-cells and Type-2 DM occurs due to insulin resistance. Gestational DM occurs in women during pregnancy due to insulin blocking by pregnancy harmones. Among these three types of DM, type-2 DM is more prevalence, and impacting so many millions of people across the world. Classification and predictive systems are actually reliable in the health care sector to explore hidden patterns in the patients data. These systems aid, medical professionals to enhance their diagnosis, prognosis along with remedy organizing techniques. The less percentage of improvement in classifier predictive accuracy is very important for medical diagnosis purposes where mistakes can cause a lot of damage to patient's life. Hence, we need a more accurate classification system for prediction of type-2 DM. Although, most of the above classification algorithms are efficient, they failed to provide good accuracy with low computational cost. In this book, we proposed various classification algorithms using soft computing techniques like Neural Networks (NNs), Fuzzy Systems (FS) and Swarm Intelligence (SI). The experimental results demonstrate that these algorithms are able to produce high classification accuracy at less computational cost. The contributions presented in this book shall attempt to address the following objectives using soft computing approaches for identification of diabetes mellitus. Introuducing an optimized RBFN model called Opt-RBFN. Designing a cost effective rule miner called SM-RuleMiner for type-2 diabetes diagnosis. Generating more interpretable fuzzy rules for accurate diagnosis of type2 diabetes using RST-BatMiner. Developing accurate cascade ensemble frameworks called Diabetes-Network for type-2 diabetes diagnosis. Proposing a Multi-level ensemble framework called Dia-Net for improving the classification accuracy of type-2 diabetes diagnosis. Designing an Intelligent Diabetes Risk score Model called Intelli-DRM estimate the severity of Diabetes mellitus. This book serves as a reference book for scientific investigators who need to analyze disease data and/or numerical data, as well as researchers developing methodology in soft computing field. It may also be used as a textbook for a graduate and post graduate level course in machine learning or soft computing.

Anbieter: buecher
Stand: 06.08.2020
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Soft Computing Techniques for Type-2 Diabetes D...
31,81 € *
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Diabetes Mellitus (DM, commonly referred to as diabetes, is a metabolic disorder in which there are high blood sugar levels over a prolonged period. Lack of sufficient insulin causes presence of excess sugar levels in the blood. As a result the glucose levels in diabetic patients are more than normal ones. It has symptoms like frequent urination, increased hunger, increase thirst and high blood sugar. There are mainly three types of diabetes namely type-1, type-2 and gestational diabetes. Type-1 DM occurs due to immune system mistakenly attacks and destroys the beta-cells and Type-2 DM occurs due to insulin resistance. Gestational DM occurs in women during pregnancy due to insulin blocking by pregnancy harmones. Among these three types of DM, type-2 DM is more prevalence, and impacting so many millions of people across the world. Classification and predictive systems are actually reliable in the health care sector to explore hidden patterns in the patients data. These systems aid, medical professionals to enhance their diagnosis, prognosis along with remedy organizing techniques. The less percentage of improvement in classifier predictive accuracy is very important for medical diagnosis purposes where mistakes can cause a lot of damage to patient's life. Hence, we need a more accurate classification system for prediction of type-2 DM. Although, most of the above classification algorithms are efficient, they failed to provide good accuracy with low computational cost. In this book, we proposed various classification algorithms using soft computing techniques like Neural Networks (NNs), Fuzzy Systems (FS) and Swarm Intelligence (SI). The experimental results demonstrate that these algorithms are able to produce high classification accuracy at less computational cost. The contributions presented in this book shall attempt to address the following objectives using soft computing approaches for identification of diabetes mellitus. Introuducing an optimized RBFN model called Opt-RBFN. Designing a cost effective rule miner called SM-RuleMiner for type-2 diabetes diagnosis. Generating more interpretable fuzzy rules for accurate diagnosis of type2 diabetes using RST-BatMiner. Developing accurate cascade ensemble frameworks called Diabetes-Network for type-2 diabetes diagnosis. Proposing a Multi-level ensemble framework called Dia-Net for improving the classification accuracy of type-2 diabetes diagnosis. Designing an Intelligent Diabetes Risk score Model called Intelli-DRM estimate the severity of Diabetes mellitus. This book serves as a reference book for scientific investigators who need to analyze disease data and/or numerical data, as well as researchers developing methodology in soft computing field. It may also be used as a textbook for a graduate and post graduate level course in machine learning or soft computing.

