Power-aware scheduling of periodic tasks in real-time systems has been extensively studied to save energy while still meeting the performance requirement. Many previous studies use the probability information of tasks' execution cycles to assist the scheduling. However, most of these approaches adopt heuristic algorithms to cope with realistic CPU models with discrete frequencies and cannot achieve the globally optimal solution. Sometimes they even show worse results than non-stochastic DVS schemes. This paper presents an optimal DVS scheme for frame-based real-time systems under realistic power models in which the processor provides only a limited number of speeds and no assumption is made on power/frequency relation. A suboptimal DVS scheme is also presented in this paper to work out a solution near enough to the optimal one with only polynomial time expense. Experiment results show that the proposed algorithm can save at most 40% more energy compared with previous ones.

This paper presents a single-chip RF tuner/OFDM demodulator for a mobile digital TV application called “1-segment broadcasting.” To achieve required performances for the single-chip receiver, a tunable technique for a low-noise amplifier (LNA) and spurious suppression techniques are proposed in this paper. Firstly, to receive all channels from 470 MHz to 770 MHz and to relax distortion characteristics of following circuit blocks such as an RF variable-gain amplifier and a mixer, a tunable technique for the LNA is proposed. Then, to improve the sensitivity, spurious signal suppression techniques are also proposed. The single-chip receiver using the proposed techniques is fabricated in 90 nm CMOS technology and total die size is 3.26 mm 3.26 mm. Using the tunable LNA and suppressing undesired spurious signals, the sensitivities of less than -98.6 dBm are achieved for all the channels.

Multi-site MIMO (Multiple Input Multiple Output) is a key technology that will enable next generation cellular networks to achieve high throughput in cell edge areas. However, a multi-site single-user MIMO system is subject to performance degradation in terms of cell throughput due to the expense of additional assignments of radio resources to cell edge user equipment. This paper presents a BS-cooperation scheduling scheme for a multi-site single-user MIMO cellular system. The proposed BS-cooperation scheduling scheme aims to maintain cell throughput while improving cell edge user throughput. The proposed scheme employs two policies with respect to the assignment of radio resource to the user equipment with multi-site connection. One is to control the opportunities for radio resource assignment to user equipment with a multi-site connection to avoid the excessive assignment of radio resources and to maintain cell throughput. The other policy governs the decision as to whether the user equipment operates with a multi-site connection or not, making it possible for the multi-site connection to contribute to the improvement in user throughput in the cell edge areas. The simulation results show that the proposed scheme is effective from the perspective of both cell throughput and cell edge user throughput.

This paper presents a 7 GHz differential current-reused voltage-controlled oscillator (CR-VCO) with low power consumption and low phase noise using 0.18-µm CMOS technology. The output power of this CR-VCO is enhanced by utilizing a trifilar-transformer-feedback technique. The lower phase noise is achieved by the more symmetric voltage swings resulting from the improved balance of switching current. At a 1.5-V DC supply voltage, the power dissipation is only 3.4 mW. The total tuning range is 1.4 GHz (17.9%) as the tuning voltage ranges from 0 V to 1.8 V. The optimum phase noise is around -117.3 dBc/Hz at a frequency offset of 1 MHz from the center frequency of 7.07 GHz. The corresponding output power is around -6.8 dBm. For the proposed CR-VCO, the calculated figures-of-merit, FOM and FOMT , are -188.9 and -193.9 dBc/Hz, respectively.

In multi-hop wireless networks, the transmitted signal is generally forwarded over several relay terminals. So, the quality of communications is degraded due to these re-transmissions over fading channels in relay terminals. Basically, the conventional cooperative relaying scheme based on cyclic delay diversity (CDD) reduces this degradation because this scheme could have numerous relay terminals which simultaneously transmit the signals. However, we cannot obtain the maximum diversity gain because of the re-transmission without considering relay channel environments. In this letter, to overcome the decreased performance, we propose an adaptive decode-and-forward (DF) relaying scheme based on CDD which uses cyclic redundancy check (CRC) code. Simulation results show that the proposed scheme provides more improvement in error performance than the conventional schemes in multi-hop networks.

In deep-submicron era, wire delay is becoming a bottleneck while pursuing even higher system clock speed. Several distributed register (DR) architectures have been proposed to cope with this problem by keeping most wires local. In this article, we propose a new resource-constrained communication synthesis algorithm for optimizing both inter-island connections (IICs) and latency targeting on distributed register-file microarchitecture (DRFM). The experimental results show that up to 24.7% and 12.7% reduction on IIC and latency can be achieved respectively as compared to the previous work.

The influence of quantization scaling is seldom considered in narrow band (NB) communications, because a high resolution analogue-to-digital converter (ADC) can be generally employed. In ultra-wideband (UWB) systems, however, the resolution of ADC is required to be low to reduce complexity, cost and power consumption. Consequently, the influence of quantization scaling is significant and should be taken into account. In this letter, effects of quantization scaling are analyzed in terms of signal to noise ratio (SNR) loss based on an uniformly distributed random signal model. For the effects of quantization scaling on bit error rate (BER) performance, however, theoretical analysis is too complicated since quantization is a nonlinear operation, hence we employ here a simulation method. The simulation results show there exists an optimum scaling to minimize BER performance for a fixed-resolution receiver; the optimum scaling power is related to the SNR of input noisy signal and the resolution of ADC.

