nils-herrmann/clean_scirepeval huggingface dataset:
An Oscillator-Based CMOS Magneto-Sensitive Biosensor With In-Situ Switched Capacitor Calibration Scheme

This letter presents a high sensitivity oscillator-based magneto-sensitive biosensor. To suppress the environmental variations, e.g., voltage vibration, temperature drift, and lower the noise floor, an in-situ switched capacitor (ISSC) based calibration scheme is proposed with little cost on on-chip area and complexity. As an implementation example, a biosensor cell is designed in a standard 180-nm CMOS process. The ISSC scheme achieves an extra 13.2 dB suppression on the effective noise floor. The magnetic sensing capability of the presented biosensor is verified, indicating the frequency shift from one single magnetic nano-particle (MNP) with 500 nm diameter is 138.5 Hz and the dynamic range of detection is at least 80 dB.
Achieving Lower Delay with Energy Efficiency in Extremely Low-Duty-Cycle and Unreliable WSN

In extremely low-duty-cycle wireless sensor networks, a sender has to wait for a certain period of time to forward a packet until its receiver becomes active, which will result in longer end-to-end delay than ever. Many works have been done to improve delivery ratio but lack of the consideration on energy efficient delivery delay. In addition, unreliable links is another challenge in wireless sensor networks. Redundancy and multiple paths can be used to cope with unreliability, but neither of them is energy efficient. Even worse, both of them have poor performance on delivery delay. In this work, we introduce a novel way of allocating erasure coded blocks over multiple paths to improve energy efficient delivery delay while achieving comparably high delivery ratio. We evaluate our algorithm with extensive simulations. Evaluations show that our design decreases delivery delay greatly with slight decrease in delivery ratio.
Azimuth scaling for inverse synthetic aperture radar images with feature registration

This paper proposes a novel azimuth scaling algorithm for estimating the relative rotation angle of two continual say sub-aperture inverse synthetic aperture radar (ISAR) images of a rigid space ISAR target by using a feature registration of coordinate locations of interested points extracted from the images above. Specifically, we firstly extract sufficient interested points and feature descriptor vectors from two sub-aperture ISAR images by Scale Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF). The interested points are then matched by using the feature registration in a two-stage manner based on Euclid-Distance and Random Sample Consensus (RANSAC). A premise to the azimuth scaling for ISAR images, the rotation angle can be estimated by precisely linking the coordinate locations of the matched interested points, followed by a determination of the least value of a cost function to achieve the azimuth scaling for measuring the real size of the target. Simulated and real data experiments validate the proposal.
Aggregating Deep Convolutional Feature Maps for Insulator Detection in Infrared Images

Insulator detection using an infrared image is challenged by variance of temperature, orientations, and a cluttered background. A robust and discriminative representation of insulators in electric power systems is needed. This paper proposes a novel method for generating this type of representation in infrared images by taking advantage of high-level discriminative Convolutional Neural Networks (CNNs) to feature the extraction framework and the deformation invariant nature of the Vector of Locally Aggregated Descriptors (VLAD) aggregator. Different from existing methods, we delve deep into the convolutional feature maps. We first extract deep activation maps from convolutional layers of a pretrained deep model and replace the last three fully-connected layers with a VLAD pooling layer to generate the representation of an insulator. Then, we train a Support Vector Machine (SVM) for binary classification. To further verify the effectiveness and robustness of our proposed feature, an insulator detection pipeline based on an object proposal is introduced. The experimental results show that our proposed method can achieve an accuracy of 93%. Meanwhile, the detection results demonstrate that our insulator detection pipeline has satisfied performance goals.
A Method of Robotic Visual Tracking for a New Automatic Laser Welding Line

An on-line visual tracking sensor system for the automation of laser welding processes in heavy industries is presented. A method of image process and features extraction for structured light image of laser welding has been developed. In order to set the range of interest, the Radon Transform is applied to determine the x and y coordinate in image coordinate system. For image de-noising, the median filtering and bi-level thresholding are used. Furthermore, the middle line of the laser stripe is extracted. Finally, a five step search method is carried out to examine the mid-point and gap width. A series of experiments show that the proposed method in this paper is effective, and its tracking detection precision is much better than traditional methods.
Design and Verification of Ultra Low Current Mode Amplifier Aiming at Biosensor Applications

Along with the booming of research and production of CMOS integrated bio-sensing system (IBS), ultra low current mode amplifier which serves for biosensor signal pre-amplification implemented in modern CMOS technology is in high demand in areas like ultra low bio-current analysis and detection, DNA probing and surveying systems and etc. In this paper, a novel current mode pre-amplifier (CMPA) module has been presented and verified in SMIC 0.18 mum CMOS process by elaborately considering gain, bandwidth, noise, and mismatch. The proposed CMPA solved the noise, bandwidth, and current headroom dilemma in the reported works, and can completely satisfy the specifications of IBS and stably provide a current gain of 20 dB, 3 dB band width of 7.03 kHz and input dynamic range of 20 bit, with only InA of DC quiescent current, while the input offset current and noise current are less than 16.0 pA and 4.67pArms, respectively.
Design of High-Power CW signal generators for WiMAX network planning

