The ever more extensive data collection from Internet of Thing (IoT) devices stresses the need for efficient application development tools. State-of-the-art IoT cloud services are powerful, but the best solutions are proprietary, and there is a growing demand for interoperability and standardization. We have investigated how to develop a nonvendor-locked framework, which exploits state of the art data management technologies, and targets effective and efficient development in this article. Focusing on the concept of measurement, we abstracted an architecture that could be applied in a variety of domains and contexts. We tested the framework and its workflow in four use cases analyzing data and enabling new services in health, automotive, and instruction. Our experience showed the benefits of the development tool, which is not tied to a commercial platform, nor requires the huge set-up times needed to start a project from scratch. The tool is released open-source, particularly supporting collaborative research.

Pervasive games are an emerging genre combining reality and computing. This paper presents a suite of simple pervasive serious games we have developed to explore the concept of “reality-enhanced gaming”, a pattern to tie game play mechanics to the outcomes/measurements of real-world activities. The prototype games were realized in the context of TEAM, an industrial research project aimed at developing apps for flexible and collaborative mobility. The proposed games are examples of different UIs we considered useful to meet various significant scenarios, goals and user typologies, especially for improving car driving styles. Given the variety of information sources, contexts of use, and target users, we abstracted a gameoriented framework (namely REAL, Reality-Enhanced AppLied games), in order to support re-use and scalability. Through a set of RESTful APIs, the REAL framework separates sensor data from actual game implementations, so as to provide different experiences to users, according to their specific needs and preferences. This concept – which allows serious game developers to focus on their specific game logic while seamlessly exploiting a variety of field sensors - is general and may be applied to a variety of domains. We validated REAL developing and field testing five typologies of serious games. Subjective evaluation results show a good level of satisfaction and perceived usefulness. More tests are needed, especially in terms of different application contexts, impact on developers, number and variety of users, and exposure time. However, outcomes confirm the significant potential of reality-enhanced game design and the importance of tools for supporting their development.

In addition to smarter road vehicles and smarter roads, more smartly human driven vehicles (that are as yet still predominantly more common-place than autonomously driven ones) currently still have a huge potential to improve road safety, fuel efficiency and to reduce vehicle exhaust emissions. In this work, we propose a human driving profiling algorithm with the means of Serious Games (SGs) – games for training and learning drivers’ trip purpose beyond a behavioral improvement via users’ motivation and engagement in a digital environment – to assist the driver in promoting more fuel efficient (low fuel consumption, FC) driving. The game supplies drivers or players with direct feedback when more inefficient, and riskier, driving manoeuvres are detectable, via sensing and analysing the changes of throttle position, engine revolutions per minute (RPM), car speed and jerks (changes in acceleration with respect to time). Such manoeuvres derived from the On-Board Diagnostic-II interface to the vehicle sensors complemented by additional sensors such as GPS location, e.g., from a mobile phone or inbuilt vehicle sensor, can be regarded as eco-driving events. Providing eco-driving feedback via the user interface of a SG, keeps the driver aware of the fuel economy and safety. We also argue that evaluating the driving style for the whole trip allows us to take into account how the dynamic driving behavior is sometimes affected by other factors (e.g., traffic congestion). In addition, this quantitative evaluation is important as a gaming mechanism, i.e., an updated score can facilitate reaching a higher gaming level, etc. In contrast to existing studies, we combine fuel efficiency with the throttle position values in the eco-driving classification module. We have done some initial analysis for this, using the naturalistic historical driving data from the enviroCar project’s open data initiative. We reason that throttle position is the most powerful indicator of fuel efficiency and driving style among the other studied parameters.

Internet of Things (IoT) technologies have a promising potential for instructional serious games related to field operations. We explore IoT's potential for serious games in the automotive application domain to improve driving, choosing fuel consumption (FC) as an indicator of the driver performance as it is strongly influenced by driving styles and can be quantified and validated. We propose a FC prediction model, exploiting three vehicular signals that are controllable by the driver (player), that are able to provide direct coaching feedback to the driver and are easily available through the widely available On-Board Diagnostic-II (OBD-II) vehicular interface: throttle position, engine rotation speed (RPM) and car speed. We processed the data with two techniques, random forest (RF) and fuzzy logic (FL). Implementation, training and testing of both models, were made using the enviroCar database which freely provides a significant amount of naturalistic drive data. Results show that RF achieves quite a higher estimation accuracy, which complements FL's ability to provide driver with easily understandable feedback. We thus argue that the combination of the two models can supply valuable information usable by game designers in the automotive environment.