Linear discriminant analysis (LDA) is one of the well-known schemes for feature extraction and dimensionality reduction of labeled data. Recently, two-dimensional LDA (2DLDA) for matrices such as images has been reformulated into symmetric 2DLDA (S2DLDA), which is solved by an iterative algorithm. In this paper, we propose a non-iterative S2DLDA and experimentally show that the proposed method achieves comparable classification accuracy with the conventional S2DLDA, while the proposed method is computationally more efficient than the conventional S2DLDA.

Power-aware X-filling is a preferable approach to avoiding IR-drop-induced yield loss in at-speed scan testing. However, the ability of previous X-filling methods to reduce launch switching activity may be unsatisfactory, due to low effect (insufficient and global-only reduction) and/or low scalability (long CPU time). This paper addresses this reduction quality problem with a novel GA (Genetic Algorithm) based X-filling method, called GA-fill. Its goals are (1) to achieve both effectiveness and scalability in a more balanced manner and (2) to make the reduction effect of launch switching activity more concentrated on critical areas that have higher impact on IR-drop-induced yield loss. Evaluation experiments are being conducted on both benchmark and industrial circuits, and the results have demonstrated the usefulness of GA-fill.

There are a great amount of various resources described in many different ways for service oriented grid environment, while traditional grid resource discovery methods could not fit more complex future grid system. Therefore, this paper proposes a novel grid resource discovery method based on association rule hypergraph partitioning algorithm which analyzes user behavior in history transaction records to provide personality service for user. And this resource discovery method gives a new way to improve resource retrieval and management in grid research.

The separation and localization of sound source signals are important techniques for many applications, such as highly realistic communication and speech recognition systems. These systems are expected to work without such prior information as the number of sound sources and the environmental conditions. In this paper, we developed a dodecahedral microphone array and proposed a novel separation method with our developed device. This method refers to human sound localization cues and uses acoustical characteristics obtained by the shape of the dodecahedral microphone array. Moreover, this method includes an estimation method of the number of sound sources that can operate without prior information. The sound source separation performances were evaluated under simulated and actual reverberant conditions, and the results were compared with the conventional method. The experimental results showed that our separation performance outperformed the conventional method.

We propose a design optimization flow for a high-speed and low-power operational transconductance amplifier (OTA) using a gm/ID lookup table design methodology in scaled CMOS. This methodology advantages from using gm/ID as a primary design parameter to consider all operation regions including strong, moderate, and weak inversion regions, and enables the lowest power design. SPICE-based lookup table approach is employed to optimize the operation region specified by the gm/ID with sufficient accuracy for short-channel transistors. The optimized design flow features 1) a proposal of the worst-case design scenario for specification and gm/ID lookup table generations from worst-case SPICE simulations, 2) an optimization procedure accomplished by the combination of analytical and simulation-based approaches in order to eliminate tweaking of circuit parameters, and 3) an additional use of gm/ID subplots to take second-order effects into account. A gain-boosted folded-cascode OTA for a switched capacitor circuit is adopted as a target topology to explore the effectiveness of the proposed design methodology for a circuit with complex topology. Analytical expressions of the gain-boosted folded-cascode OTA in terms of DC gain, frequency response and output noise are presented, and detailed optimization of gm/IDs as well as circuit parameters are illustrated. The optimization flow is verified for the application to a residue amplifier in a 10-bit 125 MS/s pipeline A/D converter implemented in a 0.18 µm CMOS technology. The optimized circuit satisfies the required specification for all corner simulations without additional tweaking of circuit parameters. We finally explore the possibility of applying this design methodology as a technology migration tool, and illustrate the failure analysis by comparing the differences in the gm/ID characteristics.

With the aim to improve the effectiveness of SAWSDL service discovery, this paper proposes a novel discovery method for SAWSDL services, which is based on the matchmaking of so-called fine-grained data semantics that is defined via sets of atomic elements with built-in data types. The fine-grained data semantics can be obtained by a transformation algorithm that decomposes parameters at message level into a set of atomic elements, considering the characteristics of SAWSDL service structure and semantic annotations. Then, a matchmaking algorithm is proposed for the matching of fine-grained data semantics, which avoids the complex and expensive structural matching at the message level. The fine-grained data semantics is transparent to the specific data structure of message-level parameters, therefore, it can help to match successfully similar Web services with different data structures of parameters. Moreover, a comprehensive measure is proposed by considering together several important components of SAWSDL service descriptions at the same time. Finally, this method is evaluated on SAWSDL service discovery test collection SAWSDL-TC2 and compared with other SAWSDL matchmakers. The experimental results show that our method can improve the effectiveness of SAWSDL service discovery with low average query response time. The results imply that fine-grained parameters fit to represent the data semantics of SAWSDL services, especially when data structures of parameters are not important for semantics.

