Over the last ten years, there has been significant progress in the use of low-rate speech coders in voice applications for computers, military communications, and civil communications. This advancement has been made ...
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Over the last ten years, there has been significant progress in the use of low-rate speech coders in voice applications for computers, military communications, and civil communications. This advancement has been made possible by the development of new speech coders that can generate high-quality speech at low data rates. The majority of existing coders include spectral representation of speech, speech waveform matching, and ”optimization” of the coder’s performance for human hearing. The goal of this paper is to provide a thorough evaluation of voice coding methods for educational purposes, with a particular emphasis on the algorithms used in low-rate cellular communication standards. The algorithm we developed using a voice-excited LPC vocoder produces clear, low-distortion results. Ordinary LPCs, on the other hand, fall short of vocoders because they can handle signals other than speech, such as music. To improve quality, additional bandwidth is used to reduce the bit rate. To improve the quality, we tried two approaches. The first was to increase the number of bits required to quantize the DCT coefficients. This coefficient would outperform the inverse DCT in closer error rearrangements. The second possibility is to increase the total number of quantized coefficients. As a result, error array rearrangements would be more accurate. The goal is to identify the point at which a method improvement outperforms the previous, better result. Other coding methods become more complex, but this vocoder suffices.
Insertion is one of the basic operations in DNA computing. Based on this operation, an evolutionary computation model, the insertion system, was defined. For the above defined evolutionary computation model, varying l...
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作者：
B. BhaskerS. MuraliResearch Scholar
School of Computer Science and Engineering Vellore Institute of Technology Vellore Tamil Nadu India Associate Professor
School of Computer Science and Engineering Vellore Institute of Technology Vellore Tamil Nadu India
Extensive and exhaustive water utilization for agriculture, industries and ground water consumption for domestic purposes has heavily deterioted the water bodies. Cloud and sensor technology is widely deployed in a se...
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Extensive and exhaustive water utilization for agriculture, industries and ground water consumption for domestic purposes has heavily deterioted the water bodies. Cloud and sensor technology is widely deployed in a several real-time applications, especially in agriculture. The transformation of data obtained from large sensor networks into a valuable knowledge and assests for applications can effectively leverage the techniques like Cloud Computing (CC). In CC, scheduling the workflow is the major concern that focuses on comprehensive execution of workflows without compromising the Quality of Service (QoS). But workflow scheduling augmented with resource allocation is extremely challenging task because of its inherent computational intensity, task dependencies, and heterogeneous cloud resources. In this article, a novel Optimum Energy and Resource Aware Workflow Scheduling (OERES) scheme that is motivated by popular Fuzzy Membership Mutation Elephant Herding Optimization (FMMEHO) algorithm is proposed, that aims to schedule the task workflow to Virtual Machines (VMs) that are involved in computation. This also concentrates on dynamically deploying and un-deploying the VMs pertaining to the task requirements. The FMMEHO algorithm is a popular nature inspired technique, which is rooted on herding patterns of the giant mammals, the elephants. This algorithm employs a clan operator that updates the location and distance of elephants depending resource and energy usage of each clan in the context of matriarch elephant. The proposed OERES schema elevates the resource utilization and simultaneously mitigates the energy usage without compromising the dependency and deadline constraints. This work uses the famous Cloud Sim simulator to simulate the underlying cloud environment to investigate the effectiveness of proposed model. The efficacy of the scheduling methods is examined based on important parameters like mean Resource Utilization (RU), Energy utilization or Consumpti
This book constitutes refereed proceedings of the 4th International Conference on Recent Trends in Advanced Computing - computer Vision and Machine Intelligence Paradigms for Sustainable Development Goals. This book c...
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ISBN:
(数字)9789811971693
ISBN:
(纸本)9789811971686;9789811971716
This book constitutes refereed proceedings of the 4th International Conference on Recent Trends in Advanced Computing - computer Vision and Machine Intelligence Paradigms for Sustainable Development Goals. This book covers novel and state-of-the-art methods in computer vision coupled with intelligent techniques including machine learning, deep learning, and soft computing techniques. The contents of this book will be useful to researchers from industry and academia. This book includes contemporary innovations, trends, and concerns in computer vision with recommended solutions to real-world problems adhering to sustainable development from researchers across industry and academia. This book serves as a valuable reference resource for academics and researchers across the globe.
The book presents advancements in computational intelligence in perception with healthcare applications. Besides, the concepts, theory, and applications in various domains of healthcare systems including decision maki...
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ISBN:
(数字)9789819988532
ISBN:
(纸本)9789819988525;9789819988556
The book presents advancements in computational intelligence in perception with healthcare applications. Besides, the concepts, theory, and applications in various domains of healthcare systems including decision making in healthcare management, disease diagnosis, and electronic health records will be presented in a lucid manner. To achieve these objectives, both theoretical advances and its applications to healthcare problems will be stressed upon. This has been done to make the edited book more flexible and to stimulate further research interest in topics. The book is divided into four sections such as theoretical foundation of computational intelligence techniques, computational intelligence in analyzing health data, computational intelligence in electronic health record (EHR), and computational intelligence in ethical issues in health care.
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