nils-herrmann/clean_scirepeval huggingface dataset:
A new soft-switching strategy for Three-Port Converter to be applied in EV application

This paper proposes a new soft-switching strategy for an isolated Three-Port bidirectional DC/DC Converter (TPC). Two inner phase shift angles will be introduced to two secondary inverters to make the modulation more flexible. Unlike published researches on TPC, this paper analyzes the converter in the frequency domain based on the fundamental harmonic approximation method. The simulation results confirm that, the maximum error between the calculated and the simulation powers is 31.2 W in the scale of 500 W (6.24%). After that, a new modulation strategy is proposed to help achieve zero-voltage switching (ZVS) characteristics. As confirmed by experiment, ZVS is achieved for all MOSFETs. The maximum efficiency of 95.58% is recorded, whereas, in the investigated power range, the average efficiency is 94.66%.
A Novel Cooperative Non-Orthogonal Multiple Access (NOMA) in Wireless Backhaul Two-Tier HetNets

In this paper, we propose to re-engineer the wireless backhaul two-tier heterogeneous networks architecture by developing a novel cooperative transmission scheme based on non-orthogonal multiple access (NOMA). To effectively manage severe interference from the newly introduced backhaul communications, we employ the cochannel time division duplexing combined with spectrum partitioning between two considered tiers. This paper’s novelty lies in the formulation to solve for the NOMA decoding order, which affects the rule of the cooperation between small cell transmissions. We propose two optimization problems of jointly designing the NOMA decoding order together with the transmit beamforming at the macro base station and power allocation at the small cells which maximize the total achievable rate and the number of satisfied users, respectively. The first and second formulated problems are both mixed integer non-convex and are generally NP-hard. To solve them, we first employ the difference of convex functions to present the formulated binary variables and then equivalently transform the optimization problems into more tractable forms. Finally, we develop an iterative low-complexity algorithm based on successive convex approximation technique and majorization minimization method, which is provable to eventually converge at a sub-optimal solution. Numerical results are extensively studied to corroborate that our proposed strategy outperforms the conventional designs in terms of total achievable rate and number of satisfied users.
About a new localized multi-criterion routing algorithm – a solution to assure quality of network

The requisition of telecom services for quality of network is more and more sophisticated, the required bandwidth, the value of delay time or packet loss ... become more popular in providing new services. To assure the quality of network, the localized routing schemes have recently been researched as a promising alternative to the currently deployed global QoS routing schemes. Different from the traditional QoS routing algorithms which use global state information, the localized routing algorithms use local information collected from source node to make routing decisions. These localized routing algorithms can be a solution for satisfying the demand of telecom market in the near future. In this paper, we propose a new localized multi-criterion QoS routing algorithm which can help to assure quality of network, and show our simulations which are better in results against other routing algorithms.
Design and simulation-based performance evaluation of a miniaturised implantable antenna for biomedical applications

Biomedical telemetry is an emerging field of research which enables the formation of a transmission link from inside a living body to an external device. Implantable medical devices are now one of such valuable advancement in the field of biomedical telemetry. Implantable patch antennas are gaining attention and are becoming more of a choice for implantable medical devices that uses mostly RF telemetry. In this work, a state-of-the-art design for a rectangular implantable flexible patch antenna is proposed. The operation band for the antenna is chosen in the Industrial, Scientific and Medical (ISM) band (2.4-2.4835 GHz). The tiny dimension of the antenna, including the 9.45 μm thickness of the patch itself allows the antenna to be highly flexible and provides excellent results even at extreme bent conditions. For simulation environment, a three-layer human tissue model was used, where the antenna was encapsulated between the fat and skin layer. CST Microwave Studio was chosen to design and simulate the antenna. Several performance parameters were simulated, such as the operating resonant frequency, the return loss, radiation pattern, specific absorption rate and also sensitivity of the antenna when introduced to bending.
Characterization of GaAs MESFET gate capacitances

An accurate and simple technique to characterize gate capacitances of small-geometry gallium-arsenide (GaAs) MESFETs is presented. The gate capacitive current is converted into voltage and detected by a lock-in amplifier. Subfemtofarad accuracy is achieved. A set of MESFETs with minimum channel length of 0.8 mu m and various channel widths has been accurately characterized. The gate-to-drain and gate-to-source capacitances show strong bias dependences.
A novel segmentation scheme for DTC-based ΔΣ fractional-N PLL

