Hybrid Architecture

High Performance Computing (HPC) applications are mapped to a cluster of multi-core processors communicating using high speed interconnects. More computational power is harnessed with the addition of hardware accelerators such as Graphics Processing Unit (GPU) cards and Field Programmable Gate Arrays (FPGAs). Particle Image Velocimetry (PIV) is an embarrassingly parallel application that can benefit from acceleration using hybrid architectures. The PIV application is mapped to a Nvidia GPU system, resulting in 3x speedup over a dual quad-core Intel processor implementation. The design methodology used to implement the PIV application on a specialized FPGA platform under development is described in brief and the resulting performance benefit is analyzed.

Hamburg sold off large swathes of urban real estate to the highest bidder in a move to build more shiny office towers and luxury apartment blocks. This process includes printing building licenses for private owners with similar intentions, particularly in disadvantaged inner city areas. The results were self-evident as rents around city-center rose to astronomical new levels and especially in former working-class or derelict inner city areas. New housing was also planned for densification of existing residential areas in a move that did nothing to mitigate the problem of soaring rents. In the past 17 years, numbers of public housing in Hamburg has dropped by over 50% (from around 210,000 units to just over 100,000). Hamburg ended 2011 with %8 office vacancy rate, with just over a million square meters of vacant space in the city. The average price for office rentals increased %11.5 from 2010. Still, the stock of public housing in St. Pauli has not changed much over the past decade. The neighborhood had 2,027 in 2010. This policy that was applied on the city for almost two decades had lots of noticeable changes on city fabric itself next to those economic consequences. All new construction had spoilt neighborhood character and destroyed Hamburg's cultural landscapes. The mutation of public spaces and streets into a 'Series of Shop Windows' serviced a different lifestyle which has nothing to do with general habits of area. People were indeed asking themselves -which was preferablea city or car parks ever more glitz or a city of affordable urban spaces but not in a way that transform their city to "another place".

Real-time crowd motion planning requires fast, realistic methods for path planning as well as obstacle avoidance. In a previous work (Morini et al. in Cyberworlds International Conference, pp. 144-151, 2007), we introduced a hybrid architecture to handle real-time motion planning of thousands of pedestrians. In this article, we present an extended version of our architecture, introducing two new features: an improved short-term collision avoidance algorithm, and simple efficient group behavior for crowds. Our approach allows the use of several motion planning algorithms of different precision for regions of varied interest. Pedestrian motion continuity is ensured when switching between such algorithms. To assess our architecture, several performance tests have been conducted, as well as a subjective test demonstrating the impact of using groups. Our results show that the architecture can plan motion in real time for several thousands of characters.

Independent Grid projects have developed their own solutions to Information Services. These solutions are not interoperable with each other, target vastly different systems and address diverse sets of requirements. To address these challenges, we designed a novel architecture for a Grid Information Service that provides unification, federation and interoperability of major grid information services. The proposed approach forms an add-on information system that interacts with the local information services and assembles their metadata instances under one hybrid architecture. We present our experiences in designing semantics and architectural design of this system. We introduce a prototype implementation and present its evaluation. The results indicate that the proposed approach achieves unification and federation of custom implementations of grid information services with negligible processing overheads.

This paper presents a novel hybrid encoding method for encoding of low-density parity-check (LDPC) codes. The design approach is applied to design 10-Gigabit Ethernet transceivers over copper cables. For a specified encoding speed, the proposed method requires substantially lower complexity in terms of area and storage. Furthermore, this method is generic and can be adapted easily for other LDPC codes. One major advantage of this design is that it does not require column swapping and it maintains compatibility with optimized LDPC decoders. For a 10-Gigabit Ethernet transceiver which is compliant with the IEEE 802.3 an standard, the proposed sequential (5-Parallel) hybrid architecture has the following implementation properties: critical path: (log2(324) + 1)Txor + Tand, number of XOR gates: 11 056, number of and gates: 1620, and ROM storage: 104 976 bits (which can be minimized to 52 488 bits using additional hardware). This method achieves comparable critical path, and requires 74%...

This is a short essay dedicated to issues of Chronotopia within the umbrella of the 15-minute city. The collection is arranged by Prof. Carlos Moreno, Scientific director and co-founder of the ETI Chair (Université Paris 1 Panthéon-Sorbonne).

