Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. By...Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. By 2020, it is estimated that the total number of Internet-connected devices being used will be between 25 and 50 billion. As these numbers grow and technologies become more mature, the volume of data being published will increase. The technology of Internet-connected devices, referred to as Internet of Things （IoT）, continues to extend the current Internet by providing connectivity and interactions between the physical and cyber worlds. In addition to an increased volume, the IoT generates big data characterized by its velocity in terms of time and location dependency, with a variety of multiple modalities and varying data quality. Intelligent processing and analysis of this big data are the key to developing smart IoT applications. This article assesses the various machine learning methods that deal with the challenges presented by IoT data by considering smart cities as the main use case. The key contribution of this study is the presentation of a taxonomy of machine learning algorithms explaining how different techniques are applied to the data in order to extract higher level information. The potential and challenges of machine learning for IoT data analytics will also be discussed. A use case of applying a Support Vector Machine （SVM） to Aarhus smart city traffic data is presented for a more detailed exploration.展开更多
Intelligent transportation system (ITS) has become a popular research topic to meet the increased demands of transportation safety,traffic efficiency,comfort in the journey and environment protection,etc. ITS applicat...Intelligent transportation system (ITS) has become a popular research topic to meet the increased demands of transportation safety,traffic efficiency,comfort in the journey and environment protection,etc. ITS applications impose higher requirements on wireless communication systems. For example,safety-related ITS services must always be low latency and entertainment-related ITS services need high data rate. The ITS dedicated short range communications (DSRC) technology to support the safetyrelated application is still under development, while long term evolution (LTE),as the next generation mobile communication systems,offers an efficient communication platform for ITS information exchange , which can meet most ITS services requirements of latency,data rate as well as communication range. In this paper,based on the time-division duplex (TDD) mode of LTE,i.e. TD-LTE,an enhanced TD-LTE network architecture is introduced to better support safety-related ITS application with low latency requirement,and some enhanced access schemes of TD-LTE are proposed to improve the performance of supporting the high-speed IP-based ITS applications in hotspots. At last,two practical application scenarios of enhanced TD-LTE systems are given.展开更多
Oral literature transcends from orality to scribality and then textuality due to technological innovation. This paper seeks to evaluate the value of the characteristics of orality as applied by Oliver Kgadime Matsepe ...Oral literature transcends from orality to scribality and then textuality due to technological innovation. This paper seeks to evaluate the value of the characteristics of orality as applied by Oliver Kgadime Matsepe in his novel Legitaphiri （Unsolved Problem） （2008）. This will be done by taking into account the significance of self and community in a developing and changing society. It is important to note that all cultures are born from orality. However, the changes that the self and community undergo have a strong impact on the communications models within the community. This is influenced by the self and community, as the writer expresses his/her views by means of language that is based on a particular community.展开更多
文摘Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. By 2020, it is estimated that the total number of Internet-connected devices being used will be between 25 and 50 billion. As these numbers grow and technologies become more mature, the volume of data being published will increase. The technology of Internet-connected devices, referred to as Internet of Things （IoT）, continues to extend the current Internet by providing connectivity and interactions between the physical and cyber worlds. In addition to an increased volume, the IoT generates big data characterized by its velocity in terms of time and location dependency, with a variety of multiple modalities and varying data quality. Intelligent processing and analysis of this big data are the key to developing smart IoT applications. This article assesses the various machine learning methods that deal with the challenges presented by IoT data by considering smart cities as the main use case. The key contribution of this study is the presentation of a taxonomy of machine learning algorithms explaining how different techniques are applied to the data in order to extract higher level information. The potential and challenges of machine learning for IoT data analytics will also be discussed. A use case of applying a Support Vector Machine （SVM） to Aarhus smart city traffic data is presented for a more detailed exploration.
基金National Science and Technology Major Project (No.2012ZX03005010-005)
文摘Intelligent transportation system (ITS) has become a popular research topic to meet the increased demands of transportation safety,traffic efficiency,comfort in the journey and environment protection,etc. ITS applications impose higher requirements on wireless communication systems. For example,safety-related ITS services must always be low latency and entertainment-related ITS services need high data rate. The ITS dedicated short range communications (DSRC) technology to support the safetyrelated application is still under development, while long term evolution (LTE),as the next generation mobile communication systems,offers an efficient communication platform for ITS information exchange , which can meet most ITS services requirements of latency,data rate as well as communication range. In this paper,based on the time-division duplex (TDD) mode of LTE,i.e. TD-LTE,an enhanced TD-LTE network architecture is introduced to better support safety-related ITS application with low latency requirement,and some enhanced access schemes of TD-LTE are proposed to improve the performance of supporting the high-speed IP-based ITS applications in hotspots. At last,two practical application scenarios of enhanced TD-LTE systems are given.
文摘Oral literature transcends from orality to scribality and then textuality due to technological innovation. This paper seeks to evaluate the value of the characteristics of orality as applied by Oliver Kgadime Matsepe in his novel Legitaphiri （Unsolved Problem） （2008）. This will be done by taking into account the significance of self and community in a developing and changing society. It is important to note that all cultures are born from orality. However, the changes that the self and community undergo have a strong impact on the communications models within the community. This is influenced by the self and community, as the writer expresses his/her views by means of language that is based on a particular community.