Automated Driving (AD) technology is rapidly advancing and being tested in large-scale pilots. The L3Pilot project will test AD functions at SAE automation level 3 and 4 in 100 cars, from 12 vehicle owners (car manufacturers and suppliers), with 1,000 drivers across 10 different countries in Europe. The project will thus generate a huge amount of data, part of which will be aggregated and shared among project participants and publicly for answering a set of research questions about the evaluation of such aspects as technical and traffic issues, user acceptance, impact, socio-economic impact. This paper investigates the design of an Internet of Things (IoT) framework aimed at storing data collected from the prototype vehicles and pre-processed in the various test sites, in order to protect privacy and intellectual property (IP). The framework is expected to make such aggregated information easily available to analysts through a web interface. The framework, of which we present also a pre-pilot lab test, is accessible through a RESTful API and features different user roles to meet the different information access requirements.

The tomorrow's elastic adaptive mobility industrial research project developed eleven collaborative mobility apps addressing various traffic issues and scenarios. The apps, involving different aspects and degrees of collaboration (e.g., direct user participation, shared objectives, coordination, etc.), aim at increasing the driver/traveler awareness and support a better behavior. This paper describes the apps and the underlying system architecture shared by the participating car manufacturers. Then, it provides a user acceptance analysis grouping the apps according to the three main types of users and stakeholders: drivers, travelers, and administrators/operators. Data, collected in five European countries, shows that acceptance and expected impact are positive. The actual road-test experience did not diminish the high expectations raised by an initial presentation on paper, showing a good maturity of the prototypes. The Administrator app cluster shows a slightly better assessment, highlighting the importance of considering collaborative mobility as a system, including road, infrastructure, and traffic management.

Present public transport services still suffer from issues such as time deviations from the static timetable, overcrowded buses, increased on board time, and long wait at bus stops. This work studies the experimental implementation of an on-demand public bus transportation service in Trikala, a medium-sized Greek city. With a view to optimize the service from both the operator's and the citizens' point of view, this paper presents an insertion heuristic solving the static multivehicle dial-a-ride problem with time windows and a fixed fleet of vehicles. Since viability of such a service depends on its ability of involving a significant number of users and getting reliable information, we tested a gamification layer, aimed at motivating public transport users to participate and behave correctly with the system. We present and discuss a novel pervasive computing architecture and various types of serious games designed to achieve these goals. We finally report early usability test results and some simulation-based indications on the design of city-scale deployable serious games to enhance public transport-based mobility.

Tangible learning is a promising branch, especially for scientific learning, allowing an enhanced sensorial involvement and participation by children. While a lot is being done on the side of programming, less has been investigated on elementary spatial and geometric concepts. The paper presents i-Vertex, an open-hardware framework for tangible serious games on geometry concepts for primary school pupils. The framework targets spatial reasoning and includes music as a related and complementary feature, which should add value also for usability. i-Vertex supports collaboration between kids and the key role of a teacher as an adult that interacts with the children in different ways, introducing them to the discovery and understanding of basic geometric concepts and physical phenomenon. At present, we have built a prototype, featuring a very limited number of vertices, and functionally tested it in lab, in two main scenarios covering topics such as lines and triangles. Based on the successful feedback of this experiment, we intend to proceed further, upgrading the platform with a more powerful and product oriented micro-controller and board.

The transportation sector is expanding its trends in accessibility, connectivity, and mobility for making the road travel as safe and convenient. Now with Services like car sharing, car pooling and rides there are new effective ways to reach the desired destination. But due to comfort reasons most of the car owners will use their car to navigate from point A to B, without caring about the pollution they produce. In this paper we describe a game based approach for motivating people to drive in a safe and environment-friendly way. The approach of this paper will allow people to measure their driving behavior within a game. The points earned in the game can not only be used for the comparison with peers but also to obtain monetary benefits in different stores.

We present a technique for dangerous curve monitoring relying on the innovative concept of Safe Driving Map (SDM), a geo-referenced database with data about safe vehicle behavior in the monitored area, also considering different weather conditions. A vehicle's data are compared with the SDM reference and the driver is warned in case of danger. A road-side unit can also be set-up, collecting information from vehicles, thus signaling possible dangers (e.g., a vehicle stopped in the curve). A preliminary evaluation was performed by developing a scenario using the PHABMACS (Physics Aware Behavior Modelling Advanced Car Simulator) driving simulator.

