A high-throughput on-chip monitoring circuit with a digital output is proposed for the variations of the NMOS and PMOS threshold voltages. A voltage-controlled delay line (VCDL) and a time-to-digital converter (TDC) are used to convert a small difference in analog voltage into a large difference in time delay. This circuit was applied to the transistors of W = 10 µm and L = 0.18 µm in a 1616 array matrix fabricated with a 0.18-µm process. The measurement of the threshold voltage shows that the maximum peak-to-peak intra-chip variation of NMOS and PMOS transistors are about 31.7 mV and 32.2 mV, respectively, for the temperature range from -25 to 75. The voltage resolutions of NMOS and PMOS transistors are measured to be 1.10 mV/bit and 3.53 mV/bit at 25, respectively. The 8-bit digital code is generated for the threshold voltage of a transistor in every 125 ns, which corresponds to the 8-MHz throughput.

This paper presents a novel parallel boost converter using switched capacitors The switches are controlled not only by periodic clock but also by voltage-mode threshold that is a key to realize strong stability, fast transient and variable output. The dynamics is described by a piecewise linear equation, the mapping procedure is applicable and the system operation can be analyzed precisely.

This paper provides an investigation of power distribution network (PDN) performance by a full-wave prediction tool and by experimental measurements. A set of six real boards characterized by increasing complexity is considered in order to establish a solid base for behaviour understanding of printed circuit boards. How the growing complexity impacts on the board performance is investigated by measurements and by simulations. Strengths and weakness of PDN modeling by the full-wave software tool Microwave Studio are highlighted and discussed.

The optical access fiber network is spreading rapidly as a result of the progress made on optical communication technologies and the availability of a wide range of broadband Internet content. If the optical access network is not properly maintained, the service quality will decrease. This paper describes some effective technologies that have been researched and developed to maintain a high quality of service, and to achieve efficient maintenance and operation.

In this paper, a microstrip lowpass filter using hairpin structure and Chip-Capacitor is proposed. Firstly, the LPF with one hairpin element is briefly designed and optimized with LC prototype structure using circuit simulator. With the capacitor loaded the proposed LPF illustrates the sharp attenuation performance near the cut-off frequency and the wideband rejection characteristics. Then, in order to improve the stopband attenuation the three-hairpin LPF is studied. By optimazing its design the attenuation is improved by 32 dB.

We have so far proposed a speaking-aid system for laryngectomees using a statistical voice conversion technique. In the proposed system, artificial speech articulated with extremely small sound source signals is detected with a Non-Audible Murmur (NAM) microphone, and then, the detected artificial speech is converted into more natural voice in a probabilistic manner. Although this system basically allows laryngectomees to speak while keeping the external source signals silent, it is still questionable how much these new sound source signals affect the converted speech quality. In this paper, we investigate the impact of various sound source signals on voice conversion accuracy. Various small sound source signals are designed by changing the spectral envelope and the waveform power independently. We conduct objective and subjective evaluations. The results of these experimental evaluations demonstrate that voice conversion accepts 1) various sound source signals with different spectral envelopes and 2) large degree of power of the sound source signals unless the power of speaking parts is almost equal to that of silence parts. Moreover, we also investigate the effectiveness of enhancing auditory feedback during speaking with the extremely small sound source signals.

A method to realize the fine frequency-tuning steps using tiny capacitors instead of Metal-Insulator-Metal (MIM) capacitors is proposed for a digitally controlled oscillator (DCO). The tiny capacitors are realized by the coplanar transmission lines which are arranged unsymmetrical in a 6 metal layers (M6) foundry of 0.18 µm CMOS technology. These transmission line based capacitors are designed by using electro-magnetic field simulator, and co-designed by using SPICE simulator. Finally, these capacitors are employed to design 15 bit DCO and fabricated the proposed DCO in 0.18 µm CMOS technology, and tested. The measured phase noise of DCO was -118.3 dBc/Hz (@1 MHz offset frequency), and the oscillating frequency tuned from 4.86 GHz to 5.36 GHz in the minimum frequency-tuning step of 18 kHz.

This paper proposes a pattern partitioning algorithm that maps multiple target patterns onto homogeneous memory-based string matchers. The proposed algorithm adopts the greedy search based on lexicographical sorting. By mapping as many target patterns as possible onto each string matcher, the memory requirements are greatly reduced.