Infrastructural Duality focuses on the temporal uses of infrastructural spaces as hybrid programmable environments. For a 15-minute city, the aim of this essay it to discuss the optimization of urban frameworks with services and amenities in order to produce a vibrant city.

While modernist slab-housing dominated the reconstruction of war-torned European cities, the typology was quickly associated with a welfare agenda for social housing and eventually dismissed as the preferred building stock. Yet in Seoul, due to its rapid population increase, slab-housing became the domineering typology controlling the metropolitan skyline. These were rapidly built in blocks of two-thousand units at a time, which would eventually produce mono-functional urban islands.
As Seoul transitions into the 4th industrial revolution and an aging society, the slab-housing typology will not meet the needs for future generations. Interconnectedness is needed in order to facilitate productivity and social innovation as the majority of the workforce will retire. New typologies of housing hybrids will be needed to provide services, amenities and social interaction between the different demographic groups. This essay looks at a pedagogical experiment for a housing studio to achieve such outcomes.

Organic-inorganic hybrid materials do not represent only a creative alternative to design new materials and compounds for academic research, but their improved or unusual features allow the development of innovative industrial applications. Nowadays, most of the hybrid materials that have already entered the market are synthesised and processed by using conventional soft chemistry based routes developed in the eighties. These processes are based on: a) the copolymerisation of functional organosilanes, macromonomers, and metal alkoxides, b) the encapsulation of organic components within sol-gel derived silica or metallic oxides, c) the organic functionalisation of nanofillers, nanoclays or other compounds with lamellar structures, etc. The chemical strategies (self-assembly, nanobuilding block approaches, hybrid MOF (Metal Organic Frameworks), integrative synthesis, coupled processes, bio-inspired strategies, etc.) offered nowadays by academic research allow, through an intelligent tuned coding, the development of a new vectorial chemistry, able to direct the assembling of a large variety of structurally well defined nano-objects into complex hybrid architectures hierarchically organised in terms of structure and functions. Looking to the future, there is no doubt that these new generations of hybrid materials, born from the very fruitful activities in this research field, will open a land of promising applications in many areas:

Concurrent with the rapid development of both dendrimers and hyperbranched polymers, a novel class of block copolymer architectures has emerged from the combination of these dendritic architectures with linear chains, the "linear-dendritic block copolymers" (LDBCs). This review gives a comprehensive summary of the state of the art in this rapidly developing field from pioneering early work to promising recent approaches.The different strategies leading to these hybrid architectures with either perfect dendrimer/dendron building blocks or imperfect, yet more conveniently accessible hyperbranched segments, are reviewed and compared. The consequences of the unusual polymer topology for supramolecular structures both in solution and in the solid state are summarized, and important differences in comparison with classical linear block copolymer structures are highlighted. Current challenges in the area of block copolymers, nanotechnology and potential applications of linear-dendritic block copolymers are also considered.

In this paper, the main role of satellite systems in hybrid satellite/terrestrial networks will be highlighted, as well as the main functions which should be performed to optimize the performance of these hybrid networks. Then, some typical services believed to occupy a great portion of the future telecommunication service market and benefiting from these hybrid architectures will be presented. Generally speaking, the list of hybrid architectures presented in this paper is not exhaustive but reflects the main work carried out in the institute of communications and navigation of DLR and in the framework of the Satellite Communications Network of Excellence "SatNEx" subsidized by the European Union, more accurately in the focus topic "Hybrid broadband network architectures" of the Joint Activity 2130 "Broadband Access Network". The critical issues related to hybrid satellite/terrestrial architectures will be identified and analyzed all along this paper and illustrated by selected realistic examples.

Driven by rapid ongoing advances in computer hardware, neuroscience and computer science, Artificial Brain research and development are blossoming. This article constitutes the first half of a two-part world survey of artificial brain projects: this part dealing with large-scale brain simulations, and the second part with biologically inspired cognitive architectures (BICAs). The large-scale brain simulations we consider in depth here include those by Markram, Modha, Boahen, Horwitz, Edelman, Izhikevich, and Just. As well as reviewing the particulars of these simulation projects, we position them in a broader perspective, comparing at the different underlying definitions of the concept of ''simulation,'' noting that in many ways the projects are modeling neurosystems at different levels as well as using different methodologies.