Dynamic charging of electric vehicle technology aims to deploy the use of electric vehicle on a large scale. In order to realize and achieve an effective and reliable system, the information and communication solutions (ICT) need to be developed. The ICT solutions look particularly to assess areas such as routing, booking of the charging lane, billing, vehicle identification, guidance to charging lane and assistance while charging. In this paper, we review the state of the art of ICT solutions and provide indications for the future research.

Producing educational serious games can be costly and time-consuming. The Service-Oriented Architecture (SOA) approach of software development can offer a solution to reduce costs and foment serious games development. In this work, we apply a model called Activity Theory-based Model of Serious Games (ATMSG) for identifying existing relevant components that can be reused for different educational serious games. We apply the derived structure to classify the elements of an existing game and to identify how it can be refactored and expanded following the SOA paradigm.

Traffic flow prediction is a fundamental functionality of intelligent transportation systems. After presenting the state of the art, we focus on nearest neighbor regression methods, which are data-driven algorithms that are effective yet simple to implement. We try to strengthen their efficacy in two ways that are little explored in literature, i.e., by adopting a multivariate approach and by adding awareness of the time of the day. The combination of these two refinements, which represents a novelty, leads to the definition of a new class of methods that we call time-aware multivariate nearest neighbor regression (TaM-NNR) algorithms. To assess this class, we have used publicly available traffic data from a California highway. Computational results show the effectiveness of such algorithms in comparison with state-of-the-art parametric and non-parametric methods. In particular, they consistently perform better than their corresponding standard univariate versions. These facts highlight the importance of context elements in traffic prediction. The ideas presented here may be further investigated considering more context elements (e.g., weather conditions), more complex road topologies (e.g., urban networks), and different types of prediction methods.

Abstract: Instruction in physics aims at achieving two goals: the acquisition of body of knowledge and problem solving skills in physics. This requires students to connect physical phenomena, physics principles, and physics sym-bols. Computer simulation provides students with graphical model that unites phenomenon and principles in physics. However, such minimally guided approach may harm learning since it overburdens the working mem-ory. Also, simulation is inadequate in promoting problem solving skills since students need to exercise with a variety of physics problems. Intelligent tutoring systems (ITS), in contrast, train students in solving physics problems. In this paper, we designed an online puzzle game in physics that combines simulation and pseudo-tutor (namely QTut). We addressed three challenges: extensibility, scalability, and reusability in designing our game. We conducted usability tests with 10 participants on the game prototype to study the user performances and perceptions for improvement. The results indicate the game as educative and moderately entertaining. The use of scaffolding in the game positively contributed to the game learning experience. Moreover, the game GUI expressed information well that made the game understandable, even with little instructions. 1

Several engineering schools offer game based learning either as a supplementary to lecturers or as an integrated part of their curriculum. Most of the games are used in a workshop setting, and much of the learning outcome is achieved through the debriefing part of the workshop, i.e. not as an integrated part of the game. One reason is that many of the games do not offer stealth assessment, and thus need interpretation of a very well skilled facilitator. In additions games only used for one specific course are costly to develop, maintain and improve and in addition facilitated games put limitations on the class size and make it costly to integrate. Thus, this article looks at under which circumstances an on-line game produced for a different course could be integrated in a facilitated and not-facilitated way.

Gamification is gaining an increasing interest, also in the field of instruction and training, thanks to its promise of engaging and motivating users. This paper presents the experience of a gamified short course on promotion of entrepreneurship that we have designed and executed for Electronic Engineering students. The short course relied on an extensive use of serious games for business and featured a team competition rewarding students' gaming and written/oral reporting activities, assigning a cumulative score to define the team ranking for the final day playoff matches. The course experience was positive, and able to meet the goals in terms of engagement, learning and promotion of interest towards entrepreneurship. The presence of teachers was very important, introducing and explaining topics and giving indications and discussing the experience with students. It is important to balance extrinsic motivation with development of intrinsic motivation, in view of promoting real education.

