nils-herrmann/clean_scirepeval huggingface dataset:
An Adaptive Weighted Least-Load Balancing Algorithm Based on Server Cluster

In order to resolve problems such as server's weight described inaccurately, load balancing schedule inefficiently and so on, which exist in the traditional load balancing algorithms Based on server cluster, a kind of adaptive weighted least-load balancing algorithm is founded in this article. The server nodes are divided into mild load nodes and non-mild load nodes. The servers are polled in the cluster, and the mild load node is selected to response users' requests directly when user-connection requests arrival. If there are no mild load nodes in the cluster, weights are adjusted adaptively according to the server connection status, and the nodes are selected which has the minimum ratio of weight to load to provide service. Through simulation on OPNET Modeler, the results indicate that the new proposed algorithm can reduce the service delay, improve the average response rate, and balance servers' load in the cluster effectively.
A 10Gbps half-rate digital clock and data recovery circuit for 60GHz receiver in 65nm CMOS

A half-rate digital clock and data recovery (CDR) circuit for 60GHz 10Gbps QPSK receiver in 65nm CMOS is presented. Analog blocks are replaced by digital equivalents to save power and area, reduce PVT variation and improves testability. Voltage-controlled oscillator (VCO) is replaced by phase interpolator (PI) which is controlled by digital control signals. Half-rate Bang-Bang phase detector (BBPD) is used to decrease the clock rate, thus, double edge-triggered sampler is needed in such multi-Gbps CDR. The CDR consumes 17.44mW with a supply voltage of 1.0V, and operates from 1.25Gbps to 6.4Gbps with a maximum clock frequency offset tolerance of 40 ppm.
Using CONDENSATION Tracking to Recover Stroke Order of Chinese Calligraphic Handwritings with CCM

Stroke order is an intrinsic writing feature which is missing in off-line handwriting. Recovering stroke order from off-line handwriting is an important task by which the visualization of writing process is possible. Chinese Calligraphic handwriting is some different with western handwriting. Traditional method with assumption of the minimization of curvature between two adjacent line segments is not applicable for Chinese Calligraphic handwriting. We propose a new framework named Chinese Calligraphic Model (CCM). With this framework CONDENSATION algorithm - conditional density propagation over time is performed to find the best matching model in model database with the input pattern to recover stroke order. Experiments results show our method is a promising way to recover stroke order from Chinese Calligraphic handwriting based on CCM by CONDENSATION tracking.
Growth time of the longitudinal coupled bunch mode beam instability at the Duke FEL facility

To determine the required power of an amplifier for the longitudinal feedback (LFB) system, the growth time of the strongest longitudinal coupled bunch mode instability (CBMI) in the Duke storage ring should be measured in advance. In 2005, we measured strength of the strongest longitudinal beam instability in the Duke storage ring with four and eight symmetrically filled buckets. By analyzing measured data, the growth time of the strongest dipole mode of the longitudinal CBMI in the Duke storage ring can be estimated. At a beam energy of 274 MeV, the growth time is about 0.365 ms for a total stored beam current of 160 mA. From the measured growth time, we estimated the required power of the amplifier for the LFB system. To damp all harmful longitudinal CBMIs with an energy deviation of 0.1 % (rms) within its growth time of 0.365 ms, we have to supply about HOW (rms) to an LFB kicker whose a central frequency is 937.3875 MHz. In this paper, we describe the growth time of the longitudinal CBMI at the Duke storage ring and the estimation of the required power for the LFB system to damp all CBMIs within 0.365 ms.
Simulation-based scheduling for photo-reconnaissance satellite

A simulation-based scheduling mechanism for photo-reconnaissance satellite is presented in this paper. The satellite scheduling problem belongs to a class of single-machine scheduling problems with time window constraint. It is NP-hard in computational complexity. Based on simulation platform, a mixed integer programming model is used to formulate the problem and an advanced tabu algorithm is adopted to solve the MIP. Numerical results demonstrate that this approach is efficient in the scheduling problems.
New method for measuring properties of ferroelectric materials in microwave

Over the last few decades, ferroelectric materials have been gaining much interest due to the unique operational characteristics they demonstrate when a dc electric field is applied. This paper is committed to introduce a new way of investigating ferroelectric materials and their characteristics under the effect of an electric field bias#about 1000V#and high frequencies (0.8GHz∼1 GHz). In the new method, TRL calibration and an electric field bias is invoked to guide the microstrip line. Meanwhile, simulation and measured results demonstrate the effectiveness of the scheme.
An embedded Node Operating System for real-time information interaction in Vehicle-to-Vehicle communication