For the application of WiMAX network planning, especially for the channel model calibration of wireless propagating, broadband and High-Power CW signal generators were designed in this paper. This work comprise two individual generators, one operates on frequency range from 2.3 GHz to 2.7 GHz and the maximum output power is 20 W, the other covers the range from 3.4 GHz to 3.6 GHz with the maximum output power of 5 W. The frequency of output signal can be tuned by a step size of 250 KHz, and the accuracy of output power is less than plusmn1.5 dB.
An Improved String Matching Algorithm for HTTP Data Reduction

In this paper, we analyze both BMH algorithm and QS algorithm, focus on the improvement of QS, and present FQS algorithm which can apply to HTTP data reduction. For building this algorithm, we considered character features of pattern strings in HTTP application data, improved the collating sequence of characters in matching process, and had the bad characters jumping strategy improved for increasing the jumping distance. Experimental results show that FQS algorithm effectively reduces matching time and a better time performance.
An interventional treatment plan system design on liver tumor

Interventional treatment becomes increasingly popular since this technique means substantially less trauma for the patient. By using VTK and ITK to build a plan system, the treatment can be high efficiency. VTK is responsible for visualization, while ITK takes care of the image segmentation and registration. By combining VTK and ITK, and using Qt as the user interface, an interventional treatment plan system is built. This system has finished several mainly functions, like DICOM data displaying in multi-planar reformation, manual segmentation, semi-automatic segmentation, surface rendering using marching cubes algorithm, volume rendering using volume ray casting algorithm. Also an interventional treatment plan system has been developed based on the medical inspection.
A New Full-Rate Orthogonal Space-Time Block Coding Scheme Based on Quaternion

This paper introduces a full rate, full diversity orthogonal space-time block code for 4 transmit antennas. The4times4 codeword matrix consists of four 2times2 Alamouti blocks, and these blocks can be viewed as quaternions which in turn represent rotations in R3. The Alamouti blocks that appear in a codeword are drawn from the icosahedral group. The code is no constellation expansion unlike some full-rate full-diversity codes in the literature. By utilizing the quaternionic form, we can find the decoding algorithm to reduce the complexity of maximum likelihood (ML) coherent decoding.
Contributory Broadcast Encryption with Efficient Encryption and Short Ciphertexts

Broadcast encryption (BE) schemes allow a sender to securely broadcast to any subset of members but require a trusted party to distribute decryption keys. Group key agreement (GKA) protocols enable a group of members to negotiate a common encryption key via open networks so that only the group members can decrypt the ciphertexts encrypted under the shared encryption key, but a sender cannot exclude any particular member from decrypting the ciphertexts. In this paper, we bridge these two notions with a hybrid primitive referred to as contributory broadcast encryption (ConBE). In this new primitive, a group of members negotiate a common public encryption key while each member holds a decryption key. A sender seeing the public group encryption key can limit the decryption to a subset of members of his choice. Following this model, we propose a ConBE scheme with short ciphertexts. The scheme is proven to be fully collusion-resistant under the decision n-Bilinear Diffie-Hellman Exponentiation (BDHE) assumption in the standard model. Of independent interest, we present a new BE scheme that is aggregatable. The aggregatability property is shown to be useful to construct advanced protocols.
Automatic Calibration of a Hydrological Model Using Multiobjective Particle Swarm Optimization and TOPSIS

The performance of a hydrological model heavily depends on choosing suitable model parameters. A framework for automatic calibration of a hydrological model named the Xinanjiang model with multiobjectives has been presented. In the calibration framework, a MOPSO algorithm was employed to find the non-dominated front in the objective space, and an entropy-based TOPSIS ranking method was used to rank the non-dominated solutions. As an application example, daily rainfall, evaporation and flow discharge data are used to calibrate and verify the Xinanjiang model in Misai catchment with an area of 799 km2. The results show that the MOPSO is efficient and robust to find non-dominated front of the Xinanjiang model. The results also show that the entropy-based TOPSIS provides an impersonal method to calculate objective weights and rank the non-dominated solutions.
DANoC: An Efficient Algorithm and Hardware Codesign of Deep Neural Networks on Chip