Medical billing is a complex, dynamic, knowledge oriented process. To avoid claim rejections almost all of the leading companies with their business related to medical billing/ medical claim processing provide some sort of claim scrubbing software tools. This research is a comparative study of two claim scrubbing tools developed at a USA based medical billing company. Although both the tools have same purpose of medical claim scrubbing but their implementation methodology is different. One is conventional software based on stored procedures and functions; we name it simply 'Medical Claim Scrubber'. And other has been developed using rule based systems concepts; so we name it 'A Rule Based System'. This paper presents strong and weak points of both the tools. A new hybrid design has also been proposed, which combines both of them. Currently this hybrid architecture has been proposed for medical billing domain, but it can be applied to virtually any domain of real life where complex, dynamic, knowledge oriented edits are required to be implemented.

This paper describes an engineering approach toward implementing the current neuroscientific understanding of how the primate brain fuses, or integrates, 'information' in the decision-making process. We describe a System of Systems (SoS) design for improving the overall performance, capabilities, operational robustness, and user confidence in Identification (ID) systems and show how it could be applied to biometrics security. We use

Roadrunner is a 1.38 Pflop/s-peak (double precision) hybrid-architecture supercomputer developed by LANL and IBM. It contains 12,240 IBM PowerXCell 8i processors and 12,240 AMD Opteron cores in 3,060 compute nodes. Roadrunner is the first supercomputer to run Linpack at a sustained speed in excess of 1 Pflop/s. In this paper we present a detailed architectural description of Roadrunner and a detailed performance analysis of the system. A case study of optimizing the MPI-based application Sweep3D to exploit Roadrunner's hybrid architecture is also included. The performance of Sweep3D is compared to that of the code on a previous implementation of the Cell Broadband Engine architecture-the Cell BE-and on multicore processors. Using validated performance models combined with Roadrunner-specific microbenchmarks we identify performance issues in the early pre-delivery system and infer how well the final Roadrunner configuration will perform once the system software stack has matured.

The increasing acceptance of XML as a standard for document markup promises to provide solutions for the problems of document management and retrieval. However, existing documents must be converted into XML. In this paper we present the AutoTag system, which automatically converts text documents into XML. The system has a hybrid architecture, arranging tagged documents on a twodimensional Self-Organizing Map (SOM) such that nearby locations contain similar documents, and then using an inductive learning algorithm to automatically extract and apply auto-tagging rules from the neighbours of an untagged document. The system is adaptive, so that once a document is tagged in XML, AutoTag learns from its errors in order to improve accuracy. The automatically tagged documents can subsequently be categorized on the Self-Organizing Map, further improving the map's resolution. Our system has been evaluated on a number of different domains, giving good results.

Challenging stellar dynamical problems, such as the study of gravothermal oscillations in star clusters, have in the past initiated the very successful building of GRAPE special purpose computers. It is discussed, that present day tasks such as the formation and evolution of galactic nuclei with one or more massive black holes and the coupled stellar and gas dynamical processes in

This paper describes the Spanish Resource Grammar, an open-source multi-purpose broad-coverage precise grammar for Spanish. The grammar is implemented on the Linguistic Knowledge Builder (LKB) system, it is grounded in the theoretical framework of Head-driven Phrase Structure Grammar (HPSG), and it uses Minimal Recursion Semantics (MRS) for the semantic representation. We have developed a hybrid architecture which integrates shallow processing functionalities -morphological analysis, and Named Entity recognition and classification -into the parsing process. The SRG has a full coverage lexicon of closed word classes and it contains 50,852 lexical entries for open word classes. The grammar also has 64 lexical rules to perform valence changing operations on lexical items, and 191 phrase structure rules that combine words and phrases into larger constituents and compositionally build up their semantic representation. The annotation of each parsed sentence in an LKB grammar simultaneously represents a traditional phrase structure tree, and a MRS semantic representation. We provide evaluation results on sentences from newspaper texts and discuss future work.

