Browsing by Author "Yi, Long"

Now showing 1 - 7 of 7
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    Automatic voice relay with open source Kiara
    (Telkom, 2009) Yi, Long; Tucker, William David
    One way for Deaf people to communicate with hearing people over the telephone is to use a voice relay. The service is often provided with a human relay operator that relays text into voice, and vice versa, on behalf of the Deaf and hearing users. In developed countries, voice relay is frequently subsidised by governments or service providers. There is no such service in South Africa. We have built several automatic voice relay systems for a disadvantaged Deaf community in Cape Town. This paper describes how we augmented a general-purpose communication system for voice relay. Kiara is a fully open source Instant Messaging, voice and video over Internet Protocol communication system based on the Session Initiation Protocol. We integrated automatic speech recognition and text-to-speech technologies into Kiara to provide real-time automatic voice relay for relayed communication. As it stands, Kiara can also be used for standard voice and video relay with a human operator.
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    Developing reproducible bioinformatics analysis workflows for heterogeneous computing environments to support African genomics
    (Springer Nature, 2018) Baichoo, Shakuntala; Bendou, Hocine; de Beste, Eugene; Yi, Long
    Background: The Pan-African bioinformatics network, H3ABioNet, comprises 27 research institutions in 17 African countries. H3ABioNet is part of the Human Health and Heredity in Africa program (H3Africa), an African-led research consortium funded by the US National Institutes of Health and the UK Wellcome Trust, aimed at using genomics to study and improve the health of Africans. A key role of H3ABioNet is to support H3Africa projects by building bioinformatics infrastructure such as portable and reproducible bioinformatics workflows for use on heterogeneous African computing environments. Processing and analysis of genomic data is an example of a big data application requiring complex interdependent data analysis workflows. Such bioinformatics workflows take the primary and secondary input data through several computationally-intensive processing steps using different software packages, where some of the outputs form inputs for other steps. Implementing scalable, reproducible, portable and easy-to-use workflows is particularly challenging. Results: H3ABioNet has built four workflows to support (1) the calling of variants from high-throughput sequencing data; (2) the analysis of microbial populations from 16S rDNA sequence data; (3) genotyping and genome-wide association studies; and (4) single nucleotide polymorphism imputation. A week-long hackathon was organized in August 2016 with participants from six African bioinformatics groups, and US and European collaborators. Two of the workflows are built using the Common Workflow Language framework (CWL) and two using Nextflow. All the workflows are containerized for improved portability and reproducibility using Docker, and are publicly available for use by members of the H3Africa consortium and the international research community. Conclusion: The H3ABioNet workflows have been implemented in view of offering ease of use for the end user and high levels of reproducibility and portability, all while following modern state of the art bioinformatics data processing protocols. The H3ABioNet workflows will service the H3Africa consortium projects and are currently in use. All four workflows are also publicly available for research scientists worldwide to use and adapt for their respective needs. The H3ABioNet workflows will help develop bioinformatics capacity and assist genomics research within Africa and serve to increase the scientific output of H3Africa and its Pan-African Bioinformatics Network.
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    KernTune: self-tuning Linux kernel performance using support vector machines
    (University of the Western Cape, 2006) Yi, Long; Connan, James; Dept. of Computer Science; Faculty of Science
    Self-tuning has been an elusive goal for operating systems and is becoming a pressing issue for modern operating systems. Well-trained system administrators are able to tune an operating system to achieve better system performance for a specific system class. Unfortunately, the system class can change when the running applications change. The model for self-tuning operating system is based on a monitor-classify-adjust loop. The idea of this loop is to continuously monitor certain performance metrics, and whenever these change, the system determines the new system class and dynamically adjusts tuning parameters for this new class. This thesis described KernTune, a prototype tool that identifies the system class and improves system performance automatically. A key aspect of KernTune is the notion of Artificial Intelligence oriented performance tuning. Its uses a support vector machine to identify the system class, and tunes the operating system for that specific system class. This thesis presented design and implementation details for KernTune. It showed how KernTune identifies a system class and tunes the operating system for improved performance.