Passive brain-computer interaction (BCI) can provide useful information to understand a user's state and anticipate intentions, which is needed to support adaptivity and personalization. Given the huge variety of audiences, a game's capability of adapting to different user profiles-in particular to keep the player in flow-is crucial to make it ever more enjoyable and satisfying. We have performed a user experiment exploiting a four-electrode electroencephalogram (EEG) tool similar to the ones that are soon likely to appear in the market for game control. We have performed a spectral characterization of the video-gaming experience, also in comparison with other tasks. Results show that the most informative frequency bands for discriminating among gaming conditions are around low beta. Simple signals from the peripheral nervous system add marginal information. Classification of three levels of user states is possible, with good accuracy, using a support vector machine (SVM) classifier. A user-independent classification performs worse than a user-dependent approach (50.1% versus 66.4% rate). Personalized SVM training and validation time is reasonable (7-8 min). Thus, we argue that a personalized system could be implemented in a consumer context and research should aim at improving classifiers that can be trained online by end users.

Games and Learning Alliance (GaLA) is the EU Network of Excellence on serious games (SG). The main expected outcome is the set-up a Virtual Research Centre (VRC) aimed at integrating, harmonizing and coordinating research on SGs and disseminating knowledge, best practices and tools as a reference point at an international level. The other two key focuses of the project are (1) the support to deployment in the actual educational and training settings and (2) the fostering of innovation and knowledge transfer through research-business dialogue. The NoE is composed of organizations that aim to integrate their activities and resources in a long-term view. A long-term perspective is systematically pursued as GaLA sets-up an infrastucture and aims at making it viable and sustainable. The major expected outcomes include: the European Society on Serious Games; the European conference on Serious Games; journal special issues; the Virtual Research Environment (VRE); the SG Living Labs (SG LLs); a MSc programme on SGs, with the relevant didactic tools; PhD projects on SGs; the schools (alignment and summer) on SGs.

This paper introduces a suit of advanced human-machine interface (HMI) with gesture interaction. Related hardware component of the system and used signal processing methods are illustrated. The design of embodied conversational geography teaching system which applies this HMI system to game-based learning is described. Finally, the advantages and meanings of the usage of this geography teaching system with gesture interaction are analyzed and presented.

Ability of adapting to different users is considered key to maximize the impact and effectiveness of Serious Games (SGs). Advances in neurosciences are making it possible to continuously monitor the player status. This paper reports the research work on the monitoring of the player flow status with a simple (4 electrode) commercial electroencephalogram (EEG). In particular, we focus on three consequential research questions: is it possible to statistically distinguish a flow from a boredom condition? For which wavelengths? Can different levels of boredom and flow be identified? Results - even if limited because of the small size of the test, are promising and enable further research. Statistically significant differences could be observed for brainwaves under various conditions. A machine learning classifier (SVM) was successful in the 2-level distinction case, in particular with personalized training.

Learning is frequently seen as an awkward activity. This problem becomes worse in technology and science topics, since they are often perceived as cold and difficult subjects to learn. On the other hand, playing is considered funny and engaging, which gives motives to people to do it voluntarily. Moreover, the current increasing use of social networks can represent an opportunity for knowledge and skill development, in particular by enabling students' collaboration and competition. This has led to the idea of exploiting and investigating the appeal and educational potential of serious games in a higher education context, in particular for technology and science topics. This paper proposes mini-games based serious game format targeting in particular higher education technology and science topics, and exploiting advanced web-based and social networking technologies, able to support easy diffusion and user competition/collaboration. We have set-up a client-server based architecture for the implementation of a prototype for a Digital Electronic System BSc course. Preliminary test results show that users have a positive attitude towards the games, as they give an average rating of 4/5 in terms of desirability. Furthermore, it takes 3 times of replays, on average, for users to achieve good scores. Usability issues are also presented and discussed.

In an indoor search and rescue mission, the two main tasks are detecting the location of survivors or broken equipments and recovering them from a building full of danger. For the outdoor robots, they can use GPS to get the path information. But in a GPS-denied environment, the robots cannot get the support from satellites. We design an air-ground robot team to provide a solution to this problem. It consists of a micro aerial vehicle with a vertical camera and a horizontal camera, and two micro ground vehicle with an ultrasonic sensor and a colour sensor. Experimental results are presented demonstrating this air-ground robot team's ability to operate successfully in indoor environments.

The Adaptive Integrated Driver-vehicle interfacE (AIDE) is an integrated project funded by the European Commission in the Sixth Framework Programme. The project, which involves 31 partners from the European automotive industry and academia, deals with behavioral and technical issues related to automotive human-machine interface (HMI) design, with a particular focus on integration and adaptation. The project involves tightly integrated empirical research, driver-behavior modeling, and methodological and technological development. This paper provides an overview of the AIDE Sub-Project 3 results dealing with the design, development, and integration of the AIDE system in three prototype vehicles, together with the evaluation results of the trials.

