In general, semi-supervised clustering can outperform unsupervised clustering. Since 2001, pairwise constraints for semi-supervised clustering have been an important paradigm in this field. In this paper, we show that pairwise constraints (ECs) can affect the performance of clustering in certain situations and analyze the reasons for this in detail. To overcome these disadvantages, we first outline some exemplars constraints. Based on these constraints, we then describe a semi-supervised clustering framework, and design an exemplars constraints expectation-maximization algorithm. Finally, standard datasets are selected for experiments, and experimental results are presented, which show that the exemplars constraints outperform the corresponding unsupervised clustering and semi-supervised algorithms based on pairwise constraints.

We evaluated a technique for protecting the copyright of digital data for 3-D printing. To embed copyright information, the inside of a 3-D printed object is constructed from fine domains that have different physical characteristics from those of the object's main body surrounding them, and to read out the embedded information, these fine domains inside the objects are detected using nondestructive inspections such as X-ray photography or thermography. In the evaluation, copyright information embedded inside the 3-D printed object was expressed using the depth of fine cavities inside the object, and X-ray photography were used for reading them out from the object. The test sample was a cuboid 46mm wide, 42mm long, and 20mm deep. The cavities were 2mm wide and 2mm long. The difference in the depths of the cavities appeared as a difference in the luminance in the X-ray photographs, and 21 levels of depth could be detected on the basis of the difference in luminance. These results indicate that under the conditions of the experiment, each cavity expressed 4 to 5bits of information with its depth. We demonstrated that the proposed technique had the possibility of embedding a sufficient volume of information for expressing copyright information by using the depths of cavities.

Particle filter algorithm is an important algorithm in the field of target tracking. however, this algorithm faces the problem of sample impoverishment which is caused by the introduction of re-sampling and easily affected by illumination variation. This problem seriously affects the tracking performance of a particle filter algorithm. To solve this problem, we introduce a particle filter target tracking algorithm based on a dynamic niche genetic algorithm. The application of this dynamic niche genetic algorithm to re-sampling ensures particle diversity and dynamically fuses the color and profile features of the target in order to increase the algorithm accuracy under the illumination variation. According to the test results, the proposed algorithm accurately tracks the target, significantly increases the number of particles, enhances the particle diversity, and exhibits better robustness and better accuracy.

This paper presents a high resolution mixed-domain Delta-Sigma (ΔΣ) time-to-digital converter (TDC) which utilizes a charge pump as time-to-voltage converter, a low resolution SAR ADC as quantizer, and a pair of delay-line digital-to-time converters to form a negative feedback. By never resetting the sampling capacitor of the charge-pump, an integrator is realized and first order noise shaping can be achieved. However, since the integrating capacitor is never cleared, this circuit is prone to charge-sharing issue during input sampling which can degrade TDC's performance. To deal with this issue, a compensation circuit consists of another pair of sampling capacitors and charge-pumps with doubled current is proposed. This TDC is designed and simulated in 65 nm CMOS technology and can operate at 200 MHz sampling frequency. For 2.5 MHz bandwidth, simulation shows that this TDC achieves 66.4 dB SNDR and 295 fsrms integrated noise for ±1 ns input range. The proposed TDC consumes 1.78 mW power that translates to FoM of 208 fJ/conv.

In this paper, a 500 MHz-BW -52.5 dB-THD Voltage-to-Time Converter (VTC) in 28 nm CMOS is presented. A two-step transition inverter raises the Voltage-to-Time (VT) conversion gain to 100 ps/V which is >10x higher than a conventional current-starved inverter. The number of required inverter stages is reduced to 4 from 64, resulting in 1/8 conversion latency and thus 13.2 dB THD suppression at a 500 MHz full Nyquist frequency. A feedback control of the bias voltage in the two-step transition inverter suppresses PVT variations in the VT conversion gain. A test-chip measurement successfully demonstrates -52.5 dB THD at 500 MHz input frequency without sampling-and-hold circuits. Effective VT conversion range over +/-64 ps time difference is measured with 1.2 Vpp differential input while keeping high linearity of less than +/-0.53 LSB INL/DNL, which results in 1 ps/LSB conversion linearity. The proposed VTC occupies 84 um2 silicon area and consumes 0.18 mW at 1 GS/s.

This paper presents the formal analysis of the feature negotiation and connection management procedures of the Datagram Congestion Control Protocol (DCCP). Using state space analysis we discover an error in the DCCP specification, that result in both ends of the connection having different agreed feature values. The error occurs when the client ignores an unexpected Response packet in the OPEN state that carries a valid Confirm option. This provides an evidence that the connection management procedure and feature negotiation procedures interact. We also propose solutions to rectify the problem.

