Catálogo de publicaciones - libros

In this paper, we proposed a processor architecture that is suitable for next generation embedded applications, especially for personal information devices such as smart phones, PDAs, and handheld computers. Latest high performance embedded processors are developed to achieve high clock speed. Because increasing performance makes design more difficult and induces large overhead, architectural evolution in embedded processor field is necessary. Among more enhanced processor types, out-of-order superscalar cannot be a candidate for embedded applications due to its excessive complexity and relatively low performance gain compared to its overhead. Therefore, new architecture with moderate complexity must be designed. In this paper, we developed a low-cost SMT architecture model and compared its performance to other architectures including scalar, superscalar and multiprocessor. Because current personal information devices have a tendency to execute multiple tasks simultaneously, SMT or CMP can be a good choice. And our simulation result shows that the efficiency of SMT is the best among the architectures considered.

In this paper, we proposed an image sharing method adopting (, ) threshold scheme. The secret image goes through Vector Quantization (VQ) scheme and permutes the locations of indices to obtain permuted indexed secret image. We select indices to form a (-1)-degree polynomial by taking indices as its coefficients. Then, the values of blocks’ indices in cover image are fed into the (-1)-degree polynomial to get the output values. After embedding the output values back to the pixels in block, we can obtain meaningful shadow images. Any out of shadow images can reconstruct the permuted indexed secret image. By inversing permutation and decoding VQ indices, we can finally reconstruct the secret image. Experimental results show that our method can get high image quality for the resultant shadow images and reconstruct secret images as well.

Event-driven, embedded applications that embody the composition of many disparate components are emerging as an important class of pervasive applications. For such applications, realizing solutions often requires a breadth of expertise. Consequently, managing the solution life cycle can be a very complex, time-intensive process. In this paper, we present a framework that eases the complexity of managing the life cycle of event-driven, pervasive solutions. We call this framework Rapid Integrated Solution Enablement or RISE. Component composition and software reuse are two central concepts of RISE, where solutions are graphically composed from reusable components using a visual editor. We describe the RISE architecture and discuss an initial prototype implementation that leverages open source technologies, such as Eclipse. Additionally, we illustrate the efficacy of RISE with an example solution for RFID supply chain logistics.

ASIPs are designed specifically for a particular application or a set of applications. Their instruction sets must be carefully tailored to provide high performance as well as to meet non-functional constraints such as silicon area and power consumption. Traditionally, evaluation of different candidate instruction sets is all carried out through simulation. However, the growing design complexity and time-to-market pressure have rendered simulation increasingly infeasible. In this paper, we present an instruction level modeling method that can rapidly evaluates several important aspects of a selected instruction set. Experimental results show that we can prune a large number of candidate instruction sets with the model, accelerate design space exploration and alleviate the pressure on simulation.

Previous research shows that there are two architectures for speech-to-speech translation (S2ST) system implementation. One is client-server based systems that should be built on the server computer but not available anytime or anywhere. The other is to build portable stand-alone devices but lacks the real-time performance. Therefore, this work presents an embedded system design for portable S2ST applications. This system is characterized by small size, low cost, real-time operation, and high portability. For realization of the proposed S2ST system, this work designs the ARM-based SoPC architecture, the speech translation intellectual property, and software procedures of the proposed SoPC. The entire design was implemented on ALTERA EPXA10. The English-to-Mandarin translation process can be completed within 0.5 second at a 40 MHz clock frequency with 1,200 translation patterns. The maximum frequency is 46.22 MHz, and the usage of logic elements is 19,318 (50% of the total logic elements of the EPXA10 device).

As a result of growth of sensor-enabled mobile devices such as PDA, cellular phone and other computing devices, in recent years, users can utilize the diverse digital contents everywhere and anytime. However, the interfaces of mobile applications are often unnatural due to limited resources and miniaturized input/output. Especially, users may feel this problem in some applications such as the mobile game. Therefore, novel interaction forms have been developed in order to complement the poor user interface of the mobile device and to increase the interest for the mobile game. In this paper, we describe the demonstration of the gesture and posture input supported by an accelerometer. The application example we created are AM-Fishing game on the mobile device that employs the accelerometer as the main interaction modality. The demos show the usability for the gesture and posture interaction.

Within the last decade the development of new technologies in the multimedia sector has advanced with stunning pace. Due to the availability of high-capacity mass storage devices at low cost private multimedia libraries containing digital video and audio items have recently gained popularity. Although attached meta-data like title, actor’s/actress’ name and creation time eases the task of finding preferred contents, it is still difficult to find a specific part within a movie one enjoyed before by remembering the time code. In this paper we introduce the BROAFERENCE system that provides a solution for the above problem. We propose meta-data creation based on recorded user experience derived from facial expressions containing joy, sadness and anger events as well as interest focus data. In the following the system layout, functionality and conducted experiments for system verification will be introduced to the reader.

The main obstacles to grid file management come from the fact that grid file resources are typically stored in heterogeneous and distributed environment and accessed through various protocols. In this paper, we propose a grid file management system called Vega [1][2] Hotfile2 for data-intensive application in widely distributed systems and grid environments. Widely distributed and heterogeneous storage resource can converge into a single uniform storage resource using virtualization techniques in Hotfile2. It is a grid middleware provides a uniform file resources view and a high level interface to access widely distributed and heterogeneous data resources. Presented here are two services that we believe are fundamental to any grid file management system: high-performance, secure transport and metadata management. In this paper, we discuss many aspects of our design and implementation in Hotfile2, present the file system interface designed to support distributed applications such as batch job. Experiments are done to illustrate its performance, extensibility, and various other features.

In this study, we suggest and implement Multi-Modal Sentential Dialog System (MMSDS) integrating 2 sensory channels with speech and haptic information based on ubiquitous computing and WWW for clear communication. The importance and necessity of MMSDS for HCI as following: 1) it can allow more interactive and natural communication functions between the hearing-impaired and hearing person without special learning and education, 2) according as it recognizes a sentential Korean Standard Sign Language (KSSL) which is represented with speech and haptics and then translates recognition results into a synthetic speech and visual illustration in real-time, it may provide a wider range of personalized and differentiated information more effectively to them, and 3) above all things, a user need not be constrained by the limitations of a particular interaction mode at any given moment because it can guarantee mobility of WPS (Wearable Personal Station for the post PC) with a built-in sentential sign language recognizer. In experiment results, while an average recognition rate of uni-modal recognizer using KSSL only is 93.1% and speech only is 95.5%, advanced MMSDS deduced an average recognition rate of 96.1% for 32 sentential KSSL recognition models.

A Speech and Character Combined Recognition Engine (SCCRE) is developed for working on Personal Digital Assistants (PDA) or on mobile devices. In SCCRE, feature extraction from speech and character is carried out separately, but recognition is performed in an engine. The recognition engine employs essentially CHMM (Continuous Hidden Markov Model) structure and this CHMM consists of variable parameter topology in order to minimize the number of model parameters and reduce recognition time. This model also adopts our proposed SSMS (Successive State and Mixture Splitting) for generating context independent model. SSMS optimizes the number of mixtures through splitting in mixture domain and the number of states through splitting in time domain. When we applied our developed engine which adopts SSMS to speech recognition for mobile devices, SSMS can reduce total number of Gaussian up to 40.0% compared with the fixed parameter models at the same recognition performance. This leads that SSMS can reduce the size of memory for models to 65% and that for processing to 82%. Moreover, recognition time decreases 17% with SSMS model but still maintains the recognition rate.