A low-voltage operational capability near 1 V along with low noise and distortion characteristics have been realized in a passive sigma-delta modulator. To achieve low-voltage operation, the dc voltage in signal paths in the switched-capacitor-filter section was set to be 0.2 V so that sufficient gate-to-source voltages were obtained for metal-oxide-semiconductor (MOS) switches in signal paths without using a gate-voltage boosting technique. In addition, the input switch that connects the input signal from the outside to the inside of an integrated circuit chip was replaced by a passive resistor to eliminate a floating switch, and gain coefficients in the feedback and input paths were modified so that the bias voltage of the digital-to-analog converter could be set to VDD and 0 V to easily activate MOS switches. As the signal swing becomes small under low-voltage operational circumstances, correlated double sampling was used to suppress the offset voltage and the 1/f noise that appeared at the input of a comparator. The modulator was fabricated using a standard CMOS 0.18-µm process, and the measured results show that the modulator realized 77 dB of dynamic range for 40 kHz of signal bandwidth with a 40 MHz sampling rate while dissipating 2 mW from a 1.1 V supply voltage.

Context-aware systems detect user's physical and social contexts based on sensor networks, and provide services that adapt to the user accordingly. Representing, detecting, and managing the contexts are important issues in context-aware systems. Composition of contexts is a useful method for these works, since it can detect a context by automatically composing small pieces of information to discover service. Danger-aware services are a kind of context-aware services which need description of relations between a user and his/her surrounding objects and between users. However when applying the existing composition methods to danger-aware services, they show the following shortcomings that (1) they have not provided an explicit method for representing composition of multi-user' contexts, (2) there is no flexible reasoning mechanism based on similarity of contexts, so that they can just provide services exactly following the predefined context reasoning rules. Therefore, in this paper, we propose a two-stage composition method based on context similarity to solve the above problems. The first stage is composition of the useful information to represent the context for a single user. The second stage is composition of multi-users' contexts to provide services by considering the relation of users. Finally the danger degree of the detected context is computed by using context similarity between the detected context and the predefined context. Context is dynamically represented based on two-stage composition rules and a Situation theory based Ontology, which combines the advantages of Ontology and Situation theory. We implement the system in an indoor ubiquitous environment, and evaluate the system through two experiments with the support of subjects. The experiment results show the method is effective, and the accuracy of danger detection is acceptable to a danger-aware system.

This paper presents an enhanced dual-path delta-sigma analog-to-digital converter. Compared with other architectures, the enhanced architecture increases the noise shaping order without any instability problems and displays analog complexity equivalent to the multi-stage noise shaping architecture. Our delta-sigma converter is based on this new architecture. It employs not only doubly-differential structure to reduce common-mode errors in the system-level but also delayed-feed-in structure to mitigate the timing constraint of the feedback signal. Regarding the circuit implementation, the first-order enhancement of the quantization noise shaping is achieved via the use of a switched capacitor circuit technique. The circuit is incorporated into the active adder in a low-distortion structure. The supporting clock generation circuit that provides additional phases of clocks with the enhancement block is also implemented in the CMOS logic gates. A digital dynamic element matching circuit (i.e., segmented data-weighted-average circuit) is designed to reduce mismatch errors caused by the feedback DAC of modulator. A test chip, fabricated in a 0.18-µm CMOS process, provides a signal-to-noise+distortion ratio (SNDR) of 75-dB for a 1.0-MHz signal bandwidth clocked at 40-MHz. The 2nd harmonic is -101 dB and the 3rd harmonic is -94 dB when a -4.5-dB 100-kHz input signal is applied.

In ubiquitous sensor networks, the estimation accuracy of a node location is limited due to the presence of non-line-of-sight (NLOS) paths. To mitigate the NLOS effects, this letter proposes a simple algorithm where NLOS identification is carried out using angle-of-arrival (AOA). Simulation results show that the use of AOA improves NLOS identification rates and location estimation accuracy.

In this paper we present a study on the design optimization of voltage-controlled oscillators. The phase noise of LC-type oscillators is basically limited by the quality factor of inductors. It has been experimentally shown that higher-Q inductors can be achieved at higher frequencies while the oscillation frequency is limited by parasitic capacitances. In this paper, the minimum transistor size and the degradation of the quality factor caused by a switched-capacitor array are analytically estimated, and the maximum oscillation frequency of VCOs is also derived from an equivalent circuit by considering parasitic capacitances. According to the analytical evaluation, the phase noise of a VCO using a 65 nm CMOS is 2 dB better than that of a 180 nm CMOS.

We consider the problem of fast identification of high-rate flows in backbone links with possibly millions of flows. Accurate identification of high-rate flows is important for active queue management, traffic measurement and network security such as detection of distributed denial of service attacks. It is difficult to directly identify high-rate flows in backbone links because tracking the possible millions of flows needs correspondingly large high speed memories. To reduce the measurement overhead, the deterministic 1-out-of-k sampling technique is adopted which is also implemented in Cisco routers (NetFlow). Ideally, a high-rate flow identification method should have short identification time, low memory cost and processing cost. Most importantly, it should be able to specify the identification accuracy. We develop two such methods. The first method is based on fixed sample size test (FSST) which is able to identify high-rate flows with user-specified identification accuracy. However, since FSST has to record every sampled flow during the measurement period, it is not memory efficient. Therefore the second novel method based on truncated sequential probability ratio test (TSPRT) is proposed. Through sequential sampling, TSPRT is able to remove the low-rate flows and identify the high-rate flows at the early stage which can reduce the memory cost and identification time respectively. According to the way to determine the parameters in TSPRT, two versions of TSPRT are proposed: TSPRT-M which is suitable when low memory cost is preferred and TSPRT-T which is suitable when short identification time is preferred. The experimental results show that TSPRT requires less memory and identification time in identifying high-rate flows while satisfying the accuracy requirement as compared to previously proposed methods.