The ubiquitous role of the cyber-infrastructures, such as the WWW, provides myriad opportunities for machine learning and its broad spectrum of application domains taking advantage of digital communication. Pattern classification and feature extraction are among the first applications of machine learning that have received extensive attention. The most remarkable achievements have addressed data sets of moderate-to-large size. The 'data deluge' in the last decade or two has posed new challenges for AI researchers to design new, effective and accurate algorithms for similar tasks using ultra-massive data sets and complex (natural or synthetic) dynamical systems. We propose a novel principled approach to feature extraction in hybrid architectures comprised of humans and machines in networked communication, who collaborate to solve a pre-assigned pattern recognition (feature extraction) task. There are two practical considerations addressed below: (1) Human experts, such as pla...

The current study offers a critical interpretation of the more transient traces of Islam in Australia, and their representation in the equally scanty tangible evidences. The scope of recent surveys in this field is increasingly inclusive. However, very few studies focus on the architecture of Muslim communities in regions where Islam is not the predominant faith, especially in the southern hemisphere. The historical Adelaide Mosque, and many others, is excluded from the historical record despite the instrumental role it played in the life of Muslim settlers. This absence raises questions about gaps, or histories untold, as well as myths received, in histories of 'Islamic' architecture that raise questions about the truth-value of the past. There is a need to examine hybridized forms and shared architectural narratives to counter the myopic but persistent representation-or fabulation-of supposedly authentic, largely Arabcentric, forms of 'Islamic' architecture. This paper argues, then, that new theoretical frameworks are required to interpret this architectural hybrid that is, we argue, typical rather than exceptional.

The Knowledge Acquisition (KA) process consists on extracting and representing knowledge of a domain expert. In this work, one of the goals is to minimize the intrinsic difficulties of the KA process. We have obtained all possible rules from the domain expert in a short time and also a set of examples. Other goal, we are proposed a Hybrid Expert

Heterogeneous computers with processors and accelerators are becoming widespread in scientific computing. However, it is difficult to program hybrid architectures and there is no commonly accepted programming model. Ideally, applications should be written in a way that is portable to many platforms, but providing this portability for general programs is a hard problem. By restricting the class of programs considered, we can make this portability feasible. We present Liszt, a domainspecific language for constructing mesh-based PDE solvers. We introduce language statements for interacting with an unstructured mesh, and storing data at its elements. Program analysis of these statements enables our compiler to expose the parallelism, locality, and synchronization of Liszt programs. Using this analysis, we generate applications for multiple platforms: a cluster, an SMP, and a GPU. This approach allows Liszt applications to perform within 12% of handwritten C++, scale to large clusters, and experience order-of-magnitude speedups on GPUs.

We present a hybrid parallel system based on commodity components to gain supercomputer power at low cost. The architecture is built around a coarse-grained PC-cluster linked by a high-speed network and fine-grained parallel processor arrays connected to each node. Identifying applications that profit from this kind of processing power is critical to justify the use of such a system. In this paper, we present a new approach to high performance protein database scanning with hybrid computing. To derive an efficient mapping onto this architecture, we designed an instruction systolic sequence comparison algorithm. This results in a database scanning implementation with significant runtime savings.

One of the most promising uses for multi agent systems is the searching for items or resources in unknown environments. The use of multi agent systems to locate unexploded ordinance proves to be an excellent example of one such application. This research explores the possibility of a hybrid architecture that implements mine detection, obstacle avoidance and route planning with a group of autonomous agents with coordination capabilities. Groups of inter cooperating multi agents working towards a common goal have the potential to perform a task faster and with an increased level of efficiency then the same number of agents acting in an independent manner. This coordination framework will address the issues involved during such unknown exploration

This paper investigates on the active and reactive power sharing of an autonomous hybrid microgrid. Unlike existing microgrids which are purely ac, the hybrid microgrid studied here comprises dc and ac sub-grids, interconnected by power electronic interfaces. The main challenge here is to manage the power flow among all the sources distributed throughout the two types of sub-grids, which certainly is tougher than previous efforts developed for only either ac or dc microgrid. This wider scope of control has not yet been investigated, and would certainly rely on the coordinated operation of dc sources, ac sources and interlinking converters. Suitable control and normalization schemes are therefore developed for controlling them with results presented for showing the overall performance of the hybrid microgrid.

