nils-herrmann/clean_scirepeval huggingface dataset:
Regularized total least squares approach for nonconvolutional linear inverse problems

In this correspondence, a solution is developed for the regularized total least squares (RTLS) estimate in linear inverse problems where the linear operator is nonconvolutional. Our approach is based on a Rayleigh quotient (RQ) formulation of the TLS problem, and we accomplish regularization by modifying the RQ function to enforce a smooth solution. A conjugate gradient algorithm is used to minimize the modified RQ function. As an example, the proposed approach has been applied to the perturbation equation encountered in optical tomography. Simulation results show that this method provides more stable and accurate solutions than the regularized least squares and a previously reported total least squares approach, also based on the RQ formulation.
An integrated rate control scheme for TCP-friendly MPEG-4 video transmission

Delivering MPEG-4 real-time video over the Internet needs rate control schemes to be employed in both the compression and transport domains. In addition to the rate matching requirement between the two schemes to ensure TCP-friendliness, the demand of smoothness also has significant impact on media quality. We propose an integrated rate control scheme for MPEG-4 video transported by a TCP-friendly rate control (TFRC) protocol. Experimental results show successful integration with relatively low rate variation for video coding. Reduced frame skipping indicates, improved temporal quality while the flickering artifact, possibly caused by rate variation, is decreased through a PSNR test.
A Controlled-Release Drug Delivery System on a Chip Using Electrolysis

A system-on-a-chip (SOC) with integrated drug reservoirs for drug delivery is proposed. Electrolysis is used to generate microbubbles, which are employed as a force to open the reservoirs and release the drug. Wireless components, including an on/off keying receiver, microcontrol unit, regulator, clock divider, and power-on reset, are integrated for remote drug activation. The proposed microchip is fabricated by Taiwan Semiconductor Manufacturing Company 0.35-μm CMOS technology followed by post-IC processing. The total size is 2.48 mm2, and the power consumption is 7.57 mW. The in vitro experiment has proven the feasibility of the proposed drug delivery SOC.
Sound Event Recognition Using Auditory-Receptive-Field Binary Pattern and Hierarchical-Diving Deep Belief Network

Automatic sound event recognition (SER) has recently attracted renewed interest. Although practical SER system has many useful applications in everyday life, SER is challenging owing to the variations among sounds and noises in the real-world environment. This paper presents a novel feature extraction and classification method to solve the problem of SER. An audio–visual descriptor, called the auditory-receptive-field binary pattern, is designed based on the spectrogram image feature, the cepstral features, and the human auditory receptive field model. The extracted features are then fed into a classifier to perform event classification. The proposed classifier, called the hierarchical-diving deep belief network, is a deep neural network system that hierarchically learns the discriminative characteristics from physical feature representation to the abstract concept. The performance of our proposed system was verified using several experiments under various conditions. Using the RWCP dataset, the proposed system achieved a recognition rate of 99.27% for real-world sound data in 105 categories. Under noisy conditions, the developed system is very robust, with which it achieved 95.06% recognition rate with 0 dB signal-to-noise ratio. Using the TUT sound event dataset, the proposed system achieves error rates of 0.81 and 0.73 in sound event detection in home and residential area scenes. The experimental results reveal that the proposed system outperformed the other systems in this field.
18.7 A remotely controlled locomotive IC driven by electrolytic bubbles and wireless powering

As implantable medical CMOS devices become a reality , motion control of such implantable devices has become the next challenge in the advanced integrated micro-system domain. With integrated sensors and a controllable propulsion mechanism, a micro-system will be able to perform tumor scan, drug delivery, neuron stimulation, bio-test, etc, in a revolutionary way and with minimum injury. Such devices are especially suitable for human hollow organs, such as urinary bladder and stomach. Motivated by the art reported in ISSCC 2012 , we demonstrate a remotely-controlled locomotive CMOS IC which is realized in TSMC 0.35μm technology. As illustrated , this chip utilizes the gas pressure resulting from electrolytic bubbles as the propulsive force. By appointing voltages to the on-chip electrolysis electrodes, one can decide the electrolysis location and thereby control the bubbles emissions as well as the direction of motion. With power management circuits, wireless receiver and micro-control unit (MCU), the received signal can be exploited as the movement control as well as wireless power. Experiments show a moving speed of 0.3mm/s of this chip. The total size is 21.2mm2 and the power consumption of the integrated circuits and the electrolysis electrodes are 125.4μW and 82μW, respectively.
A Transceiver Design Based on Uniform Channel Decomposition and MBER Vector Perturbation