The adoption of the digital/time converter (DTC) circuit has improved the performance of ΔΣ fractional-N phase-locked loops (PLLs). Accurate cancellation of ΔΣ quantization error via the DTC requires an automatic calibration made by an LMS loop. A high-order ΔΣ speeds up calibration convergence and improves PLL spectral purity, though at the price of larger quantization error and wider DTC range. To overcome this problem, we propose an innovative parallel segmentation scheme which reduces the range of quantization error without compromising spectral purity and convergence speed. The effectiveness of the proposed segmentation scheme is demonstrated via behavioral-level simulations of a digital PLL and compared to the conventional cascaded segmentation scheme.
An Inertial-Aided Homography-Based Visual Servo Control Approach for (Almost) Fully Actuated Autonomous Underwater Vehicles

A nonlinear inertial-aided image-based visual servo control approach for the stabilization of (almost) fully actuated autonomous underwater vehicles (AUVs) is proposed. It makes use of the homography matrix between two images of a planar scene as feedback information while the system dynamics are exploited in a cascade manner in a control design: An outer-loop control defines a reference setpoint based on the homography matrix and an inner-loop control ensures the stabilization of the setpoint by assigning the thrust and torque controls. Unlike conventional solutions that only consider the system kinematics, the proposed control scheme is novel in considering the full system dynamics (incorporating all degrees of freedom, nonlinearities, and couplings, as well as interactions with the surrounding fluid) and in not requiring information of the relative depth and normal vector of the observed scene. Augmented with integral corrections, the proposed controller is robust with respect to model uncertainties and disturbances. The almost global asymptotic stability of the closed-loop system is demonstrated, which is the largest domain of attraction one can achieve by means of continuous feedback control. Simulation results illustrating these properties on a realistic AUV model subjected to a sea current are presented and finally experimental results on a real AUV are reported.
A keypoint approach for change detection between SAR images based on graph theory

This paper investigates the problem of change detection in multitemporal Synthetic Aperture Radar (SAR) images. Our proposition is to perform a keypoint-based algorithm to detect land-cover changes between two SAR images employing the graph theory combined with the log-ratio operator. First, a set of feature points is extracted from one of the two images. A weighted graph is then constructed to connect these keypoints based on their similarity measures from this first image. Based on this graph, our motivation is to measure the coherence between the information carried by the two images. In other words, the change level will depend on how much the second image still conforms to the graph constructed from the first image. Furthermore, due to the presence of speckle noise, the log-ratio operator will be exploited to replace the image difference operator. Experiments performed on real SAR images using the proposed algorithm provide very promising and competitive results compared to classical methods.
13.6 A 2.4GHz WLAN digital polar transmitter with synthesized digital-to-time converter in 14nm trigate/FinFET technology for IoT and wearable applications

To benefit from Moore's law and minimize form-factor and active power consumption, digital-rich SoCs should be integrated in the most advanced technology node. If the transceiver is integrated in a different technology node, multi-chip solutions are required, increasing system cost and form-factor. Traditional radio architectures require extensive use of high-quality passives, which might use large silicon area or not be available due to process limitations. Fast time to market also demands quicker design cycles, where extensive use of standard digital cells and even automated place-and-route tools for layout is preferred . The proposed transmitter leverages a polar architecture with synthesized digital-to-time converter (DTC) wideband phase modulator, an all-digital PLL and a digital PA with matching network implemented on a flip-chip package to enable single-chip integration in 14nm trigate/finFET technology for IoT and wearable SoCs.
BFC: High-performance distributed big-file cloud storage based on key-value store

Nowadays, cloud-based storage services are rapidly growing and becoming an emerging trend in data storage field. There are many problems when designing an efficient storage engine for cloud-based systems with some requirements such as big-file processing, lightweight meta-data, low latency, parallel I/O, deduplication, distributed, high scalability.  stores played an important role and showed many advantages when solving those problems. This paper presents about Big File Cloud (BFC) with its algorithms and architecture to handle most of problems in a big-file cloud storage system based on key-value store. It is done by proposing low-complicated, fixed-size meta-data design, which supports fast and highly-concurrent, distributed file I/O, several algorithms for resumable upload, download and simple data deduplication method for static data. This research applied the advantages of ZDB - an in-house key-value store which was optimized with auto-increment integer keys for solving big-file storage problems efficiently. The results can be used for building scalable distributed data cloud storage that support big-file with size up to several terabytes.
A multichannel approach to metric-based SAR autofocus

The autofocus problem in synthetic aperture radar (SAR) is considered. We precisely characterize the multichannel nature of the SAR autofocus problem by constructing a low-dimensional sub-space where the perfectly-focused image resides. To obtain a unique solution, we perform a sharpness optimization within this sub-space. The subspace characterization enables the sharpness optimization to be performed in a vector space, which is conceptually simpler, and allows the SAR autofocus problem to be cast into a similar framework with other image restoration problems where fast algorithms and efficient methods have been established. We present experimental results demonstrating that the proposed framework can be used to bring the ideas of blind multichannel deconvolution techniques to the SAR autofocus problem, allowing the dimension of the solution subspace to be reduced further.
A local feature vector for an adaptive hybrid fingerprint matcher