The network is becoming faster day by day. High-speed links, of many Gbps, are considered as commodity technology empowering the Internet. On the other hand, Moore's law still applies to current processing power. It needs about 18 months for CPUs to double the number of their transistors. A very fast network composed by not as fast processors is unable to perform basic operations needed in the security field, like firewalling and intrusion detection. In this paper, we propose a novel system, which promotes security operations in the optical domain. We describe all hardware components-optical and digital-and the software, which renders the system functional. We outline application scenarios in which a hybrid architecture of optical and digital parts, like the one we propose in this paper, can offer significant benefit to the network from a security perspective.

In this paper we compare the routing architecture of island-style FPGAs based on field-programmable switch boxes with a maskprogrammable routing structure, in order to assess its position in the design space of routing opportunities available to VLSI IC designers. Although the results presented in this work depend on a few implementation details that will be discussed in the paper, the mask-programmable routing structure shows a large area saving and delay improvement with respect to the field-programmable switch box. As a consequence, we believe that between the two bounds of the design space, i.e., ASICs and FPGAs, there are several hybrid architectural solutions trading off performances, power, area, and programmability, which in the future can be considered for different applications.

The paper outlines a hybrid architecture for a partial parser based on regular grammars over XML documents. The parser is used to support the annotation process in the BulTreeBank project. Thus the parser annotates only the 'sure' cases. To maximize the number of the analyzed phrases the parser applies a set of grammars in a dynamic fashion. Each grammar determines not only the constituent structure (plus some syntactic dependencies internal to the structure), but also a description of the local and global context of the recognized phrase. The grammars available to the parser are arranged in a network. The order of the grammars application depends on the initial ordering in the network and the descriptions associated with the grammars. Thus the traverse is not deterministic. Additionally, the application of the grammars can be interleaved with the applications of other XML tools like remove, insert and transform operations. This architecture provides a flexible means for g...

In this paper I combine an overview of the goals and major approaches in cross-language information retrieval with some observations of current trends and with a report on a CLIR project that differs in many respects from most research activities in the fast growing area. In the overview, I will start from a generic model of an information retrieval system. Then the necessary extensions will be introduced that are needed for allowing queries in a language different from the document language. Several options for adding translation technology will be contrasted. I will then report on the research strategy followed in the EU-funded international project Mulinex. In this project a complete modular CLIR system was developed and integrated as the core software for a number of applications and as a plattform for research and technology development.

Existing approaches to high-level robot control which support deliberation in one form or another usually do not view the time spent on reasoning as critical, which is true in typical applications like office delivery. This is not so, however, in domains like robotic soccer where a team of robots must cooperate in a highly dynamic environment and where actions need to be chosen under tight resource constraints. For this reason, most existing systems for such domains rely on purely reactive architectures without a reasoning component. Our aim is to build robotic soccer agents which are capable of limited forms of deliberation using the action language Golog. In order to meet the real-time constraints, we propose to integrate Golog into a hybrid architecture, which enables the robot to react to the environment very fast as well as to choose actions proposed by the reasoning component. We feel that Golog is particularly well-suited for the reasoning component because it allows to limit the search space by programming complex actions and because of recent advances in extending the expressiveness of the language to deal with issues like continuous change, event-driven behavior, and uncertainty, all of which are important in a domain like robotic soccer.

In this paper we propose a hybrid control architecture which combines aspects of classic control and behavior-based control. The aspects of continuous systems and discrete eventsystems are both considered. This hybrid architecture combines the advantages of behaviorbased control and classic control, allowing for a theoretical study on the stability conditions for the system. In addition, the use of Petri nets to model the discrete-event aspects enables a formal study of the conflicts between behaviors and the way to overcome them.

Automated singer identification is important in organising, browsing and retrieving data in large music databases. In this paper, we propose a novel scheme, called Hybrid Singer Identifier (HSI), for automated singer recognition. HSI can effectively use multiple low-level features extracted from both vocal and non-vocal music segments to enhance the identification process with a hybrid architecture and build profiles of individual singer characteristics based on statistical mixture models. Extensive experimental results conducted on a large music database demonstrate the superiority of our method over state-of-the-art approaches.

