This paper proposes a scatterer information estimation method using numerical data for the response waveform of a backward transient scattering field for both E- and H-polarizations when a two-dimensional (2-D) coated metal cylinder is selected as a scatterer. It is assumed that a line source and an observation point are placed at different locations. The four types of scatterer information covered in this paper are the relative permittivity of a surrounding medium, the relative permittivity of a coating medium layer and its thickness, and the radius of a coated metal cylinder. Specifically, a time-domain saddle-point technique (TD-SPT) is used to derive scatterer information estimation formulae from the amplitude intensity ratios (AIRs) of adjacent backward transient scattering field components. The estimates are obtained by substituting the numerical data of the response waveforms of the backward transient scattering field components into the estimation formulae and performing iterative calculations. Furthermore, a minimum thickness of a coating medium layer for which the estimation method is valid is derived, and two kinds of applicable conditions for the estimation method are proposed. The effectiveness of the scatterer information estimation method is verified by comparing the estimates with the set values. The noise tolerance and convergence characteristics of the estimation method and the method of controlling the estimation accuracy are also discussed.

Wireless technology improvements have been continually increasing, resulting in greater needs for system design and implementation to accommodate all newly emerging standards. As a result, developing a system that ensures compatibility with numerous wireless systems has sparked interest. As a result of their flexibility and scalability over alternative wireless design options, software-defined radios (SDRs) are highly motivated for wireless device modelling. This research paper delves into the difficulties of designing a reconfigurable multi modulation baseband modulator for SDR systems that can handle a variety of wireless protocols. This research paper has proposed an area-efficient Reconfigurable Baseband Modulator (RBM) model to accomplish multi modulation scheme and resolve the adaptability and flexibility issues with the wide range of wireless standards. This also presents the feasibility of using a multi modulation baseband modulator to maximize adaptability with the least possible computational complexity overhead in the SDR system for next-generation wireless communication systems and provides parameterization. Finally, the re-configurability is evaluated concerning the appropriate symbols generations and analyzed its performance metrics through hardware synthesize results.

In this paper, we propose an interpretation method on amplitude intensities for response waveforms of backward transient scattered field components for both E- and H-polarizations by a 2-D coated metal cylinder. A time-domain (TD) asymptotic solution, which is referred to as a TD Fourier transform method (TD-FTM), is derived by applying the FTM to a backward transient scattered field expressed by an integral form. The TD-FTM is represented by a combination of a direct geometric optical ray (DGO) and a reflected GO (RGO) series. We use the TD-FTM to derive amplitude intensity ratios (AIRs) between adjacent backward transient scattered field components. By comparing the numerical values of the AIRs with those of the influence factors that compose the AIRs, major factor(s) can be identified, thereby allowing detailed interpretation method on the amplitude intensities for the response waveforms of backward transient scattered field components. The accuracy and practicality of the TD-FTM are evaluated by comparing it with three reference solutions. The effectiveness of an interpretation method on the amplitude intensities for response waveforms of backward transient scattered field components is revealed by identifying major factor(s) affecting the amplitude intensities.

This brief presents a slope analog-digital converter (ADC)-based supply voltage monitor (SVM) for biofuel-cell-powered supply-sensing systems operating in a supply voltage range of 0.18-0.35V. The proposed SVM is designed to utilize the output of energy harvester extracting power from biological reactions, realizing energy-autonomous sensor interfaces. A burst pulse generator uses a dynamic leakage suppression logic oscillator to generate a stable clock signal under the sub-threshold region for pulse counting. A slope-based voltage-to-time converter is employed to generate a pulse width proportional to the supply voltage with high linearity. The test chip of the proposed SVM is implemented in 180-nm CMOS technology with an active area of 0.018mm2. It consumes 2.1nW at 0.3V and achieves a conversion time of 117-673ms at 0.18-0.35V with a nonlinearity error of -5.5/+8.3mV, achieving an energy-efficient biosensing frontend.

This brief proposes a solar-cell-assisted wireless biosensing system that operates using a biofuel cell (BFC). To facilitate BFC area reduction for the use of this system in area-constrained continuous glucose monitoring contact lenses, an energy harvester combined with an on-chip solar cell is introduced as a dedicated power source for the transmitter. A dual-oscillator-based supply voltage monitor is employed to convert the BFC output into digital codes. From measurements of the test chip fabricated in 65-nm CMOS technology, the proposed system can achieve 99% BFC area reduction.

This paper studies a harvested power-oriented simultaneous wireless information and power transfer (SWIPT) scheme over multiple-input multiple-output (MIMO) interference channels in which energy harvesting (EH) circuits exhibit nonlinearity. To maximize the power harvested by all receivers, we propose an algorithm to jointly optimize the transmit beamforming vectors, power splitting (PS) ratios and the receive decoding vectors. As all variables are coupled to some extent, the problem is non-convex and hard to solve. To deal with this non-convex problem, an iterative optimization method is proposed. When two variables are fixed, the third variable is optimized. Specifically, when the transmit beamforming vectors are optimized, the transferred objective function is the sum of several fractional functions. Non-linear sum-of-ratios programming is used to solve the transferred objective function. The convergence and advantage of our proposed scheme compared with traditional EH circuits are validated by simulation results.