Uniform channel decomposition (UCD), as an improvement of geometric mean decomposition (GMD), is capable of decomposing a multiple-input-multiple-output (MIMO) channel into multiple subchannels having an identical capacity. Vector precoding (VP) is a powerful scheme, which is capable of mitigating multiuser interference (MUI) at the transmitter, provided that the channels of the users are known. In this paper, a novel joint transceiver design based on the UCD and the minimum bit error rate (MBER) VP principles is proposed for MIMO systems, in which the precoding and equalization matrices are calculated by UCD, whereas the perturbation vector is chosen to minimize the system's bit error ratio (BER). This UCD-MBER-VP transceiver design outperforms several state-of-the-art benchmark algorithms in terms of achievable BER performance without imposing an increased computational complexity, particularly for rank-deficient systems.
Maintenance of sequential patterns for record deletion

We previously proposed an incremental mining algorithm for maintenance of sequential patterns based on the concept of pre-large sequences as new records were inserted. In this paper we attempt to apply the concept of pre-large sequences to maintain sequential patterns as records are deleted. Pre-large sequences are defined by a lower support threshold and an upper support threshold. They act as buffers to avoid the movements of sequential patterns directly from large to small and, vice-versa. Our proposed algorithm does not require rescanning original databases until the accumulative amount of deleted customer sequences exceeds a safety bound, which depends on database size. As databases grow larger, the number of deleted customer sequences allowed before database rescanning is required also grows. The proposed approach is thus efficient for a large database.
Pulse waveform as an indicator of baseline offset in pulse transit time based blood pressure estimation

Cuff-less blood pressure (BP) estimation using pulse transit time (PTT) is a promising method for long-term BP monitoring. However, state-of-art PTT models are unable to trace the change of pressure baseline in subjects, which limits their application in long-term BP tracking. This study investigated the relationship between the change of pressure baseline and pulse waveform in long-term BP monitoring. In the study, a total of 36 subjects received daily monitoring of systolic BP (SBP) and PTT for over one month. Linear regression was used to develop the SBP-ln(PTT) model for each subject. SBP predictions with regression differences greater than + SD (7.63 mmHg) were assumed to be with positive/negative baseline offset. For each subject, 12 features extracted from pulse waveform were obtained and their values were converted to standard scores to quantify pulse waveform variation. Independent two-sample t-test showed five pulse wave features changed significantly when subjects' pressure baseline varied. Furthermore, the consistency of pulse waveform variation was validated over the change of pressure baseline in subjects. In summary, this study demonstrated that pulse waveform could indicate baseline offset in PTT-based BP estimation. By highlighting five pulse wave features, this study provides novel insights to overcome the challenge of frequent calibrations in long-term PTT-based BP monitoring.
Complexity modeling of scalable video decoding

This paper addresses the computational complexity of scalable video decoding using emerging scalable extension of H- 264/AVC (SVC) standard compliant decoder. Scalable functionalities provided by SVC standard encompass temporal, spatial, quality enhancements and their combinations. The complexity model for decoding a bit stream with only temporal, spatial, or quality scalability are developed first. We then extend to a more general model for decoding a bit stream with arbitrarily combined scalability. Comparison with the number of clock cycles used in SVC decoding on a PC shows that the proposed model is very accurate.
Effects of YAG: Ce Phosphor Particle Size on Luminous Flux and Angular Color Uniformity of Phosphor-Converted White LEDs

Effects of YAG: Ce phosphor particle size on the luminous flux and angular color uniformity have been studied by using Monte Carlo ray-tracing simulation. A white LED model basing on Cree XLamp is constructed. The phosphor particle size is changed from 2 to 20 μm. Different simulation cases are carried out by changing the phosphor concentration and thickness. Results revealed that the luminous flux and angular color uniformity have complex relationships with the particle size depending on applied phosphor concentration and desired color temperature. A general finding is that an increase of the particle size is beneficial for the improvement of luminous flux but leads to worse angular color uniformity. A 2 μm particle achieves not only the best angular color uniformity but the lowest luminous flux. A particle size larger than 10 μm generates the highest luminous flux at low color temperature when the concentration is around 1.5 g/cm3. A particle size between 2 μm and 10 μm shows combined moderate performance when the phosphor concentration is higher than 2 g/cm3. To realize the best combined performance, a particle size around 6 μm is suggested.
Prediction of weather impacted airport capacity using RUC-2 forecast

