374,798 research outputs found
An Efficient Requirement-Aware Attachment Policy for Future Millimeter Wave Vehicular Networks
The automotive industry is rapidly evolving towards connected and autonomous
vehicles, whose ever more stringent data traffic requirements might exceed the
capacity of traditional technologies for vehicular networks. In this scenario,
densely deploying millimeter wave (mmWave) base stations is a promising
approach to provide very high transmission speeds to the vehicles. However,
mmWave signals suffer from high path and penetration losses which might render
the communication unreliable and discontinuous. Coexistence between mmWave and
Long Term Evolution (LTE) communication systems has therefore been considered
to guarantee increased capacity and robustness through heterogeneous
networking. Following this rationale, we face the challenge of designing fair
and efficient attachment policies in heterogeneous vehicular networks.
Traditional methods based on received signal quality criteria lack
consideration of the vehicle's individual requirements and traffic demands, and
lead to suboptimal resource allocation across the network. In this paper we
propose a Quality-of-Service (QoS) aware attachment scheme which biases the
cell selection as a function of the vehicular service requirements, preventing
the overload of transmission links. Our simulations demonstrate that the
proposed strategy significantly improves the percentage of vehicles satisfying
application requirements and delivers efficient and fair association compared
to state-of-the-art schemes.Comment: 8 pages, 8 figures, 2 tables, accepted to the 30th IEEE Intelligent
Vehicles Symposiu
Optimization of depth-based routing for underwater wireless sensor networks through intelligent assignment of initial energy
Underwater Wireless Sensor Networks (UWSNs) are extensively used to explore the diverse marine environment. Energy efficiency is one of the main concerns regarding performance of UWSNs. In a cooperative wireless sensor network, nodes with no energy are known as coverage holes. These coverage holes are created due to non-uniform energy utilization by the sensor nodes in the network. These coverage holes degrade the performance and reduce the lifetime of UWSNs. In this paper, we present an Intelligent Depth Based Routing (IDBR) scheme which addresses this issue and contributes towards maximization of network lifetime. In our proposed scheme, we allocate initial energy to the sensor nodes according to their usage requirements. This idea is helpful to balance energy consumption amongst the nodes and keep the network functional for a longer time as evidenced by the results provided
Predicting and improving the recognition of emotions
The technological world is moving towards more effective and friendly human computer interaction. A key factor of these emerging requirements is the ability of future systems to recognise human emotions, since emotional information is an important part of human-human communication and is therefore expected to be essential in natural and intelligent human-computer interaction. Extensive research has been done on emotion recognition using facial expressions, but all of these methods rely mainly on the results of some classifier based on the apparent expressions. However, the results of classifier may be badly affected by the noise including occlusions, inappropriate lighting conditions, sudden movement of head and body, talking, and other possible problems. In this paper, we propose a system using exponential moving averages and Markov chain to improve the classifier results and somewhat predict the future emotions by taking into account the current as well as previous emotions
Design of the Artificial: lessons from the biological roots of general intelligence
Our desire and fascination with intelligent machines dates back to the
antiquity's mythical automaton Talos, Aristotle's mode of mechanical thought
(syllogism) and Heron of Alexandria's mechanical machines and automata.
However, the quest for Artificial General Intelligence (AGI) is troubled with
repeated failures of strategies and approaches throughout the history. This
decade has seen a shift in interest towards bio-inspired software and hardware,
with the assumption that such mimicry entails intelligence. Though these steps
are fruitful in certain directions and have advanced automation, their singular
design focus renders them highly inefficient in achieving AGI. Which set of
requirements have to be met in the design of AGI? What are the limits in the
design of the artificial? Here, a careful examination of computation in
biological systems hints that evolutionary tinkering of contextual processing
of information enabled by a hierarchical architecture is the key to build AGI.Comment: Theoretical perspective on AGI (Artificial General Intelligence
Towards Intelligent Chatbots for Customer Care - Practice-Based Requirements for a Research Agenda
Chatbots bare a great potential to save efforts and costs in customer care through service automation. Current results are however still at an early stage in functionality and not widely attainable. Here, developing a new form of intelligent chatbots is a current challenge still under review. While there have been numerous proposals for future work, virtually all agenda-setting contributions are solely based on scientific literature. This is unsatisfactory from both an academic and practical perspective, as the industrial view on the future of chatbots seems to be neglected. Therefore, this work explores how professional experts see the future of intelligent chatbots for customer care and suggests how practice can guide research based on an expert panel with 17 industrial partners. Our work identifies research opportunities based on the demands and views of key practitioners by pin-pointing expected trends. Furthermore, based on the expert opinions, we derive guidelines for organizations which state key factors that should be considered in the development or adoption of chatbots in customer care
An approach to the formal specification of holonic control systems
In the manufacturing world, globalisation leads to a trend towards the reduction of batches and product life cycle, and the increase of part diversity, which are in conflict with other requirements, such as the cost reduction achieved with higher productivity. Thus, the challenge is to develop flexible, agile and intelligent management and control architectures that satisfy the referred requirements. The holonic manufacturing and the agent-based manufacturing approaches allow a new approach to the manufacturing problem, through concepts such as modularity, decentralisation, autonomy and re-use of control software components. ADACOR, one of the holonic architectures recently proposed, defines a set of autonomous and intelligent holons aiming to improve the performance of control system in industrial scenarios characterised by the frequent occurrence of unexpected disturbances. The formal modeling and validation of the specifications of the ADACOR-holons and of the interactions between these holons to implement the manufacturing control functions is of critical importance. In this paper, a formal methodology is introduced and applied to model the dynamic behaviour of the ADACOR-holon classes
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