A core area of P2P systems research is the topology of the overlay network. It has ranged from random unstructured networks like Gnutella [8] to architectures to the recent trend of structured overlays based on Distributed Hash Tables (DHTs) . While the unstructured networks have excessive lookup costs and un-guaranteed lookups, the structured systems offer no anonymity and delegate control over data items to unrelated peers. In this paper, we present an in-themiddle hybrid architecture which uses a mix of both topologies to create a decentralized P2P infrastructure. The system provides scalable and guaranteed lookups in addition to mutual anonymity and also allows hosting content with the content-owner. We validate our architecture through a thorough analytical and empirical performance analysis of the system.

This paper aims at providing different cost-efficient solutions for the channel impairments in tropical areas. In order to extend service to isolated areas, we propose an hybrid architecture based on DVB-S2/RCS + Wi-Fi networks. In this scenario, the delay of the ACM reaction to fade changes can affect the quality of the video transmission, especially because of the characteristics of tropical deep fading events. In order to avoid QoS reduction, we focus on the DVB PHY-layer shifted threshold, which we study not only for different Amazon areas and different rain conditions, but also for different reaction delays. The performance of the PHY-layer selector is evaluated in terms of video quality (PSNR), packet error rate and bandwidth efficiency.

This paper describes the Spanish Resource Grammar, an open-source multi-purpose broad-coverage precise grammar for Spanish. The grammar is implemented on the Linguistic Knowledge Builder (LKB) system, it is grounded in the theoretical framework of Head-driven Phrase Structure Grammar (HPSG), and it uses Minimal Recursion Semantics (MRS) for the semantic representation. We have developed a hybrid architecture which integrates shallow processing functionalities -morphological analysis, and Named Entity recognition and classification -into the parsing process. The SRG has a full coverage lexicon of closed word classes and it contains 50,852 lexical entries for open word classes. The grammar also has 64 lexical rules to perform valence changing operations on lexical items, and 191 phrase structure rules that combine words and phrases into larger constituents and compositionally build up their semantic representation. The annotation of each parsed sentence in an LKB grammar simultaneously represents a traditional phrase structure tree, and a MRS semantic representation. We provide evaluation results on sentences from newspaper texts and discuss future work.

In relay-based wireless networks, messages need to be forwarded via intermediate relay mobile terminals (MTs). However, because of various transmission distances and unbalanced traffic load, some relay MTs may tend to drain their batteries faster than others. After a certain number of MTs deplete their battery energy, the peer-to-peer communication may become disconnected. Depletion of the battery energy of any

The implementation of an optimal Bayesian algorithm for digital equalization is infeasible due to its computational complexity. In this paper we present a new approach to Bayesian blind equalization which is based on a hybrid architecture involving Neural Networks and Evolutionary Computation concepts. We develop a theoretical analysis which leads t o recursive formulas to estimate the Probability Density Functions (PDFs) of both the channel and the received samples. These parameters are used directly by the algorithms t o perform equalization. Beginning with a brief revision of previous neural, genetic and Radial Basis Function (RBF) networks-based approaches, we outline the theoretical algorithm that will serve as a reference for future neuro-evolutionary derivations. We also show the capability of these structures t o perform blind Bit Error Rate (BER) estimation in reception. Finally, several computer simulations and comparative results are exposed.

We propose a novel context-dependent (CD) model for large-vocabulary speech recognition (LVSR) that leverages recent advances in using deep belief networks for phone recognition. We describe a pre-trained deep neural network hidden Markov model (DNN-HMM) hybrid architecture that trains the DNN to produce a distribution over senones (tied triphone states) as its output. The deep belief network pre-training algorithm is a robust and often helpful way to initialize deep neural networks generatively that can aid in optimization and reduce generalization error. We illustrate the key components of our model, describe the procedure for applying CD-DNN-HMMs to LVSR, and analyze the effects of various modeling choices on performance. Experiments on a challenging business search dataset demonstrate that CD-DNN-HMMs can significantly outperform the conventional context-dependent Gaussian mixture model (GMM)-HMMs, with an absolute sentence accuracy improvement of 5.8% and 9.2% (or relative error reduction of 16.0% and 23.2%) over the CD-GMM-HMMs trained using the minimum phone error rate (MPE) and maximum-likelihood (ML) criteria, respectively.