This study proposes a design and calibration method for a small-footprint, low-frequency, and low-power gate leakage timer using a differential leakage technique for IoT applications. The proposed gate leakage timer is different from conventional ones because it is composed of two leakage sources and exploits differential leakage current for the charging capacitor. This solution alleviates the inherent trade-off between small-footprint and low-frequency in the conventional gate leakage timer. Furthermore, a calibration method to suppress variations of the output frequency is proposed in this paper. To verify the effectiveness of the proposed gate leakage timer, a test chip was fabricated using 55-nm-DDC-CMOS technology. The test chip successfully demonstrates the highest figure of merit (FoM) of the product of the capacitor area (0.072µm2) and output frequency (0.11Hz), which corresponds to an improvement by a factor of 2,121 compared to the conventional one. It also demonstrates the operation with 4.5pW power consumption. The total footprint can be reduced to be 28µm2, which enables low-cost and low-power IoT edges. The scaling scenario shows that the proposed technique is conducive to technology scaling.

With the evolution of autonomous distributed systems such as smart cities, autonomous vehicles, smart control and scheduling systems there is an increased need for approaches to manage the execution of services to deliver real-time performance. As Cloud-hosted services are increasingly used to provide intelligence and analytic functionality to Internet of Things (IoT) systems, Quality of Service (QoS) techniques must be used to guarantee the timely service delivery. This paper reviews state-of-the-art QoS and Cloud techniques for real-time service delivery and data analysis. A review of straggler mitigation and a classification of real-time QoS techniques is provided. Then a mathematical framework is presented capturing the relationship between the host execution environment and the executing service allowing the response-times to predicted throughout execution. The framework is shown experimentally to reduce the number of QoS violations by 21% and provides alerts during the first 14ms provide alerts for 94% of future violations.

Applying Software Defined Network (SDN) technology to wireless networks are attracting much attention. Our previous study proposed a channel utilization method based on SDN/OpenFlow technology to improve the channel utilization efficiency of the multi-channel wireless backhaul network (WBN). However, since control messages are inherently transmitted with data traffic on a same channel in WBN, it inevitably degrades the network capacity. Specifically, the amount of control messages for collecting statistical information of each flow (FlowStats) linearly increases with the number of ongoing flows, thereby being the dominant overhead for backhaul networks. In this paper, we propose a new method that prevents the increase of control traffic while retaining the network performance of the previous method. Our proposed method uses statistical information of each interface (PortStats) instead of per-flow information (FlowStats), and handles multiple flows on the interface together if possible. Otherwise, to handle individual flow, we propose a way to estimate per-flow information without introducing extra control messages. Finally, we show that the proposed method offers the same performance with the previous method, while greatly reducing the amount of control traffic.

The fifth generation (5G) system using millimeter waves is considered for application to high traffic areas with a dense population of pedestrians. In such an environment, the effects of shadowing and scattering of radio waves by human bodies (HBs) on propagation channels cannot be ignored. In this paper, we clarify based on measurement the characteristics of waves scattered by the HB for typical non-line-of-sight scenarios in street canyon environments. In these scenarios, there are street intersections with pedestrians, and the angles that are formed by the transmission point, HB, and reception point are nearly equal to 90 degrees. We use a wide-band channel sounder for the 67-GHz band with a 1-GHz bandwidth and horn antennas in the measurements. The distance parameter between antennas and the HB is changed in the measurements. Moreover, the direction of the HB is changed from 0 to 360 degrees. The evaluation results show that the radar cross section (RCS) of the HB fluctuates randomly over the range of approximately 20dB. Moreover, the distribution of the RCS of the HB is a Gaussian distribution with a mean value of -9.4dBsm and the standard deviation of 4.2dBsm.

CMOS amperometric sensors with a microelectrode array offer great potential for counting bacteria because of their low cost, compact size, and ease of use. This paper presents a current-integration-based CMOS amperometric sensor for high-sensitivity bacteria counting. It has a current integrator for noise reduction and reportedly the most large-scale microelectrode array (1024 × 1024). This proposed sensor can count the number of bacteria ranging from a single cell to approximately a million cells. A prototype chip was fabricated using two-poly three-metal (2P3M) 0.6-µm standard CMOS technology. A 7.6 × 7.1-mm2 chip operates from a 5V supply at 1.9mA. In addition, by using the prototype chip, we performed electrochemical measurement and partial 2D imaging of silicone through constant potential amperometry. The measurement results indicate that the proposed sensor chip was able to accurately readout redox current from the 1024 × 1024 sensor array.