Designing games that support knowledge and skill acquisition has become a promising frontier of education techniques, since games are able to capture the user concentration for long periods and can present users with realistic and compelling challenges. In this scenario, there is a need for scientific and engineering methods to build games not only as more realistic simulations of the physical world but as means to provide effective learning experiences. Abstracting state of the art serious games' (SGs) features, we propose a new design methodology for the sand box serious games (SBSGs) class, decoupling content from the delivery strategy during the gameplay. This methodology aims at making design more efficient and standardized in order to meet the growing demand for interactive learning. The methodology consists in modeling an SBSG as a hierarchy of tasks (e.g., missions) and specifies the requirements for a runtime scheduling policy that maximizes learning objectives in a full entertainment context. The policy is learned by an experience engine (EE) based on computational intelligence. In this approach, the domain-expert author focuses on the creation and semantic annotation of tasks. Tasks are put in a repository and can then be exploited by game designers who define the expected learning curve and other requirements about education and entertainment for the game. The task sequencing that aims at matching such specifications with the real user profile is then presented to the EE. The EE can operate also in absence of the specification of the learning curve, continuously adapting the game flow without aiming at the achievement of target knowledge levels predefined by the author. We have implemented an EE module based on genetic computation and reinforcement learning (RL) atop of a state-of-the-art game engine. Test results show that the EE is able to define in real-time missions that meet the requirements expressed by the author.

Abstract The RFID technology is becoming ever more popular in the development of ubiquitous computing applications. A full exploitation of the RFID potential requires the study and implementation of human–computer interaction (HCI) modalities to be able to support wide usability by the target audience. This implies the need for programming methodologies specifically dedicated to support the easy and efficient prototyping of applications to have feedback from early tests with users. On the basis of our field‐working experience, we have designed oDect, a high‐level language and platform‐independent application programming interface (API), ad hoc designed to meet the needs of typical applications for mobile devices (smart phones and PDAs). oDect aims at allowing application developers to create their prototypes focusing on the needs of the final users, without having to care about the low‐level software that interacts with the RFID hardware. Further, in an end‐user developing (EUD) approach, oDect provides specific support for the application end‐user herself to cope with typical problems of RFID applications in detecting objects. We describe in detail the features of the API and discuss the findings of a test with four programmers, where we analyse and evaluate the use of the API in four sample applications. We also present results of an end‐user test, which investigated strengths and weaknesses of the territorial agenda (TA) concept. The TA is an RFID‐based citizen guide that aids—through time‐ and location‐based reminders—users in their daily activities in a city. The TA directly exploits EUD features of oDect, in particular concerning the possibility of linking detected objects with custom actions. Copyright © 2008 John Wiley & Sons, Ltd.

Abstract Recent advances in Virtual Machine's technology have led to the diffusion of Java execution environments which provide performance levels comparable to those of traditional languages such as C/C++ and Fortran. This paper's focus is on method calls, a well researched area of compilers' optimization. In particular, we evaluate the impact on the performance of the Java virtual call mechanism and the advantages which can be obtained through the inlining optimization. Moreover, we propose a new heuristic methodology which allows us to consider whole sequences of methods for the inlining decision and not only simple couples of caller–callee methods. The proposed methodology operates at bytecode level and is applicable only to the calls that can be resolved at compile time. Thus, we execute a devirtualization algorithm before the inlining decision, in order to enlarge the basis for the optimization. We made empirical measures on three major platforms (Unix, Windows and Linux) by using the SPEC JVM98 benchmark suite. Results reveal an average performance improvement of 1.9% with devirtualization and 5.5% with inlining. We discuss the different behaviour of single benchmarks and virtual machines, arguing that dynamic compilers are not yet able to fully exploit the wider scope for intra‐procedural optimization offered by eliminating the calls. Finally, we show that taking into consideration whole sequences of calls—instead of single calls—is effective only on a few benchmarks where hotspots of execution involve cycles of nested methods. Copyright © 2003 John Wiley & Sons, Ltd.

