Suchergebnisse

Intro -- Preface -- Organization -- Contents -- Artificial Intelligence and Data Science Track -- A Novel Method of Pre-processing Using Dental X-Ray Images by Adaptive Morpho Histo Wavelet Denoising (AMHW) Method -- Abstract -- 1 Introduction -- 2 Proposed Work -- 3 Result and Discussion -- 3.1 Adaptive Morpho - Histo Wavelet Denoising (AMHW) -- 4 Conclusion -- References -- Knowledge Based System for Diagnosis and Treatment of Mango Diseases -- Abstract -- 1 Introduction -- 2 Statement of the Problem -- 3 Objective of the Study -- 3.1 General Objective -- 3.2 Specific Objectives -- 4 Scope of the Study -- 5 Significance of the Study -- 6 Methodology of the Study -- 6.1 Research Design -- 6.2 Sources of Data and Data Collection Methods -- 6.3 Knowledge Modeling and Representation Method -- 6.4 KBS Implementation Tool -- 7 Implementation and Experimentations -- 7.1 Architecture of the Proposed Prototype -- 8 Testing and Evaluation of the Prototype System -- 9 Conclusion and Recommendation -- 9.1 Conclusion -- 9.2 Recommendation -- References -- A Genetic Algorithm-Based Approach for Test Case Prioritization -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Proposed Algorithm -- 3.1 Initial Population -- 3.2 Selection -- 3.3 Crossover -- 3.4 Mutation -- 3.5 Fitness Function -- 4 Proposed Model -- 5 Experiment and Results -- 5.1 Research Questions -- 5.2 Experiment to Evaluate APDF of the Different Subject Program Using Random and GA Based Technique -- 5.3 Experiment to Evaluate the Execution Time (Time Complexity) with Different Chromosome Length and Number of Generations -- 6 Conclusion -- References -- Stationary Wavelet Transform for Automatic Epileptic Seizure Detection -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Signal Decomposition -- 2.3 Feature Extraction -- 2.4 Classifying Seizures -- 3 Results and Discussion.

In this article, an incubator platform concept is presented to demonstrate the authors' approach in meeting the enormous challenges faced by future multidisciplinary research and education. The abstraction level of laboratory projects needs to be raised to a level where the researchers and students have the opportunity to deal with hands-on real-life system-level problems and decisions, while simultaneously various fundamental key technologies of the information society are integrated into the systems. Their approach is concretized by an Incubator experimental platform. Facilitated by this environment, researchers, engineers and students can join their efforts in developing next-generation products in a well-organized manner. The targeted products must meet the increasingly important special characteristics required for the digital era – self- and context-awareness, built-in information security, distributed networking, enormous scalability and device interoperability. Many projects are today developed by distributed multicultural teams, so it is a necessity that the development can also be implemented in co-operation of several universities in different countries, in order to promote the career skills of the students. The incubator platform proposed in this article is able to provide viable answers and solutions to all the mentioned challenges in engineering research and education, coupling the curriculum tightly to top-class academic research.