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    KernTune: Self-tuning Linux Kernel Performance Using Support Vector Machines
    (University of the Western Cape, 2006) Yi, Long; Connan, James
    Self-tuning has been an elusive goal for operating systems and is becoming a pressing issue for modern operating systems. Well-trained system administrators are able to tune an operating system to achieve better system performance for a specific system class. Unfortunately, the system class can change when the running applications change. Our model for self-tuning operating system is based on a monitor-classify- adjust loop. The idea of this loop is to continuously monitor certain performance metrics, and whenever these change, the system determines the new system class and dynamically adjusts tuning parameters for this new class. This thesis describes KernTune, a prototype tool that identifies the system class and improves system performance automatically. A key aspect of KernTune is the notion of Artificial Intelligence (AI) oriented performance tuning. It uses a support vector machine (SVM) to identify the system class, and tunes the operating system for that specific system class. This thesis presents design and implementation details for KernTune. It shows how KernTune identifies a system class and tunes the operating system for improved performance.
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    KernTune: Self-tuning Linux kernel performance using support vector machines
    (Association for Computing Machinery, 2007) Yi, Long; Connan, James
    Self-tuning has been an elusive goal for operating systems and is becoming a pressing issue for modern operating systems. Well-trained system administrators are able to tune an operating system to achieve better system performance for a specific system class. Unfortunately, the system class can change when the running applications change. Our model for self-tuning operating system is based on a monitor-classify-adjust loop. The idea of this loop is to continuously monitor certain performance metrics, and whenever these change, the system determines the new system class and dynamically adjusts tuning parameters for this new class. This paper describes KernTune, a prototype tool that identifies the system class and improves system performance automatically. A key aspect of KernTune is the notion of Artificial Intelligence (AI) oriented performance tuning. It uses a support vector machine (SVM) to identify the system class, and tunes the operating system for that specific system class. This paper presents design and implementation details for KernTune. It shows how KernTune identifies a system class and tunes the operating system for improved performance.
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    Kiara: an open source SIP system to support Deaf telephony
    (Telkom, 2008) Yi, Long; Tucker, William David
    This paper describes Kiara, an open source SIPbased communication system that provides the building blocks to enable Deaf relay services. We have implemented a prototype that provides real-time text, voice and video to a variety of end user devices over a variety of networks. The work-in-progress concerns the addition of relay services for the Deaf.
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    Self-tuning Linux Kernel Performance Using Support Vector Machines
    (University of the Western Cape, 2006) Yi, Long; Connan, James
    In this chapter, we provide the motivation and background behind the automatic optimisation of an operating system. We begin with a discussion of some of the difficulties of automatic operating system optimisation and the benefits of automatic optimisation technology which inspired our research. We then describe the research problem and aims. Thereafter, our approach and methodology are explained. Finally, the organisation of the thesis and summary are presented. 1.1 Background and Motivation In today's networking world, a mission-critical server requires consistently good performance [2] . To this end, almost all operating systems which run on such a critical server are managed by system administrators who should be skillful and experienced in tuning operating systems by adjusting system configuration and performance parameters of the operating system to run a specific system workload. This involves system capacity planning, performance metrics, workload characteristics, system settings, etc. Skillful system administrators are scarce and expensive. As computer hardware becomes cheaper and free critical computer software becomes more viable, e.g., Linux, Samba, Mysql, Apache, the total cost of ownership for building and maintaining a mission-critical server becomes more and more dominated by the cost of human resources. Furthermore, with the increasing number of new applications and services, a modern operating system offers more system parameters with larger ranges for more system classes than ever before. This situation serves as our motivation for a new generation of automatic optimisation technology for operating systems. The potential benefits of the automatic optimisation technology will be amplified as future applications and operating systems become more complex.