A multiple-input switched-capacitor DC-DC converter which can realize long battery runtime is proposed in this letter. Unlike conventional converters for a back-lighting application, the proposed converter drives some LEDs by converting energy from solar cells. Furthermore, the proposed converter can charge a lithium battery when an output load is light. The validity of circuit design is confirmed by theoretical analyses, simulations, and experiments.

This paper presents an IP performance management system having the triple frameworks of performance measurement, topology monitoring and data analysis. The system infers the causal location of the performance degradation with a network tomographic approach. Since the Internet is still highly prone to performance deterioration due to congestion, router failure, and so forth, not only detecting performance deterioration, but also monitoring topology and locating the performance-degraded segments in real-time is vital to ensure that Internet Service Providers can mitigate or prevent such performance deterioration. The system is implemented and evaluated through a real-world experiment and its considerable potential for practical network operations is demonstrated.

In this letter, we develop an anycast-based emergency service for healthcare wireless sensor networks. The new service could operate with sensors to detect and activate an alarm system based on predefined conditions that are specific to the patient and the disease. The new service is implemented on 802.15.4 ZigBee which usually has large control overhead and long transmission times. To improve the service performance, our service identifies the closest emergency service provider to alleviate the control overhead and achieve immediate assistance when a patient requests for an emergency service. We also increase the reliability of packet transmission by using a Recovery Point scheme. Our simulations and experiment demonstrate that our scheme is efficient and feasible for healthcare wireless sensor networks.

With the progress of ubiquitous technology, ubiquitous learning presents new opportunities to learners. Situations of a learner can be grasped through analyzing the learner's actions collected by sensors, RF-IDs, or cameras in order to provide support at proper time, proper place, and proper situation. Training for acquiring skills and enhancing physical abilities through exercise and experience in the real world is an important domain in u-learning. A training program may last for several days and has one or more training units (exercises) for a day. A learner's performance in a unit is considered as short term state. The performance in a series of units may change with patterns: progress, plateau, and decline. Long term state in a series of units is accumulatively computed based on short term states. In a learning/training program, it is necessary to apply different support strategies to adapt to different states of the learner. Adaptation in learning support is significant, because a learner loses his/her interests easily without adaptation. Systems with the adaptive support usually provide stimulators to a learner, and a learner can have a great motivation in learning at beginning. However, when the stimulators reach some levels, the learner may lose his/her motivation, because the long term state of the learner changes dynamically, which means a progress state may change to a plateau state or a decline state. In different long term learning states, different types of stimulators are needed. However, the stimulators and advice provided by the existing systems are monotonic without changeable support strategies. We propose a mutual adaptive support. The mutual adaptation means each of the system and the learner has their own states. On one hand, the system tries to change its state to adapt to the learner's state for providing adaptive support. On the other hand, the learner can change its performance following the advice given based on the state of the system. We create a ubiquitous pet (u-pet) as a metaphor of our system. A u-pet is always with the learner and encourage the leaner to start training at proper time and to do training smoothly. The u-pet can perform actions with the learner in training, change its own attributes based on the learner's attributes, and adjust its own learning rate by a learning function. The u-pet grasps the state of the learner and adopts different training support strategies to the learner's training based on the learner's short and long term states.

This paper describes diffusion of electric vehicles and novel social infrastructure from the viewpoint of systems innovation theory considering both human society aspects and elemental technological aspects. Firstly, fundamentals of the systems innovation theory and the platform theory are mentioned. Secondly, discussion on mobility from the viewpoint of the human-society layer and discussion of electrical vehicles from the viewpoint of the elemental techniques are carried out. Thirdly, based on those, R & D, measures are argued such as establishment of the ubiquitous noncontact feeding and authentication payment system is important. Finally, it is also insisted that after the establishment of this system the super smart grid with temporal and spatial control including demand itself with the low social cost will be expected.

Wireless sensor networks with a star network topology are commonly applied for health monitoring systems. To determine the condition of a patient, sensor nodes are attached to the body to transmit the data to a coordinator. However, this process is inefficient because the coordinator is always communicating with each sensor node resulting in a data processing workload for the coordinator that becomes much greater than that of the sensor nodes. In this paper, a method is proposed to reduce the number of data transmissions from the sensor nodes to the coordinator by establishing a threshold for data from the biological signals to ensure that only relevant information is transmitted. This results in a dramatic reduction in power consumption throughout the entire network.