Information interaction system plays an important role in establishing a real-time and high-efficient traffic management platform in Intelligent Transportation System (ITS) applications. However, the present transmission technology still exists some defects in satisfying with the real-time performance of users data demand in Vehicle-to-Vehicle (V2V) communication. In order to solve this problem, this paper puts forward a novel Node Operating System (NDOS) scheme to realize the real-time data exchange between vehicles with wireless communication chips of mobile devices, and creates a distributed information interaction system for the interoperability between devices from various manufacturers. In addition, optimized data forwarding scheme is discussed for NDOS to achieve better transmission property and channel resource utilization. Experiments have been carried out in Network Simulator 2 (NS2) evaluation environment, and the results suggest that the scheme can receive higher transmission efficiency and validity than existing communication skills.
Video Analytics for Surveillance: Theory and Practice [From the Guest Editors]

Video analytics, loosely defined as autonomous understanding of events occurring in a scene monitored by multiple video cameras, has been rapidly evolving in the last two decades. Despite this effort, practical surveillance systems deployed today are not yet capable of autonomous analysis of complex events in the field of view of cameras. This is a serious deficiency as video feeds from millions of surveillance cameras worldwide are not analyzed in real time and thus cannot help with accident, crime or terrorism prevention, and mitigation, issues critical to the contemporary society. Today, these feeds are, at best, recorded to facilitate post-event video forensics.
Wide-range, person- and illumination-insensitive head orientation estimation

We present an algorithm for estimation of head orientation, given cropped images of a subject's head from any viewpoint. Our algorithm handles dramatic changes in illumination, applies to many people without per-user initialization, and covers a wider range (e.g., side and back) of head orientations than previous algorithms. The algorithm builds an ellipsoidal model of the head, where points on the model maintain probabilistic information about surface edge density. To collect data for each point on the model, edge-density features are extracted from hand-annotated training images and projected into the model. Each model point learns a probability density function from the training observations. During pose estimation, features are extracted from input images; then, the maximum a posteriori pose is sought, given the current observation.
3 kA Power Supplies for the Duke OK-5 FEL Wigglers

The next generation electromagnetic OK-5/Duke storage ring FEL wigglers ,  require three 3kA/70V power supplies with current stability about 20 ppm and current ripples less than 20 ppm in their full operating range. Duke FEL Laboratory acquired three out-of-service SCR controlled power supplies (Trans-Rex, 5kA/100V), which were built almost 30 years ago. The existing archaic firing circuit, lack of any output voltage filtering and with an outdated DCCT, would not be able to meet the above requirements. To deliver the desirable high performance with very limited funds, all three Trans-Rex power supplies have been completely rebuilt in-house at DFELL. Modern high stability electronic components and a high precision Danfysik DCCT have been used. A new symmetrical firing circuit, efficient passive filter and reliable transformer-coupled active filter are used to reduce output current ripples to an appropriate level. At the present time, all three refurbished power supplies are in operation. One of these power supplies was used since August, 2004 to feed OK-4 wigglers with good overall performance. Others two have been tested and used as power supplies for magnetic measurements.
The feasibility study of measuring the polarization of a relativistic electron beam using a Compton scattering Gamma-ray Source

The Compton scattering of a circularly polarized photon beam and a polarized electron beam leads to an asymmetric spatial distribution of the gamma rays. This asymmetry has been calculated for the high intensity gamma-ray source (HIGS) beam at Duke University. Owing to the high intensity of the HIGS beam, this asymmetry is determined to be measurable with a small statistical error using a simple optical imaging system for gamma-ray beams. We propose to set up this system to measure the polarization of the electron beam in the Duke storage ring.
An algorithm of restraining the receiver position errors for moving source localization using TDOA

This paper analyzes the observability of estimating simultaneously the initial position and velocity of a constant velocity source by two fixed receivers using TDOA measurements observed many a time. From the geometrical means of vector operations, it arrives at the conclusion that the conditions are similar to those in the general source localization by multi-receivers using TDOA. Then the Cramer-Rao lower bound with erroneous receiver positions is derived in this paper and an algorithm based on Taylor-series is proposed to restrain the errors. Both theoretical development and Monte Carlo simulations prove that the algorithm can reach the Cramer-Rao lower bound under Gaussian noise when it converges.
Evaluation of RF and logic performance for 40 nm InAs/InGaAs composite channel HEMTs for high-speed and low-voltage applications