Abstract The ever more widespread diffusion of Java interfaces and animations has highlighted the performance problems of the Java graphics environment. We have analysed the bottleneck and created a set of APIs that support direct access to platform specific hardware resources for graphics acceleration. We have also re‐implemented standard APIs in order to allow transparent direct access also by programs using standard JFC. The improvement in performance of about one order of magnitude encourages the utilization of Java for realizing fluid animations on large windows. Copyright © 2001 John Wiley & Sons, Ltd.

Low performance of Java code execution (J. Gosling et al., 1996) has risen in the computer science community the awareness of the need for reengineering. This is mainly due to the software layer called Java Virtual Machine (T. Lindholm and F. Yellin, 1997), which allows Java applications to be multiplatform, but also to object oriented languages features, that impose a higher performance cost than procedural languages (B. Calder et al., 1994). Dynamic message dispatching (also called virtual invocation), for instance, is the mechanism that allows polymorphism, one of the most interesting features of object oriented technology. Comparing this mechanism with a statically resolved function call, two kinds of overhead can be singled out (a direct cost and an indirect cost) (K. Driesen and U. Holzle, 1996), that make the utilization of virtual invocations time-consuming. The authors present an analysis of the invocation profile of Java applications, assessing the actual necessity for dynamic dispatching, analyzing the related performance costs and determining rules for an algorithm for the automatic inlining of methods.

Clock disabling for power management has been implemented in some microcontrollers, but the wake-up time of Xtal/PLL-based systems is incompatible with fast interrupt response. On the other hand, hardwired on-chip clocking has been used for dedicated circuits. We illustrate the design issues of a general-purpose microcontroller core with a programmable on-chip fully-digital clock generator. The CPU is compatible with the PIC16C57 instruction set and supports software-controlled clocking modes-ranging from 44 MHz up to 124 MHz; on-line self-tuning of the maximum full-speed frequency in case of peak-performance requirements; ultra-fast wake-up even with totally disabled clock generator-namely 8.6 ns.

This paper describes a parallel VLSI implementation of a private-key cryptographic system based on Peano-Hilbert curves. The basic unit of the VLSI architecture is the Crypto Processor, that is an SIMD composed of a grid of 256/spl times/256 processing units performing elementary operations of encoding process. The key length of the system, measured as number of free parameters, depends linearly on hardware complexity: the cryptographic system is modular and its implementation is very cheap. The CP has been implemented as a single chip with a 1-micron CMOS technology and shows a working frequency of 30 MHz. The chip can be used in consumer applications as well as add-on whenever a certain degree of safety in communication is required.

We consider the design process of VLSI systems dedicated to the real-time implementation of cooperative algorithms whose functionalities can be characterized by multilayer ensembles of simple elements which interact locally. These algorithms are related, even though not exclusively, to the implementation of various tasks in low-level machine vision. The starting point in the design process is the formulation of the sequential algorithm that computes the behavior of the system. Algorithmic transformations are performed to expose the parallelism originally present in the task. Given the description in terms of parallel loops, we partition the system and organize it as a set of processing units. The architectural structure of these units takes properly into account the algorithmic constraints on precision both in data representation and computation. The program flow implemented by our programmable architectural solution (ASIP) is an iterative sequence of multiply-and-accumulate operations performed in parallel. The programmability concerns both the structure/coefficients of the algorithm-depending on the specific application-and its computational parameters. The architecture's main blocks are described in VHDL and synthesized as a semi-custom chip, using standard tools. Following this procedure, we designed an ASIP core for performing real-time texture-based image segregation.

Addition techniques are divided into fixed-time and variable-time ones. While variable time techniques can achieve log/sub 2/(N) average addition time for N-bit operands, the hardware overhead have always made fixed-time adders preferable, such as Carry Lookahead and Carry Select. We present a new variable-time addition technique whose average delay is much lower than log/sub 2/(N) and whose overhead is lower than the one of a CLA adder. The new approach is made feasible by a proper application of VLSI dynamic logic design. We show the mathematical proof, the logic implementation, and the VLSI realization of the new adder. We report circuit simulation results and their comparison with the analytical model.

This paper presents a hardware approach to the design of fuzzy controllers which, by exploiting some peculiar characteristics of fuzzy logic computation, allows one to save power consumption and increase computing speed. We show that the computation involved in a fuzzy controller has some statistic features that can be exploited by asynchronous computation. This paper presents a quantitative study of the statistical properties of fuzzy computation. A design methodology is introduced, and two experimental applications are shown.