Automatic detection of network intrusion is a challenging task because of increasing types of attacks. Many of the existing approaches either are rigid, inflexible designs tailored to a specific situation or require manual setting of design parameters such as the initial number of clusters. In this paper we allow the design parameters to be determined dynamically by adopting a layered hybrid architecture, hence resolving the aforementioned shortcomings. The first layer uses FCM and GK fuzzy clustering to extract the features and the second layer uses a set of RBF neural networks to perform the classification. The flexible design parameters are initial number of clusters, number of RBF networks and number of neurons inside each network which are determined with minimal input from the user. The simulation result shows high detection rates as well as fewer false positives compared to earlier approaches.

With the prevalence of multi-core processors and cloud computing, the server consolidation using virtualization has increasingly expanded its territory, and the degree of consolidation has also become higher. As a large number of virtual machines individually require their own disks, the storage capacity of a data center could be exceeded. To address this problem, copy-on-write storage systems allow virtual machines to initially share a template disk image. This paper proposes a hybrid copy-on-write storage system that combines solid-state disks and hard disk drives for consolidated environments. In order to take advantage of both devices, the proposed scheme places a read-only template disk image on a solid-state disk, while write operations are isolated to the hard disk drive. In this hybrid architecture, the disk I/O performance benefits from the fast read access of the solid-state disk, especially for random reads, precluding write operations from the degrading flash memory performance. We show that the hybrid virtual disk, in terms of performance and cost, is more effective than the pure copy-on-write disks for a highly consolidated system.

We are developing robot controllers based on biomimetic design principles. The goal is to realise the adaptive capabilities of the animal models in natural environments. We report feasibility studies of a hybrid architecture that instantiates a command and coordinating level with computed discrete-time map-based (DTM) neuronal networks and the central pattern generators with analogue VLSI (Very Large Scale Integration) electronic neuron (aVLSI) networks. DTM networks are realised using neurons based on a 1-D or 2-D Map with two additional parameters that define silent, spiking and bursting regimes. Electronic neurons (ENs) based on Hindmarsh-Rose (HR) dynamics can be instantiated in analogue VLSI and exhibit similar behaviour to those based on discrete components. We have constructed locomotor central pattern generators (CPGs) with aVLSI networks that can be modulated to select different behaviours on the basis of selective command input. The two technologies can be fused by interfacing the signals from the DTM circuits directly to the aVLSI CPGs. Using DTMs, we have been able to simulate complex sensory fusion for rheotaxic behaviour based on both hydrodynamic and optical flow senses. We will illustrate aspects of controllers for ambulatory biomimetic robots. These studies indicate that it is feasible to fabricate an electronic nervous system controller integrating both aVLSI CPGs and layered DTM exteroceptive reflexes.

Healthcare Information Systems are nowadays among the world's largest, fastest-growing and most information intensive indus- tries. Additionally, Intensive Care Units are widely considered as the most technologically advanced environments within a hospital. In such environments, physicians are confronted with the challenge of storing and analyzing terabytes of data that stream in real-time from inpatients to centralized clinical information systems. In

Over the past decades, the design and development of mission based Autonomous Underwater Vehicle (AUV) continues to challenge researchers. Although AUV technology has matured and commercial systems have appeared in the market, a generic yet robust AUV command and control (C2) system still remains a key research area. This paper presents a command and control system architecture for modular AUVs. We particularly focus on the design and development of a generic control and software architecture for a single modular AUV while allowing natural extensions to multi-vehicle scenarios. This proposed C2 system has a hybrid modular-hierarchical control architecture. It adopts top-down approach in mission level decision making and task planning while utilizing bottom-up approach for navigational control, obstacle avoidance and vehicle fault detection. Each level consists of one or more autonomous agent components handling different C2 tasks. This structure provides the vehicle developers with an explicit view of the clearly defined control responsibilities at different level of control hierarchy. The resultant C2 system is currently operational on the STARFISH AUV built at the ARL of the National University of Singapore. It has successfully executed some autonomous missions during sea trials carried out around the Singapore coastal area.