The DC and RF performances of 40 nm high electron mobility transistors (HEMTs) with composite channel of InAs channel and In<sub>0.53</sub>Ga<sub>0.47</sub>As sub-channel were demonstrated. The drain current was 870 mA/mm (V<sub>ds</sub>=0.4V, V<sub>gs</sub>=0V) and maximum g<sub>m</sub> was 1750 mS/mm (V<sub>ds</sub>=0.5V, V<sub>gs</sub>=-0.65V). The devices showed high current gain cutoff frequency (f<sub>T</sub>) of 420 GHz and low gate delay time of 0.77 ps owing to the nanometer gate length and extremely high electron mobility of the InAs channel. Under low DC power consumption; these InAs HEMTs still exhibited excellent RF and logic performance which indicates these devices have great potential for future high-speed and low-voltage applications.
An improved algorithm of synchronization based on maximum correlation for GSM signals

Several traditional algorithms of synchronization of GSM signal first discussed in this paper. They do not work well at low signal-noise-ratio. An improved algorithm based on maximum correlation is proposed in this paper. This paper compares and analyses the proposed algorithm with the traditional algorithm. Finally, a simulation has been taken to show the performance of different algorithm. The simulation shows that the proposed algorithm can conquer the strong interfere and synchronize accurately.
Online Variable Coding Length Product Quantization for Fast Nearest Neighbor Search in Mobile Retrieval

Quantization methods are crucial for efficient nearest neighbor search in many applications such as image, music, or product search. As mobile devices are becoming increasingly more popular, the quantization methods on mobile devices are more important, because a large portion of the search queries are becoming performed on mobile devices. One important characteristic of the communication on mobile devices is the inherent unreliability of their communication channels. In order to adapt the quality changes of the communication channels, we need to change the coding length of the quantization accordingly. The existing quantization methods use fixed-length codebooks, and it is expensive to retrain another codebook with different coding length. In this paper, we propose a novel variable length product quantization framework that consists of a set of fast universal scalar quantizers. The framework is capable of producing variable length quantization without retraining the codebook. Each data vector is transformed into a new space to reduce the correlation across dimensions. A proper number of bits is allocated to represent the scalar component in each dimension according to the given coding length. For each component, we estimate its probability density function (PDF) and design an efficient universal scalar quantizer based on the PDF and the allocated bits. To reduce distortion, we learn a Gaussian mixture model for the data. The experimental results show that, compared to state-of-the-art product quantization methods, our approach can construct the codebooks online for variable coding lengths and achieve the comparable performance.
Modeling and Fast Eye Diagram Estimation of Ringing Effects on Branch Line Structures

Significant ringing effects due to multiple reflections are first addressed for the slightly unbalanced address lines in the double data rate memory systems. A resistance-inductance-capacitance resonance model is proposed to explain its occurrence by fitting the transfer function in frequency domain. The transient analysis can then be performed easily and the peak distortion analysis is used to predict its eye height. The cases with the worst signal integrity were identified and a simple design rule is derived to avoid its occurrence, which is dependent on the attenuation constant of the transmission line and the data rate of the signal.
Modified adaptive resonance theory for alarm correlation based on distance hierarchy in mobile networks

Nowadays, a fault management incorporating with alarm correlation rules play an important role on network management and maintenance. Alarms are unsolicited messages received from network elements or network management systems carrying information about malfunction location, type, severity and other relevant information. Usually, alarm information consists of categorical and numerical attributes and is difficult to be processed by most of clustering algorithms. This paper introduces a method of mining correlation rules of alarm messages by modified adaptive resonance theory network (MART) algorithm. The experiments illustrate good performance of the proposed algorithm with concept hierarchy tree to solve similar degrees of mixed data. Furthermore, this method could be used to build a hybrid system with traditional case-based reasoning system.
Indium Phosphide Heterobipolar Transistor Technology Beyond 1-THz Bandwidth

Recent improvements in the fabrication technology of InGaAs/InP heterobipolar transistors have enabled highly scaled transistors with power gain bandwidths above 1 THz. Limitations of the conventional fabrication process that reduce RF bandwidth have been identified and mitigated, among which are high resistivity base ohmic contacts, resistive base electrodes, excessive emitter end undercut, and insufficient undercut of large-diameter base posts. A novel two-step deposition process for self-aligned metallization of sub-20-nm bases has been developed and demonstrated. In the first step, a metal stack is directly evaporated onto the base semiconductor without any lithographic processing so as to minimize contamination from resist/developer chemistry. The composite metal stack exploits an ultrathin layer of platinum that controllably reacts with base, yielding low contact resistance, as well as a thick refractory diffusion barrier, which permits stable operation at high current densities and elevated temperatures. Further reduction of overall base access resistance is achieved by passivating base and emitter semiconductor surfaces in a combined atomic layer deposition Al2O3 and plasma-enchanced chemical vapor depositon SiNx sidewall process. This technology enables the deposition of low-sheet-resistivity base electrodes, further improving overall base access resistance and fmax bandwidth. Additional process enhancements include the significant reduction of device parasitics by scaling base posts and controlling emitter end and base postundercut.
Discovering optimal brain states for problem solving with EEG

