A PC Cluster High-Fidelity Mobile Crane Simulator

[[abstract]]The mobile crane simulator is a project sponsored by Employment and Vocational Training Administration, Council of Labor Affair, Executive Yuan, Taiwan, to build a safe device for training and licensing. This paper presents the principle and mechanism to build a high-fidelity interactive visual simulator on a cluster of PCs. The implemented mobile crane simulator uses the peer-to-peer architecture with the push and pull mechanism to achieve the parallelism among distributed tasks. A distributive simulation socket, called Communication Backbone(CB), is adopted to integrate the functional tasks of the mobile crane simulator in a PC clustering environment. With CB, tasks of the simulated mobile crane are executed as standalone applications and seamlessly communicate with each other through CB. Finally, the system response rate of the implemented mobile crane simulator achieves 16 times per second which is larger than human acceptable perception rate as suggested by the human factors studies.[[abstract]]The mobile crane simulator is a project sponsored by Employment and Vocational Training Administration, Council of Labor Affair, Executive Yuan, Taiwan, to build a safe device for training and licensing. This paper presents the principle and mechanism to build a high-fidelity interactive visual simulator on a cluster of PCs. The implemented mobile crane simulator uses the peer-to-peer architecture with the push and pull mechanism to achieve the parallelism among distributed tasks. A distributive simulation socket, called Communication Backbone(CB), is adopted to integrate the functional tasks of the mobile crane simulator in a PC clustering environment. With CB, tasks of the simulated mobile crane are executed as standalone applications and seamlessly communicate with each other through CB. Finally, the system response rate of the implemented mobile crane simulator achieves 16 times per second which is larger than human acceptable perception rate as suggested by the human factors studies

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

An intuitive control space for material appearance

Many different techniques for measuring material appearance have been proposed in the last few years. These have produced large public datasets, which have been used for accurate, data-driven appearance modeling. However, although these datasets have allowed us to reach an unprecedented level of realism in visual appearance, editing the captured data remains a challenge. In this paper, we present an intuitive control space for predictable editing of captured BRDF data, which allows for artistic creation of plausible novel material appearances, bypassing the difficulty of acquiring novel samples. We first synthesize novel materials, extending the existing MERL dataset up to 400 mathematically valid BRDFs. We then design a large-scale experiment, gathering 56,000 subjective ratings on the high-level perceptual attributes that best describe our extended dataset of materials. Using these ratings, we build and train networks of radial basis functions to act as functionals mapping the perceptual attributes to an underlying PCA-based representation of BRDFs. We show that our functionals are excellent predictors of the perceived attributes of appearance. Our control space enables many applications, including intuitive material editing of a wide range of visual properties, guidance for gamut mapping, analysis of the correlation between perceptual attributes, or novel appearance similarity metrics. Moreover, our methodology can be used to derive functionals applicable to classic analytic BRDF representations. We release our code and dataset publicly, in order to support and encourage further research in this direction

Green inter-cluster interference management in uplink of multi-cell processing systems

This paper examines the uplink of cellular systems employing base station cooperation for joint signal processing. We consider clustered cooperation and investigate effective techniques for managing inter-cluster interference to improve users' performance in terms of both spectral and energy efficiency. We use information theoretic analysis to establish general closed form expressions for the system achievable sum rate and the users' Bit-per-Joule capacity while adopting a realistic user device power consumption model. Two main inter-cluster interference management approaches are identified and studied, i.e., through: 1) spectrum re-use; and 2) users' power control. For the former case, we show that isolating clusters by orthogonal resource allocation is the best strategy. For the latter case, we introduce a mathematically tractable user power control scheme and observe that a green opportunistic transmission strategy can significantly reduce the adverse effects of inter-cluster interference while exploiting the benefits from cooperation. To compare the different approaches in the context of real-world systems and evaluate the effect of key design parameters on the users' energy-spectral efficiency relationship, we fit the analytical expressions into a practical macrocell scenario. Our results demonstrate that significant improvement in terms of both energy and spectral efficiency can be achieved by energy-aware interference management

