A large majority of worldwide population, such as office workers and long journey vehicle drivers, spends lot of time everyday in sedentary activities. In this paper, we speciffically focus on the assessment of differ...
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In this paper, a novel game theory based approach for task scheduling on emerging heterogeneous embeddedsystems is proposed. It relies on the auction concept to assign tasks to players, where players compete against ...
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this paper sought to investigate the most relevant criteria for determination of an embedded stereo vision system, both in the choice of the cameras and in terms of the processing platform to be used for plant phenoty...
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this paper sought to investigate the most relevant criteria for determination of an embedded stereo vision system, both in the choice of the cameras and in terms of the processing platform to be used for plant phenotyping. Since this paper is a result of a preliminary study of the real implementation itself, the main motivation was to evaluate the accuracy of the low-cost visual system's field of view and its viability for the proposed application. In addition, the real agricultural scenario was presented and studied, showing how the stereo system should be modeled to meet the accuracy and the portability requirements for using in situ machine vision in agricultural decision-making processes.
As distributed IoT applications become larger and more complex, the simple processing of raw sensor and actuation data streams becomes impractical. Instead, data streams must be fused into tangible facts and these pie...
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As distributed IoT applications become larger and more complex, the simple processing of raw sensor and actuation data streams becomes impractical. Instead, data streams must be fused into tangible facts and these pieces of information must be combined with a background knowledge to infer new bits of knowledge. And since many IoT applications require almost real-time reactivity to stimuli from the environment this information inference process has to be performed in a continuous, on-line manner. this paper proposes a new semantic model for data stream processing and real-time symbolic reasoning based on the concepts of Semantic Stream and Fact Stream, as a natural extensions of Complex Event Processing (CEP) and RDF (graph-based knowledge model). the main advantages of our approach are that: (a) it considers time as a key relation between pieces of information, (b) the processing of streams can be implemented using CEP and that (c) it is general enough to be applied to any Data Stream Management System (DSMS).
As withthe requirements of high-performance and flexible computing, reconfigurable computingsystems have become a subject of a great deal of research. Reconfigurable computingsystems have to deal with unpredictable...
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As withthe requirements of high-performance and flexible computing, reconfigurable computingsystems have become a subject of a great deal of research. Reconfigurable computingsystems have to deal with unpredictable events from the environment such as arrival of new tasks, and hardware or software failures, by adapting the task allocation and scheduling, in order to maintain the system feasibility and performance. this paper presents a novel adaptive approach to address the real-time task scheduling issue in reconfigurable multiprocessor embeddedsystems based on energy harvesting withthe consideration of system performance optimization. An energy efficient offline task mapping and scheduling algorithm is proposed to balance the workload in the multiprocessor embedded system. In order to optimize the system performance and to guarantee the system correctness in the presence of reconfiguration scenarios, a distributed control system is built to process a task migration. A cost function to evaluate the energy and time overheads of tasks migration is proposed. Extensive performance evaluations show the effectiveness of the proposed approach in terms of deadline miss ratio, and the energy gain compared withthe related state-of-the-art techniques.
the rapid growth of social media, such as twitter, provides a great opportunity for identifying and analyzing people's emotions in response to various public events, such as epidemics, terrorist attacks and politi...
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the rapid growth of social media, such as twitter, provides a great opportunity for identifying and analyzing people's emotions in response to various public events, such as epidemics, terrorist attacks and political elections. Detecting the emotions of people on different events are crucial in many applications. However, the high volume and fast pace of social media make it challenging to analyze public emotions from social media data in real-time. In this paper we propose a method to measure public emotion and predict important moments during particular public events. Given a stream of tweets, we analyze the impact of major public events, both tragic and enthusiastic ones, on public emotion. We develop a full-stack architecture that performs real-time emotion analysis on Twitter streams. We design a supervised learning approach for classifying tweets based on the type of the emotion they elicit. then we aggregate each emotion class to discover emotion-evolving patterns over time. We also propose an online approach to predict emotion-intensive moments during real-life events. Our emotion analysis methodology is shown to present a fast and robust way of analyzing online stream of tweets.
Unwholesome lifestyles can reduce lifespan by several years or even decades. therefore, raising awareness and promoting healthier behaviors prove essential to revert this dramatic panorama. Virtual coaching systems ar...