We present a study addressing a hardware implementation of the Boltzmann machine that relies on the concept of asynchronous digital system. The constraint of concurrently switching only unconnected neurons is dynamically satisfied by using an asynchronous distributed control mechanism. The design of the control architecture is derived from a formal definition of the problem by means of the trace theory. Computer simulations show the efficiency of the proposed approach.

A large fraction of software designs using microcontrollers is today adopting fuzzy logic algorithms and this fraction is likely to increase in the future. Hardware implementation of fuzzy logic ranges from standard microprocessors to dedicated ASICs and each different approach is targeted to a different application domain or market area. In this paper, we present an overview of the computational complexity of the fuzzy inference process and the various techniques adopted for fuzzy control tasks, highlighting the tradeoffs that can guide a system designer toward correct choices according to application features and cost/performance issues. In addition, we detail three case studies of architectures that address three different market segments in the fuzzy hardware scenario: dedicated fuzzy coprocessors, RISC processors with specialized fuzzy support and application specific fuzzy ASICs.>

We present the analytical model and the electrical characterization of a controllable delay component for a micropipeline architecture suitable for being designed with a semicustom design approach. An interesting feature of the component is that it is lockable, i.e., it can be controlled in an on/off fashion, permitting synchronous operation for testing purposes by means of an opportune architecture model.>

The Boltzmann Machine is a neural model based on the same principles of simulated annealing that reaches good solutions, reduces the computational requirements, and is well suited for a low-cost, massively parallel hardware implementation. In this paper we present a connectionist approach to the problem of block placement in the plane to minimize wire length, based on its formalization in terms of the Boltzmann Machine. We detail the procedure to build the Boltzmann Machine by formulating the placement problem as a constrained quadratic assignment problem and by defining an equivalent 0-1 programming problem. The key features of the proposed model are: (1) high degree of parallelism in the algorithm, (2) high quality of the results, often near-optimal, and (3) support of a large variety of constraints such as arbitrary block shape, flexible aspect ratio, and rotations/reflections. Experimental results on different problem instances show the skills of the method as an effective alternative to other deterministic and statistical techniques.>

VLIW processors are viewed as an attractive way of achieving instruction-level parallelism because of their ability to issue multiple operations per cycle with relatively simple control logic. They are also perceived as being of limited interest as products because of the problem of object code compatibility across processors having different hardware latencies and varying levels of parallelism. The author introduces the concept of delayed split-issue and the dynamic scheduling hardware which, together, solve the compatibility problem for VLIW processors and, in fact, make it possible for such processors to use all of the interlocking and scoreboarding techniques that are known for superscalar processors.>

The problem of optimizing the sequential algorithm for the Boltzmann machine (BM) is addressed. A solution that is based on the locality properties of the algorithm and makes possible the efficient computation of the cost difference between two configurations is presented. Since the algorithm performance depends on the number of accepted state transitions in the annealing process, a theoretical procedure is formulated to estimate the acceptance probability of a state transition. In addition, experimental data are provided on a well-known optimization problem travelling salesman problem to have a numerical verification of the theory, and to show that the proposed solution obtains a speedup between 3 and 4 in comparison with the traditional algorithm.

The demand of increasing computation power for symbolic processing has given a strong impulse to the development of ASICs dedicated to the execution of prolog. Unlike past microcoded implementation based on the Warren machine model, novel trends in high performance Prolog processors suggest the implementation of RISC-based processors committed to prolog only through the adoption of a few basic dedicated features, like the Berkeley Abstract Machine (BAM) processor.Following the idea of using a smart compiler for a simple instruction set, the SYMBOL project represents an experiment in applying global compaction techniques and VLIW design philosophy to the static exploitation of instruction-level parallelism in Prolog.This paper presents code analysis results and shows how we can approach the theoretical speed-up limit (about 3) imposed by Amdahl's law on shared memory models, by means of global code optimizations and a suitable architectural support. In addition, we show implementation details and some preliminary data of a VLSI prototype architecture.

A router based on a tile-expansion algorithm and corner stitching data structure is presented. This program finds connections with a minimum number of jogs and it ensures that a possible solution will be found. Using a working tree, it allows an exhaustive and recursive search along all available areas for routing. The connections are made going back through the working tree until the starting terminal is reached. There are two Manhattan layers that the user can choose for each direction to implement connections; the router can be used to wire hierarchical blocks using a chip planning methodology. The program has been successfully tested on examples concerning different classes of problems.