Artificial lighting is responsible for a large portion of total energy consumption and has great potential for energy saving. This paper designs an LED light control algorithm based on users' localization using multiple battery-less binary human detection sensors. The proposed lighting control system focuses on reducing office lighting energy consumption and satisfying users' illumination requirement. Most current lighting control systems use infrared human detection sensors, but the poor detection probability, especially for a static user, makes it difficult to realize comfortable and effective lighting control. To improve the detection probability of each sensor, we proposed to locate sensors as close to each user as possible by using a battery-less wireless sensor network, in which all sensors can be placed freely in the space with high energy stability. We also proposed to use a multi-sensor-based user localization algorithm to capture user's position more accurately and realize fine lighting control which works even with static users. The system is actually implemented in an indoor office environment in a pilot project. A verification experiment is conducted by measuring the practical illumination and power consumption. The performance agrees with design expectations. It shows that the proposed LED lighting control system reduces the energy consumption significantly, 57% compared to the batch control scheme, and satisfies user's illumination requirement with 100% probability.

This contribution presents and analyzes the statistical regularity related to the noise power spectrum series and the speech spectrum series. It also undertakes a thorough inquiry of the quasi-Gaussian distributed power spectrum series obtained using the radical root transformation. Consequently, a noise-estimation algorithm is proposed for speech enhancement. This method is effective for separating the noise power spectrum from the noisy speech power spectrum. In contrast to standard noise-estimation algorithms, the proposed method requires no speech activity detector. It was confirmed to be conceptually simple and well suited to real-time implementations. Practical experiment tests indicated that our method is preferred over previous methods.

This letter introduces a new model for backscatter assisted wireless powered communication networks (BAWPCNs) that include a hybrid access point (HAP) and multiple backscatter communication (BackCom) and traditional wireless powered communication network (WPCN) users. To make full use of time to transmit information, both backscatter and harvest-then-transmit (HTT) modes are employed. In the proposed model, during the first time slot dedicated for energy transfer in traditional WPCNs, the traditional WPCN users harvest energy radiated by the HAP, and simultaneously the BackCom users reflect modulated signals to the HAP. The traditional WPCN users are scheduled during the remaining time slots via time division multiple access (TMDA). The optimal time allocation policies for the half-duplex (HD) and full-duplex (FD) BAWPCNs are obtained to maximize the system throughput. The tradeoff between backscatter and HTT modes is analyzed. Simulation results demonstrate the superiority of the proposed model.

In the field of action recognition, Spatio-Temporal Interest Points (STIPs)-based features have shown high efficiency and robustness. However, most of state-of-the-art work to describe STIPs, they typically focus on 2-dimensions (2D) images, which ignore information in 3D spatio-temporal space. Besides, the compact representation of descriptors should be considered due to the costs of storage and computational time. In this paper, a novel local descriptor named 3D Gradient LBP is proposed, which extends the traditional descriptor Local Binary Patterns (LBP) into 3D spatio-temporal space. The proposed descriptor takes advantage of the neighbourhood information of cuboids in three dimensions, which accounts for its excellent descriptive power for the distribution of grey-level space. Experiments on three challenging datasets (KTH, Weizmann and UT Interaction) validate the effectiveness of our approach in the recognition of human actions.

This letter considers the robust transceiver design for multiple-input multiple-output interference channels under channel state information mismatch. According to alternating schemes, an adaptive algorithm is proposed to solve the minimum SINR maximization problem. Simulation results show the convergence and the effectiveness of the proposed algorithm.

This paper studies the supervisory control of partially observed quantitative discrete event systems (DESs) under the fixed-initial-credit energy objective. A quantitative DES is modeled by a weighted automaton whose event set is partitioned into a controllable event set and an uncontrollable event set. Partial observation is modeled by a mapping from each event and state of the DES to the corresponding masked event and masked state that are observed by a supervisor. The supervisor controls the DES by disabling or enabling any controllable event for the current state of the DES, based on the observed sequences of masked states and masked events. We model the control process as a two-player game played between the supervisor and the DES. The DES aims to execute the events so that its energy level drops below zero, while the supervisor aims to maintain the energy level above zero. We show that the proposed problem is reducible to finding a winning strategy in a turn-based reachability game.

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.

Existing noise inference algorithms neglected the smooth characteristics of noise data, which results in executing slowly of noise inference. In order to address this problem, we present a noise inference algorithm based on fast context-aware tensor decomposition (F-CATD). F-CATD improves the noise inference algorithm based on context-aware tensor decomposition algorithm. It combines the smoothness constraint with context-aware tensor decomposition to speed up the process of decomposition. Experiments with New York City 311 noise data show that the proposed method accelerates the noise inference. Compared with the existing method, F-CATD reduces 4-5 times in terms of time consumption while keeping the effectiveness of the results.