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ISBN:
(纸本)9783319675855;9783319675848
Unwholesome lifestyles can reduce lifespan by several years or even decades. therefore, raising awareness and promoting healthier behaviors prove essential to revert this dramatic panorama. Virtual coaching systems are at the forefront of digital solutions to educate people and procure a more effective health self-management. Despite their increasing popularity, virtual coaching systems are still regarded as entertainment applications with an arguable efficacy for changing behaviors, since messages can be perceived to be boring, unpersonalized and can become repetitive over time. In fact, messages tend to be quite general, repetitive and rarely tailored to the specific needs, preferences and conditions of each user. In the light of these limitations, this work aims at help building a new generation of methods for automatically generating user-tailored motivational messages. While the creation of messages is addressed in a previous work, in this paper the authors rather present a method to automatically extract the semantics of motivational messages and to create the ontological representation of these messages. the method uses first natural language processing to perform a linguistic analysis of the message. the extracted information is then mapped to the concepts of the motivational messages ontology. the proposed method could boost the quantity and diversity of messages by automatically mining and parsing existing messages from the internet or other digitised sources, which can be later tailored according to the specific needs and particularities of each user.
For customers of cloud-computing platforms it is important to minimize the infrastructure footprint and associated costs while providing required levels of Quality of Service (QoS) and Quality of Experience (QoE) dict...
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For customers of cloud-computing platforms it is important to minimize the infrastructure footprint and associated costs while providing required levels of Quality of Service (QoS) and Quality of Experience (QoE) dictated by the Service Level Agreement (SLA). To assist withthat cloud service providers are offering: (1) horizontal resource scaling through provisioning and destruction of virtual machines and containers, (2) vertical scaling through changing the capacity of individual cloud nodes. Existing scaling solutions mostly concentrate on low-level metrics like CPU load and memory consumption which doesn’t always correlate withthe level of SLA conformity. Such technical measures should be preprocessed and viewed from a higher level of abstraction. Application level metrics should also be considered when deciding upon scaling the cloud-based solution. Existing scaling platforms are mostly proprietary technologies owned by cloud service providers themselves or by third parties and offered as Software as a Service. Enterprise applications could span infrastructures of multiple public and private clouds, dictating that the auto-scaling solution should not be isolated inside a single cloud infrastructure. the goal of this paper is to address the challenges above by presenting the architecture of Auto-scaling and Adjustment Platform for Cloud-based systems (ASAPCS). It is based on open-source technologies and supports integration of various low and high level performance metrics, providing higher levels of abstraction for design of scaling algorithms. ASAPCS can be used with any cloud service provider and guarantees that move from one cloud platform to another will not result in complete redesign of the scaling algorithm. ASAPCS itself is horizontally scalable and can process large amounts of real-time data which is particularly important for applications developed following the microservices architectural style. ASAPCS approaches the scaling problem in a nonstandar
Transportable nodes in a healthy and demanding network set-up of Mobile Adhoc Network (MANET) are self-governing with self-configurable potential due to high occurrence of topology alteration and changeable rescheduli...
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ISBN:
(纸本)9781509027187
Transportable nodes in a healthy and demanding network set-up of Mobile Adhoc Network (MANET) are self-governing with self-configurable potential due to high occurrence of topology alteration and changeable rescheduling of the network mechanism during data communication. Due to simplicity of set up, the energetic networking system in MANET is very victorious in conditions where it is complicated to create communications system and infrastructure based network. Numerous routing protocols for MANETs accompanying realtimeapplications have been developed, basic intention being optimal consumption of resource in resource limited situation, least power utilization using limited battery power of the highly short-lived mobile nodes and victorious realtime data broadcast within their deadline. this paper presents an efficient Quality of Service architecture using inter layer communication with a highly efficient realtime scheduler design at the network layer with improved RMA (Rate Monotonic Algorithm) and EDF(Earliest Deadline First) scheduling that efficiently schedules multiple realtimeapplications without missing any of their deadline. Simulation results in NetSim ver 8 ensures healthier network performance in terms of better jitter, packet delivery ratio and network lifetime when compared with other similar Cross layer based approaches for video file transmission.
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