For the future medical diagnostics, high-sensitive, rapid, and cost effective biosensors to detect the biomarkers have been desired. In this study, the polymer-based two-dimensional photonic crystal (2D-PC) was fabricated using nanoimprint lithography (NIL) for biosensing application. In addition, for biosensing application, label-free detection of fibrinogen which is a biomarker to diagnose the chronic obstructive pulmonary disease (COPD) could be achieved using antigen-antibody reaction high-sensitively (detection limit: pg/ml order) and rapidly. Using this polymer-based 2D-PC, optical biosensor can be developed cost effectively. Furthermore, by using polymer as a base material for fabrication of 2D-PC, label-free detection of antigen-antibody reaction can be performed in visible region.

Smartphones have become vital devices in the current on-the-go Thai culture. Typically, virtual keyboards serve as tools for text input on smartphones. Due to the limited screen area and the large number of Thai characters, the size of each button on the keyboard is quite small. This leads to character mistyping and low typing speed. In this paper, we present a typical framework of a Thai Input Method on smartphones which includes four processes; Character Candidate Generation, Word Candidate Generation, Word Candidate Display, and Model Update. This framework not only works with Thai, it works with other letter-based languages as well. We also review virtual keyboards and techniques currently used and available for Thai text input.

This paper presents the design and proof-of-concept validation of a novel network-assisted spectrum coordination (NASCOR) service for improved radio coexistence in future shared spectrum bands. The basic idea is to create an overlay network service for dissemination of spectrum usage information between otherwise independent radio devices and systems, enabling them to implement decentralized spectrum coexistence policies that reduce interference and improve spectrum packing efficiency. The proposed method is applicable to unlicensed band and shared spectrum systems in general (including femtocells), but is particularly relevant to emerging TV white spaces and cognitive radio systems which are still in need of scalable and accurate solutions for both primary-to-secondary and secondary-to-secondary coordination. Key challenges in enabling a network layer spectrum coordination service are discussed along with the description of our system architecture and a detailed case-study for a specific example of spectrum coordination: client-AP association optimization in dense networks. Performance gains are evaluated through large-scale simulations with multiple overlapping networks, each consisting of 15-35 access points and 50-250 clients in a 0.5×0.5 sq.km. urban setting. Results show an average of 150% improvement in random deployments and upto 7× improvements in clustered deployments for the least-performing client throughputs with modest reductions in the mean client throughputs.

A novel fabrication approach for the amperometric biosensor composed of carbon nanotubes (CNT), a plasma-polymerized film (PPF), hexamineruthenium(III)chloride (RU), and enzyme glucose oxidase (GOD) is reported. The configuration of the electrochemical electrode is multilayer films which contain sputtered gold, lower acetonitrile PPF, CNT, RU, GOD, and upper acetonitrile PPF, sequentially. First, PPF deposited on Au acts as a permselective membrane and as a scaffold for CNT layer formation. Second, PPF directly deposited on GOD acts as a matrix for enzyme immobilization. To facilitate the electrochemical communication between the CNT layer and GOD, CNT was treated with nitrogen plasma. The electron transfer mediator RU play a role as the mediator, in which the electron caused by enzymatic reaction transports to the electrode. The synergy between the electron transfer mediator and CNT provides benefits in terms of lowering the operational potential and enhancing the sensitivity (current). The optimized glucose biosensor revealed a sensitivity of 3.4µA mM-1 cm-2 at +0.4V vs. Ag/AgCl, linear dynamic range of 2.5-19mM, and a response time of 6s.

It is well known that cognitive radio (CR) techniques have great potential for supporting future demands on the scarce radio spectrum resources. For example, by enabling the utilization of spectrum bands temporarily not utilized by primary users (PUs) licensed to operate on those bands. Spectrum sensing is a well-known CR technique for detecting those unutilized bands. However, the spectrum sensing outcomes cannot be perfect and there will always be some misdetections and false alarms which will affect the performance thereby degrading the quality of service (QoS) of PUs. Continuous time Markov chain (CTMC) based modeling has been widely used in the literature to evaluate the performance of CR networks (CRNs). A major limitation of the available literature is that all the key factors and realistic elements such as the effect of imperfect sensing and state dependent transition rates are not modeled in a single work. In this paper, we present a CTMC based model for analyzing the performance of CRNs. The proposed model differs from the existing models by accurately incorporating key elements such as full state dependent transition rates, multi-channel support, handoff capability, and imperfect sensing. We derive formulas for primary termination probability, secondary success probability, secondary blocking probability, secondary forced termination probability, and radio resource utilization. The results show that incorporating fully state dependent transition rates in the CTMC can significantly improve analysis accuracy, thus achieving more realistic and accurate analytical model. The results from extensive Monte Carlo simulations confirm the validity of our proposed model.