60GHz wireless communication requires analog baseband circuits having a bandwidth of about 1GHz. This paper presents a wide bandwidth current-mode low pass filter technique which involves current amplifiers, resistors and capacitors. The proposed current-mode filter is obtained by replacing an integrator employing an op-amp with another integrator employing a current amplifier. With the low input impedance current amplifier having little variation of the input impedance, the proposed filter is expected to improve linearity and power efficiency. The proposed current amplifier which employs super source follower topology with complementary input is suitable for the filter because of its class AB operation. Although simulation results shows the conventional current amplifier which employs super source follower topology without the complementary input has 12Ω variation and 30Ω input impedance, the proposed current amplifier has 1Ω variation and 21Ω input impedance. A fourth order 1GHz bandwidth filter which involves the proposed current amplifiers is designed in a 65nm CMOS technology. The filter can achieve IIP3 of 1.3dBV and noise of 0.6mVrms with power consumption of 13mW under supply voltage of 1.2V according to simulation results with layout parasitic extraction models. Active area of the filter is 380μm×170μm.

In this paper, a new effective C/N0 theoretical model for global navigation satellite system (GNSS) receiver is proposed, in the presence of continuous wave interference (CWI). The proposed model is derived based on an interesting finding, correlator may output direct current (DC) in the presence of CWI. The DC introduced by CWI eventually leads to increase of carrier power estimation. It is totally different from current assumption that interference just causes noise power increase after correlation. The proposed model is verified by simulation.

In heterogenous networks (HetNets), the deployment of small cells with the reuse of limited frequency resources to improve the spectral efficiency results in cross- and co-tier interference. In addition, the excessive power usage in such networks is also a critical problem. In this paper, we propose precoding and postcoding schemes to tackle interference and energy efficiency (EE) challenges in the two-tier downlink multiple-input-multiple-output (MIMO) HetNets. We propose transmission strategies based on hierarchical partial coordination (HPC) of the macro cell and small cells to reduce channel state information (CSI) exchange and guarantee the quality of service (QoS) in the upper tier with any change of network deployment in the lower tier. We employ the interference alignment (IA) scheme to cancel cross- and co-tier interference. Additionally, to maximize the EE, power allocation schemes in each tier are proposed based on a combination of Dinkelbach's method and the bisection searching approach. To investigate insights on the optimization problem, a theoretical analysis on the relationship between the maximum achievable EE and the transmit power is derived. Simulation results prove the superior EE performance of the proposed EE maximization scheme over the sum rate maximization approach and confirm the validity of our theoretical findings.

A novel spur cancelled clock generator (SCCG) capable of recovering RX sensitivity degradations caused by digital clocks in wireless SoCs is presented. Clock spurs that degrade RX sensitivities are canceled by applying the SCCG to digital circuits or ADCs. The SCCG is integrated into a Bluetooth Low Energy (BLE) SoC fabricated in a 65 nm CMOS process. A measured clock spur reduction of 34 dB and an RX sensitivity recovery of 5 dB are achieved by the proposed SCCG. The power consumption and occupied area of the SCCG is only 18 µW and 40 μm × 120 μm, respectively.

We propose a statistical processing method to reduce the time of chip test of high-resolution and low-speed analog-to-digital converters (ADCs). For this kinds of ADCs, due to the influence of noise, conventional histogram or momentum method suffers from long time to collect required data for averaging. The proposed method, based on physically weighing the ADC, intending to physical weights in ADC/DAC under test. It can suppress white noise to 1/22 than conventional method in a case of 10bit binary ADC. Or it can reduce test data to 1/8 or less, which directly means to reduce measuring time to 1/8 or less. In addition, it earns complete Integrated Non-Linearity (INL) and Differential Non-linearity (DNL) even missing codes happens due to less data points. In this report, we theoretically describe how to guarantee missing codes at lacked measured data points.

This paper presents a thin, compact beacon transmitter operating without needing battery replacement by using a photovoltaic (PV) film harvester. The beacon is formed of a power-control circuit (PCC) that can monitor small amounts of power from the harvester and properly control mode switching at low-power consumption. This leads to the realization of a maintenance-free beacon requiring no battery replacement. The beacon prototype is 55×20×2 mm in size and has a PV cell of 3 cm2. It allows a start-up operation from just 44-lux illuminance. The PV area required for the operation can be 1.7 times smaller than that of conventional beacons, thanks to the current saving with appropriate sequential control of the PCC. Since the beacon makes operation possible in emergency stairs, underground passages and other dark places, the application field for Internet of things (IoT) services can be expanded. Furthermore, a beacon equipped with a secondary battery (BSB: Beacon with Secondary Battery) can be configured by adding a charge-discharge power monitoring circuit. The BSB transmits an advertising packet during the daytime while charging surplus power, and works using the stored power during the night; this results in a continuous operation for one week with one transmission every 3 seconds even at 0-lux illuminance. Without developing a new radiofrequency chip or module, commercial low-power devices can be easily adjusted depending on the application by adding appropriate power-control circuits. We are convinced that this design scheme will be effective as a rapid design proposal for IoT services.