In this paper, we introduce a hybrid fingerprint matcher which consists of two stages: local minutiae matching stage and consolidation stage. In the former stage, each minutia in the fingerprint is represented by a local feature vector which is built from the features of the neighboring minutiae within a fixed-radius circle around it. The features of each neighboring minutia are defined according to the spatial relationship with the central minutia and used for matching task. New calculation methods of the adaptive matching conditions for two neighboring minutiae and the local similarity score between two central minutiae are introduced. The latter stage performs multiple alignments based on the pairs of matching minutiae to produce the final matching score between two fingerprints. Extensive experiments over a public database used in Fingerprint Verification Competition 2002 (FVC2002) prove a considerable improvement in accuracy of our proposed algorithm against some well-known techniques and Top 5 participants of FVC2002.
An Efficient and Reliable MAC in VANETs

Vehicular Ad hoc Network (VANET) is developed to enhance the safety, comfort and efficiency of driving. The IEEE 802.11p/WAVE and IEEE 1609.4 family are standards intended to support wireless access in VANETs. In this paper, we propose an Efficient and Reliable MAC protocol for VANETs (VER-MAC) which allows nodes to broadcast safety packets twice during both the control channel interval and service channel interval to increase the safety broadcast reliability. By using the additional data structures, nodes can transmit service packets during the control channel interval to improve the service throughput.
An MC-SPP approach for noise reduction in dual microphone case with power level difference

This paper proposes to use multichannel speech presence probability (MC-SPP) to modify and improve the noise reduction quality of the power level difference (PLD) algorithm for dual microphone case. Firstly, a modified Wiener filter is proposed with a varying scaling factor depending on MC-SPP, which helps solve the speech distortion problem usually encountered in noise reduction algorithms. Secondly, an improved PLD noise estimation is proposed with a varying updating factor, also depending on the MC-SPP, which reduces noise and increase output SINR a lot while suffer only a little in speech distortion. These algorithms are simulated, compared and verified for various noise and SINR scenarios.
Adaptive steganography technique to secure patient confidential information using ECG signal

In this paper, we propose a method of protecting patient information using adaptive steganography technique on ECG (Electrocardiogram) signal. The process of embedding information uses the LSB (Least Significant Bit) matching algorithm to reduce the change on the cover object. Patient information is only embedded in the signal between the T-P wave (resting heart) to prevent the interfere with important features of the ECG signal. Experimental results show that the healthcare information is extracted accurately while the invisibility of secret data is significantly improved.
An Unsupervised Feature Selection Dynamic Mixture Model for Motion Segmentation

The automatic clustering of time-varying characteristics and phenomena in natural scenes has recently received great attention. While there exist many algorithms for motion segmentation, an important issue arising from these studies concerns that for which attributes of the data should be used to cluster phenomena with a certain repetitiveness in both space and time. It is difficult because there is no knowledge about the labels of the phenomena to guide the search. In this paper, we present a feature selection dynamic mixture model for motion segmentation. The advantage of our method is that it is intuitively appealing, avoiding any combinatorial search, and allowing us to prune the feature set. Numerical experiments on various phenomena are conducted. The performance of the proposed model is compared with that of other motion segmentation algorithms, demonstrating the robustness and accuracy of our method.
A force direction control method for robotic bipedal walking based on a reduced order model

In this paper, we present a control method for bipedal robotic walking based on insights we obtain from simple models. Inspired by the virtual pendulum (VP) concept and the spring-mass walking models, we propose a force direction control method to redirect the axial force of a compliant leg in order for walking with upright trunk. We first consider a dynamic simulation of a simple planar walking model to validate the proposed method with proper foot placement rule, under the presence of force disturbance. Finally, we design a controller to implement the proposed force direction control scheme onto a more realistic model, a planar five link biped, which involves individual leg controller and walking state machine. The simulation results indicate that the robot model equipped with the proposed controller can overcome terrains with moderate roughness.
A/D conversion based on signal decomposition for DSP applications

Digital Signal Processing (DSP) systems operating on analog inputs are often limited by sampling rates of Analog to Digital Converters (ADC). ADCs are critical components since they tend to determine the overall system performance. Hence it is important that ADCs possess characteristics like high sampling rate, low conversion delay and high resolution that enhance system performance. In this paper, we propose a novel ADC to be used in signal processing based on signal decomposition. The proposed scheme folds the input signal symmetrically prior to quantization by high speed comparators. However, unlike folding ADCs that divide the input analog signal into two components, corresponding to coarse and fine quantization, the proposed converter minimizes delay and circuit complexity by introducing a Folding Bit. It does not use explicit circuits for coarse and fine quantization but uses only folding circuits to generate both most significant and least significant bits directly eliminating synchronizing problems normally encountered in the recombination of coarse and fine quantized bits.
A novel fabrication method of the tiny aperture tip on silicon cantilever for near field scanning optical microscopy