This paper describes a computer-aided diagnosis (CAD) method to classify pneumoconiosis on HRCT images. In Japan, the pneumoconiosis is divided into 4 types according to the density of nodules: Type 1 (no nodules), Type 2 (few small nodules), Type 3-a (numerous small nodules) and Type 3-b (numerous small nodules and presence of large nodules). Because most pneumoconiotic nodules are small-sized and irregular-shape, only few nodules can be detected by conventional nodule extraction methods, which would affect the classification of pneumoconiosis. To improve the performance of nodule extraction, we proposed a filter based on analysis the eigenvalues of Hessian matrix. The classification of pneumoconiosis is performed in the following steps: Firstly the large-sized nodules were extracted and cases of type 3-b were recognized. Secondly, for the rest cases, the small nodules were detected and false positives were eliminated. Thirdly we adopted a bag-of-features-based method to generate input vectors for a support vector machine (SVM) classifier. Finally cases of type 1,2 and 3-a were classified. The proposed method was evaluated on 175 HRCT scans of 112 subjects. The average accuracy of classification is 90.6%. Experimental result shows that our method would be helpful to classify pneumoconiosis on HRCT.

Various information and communication technology (ICT) applications have been introduced for use in disaster-stricken areas. Of these, those for healthcare purposes proved useful when used for continually monitoring health conditions and easily using medical and healthcare devices, such as sphygmomanometers, which are familiar to the public. Devices that were easy to understand and use were more acceptable in the first post-disaster stage in a temporary housing community as victims were experiencing mental and physical trauma. After gaining the trust of medical/healthcare staff caring for the victims, we could move to the next stage with their support. ICT technologies are tools and are basically invisible to victims; a notion we have recognized anew. This paper introduces our activities in the area of healthcare monitoring services. The UMe-1 system and subset health check kiosk version 0 are introduced. The kiosk is simple and important for life support advisers in support centers as a tool for checking the health condition of residents. Not all those living in the target temporary housing community are currently using the kiosk due to its location within the widespread premises, but the director of a support center recognizes the utility of the kiosk and expects that a community-based kiosk and user-friendly BAN device could be used at home for mimamori (the Japanese concept of informally monitoring healthcare) because residents living far from support centers have difficulty regularly visiting the center, especially in the winter. We introduced a television-based, in-home health check kiosk and are currently working on its development. There are gaps between actually deployable technologies and research results, but it is also important to continue to address research issues concerning reducing impact through the user interface and introducing less stress to the everyday lives of disaster victims.

In this paper, a fast and automated method of counting pedestrians in crowded areas is proposed along with three contributions. We firstly propose Local Empirical Templates (LET), which are able to outline the foregrounds, typically made by single pedestrians in a scene. LET are extracted by clustering foregrounds of single pedestrians with similar features in silhouettes. This process is done automatically for unknown scenes. Secondly, comparing the size of group foreground made by a group of pedestrians to that of appropriate LET captured in the same image patch with the group foreground produces the density ratio. Because of the local scale normalization between sizes, the density ratio appears to have a bound closely related to the number of pedestrians who induce the group foreground. Finally, to extract the bounds of density ratios for groups of different number of pedestrians, we propose a 3D human models based simulation in which camera viewpoints and pedestrians' proximity are easily manipulated. We collect hundreds of typical occluded-people patterns with distinct degrees of human proximity and under a variety of camera viewpoints. Distributions of density ratios with respect to the number of pedestrians are built based on the computed density ratios of these patterns for extracting density ratio bounds. The simulation is performed in the offline learning phase to extract the bounds from the distributions, which are used to count pedestrians in online settings. We reveal that the bounds seem to be invariant to camera viewpoints and humans' proximity. The performance of our proposed method is evaluated with our collected videos and PETS 2009's datasets. For our collected videos with the resolution of 320 × 240, our method runs in real-time with good accuracy and frame rate of around 30 fps, and consumes a small amount of computing resources. For PETS 2009's datasets, our proposed method achieves competitive results with other methods tested on the same datasets [1],[2].

In this paper, we study the problem of distributed spectrum allocation under a vertical spectrum sharing scenario in a cognitive radio network. The secondary users share the spectrum licensed to the primary user by observing the activity statistics of the primary users, and regulate their transmission strategy in order to abide by the spectrum sharing etiquette. When the primary user is inactive in a subset of the available frequency bands, from the perspective of the secondary users the problem reduces to a distributed horizontal spectrum sharing. For a specific class of networks, the latter problem is addressed by the recently proposed GADIA algorithm [1]. In this paper, we present analytical and numerical results on the performance of the GADIA algorithm in conjunction with the above-mentioned vertical spectrum sharing scenario. These results reveal near-optimal performance guarantees for the overall vertical spectrum sharing scenario.