Anbieter: buecher
Stand: 06.08.2020
Zum Angebot
Soft Computing Techniques for Type-2 Diabetes D...
31,43 € *
ggf. zzgl. Versand

Diabetes Mellitus (DM, commonly referred to as diabetes, is a metabolic disorder in which there are high blood sugar levels over a prolonged period. Lack of sufficient insulin causes presence of excess sugar levels in the blood. As a result the glucose levels in diabetic patients are more than normal ones. It has symptoms like frequent urination, increased hunger, increase thirst and high blood sugar. There are mainly three types of diabetes namely type-1, type-2 and gestational diabetes. Type-1 DM occurs due to immune system mistakenly attacks and destroys the beta-cells and Type-2 DM occurs due to insulin resistance. Gestational DM occurs in women during pregnancy due to insulin blocking by pregnancy harmones. Among these three types of DM, type-2 DM is more prevalence, and impacting so many millions of people across the world. Classification and predictive systems are actually reliable in the health care sector to explore hidden patterns in the patients data. These systems aid, medical professionals to enhance their diagnosis, prognosis along with remedy organizing techniques. The less percentage of improvement in classifier predictive accuracy is very important for medical diagnosis purposes where mistakes can cause a lot of damage to patient's life. Hence, we need a more accurate classification system for prediction of type-2 DM. Although, most of the above classification algorithms are efficient, they failed to provide good accuracy with low computational cost. In this book, we proposed various classification algorithms using soft computing techniques like Neural Networks (NNs), Fuzzy Systems (FS) and Swarm Intelligence (SI). The experimental results demonstrate that these algorithms are able to produce high classification accuracy at less computational cost. The contributions presented in this book shall attempt to address the following objectives using soft computing approaches for identification of diabetes mellitus. Introuducing an optimized RBFN model called Opt-RBFN. Designing a cost effective rule miner called SM-RuleMiner for type-2 diabetes diagnosis. Generating more interpretable fuzzy rules for accurate diagnosis of type2 diabetes using RST-BatMiner. Developing accurate cascade ensemble frameworks called Diabetes-Network for type-2 diabetes diagnosis. Proposing a Multi-level ensemble framework called Dia-Net for improving the classification accuracy of type-2 diabetes diagnosis. Designing an Intelligent Diabetes Risk score Model called Intelli-DRM estimate the severity of Diabetes mellitus. This book serves as a reference book for scientific investigators who need to analyze disease data and/or numerical data, as well as researchers developing methodology in soft computing field. It may also be used as a textbook for a graduate and post graduate level course in machine learning or soft computing.

Anbieter: buecher
Stand: 06.08.2020
Zum Angebot
Soft Computing Techniques for Type-2 Diabetes D...
31,81 € *
ggf. zzgl. Versand

Diabetes Mellitus (DM, commonly referred to as diabetes, is a metabolic disorder in which there are high blood sugar levels over a prolonged period. Lack of sufficient insulin causes presence of excess sugar levels in the blood. As a result the glucose levels in diabetic patients are more than normal ones. It has symptoms like frequent urination, increased hunger, increase thirst and high blood sugar. There are mainly three types of diabetes namely type-1, type-2 and gestational diabetes. Type-1 DM occurs due to immune system mistakenly attacks and destroys the beta-cells and Type-2 DM occurs due to insulin resistance. Gestational DM occurs in women during pregnancy due to insulin blocking by pregnancy harmones. Among these three types of DM, type-2 DM is more prevalence, and impacting so many millions of people across the world. Classification and predictive systems are actually reliable in the health care sector to explore hidden patterns in the patients data. These systems aid, medical professionals to enhance their diagnosis, prognosis along with remedy organizing techniques. The less percentage of improvement in classifier predictive accuracy is very important for medical diagnosis purposes where mistakes can cause a lot of damage to patient's life. Hence, we need a more accurate classification system for prediction of type-2 DM. Although, most of the above classification algorithms are efficient, they failed to provide good accuracy with low computational cost. In this book, we proposed various classification algorithms using soft computing techniques like Neural Networks (NNs), Fuzzy Systems (FS) and Swarm Intelligence (SI). The experimental results demonstrate that these algorithms are able to produce high classification accuracy at less computational cost. The contributions presented in this book shall attempt to address the following objectives using soft computing approaches for identification of diabetes mellitus. Introuducing an optimized RBFN model called Opt-RBFN. Designing a cost effective rule miner called SM-RuleMiner for type-2 diabetes diagnosis. Generating more interpretable fuzzy rules for accurate diagnosis of type2 diabetes using RST-BatMiner. Developing accurate cascade ensemble frameworks called Diabetes-Network for type-2 diabetes diagnosis. Proposing a Multi-level ensemble framework called Dia-Net for improving the classification accuracy of type-2 diabetes diagnosis. Designing an Intelligent Diabetes Risk score Model called Intelli-DRM estimate the severity of Diabetes mellitus. This book serves as a reference book for scientific investigators who need to analyze disease data and/or numerical data, as well as researchers developing methodology in soft computing field. It may also be used as a textbook for a graduate and post graduate level course in machine learning or soft computing.