Quality of service differentiation for multimedia delivery in wireless LANs

Delivering multimedia content to heterogeneous devices over a variable networking environment while maintaining high quality levels involves many technical challenges. The research reported in this thesis presents a solution for Quality of Service (QoS)-based service differentiation when delivering multimedia content over the wireless LANs. This thesis has three major contributions outlined below: 1. A Model-based Bandwidth Estimation algorithm (MBE), which estimates the available bandwidth based on novel TCP and UDP throughput models over IEEE 802.11 WLANs. MBE has been modelled, implemented, and tested through simulations and real life testing. In comparison with other bandwidth estimation techniques, MBE shows better performance in terms of error rate, overhead, and loss. 2. An intelligent Prioritized Adaptive Scheme (iPAS), which provides QoS service differentiation for multimedia delivery in wireless networks. iPAS assigns dynamic priorities to various streams and determines their bandwidth share by employing a probabilistic approach-which makes use of stereotypes. The total bandwidth to be allocated is estimated using MBE. The priority level of individual stream is variable and dependent on stream-related characteristics and delivery QoS parameters. iPAS can be deployed seamlessly over the original IEEE 802.11 protocols and can be included in the IEEE 802.21 framework in order to optimize the control signal communication. iPAS has been modelled, implemented, and evaluated via simulations. The results demonstrate that iPAS achieves better performance than the equal channel access mechanism over IEEE 802.11 DCF and a service differentiation scheme on top of IEEE 802.11e EDCA, in terms of fairness, throughput, delay, loss, and estimated PSNR. Additionally, both objective and subjective video quality assessment have been performed using a prototype system. 3. A QoS-based Downlink/Uplink Fairness Scheme, which uses the stereotypes-based structure to balance the QoS parameters (i.e. throughput, delay, and loss) between downlink and uplink VoIP traffic. The proposed scheme has been modelled and tested through simulations. The results show that, in comparison with other downlink/uplink fairness-oriented solutions, the proposed scheme performs better in terms of VoIP capacity and fairness level between downlink and uplink traffic

Belle II Technical Design Report

The Belle detector at the KEKB electron-positron collider has collected almost 1 billion Y(4S) events in its decade of operation. Super-KEKB, an upgrade of KEKB is under construction, to increase the luminosity by two orders of magnitude during a three-year shutdown, with an ultimate goal of 8E35 /cm^2 /s luminosity. To exploit the increased luminosity, an upgrade of the Belle detector has been proposed. A new international collaboration Belle-II, is being formed. The Technical Design Report presents physics motivation, basic methods of the accelerator upgrade, as well as key improvements of the detector.Comment: Edited by: Z. Dole\v{z}al and S. Un

Learning, Categorization, Rule Formation, and Prediction by Fuzzy Neural Networks

National Science Foundation (IRI 94-01659); Office of Naval Research (N00014-91-J-4100, N00014-92-J-4015) Air Force Office of Scientific Research (90-0083, N00014-92-J-4015

Development of statistical and computational methods to estimate functional connectivity and topology in large-scale neuronal assemblies

One of the most fundamental features of a neural circuit is its connectivity since the single neuron activity is not due only to its intrinsic properties but especially to the direct or indirect influence of other neurons1. It is fundamental to elaborate research strategies aimed at a comprehensive structural description of neuronal interconnections as well as the networks\u2019 elements forming the human connectome. The connectome will significantly increase our understanding of how functional brain states emerge from their underlying structural substrate, and will provide new mechanistic insights into how brain function is affected if this structural substrate is disrupted. The connectome is characterized by three different types of connectivity: structural, functional and effective connectivity. It is evident that the final goal of a connectivity analysis is the reconstruction of the human connectome, thus, the application of statistical measures to the in vivo model in both physiological and pathological states. Since the system under study (i.e. brain areas, cell assemblies) is highly complex, to achieve the purpose described above, it is useful to adopt a reductionist approach. During my PhD work, I focused on a reduced and simplified model, represented by neural networks chronically coupled to Micro Electrodes Arrays (MEAs). Large networks of cortical neurons developing in vitro and chronically coupled to MEAs2 represent a well-established experimental model for studying the neuronal dynamics at the network level3, and for understanding the basic principles of information coding4 learning and memory5. Thus, during my PhD work, I developed and optimized statistical methods to infer functional connectivity from spike train data. In particular, I worked on correlation-based methods: cross-correlation and partial correlation, and information-theory based methods: Transfer Entropy (TE) and Joint Entropy (JE). More in detail, my PhD\u2019s aim has been applying functional connectivity methods to neural networks coupled to high density resolution system, like the 3Brain active pixel sensor array with 4096 electrodes6. To fulfill such an aim, I re-adapted the computational logic operations of the aforementioned connectivity methods. Moreover, I worked on a new method based on the cross-correlogram, able to detect both inhibitory and excitatory links. I called such an algorithm Filtered Normalized Cross-Correlation Histogram (FNCCH). The FNCCH shows a very high precision in detecting both inhibitory and excitatory functional links when applied to our developed in silico model. I worked also on a temporal and pattern extension of the TE algorithm. In this way, I developed a Delayed TE (DTE) and a Delayed High Order TE (DHOTE) version of the TE algorithm. These two extension of the TE algorithm are able to consider different temporal bins at different temporal delays for the pattern recognition with respect to the basic TE. I worked also on algorithm for the JE computation. Starting from the mathematical definition in7, I developed a customized version of JE capable to detect the delay associated to a functional link, together with a dedicated shuffling based thresholding approach. Finally, I embedded all of these connectivity methods into a user-friendly open source software named SPICODYN8. SPICODYN allows the user to perform a complete analysis on data acquired from any acquisition system. I used a standard format for the input data, providing the user with the possibility to perform a complete set of operations on the input data, including: raw data viewing, spike and burst detection and analysis, functional connectivity analysis, graph theory and topological analysis. SPICODYN inherits the backbone structure from TOOLCONNECT, a previously published software that allowed to perform a functional connectivity analysis on spike trains dat