Based on sliding-window rule application and extraction filtering, we present a framework for extracting multi-slot frames describing chemical reactions from Thai free text with unknown target-phrase boundaries. A supervised rule learning algorithm is employed for automatic construction of pattern-based extraction rules from hand-tagged training phrases. A filtering method is devised for removal of incorrect extraction results based on features observed from text portions appearing between adjacent slot fillers in source documents. Extracted reaction frames are represented as concept expressions in description logics and are used as metadata for document indexing. A document knowledge base supporting semantics-based information retrieval is constructed by integrating document metadata with domain-specific ontologies.

A 1.8 V, 5 GHz low power frequency synthesizer for Wireless Sensor Networks is presented in 0.18 µm CMOS technology. A low power phase-switching prescaler is designed, and the current mode phase rotator is merged into the first divide-by-2 circuit of the prescaler to reduce power and propagation delay. An improved charge pump circuit is proposed to compensate for the dynamic effects with the charge pump. By a divide-by-2 circuit, the frequency synthesizer can provide a 2.324-2.714 GHz quadrature output frequency in 1 MHz steps with a 4 MHz reference frequency. The measured output phase noise is -110 dBc/Hz at 1-MHz offset frequency. The power consumption of the PLL is 11.2 mW at 1.8 V supply voltage.

This paper presents a robust framework of human-computer interaction from the hand gesture vision in the presence of realistic and challenging scenarios. To this end, several novel components are proposed. A hybrid approach is first proposed to automatically infer the beginning position of hand gestures of interest via jointly optimizing the regions given by an offline skin model trained from Gaussian mixture models and a specific hand gesture classifier trained from the Adaboost technique. To consistently track the hand in the context of using kernel based tracking, a semi-supervised feature selection strategy is further presented to choose the feature subspaces which appropriately represent the properties of offline hand skin cues and online foreground-background-classification cues. Taking the histogram of oriented gradients as the descriptor to represent hand gestures, a soft-decision approach is finally proposed for recognizing static hand gestures at the locations where severe ambiguity occurs and hidden Markov model based dynamic gestures are employed for interaction. Experiments on various real video sequences show the superior performance of the proposed components. In addition, the whole framework is applicable to real-time applications on general computing platforms.

In this paper, we study opacity-enforcing supervisory control of discrete event systems. We consider the case that the secrete behavior of the system is specified by multiple secret languages, and synthesize a maximally permissive supervisor that enforces opacity for all secret languages. We prove that, under a certain assumption on observable and uncontrollable events, a maximally permissive opacity-enforcing supervisor can be synthesized in a modular fashion.

Wide-band noise modulation is added to the adaptive scan technique for spaceborne rain radar. The performance of this technique is studied by simulation using one month of TRMM (Tropical Rainfall Measuring Mission) Precipitation Radar (PR) data from the viewpoints of improving the sensitivity and reducing power consumption. The results show that the adaptive scan technique with wide-band noise modulation uses about 25% less energy than the conventional scanning technique. The adaptive scan using wide-band noise modulation is more effective than that using a normal pulse for localized rainy areas. Surface data as well as rainfall data can be obtained by using the adaptive scan using wide-band noise modulation.

Scalability and availability are the key features of parallel database systems. To realize scalability, many dynamic load-balancing methods with data placement and parallel index structures on shared-nothing parallel infrastructure have been proposed. Data migration with range-partitioned placement using a parallel Btree is one solution. The combination of range partitioning and chained declustered replicas provides high availability (HA) while preserving scalability. However, independent treatment of the primary and backup data in each node requires long failover times. We propose a novel method for the compound treatment of chained declustered replicas using a parallel Btree, termed the Fat-Btree. In the proposed method, a single Fat-Btree provides access paths to both the primary and backup data of all processor elements (PEs), which greatly reduces failover time. Moreover, these access paths overlap between two neighboring PEs, which enables dynamic load balancing without physical data migration by dynamically redirecting the access paths. In addition, this compound treatment improves memory space utilization to enable index processing with good scalability. Experiments using PostgreSQL on a 160-node PC cluster demonstrate the effectiveness of the high scalability and availability of our proposed method.

Recently, to track and relate news documents from several sources, association rule mining has been applied due to its performance and scalability. This paper presents an empirical investigation on how term representation basis, term weighting, and association measure affects the quality of relations discovered among news documents. Twenty four combinations initiated by two term representation bases, four term weightings, and three association measures are explored with their results compared to human judgment of three-level relations: completely related, somehow related, and unrelated relations. The performance evaluation is conducted by comparing the top-k results of each combination to those of the others using so-called rank-order mismatch (ROM). The experimental results indicate that a combination of bigram (BG), term frequency with inverse document frequency (TFIDF) and confidence (CONF), as well as a combination of BG, TFIDF and conviction (CONV), achieves the best performance to find the related documents by placing them in upper ranks with 0.41% ROM on top-50 mined relations. However, a combination of unigram (UG), TFIDF and lift (LIFT) performs the best by locating irrelevant relations in lower ranks (top-1100) with 9.63% ROM. A detailed analysis on the number of the three-level relations with regard to their rankings is also performed in order to examine the characteristic of the resultant relations. Finally, a discussion and an error analysis are given.