Anbieter: buecher
Stand: 06.08.2020
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DRUS: A New Proposed Interoperable DRM Solution
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DRUS: A New Proposed Interoperable DRM Solution ab 59 EURO A novel Hardware-Software solution for the DRM interoperability problem

Anbieter: ebook.de
Stand: 06.08.2020
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Trireforming- An emerging technique for syngas ...
54,90 € *
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The proposed work outlines the modeling aspects of kinetic evaluation for different types of reforming processes namely, Trireforming of methane (TRM), partial oxidation of methane(POM), Dry reforming of methane(DRM) and Steam reforming of methane(SRM). The results figure out Trireforming to be the most synergetic process as being combination of steam reforming, pom and dry reforming, it can not only produces synthesis gas (CO+H2) with desired H2/CO ratios(1.1-1.95) but also results in higher values of conversion for methane and carbon dioxide. These advantages have been demonstrated by tri-reforming of CH4 in a fixed-bed flow reactor at 1123K with supported nickel catalysts. Over 97% CH4 conversion and about 68 % CO2conversion can be achieved in tri-reforming over NiAl2O3 catalysts. The kinetic evaluation of partial oxidation of methane indicated the methane conversion to be around 96% with CO2 conversion of about 50.967% and H2/CO ratio to be in range of 1 -1.7.Though POM shows higher methane conversion but it lags in CO2 conversion and H2/CO ratio as compared to Trireforming. Moreover,in this process, oxygen is usually 40-50% higher than the required amount results excellence.

Anbieter: Dodax
Stand: 06.08.2020
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Technology and platform to manage rights and va...
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This book documents the contribution made by the author to the development of a DRM system specification providing all users of a Digital Media Value Chain with an open, standard, interoperable and reconfigurable solution enabling a broad variety of business models to be implemented. These range from simply informing what other users can do on content (e.g. the Creative Commons approach), to a full-fledged DRM system enforcing protection. The system described in this book may allow to monetize the value contributed by each player to the value chain, reducing the costs associated to online micro-payments for digital media and guaranteeing privacy of personal data and transaction information. To achieve this goal, a number of existing standard technologies have been integrated, adapted or extended, a number of missing key technologies have been developed, proposed and converted to ISO standards.

Anbieter: Dodax
Stand: 06.08.2020
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DRUS: A New Proposed Interoperable DRM Solution
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The advent of consumer digital media products has vastly increased the concerns of copyright-dependent organizations within the music and movie industries. The increase usage of personal computers as household appliances has made it convenient for consumers to convert media originally in a physical/analog form into a digital form. This combined with the Internet and popular file sharing tools, has made unauthorized distribution of copies of copyrighted digital media much easier. The Digital Rights Management (DRM) field was thus spawned to prevent unauthorized access to digital content. The DRM solutions exist as either proprietary products owned by companies or as open standards. Most of the implemented DRM solutions suffer mainly from interoperability issue. This could kill the competition in the market through locking the users to certain products only. In this book, a new DRM system is proposed which overcomes the interoperability issue which exists in today s DRM products. This new DRM system is called Digital Rights Unit System (DRUS).

Anbieter: Dodax
Stand: 06.08.2020
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