To characterize neuro-cognitive dynamics during problem solving, high-density electroencephalography (EEG) (128 channels) was recorded as healthy adults engaged in math puzzles and rated the degree of insight that they experienced during the solution process. Higher levels of insight were typically associated with longer solution latencies. Time-frequency transforms of artifact-corrected EEG time series data from six pilot subjects revealed distinct left and right hemisphere contributions during the problem-solving phase irrespective of participants' subjective insight experience. However, while few topographic differences as a function of insight rating were discerned, insight solutions tended to involve more sustained and stronger desynchronization of scalp-recorded activities in the alpha, beta, and gamma ranges relative to non-insight trials. These findings may help to uncover "cortical signatures" associated with successful problem solving in math and other domains.
Incremental Maintenance of Topological Patterns in Spatial-Temporal Database

Spatial temporal mining is an important research area with many interesting topics. Most spatial temporal databases are updating incrementally with time. Some discovered topological patterns may be invalidated and some new topological patterns may be introduced by the evolution of databases. However, the existing static algorithms are usually inefficient and not feasible to maintain topological patterns in an incremental environment. In this paper, we develop an efficient algorithm, Inc_TMiner (Incremental Topology Miner) to incrementally maintain topological patterns in spatial-temporal databases. The experimental results indicate that Inc_TMiner significantly outperforms state-of-the-art algorithms in execution time and possesses graceful scalability.
Adaptive incremental video super-resolution with temporal consistency

Video super-resolution can be generally divided into two categories: incremental video super-resolution and simultaneous video super-resolution. Incremental video super-resolution algorithms are usually faster, but their results cannot be guaranteed to be visually consistent to the human vision system. An adaptive incremental video super-resolution framework with the temporal consistency constraint is proposed in this paper. The temporal consistency among the video frames is enforced by imposing the similarity between the adjacent reconstructed HR frames. The variances of the potential functions, which affect the weights of the different terms in the utility function, are adaptively determined so that the algorithm is robust to various motion and image content situations. Some considerations, such as the incremental motion estimation, are also incorporated to improve the efficiency of the algorithm, which makes the proposed algorithm near-realtime. The experimental results show that the proposed algorithm can generate HR video with high quality while saving the computational time as well.
Learning in content-based image retrieval

In this paper we address several aspects of the learning problem in content-based image retrieval (CBIR). First, we introduce the linear and kernel-based biased discriminant analysis, or BiasMap, to fit the unique nature of relevance feedback as a small sample biased classification problem. Secondly, a WARF (word association via relevance feedback) formula is presented for learning keyword relations during the process of relevance feedback. We also introduce our new user interface for CBIR, ImageGrouper, which is designed to support more sophisticated user feedbacks and annotations. Finally, we use the D-EM (Discriminant-EM) algorithm as a way of exploiting unlabeled data in CBIR and offer some insights as to when unlabeled data will help.
A field model for human detection and tracking

The large shape variability and partial occlusions challenge most object detection and tracking methods for nonrigid targets such as pedestrians. This paper presents a new approach based on a two-layer statistical field model that characterizes the prior of the complex shape variations as a Boltzmann distribution and embeds this prior and the complex image likelihood into a Markov field. A probabilistic variational analysis of this model reveals a set of fixed-point equations characterizing the equilibrium of the field. It leads to computationally efficient methods for calculating the image likelihood and for training the model. Based on that, effective algorithms for detecting nonrigid objects are developed. This new approach has several advantages. First, it is intrinsically suitable for capturing local nonrigidity. In addition, due to the distributed likelihood, this approach is robust to partial occlusions. Moreover, the two-layer structure provides large flexibility of modeling the image observations, which makes the new method robust to clutters. Extensive experiments demonstrate its effectiveness.
A 12-bit 4-kHz incremental ADC with loading-free extended counting technique

In this design, a low-power incremental ADC employing the loading-free architecture for the extended counting technique is proposed. The proposed topology uses a multi-bit SAR ADC to complete the extended counting conversion, but the integrator of the preceding incremental ADC is not loaded by the DAC array of the SAR ADC, which means the opamp power can be reduced. This work adopts an incremental ADC to convert the first 5-bit MSB and a synchronous SAR ADC to convert the last 7-bit LSB, and thus totally 12-bit resolution can be obtained without calibration. The proposed topology is capable of achieving high resolution, and furthermore holds the power efficient advantage of SAR ADCs. The proposed ADC is implemented in a 0.18-μm 1P6M CMOS process. Under 4-kHz input signal bandwidth and 23.07-μW power consumption, the peak signal-to-noise and distortion ratio is 69.38 dB. The active core area including clock generator occupies of 0.33 mm2.