Deep neural networks (NNs) are the state-of-the-art models for understanding the content of images and videos. However, implementing deep NNs in embedded systems is a challenging task, e.g., a typical deep belief network could exhaust gigabytes of memory and result in bandwidth and computational bottlenecks. To address this challenge, this paper presents an algorithm and hardware codesign for efficient deep neural computation. A hardware-oriented deep learning algorithm, named the deep adaptive network, is proposed to explore the sparsity of neural connections. By adaptively removing the majority of neural connections and robustly representing the reserved connections using binary integers, the proposed algorithm could save up to 99.9% memory utility and computational resources without undermining classification accuracy. An efficient sparse-mapping-memory-based hardware architecture is proposed to fully take advantage of the algorithmic optimization. Different from traditional Von Neumann architecture, the deep-adaptive network on chip (DANoC) brings communication and computation in close proximity to avoid power-hungry parameter transfers between on-board memory and on-chip computational units. Experiments over different image classification benchmarks show that the DANoC system achieves competitively high accuracy and efficiency comparing with the state-of-the-art approaches.
Design and Analysis of a Minimum Time Buckets Synchronization Algorithm for Parallel and Distributed Simulation

Time synchronization is critical for parallel and distributed simulation (PADS). In this paper we first compare the two main synchronization mechanisms in PADS, namely conservative and optimistic protocols. Then we propose a Minimum Time Buckets synchronization algorithm, which can optimistically schedule events without sending anti-messages. Comparing to the well-known Breathing Time Bucket (MTB) synchronization algorithm, our algorithm reduces the waiting time and rollback probability for logical processes, yet it commits the same number of events in each time advance interval. Experiment results show that the MTB algorithm can effectively decrease the rollback rate, reduce the execution time, and achieve a higher speed up.
Design of hollow-core photonic band-gap fibers for CH4 and C2H2 optical fiber sensors

A hollow-core photonic band-gap fiber for optical fiber sensors is designed. According to the calculation, we get the parameters of the photonic band-gap fiber as d=0.94∗2.60μm, R=Λ=2.60μm for C<inf>2</inf>H<inf>2</inf>, and d=0.94∗2.41μm, R=Λ=2.41μm for CH<inf>4</inf>. Around the wavelength of λ<inf>C2H2</inf> = 1.53μm and λ<inf>CH4</inf> = 1.66 μm, 98% of the energy is propagated in the core, the fiber is suitable to be used to detect the gas such as CH<inf>4</inf> and C<inf>2</inf>H<inf>2</inf>.
A multichannel data acquisition system design for Guided Waves Ultrasound Testing

Guided Waves Ultrasound Testing (GWUT) is a non-destructive testing (NDT) testing technology, widely used in industry for testing corrosion and degradations in long distance pipelines. GWUT has the advantage of 100% coverage of the pipe wall over many meters from a single test location. Multiple transmit and receive channels are required to drive a large number of piezoelectric transducers in order to excite axisymmetric GWU that are uniform around the pipe circumference for even inspection. This paper presents an efficient and reliable multichannel receiver system design for the GWUT, which makes it possible for meeting critical timing requirements for multichannel data acquisition with real-time DSP functions, such as accumulation and saturation detection. The design has been successfully used in a new generation commercial testing equipment to improve the system efficiency by reducing component counts, PCB size and power consumption. The system has been designed not only to meet the current hardware specifications, but also with the potential to increase the number of receiver channels for a more complicated system.
AnnoSearch: Image Auto-Annotation by Search

Although it has been studied for several years by computer vision and machine learning communities, image annotation is still far from practical. In this paper, we present AnnoSearch, a novel way to annotate images using search and data mining technologies. Leveraging the Web-scale images, we solve this problem in two-steps: 1) searching for semantically and visually similar images on the Web, 2) and mining annotations from them. Firstly, at least one accurate keyword is required to enable text-based search for a set of semantically similar images. Then content-based search is performed on this set to retrieve visually similar images. At last, annotations are mined from the descriptions (titles, URLs and surrounding texts) of these images. It worth highlighting that to ensure the efficiency, high dimensional visual features are mapped to hash codes which significantly speed up the content-based search process. Our proposed approach enables annotating with unlimited vocabulary, which is impossible for all existing approaches. Experimental results on real web images show the effectiveness and efficiency of the proposed algorithm.
Design and research of KALMAN filter in MULTI-GNSS receiver

With the rapid development of GNSS receiver's performance and the coming of each GNSS's Full Operational Capability (FOC), compatibility and interoperability must be one of the developing trends of GNSS positioning. In this study, a compatible kalman filter was designed. The performances of the compatible kalman filter (KF) and traditional Least Square (LS) were compared through BDS, GPS, and GLONASS real static data in different conditions. The result shows that the compatible KF has more stability and robustness than LS. Position solutions can be obtained from the compatible KF even when the number of satellites is not enough for LS.
An improved robust fuzzy-PID controller with optimal fuzzy reasoning