In this paper we present a novel fabrication method of a miniature aperture on a Si cantilever for Near field Scanning Optical Microscopy (NSOM). The Si cantilever with a SiO/sub 2/ pyramidal tip was microfabricated in a batch process. The silicon was thermally oxidized at low temperature (1050/spl deg/C). Due to the effect of locally compressive intrinsic stress within the oxide on the solubility of oxygen, the thermal silicon oxide at the bottom of the pyramidal etch pit is thinner. Thus, a tiny aperture can be created by partly etching the SiO/sub 2/ in buffered HF solution. Using the etching method aperture size ranging from 150 nm to 500 nm have been experimental realized. By optimizing the SiO/sub 2/ etching time, sub 100 nm size apertures are feasible using the fabrication method. The fabricated probe was mounted to an Atomic Force Microscope (AFM) head. The AFM in contact mode and corresponding NSOM images of Au patterns on Si wafer were simultaneously recorded.
An empirical study of discriminative sequence labeling models for Vietnamese text processing

This paper presents an empirical study of two widely-used sequence prediction models, Conditional Random Fields (CRFs) and Long Short-Term Memory Networks (LSTMs), on two fundamental tasks for Vietnamese text processing, including part-of-speech tagging and named entity recognition. We show that a strong lower bound for labeling accuracy can be obtained by relying only on simple word-based features with minimal handcrafted feature engineering, of 90.65% and 86.03% performance scores on the standard test sets for the two tasks respectively. In particular, we demonstrate empirically the surprising efficiency of word embeddings in both of the two tasks, with both of the two models. We point out that the state-of-the-art LSTMs model does not always outperform significantly the traditional CRFs model, especially on moderate-sized data sets. Finally, we give some suggestions and discussions for efficient use of sequence labeling models in practical applications.
Cooperative Optical Trapping and Manipulation of Multiple Cells With Robot Tweezers

While several control schemes and automation techniques have been proposed for coordination and manipulation of multiple cells using optical tweezers, open-loop control methods are always utilized by treating the positions of lasers as the control inputs instead of feedback variables. As the positions of laser beams are not utilized in feedback control, it is, therefore, assumed in the literature that the multiple cells are always trapped by the laser beams throughout the manipulation task. However, the control techniques fail when the cells are not initially trapped by the laser beams, or when the laser beams move too fast, such that the cells escape from the traps during manipulation. This paper presents a closed-loop control formulation and strategy for optical manipulation of multiple cells, based on the cooperative movement of the motorized stage and the beam steering system. The closed-loop control method enables the trapping operation to be automatically activated whenever the cells are not inside the optical traps. The proposed controller does not require exact knowledge on the dynamic parameters and the varying trapping stiffness. Lyapunov methods are employed in the stability analysis of the optical tweezers system. Experimental results are presented to illustrate the performance of the proposed controller.
240-bit collective signature protocol in a non-cyclic finite group

The article describes a collective digital signature protocol based on the difficulty of the discrete logarithm problem modulo a composite number that is a product of two strong primes having the 2:1 size ratio. The usage of difficult problems provide signature protocol with security improvement, because the probability to break the protocol has been reduced significant. This can be achieved due to the appearance of breakthrough solutions in the area of the factoring problem and the discrete logarithm modulo a prime problem. One of the features of the protocol is using the non-cyclic finite group. After selecting appropriate parameters which provide 80-bit security, the size of the proposed collectively signature is 240 bits and is not dependent on the number of signers.
Agent-based simulation on avian influenza in Vietnam: Basic characteristics of the epidemic and efficiency evaluation of control measures

During the first large outbreak of avian influenza (H5N1) in 2004 in Vietnam, an estimated 45 million poultry were culled or died, which resulted in a direct loss of approximately 0.1 percentage points of GDP (World Bank, 2005). The need for an effective strategy is not only the concern of biology and medical science but also of epidemiology.  We use a mathematical model to estimate the transmission probability of the disease based on daily reported number of dead poultry in northern Vietnam in November of 2005. The estimated values then are applied in an agent-based model which is used to evaluate the efficiency of current under-taken control measures.  The results imply a combination of culling 10% of infected poultry, 50% of preventive vaccinating and limiting transport of poultry, poultry products when 1% of the population were reported infectious could keep the disease under control and halt the infection process within 65 days.  To prevent a new major outbreak of avian influenza in domestic poultry, a comprehensive strategy of culling, bio-security control and large-scale vaccination campaign should be set up in motion.