Many fuzzy control schemes used in industrial practice today are based on some simplified fuzzy reasoning methods, which are simple but at the expense of losing robustness, missing fuzzy characteristics, and having inconsistent inference. The concept of optimal fuzzy reasoning is introduced in this paper to overcome these shortcomings. The main advantage is that an integration of the optimal fuzzy reasoning with a PID control structure will generate a new type of fuzzy-PID control schemes with inherent optimal-tuning features for both local optimal performance and global tracking robustness. This new fuzzy-PID controller is then analyzed quantitatively and compared with other existing fuzzy-PID control methods. Both analytical and numerical studies clearly show the improved robustness of the new fuzzy-PID controller.
Device physics and EM simulation based modeling methodology for LDMOS RF power transistors

In this paper, process, device, and electromagnetic simulations are combined to produce a distributed nonlinear model for an LDMOS RF power transistor. The simulation challenges are handled by using multiple simulators, each with a suitable role in the modeling process. Semiconductor fabrication and device operation are performed through the process and device technology computer aided design (TCAD) tool. The outcome from the TCAD simulations are used to generate a nonlinear compact model for a small section of the device. To form the complete transistor model, many small sections of the compact model are connected by a large-scale interconnect network, which is modeled based on electromagnetic (EM) simulations. For convenient use in circuit simulator, the distributed nonlinear model is implemented by a script-generated comprehensive netlist. It is demonstrated that this purely simulation-based model can accurately predict device behavior under DC, small-signal, and large-signal tests, and is useful for first-pass computer-aided design before wafer fabrication.
Designation of Spares Consumption Quota Data Warehouse

Pointing at the problem that the spares consumption quota has been using the experience to develop, which makes spares application random and blind, this paper puts forward to build the reasonable lifeless-repairable spares consumption quota model. Analyze and determine the factors influencing the lifeless-repairable spares consumption, use BP neural network to predict, and use genetic algorithm to optimize the weights and thresholds of BP neural network, so that the network can obtain the global minimum point. The example shows that the model's predicted results are relatively accurate and has high practicability.
A 56-to-66 GHz quadrature phase-locked loop with a wide locking range divider chain in 65nm CMOS

A low power and low phase noise phase-locked loop (PLL) is proposed in this paper to provide a quadrature millimeter-wave source for the 60GHz direct-conversion transceiver. An in-phase injection-coupled quadrature voltage controlled oscillator (IPIC-QVCO)  whose symmetric coupling structure is composed of four diode-connected transistors is implemented to optimize both phase noise and phase error. Besides, a novel feedback is proposed in the QVCO to reduce phase noise while remaining the oscillation frequency range unchanged. This PLL employs divider chain with a wide locking range consisting of a digitally controlled injection-locked frequency divider (ILFD) with a 2-bit binary-weighted switch-capacitor bank, 3 current mode logic (CML) dividers, and a multiple modulator divider (MMD). The proposed PLL is designed with a 65nm CMOS technology, and the QCVO achieves a tuning range of 16.39% from 55.95GHz to 65.94GHz with a phase noise of -97.5dBc/Hz at 1MHz offset while consuming 12mW of power. Extensive simulation show that the PLL achieves an excellent phase noise performance of -92dBc/Hz at 1MHz offset and covers all the four required frequency in IEEE802.11ad (58.32GHz, 60.48GHz, 62.64GHz, and 64.80GHz, respectively.) while consuming only 30mW of power from a 1.2 V supply.
A wide-locking range V-Band injection-locked frequency divider

A novel injection-locked frequency divider for V-Band frequency synthesis is proposed in this paper. Thanks to the nMOS realized in triple-well technology with N-well floating, the source and its body can be connected together to get rid of the body effect and thus reduce the nMOS threshold voltage, which helps enhance the injection efficiency in the direct injection-locked frequency dividers. The proposed divider is implemented in 90-nm CMOS technology and draws only 1-mA from 0.9-V low voltage supply. The simulation results show that the proposed frequency divider can work from 52-GHz to 65-GHz with 0-dBm input power. The division bandwidth is improved by 5-GHz comparing to the conventional structures.
An Image Segmentation Framework Based on Patch Segmentation Fusion

In this paper we present an image segmentation framework based on patch segmentation fusion. An image is first split into small patches. Segmentation is then performed on each patch using the algorithms of standard normalized cut (Shi and Malik, 1997), mean shift clustering (C. D. and M. P., 2002), or K-means clustering. Each region in a patch segmentation is assigned a label so as to represent different parts. After that, a connectedness value is calculated between any two overlapping patch segmentations with certain kinds of labeling. A weight called border strength is calculated for a segmentation with a certain labeling. We optimize a global criterion function that quantifies the consistency and quality of patch segmentations by a simulated annealing algorithm in order to find the optimal patch segmentations and labeling. Finally, global segmentation is reconstructed by fusing patch segmentations by multiple techniques. Experimental results on natural images are reported. Precision and recall rates are also calculated to evaluate the performance quantitively