Weather induced airborne delays have caused significant problems at the major commercial airports in the United States. Using Rapid Updated Cycle forecast data (RUC-2), this paper presents real case studies for assessing the impact of weather on airport capacities by Quadratic Response Surface (QRS) linear regression models and ensemble Bagging Decision Tree regression (BDT) models. Three high-demand major airports: Newark Liberty International Airport (EWR), Chicago O'Hare International Airport (ORD), and Atlanta International Airport (ATL) were selected for the analysis. Both QRS and BDT models were developed and evaluated using the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) data and RUC-2 weather forecasts for these airports. The performances of the two weather impacted airport capacity models were compared and the errors between estimates and observations of airport arrival rates (AAR) were evaluated. The accuracy of AAR predictions in several hour look-ahead times using RUC-2 forecast weather was examined. The experimental results show that the accuracies of AAR estimations by nonlinear BDT regression models are much better than that from QRS multiple linear regression models. With airport AAR BDT models, the errors on weather corresponding AAR estimates using RUC weather data are smaller than that by METAR surface weather observations. Considering RUC includes much more weather information than METAR does, these findings strongly suggest that the adverse weather impact on airport capacity is complicated, relies on many predicting variables carried by RUC and it is inherently nonlinear. As a consequence, by using RUC weather forecasts, root mean squared error (RMSE) of the airport AAR BDT model predictions at one-hour look-ahead time are less than one and two arrival aircrafts per quarterly-hour for EWR and ORD/ATL airport, respectively. The ratio between AAR RMSE and average AAR for AAR predictions at one to eight hour look-ahead time is less than 10% for all three airports with nonlinear BDT models using RUC-2 weather forecasts. These results appear to be reasonably good.
Hierarchical Genetic Algorithms for Channel Allocation in Wireless Networks

Hierarchical genetic algorithms (HGA) as a tool for a search and optimizing methodology has now reached a mature stage. The minimum resource facility to carry user traffic which is called a channel unit (CU) is composed of the IEEE 802.16 medium access control (MAC) protocol. The control of the number of CU depending on traffic load solves heterogeneous and asymmetrical traffic problem in 4G system. In a cellular network, the call arrival rate, the call duration and the communication overhead between the base stations and the control center are vague and uncertain. Whether the criteria of concern be nonlinear, constrained, discrete or NP hard. In this paper, the HGA is used to tackle the neural network (NN) topology as well as the fuzzy logic controller for the dynamic CUs allocation scheme in wireless access net-works. Therefore, we propose a new efficient HGA CUs allocation (HGACA) in cellular networks. It aims to efficiently satisfy their diverse quality-of-service (QoS) requirements of multimedia traffic. The results show that our algorithm has lower blocking rate, lower dropping rate, less update overhead, and shorter channel acquisition delay than previous methods.
A link bundled auxiliary graph model for constrained dynamic traffic grooming in WDM mesh networks

This paper addresses the two-layer dynamic traffic grooming problem in wavelength-division-multiplexed (WDM) mesh optical networks subject to resource constraints and the generalized wavelength continuity (GWC) constraint. The GWC constraint is a relaxed wavelength continuity constraint which incorporates various kinds of wavelength conversion capabilities that exist in optical networks. As an improvement over the existing layered auxiliary graph (layered-AG) approach which represents each wavelength separately in the auxiliary graph, we introduce a largely simplified link bundled auxiliary graph (LBAG) model and propose the SAG-LB method to find paths and assign wavelengths for new lightpaths subject to the GWC constraint. We propose the constrained integrated grooming algorithm (CIGA) based on the LBAG model. A grooming policy influences the resource utilization by determining the weight function of the auxiliary graph. We propose the least resource path first (LR) grooming policy, which is an improvement over the existing grooming policies in the literature, by integrating the wavelength and transceiver metrics together. Simulation results show that the LBAG model achieves a comparable blocking performance with the layered-AG approach while using a significantly less amount of running time. We also present the worst case time complexity analysis of the CIGA grooming algorithm and evaluate the performance of the LR grooming policy by simulation.
Lapped orthogonal transforms designed for error-resilient image coding

This paper describes a new design method for lapped orthogonal transforms (LOTs) that can provide a desired tradeoff between coding efficiency and resilience to transmission errors. Traditionally, LOT bases have been designed solely to maximize coding efficiency. When certain coefficients are lost due to transmission channel impairments, the reconstructed image is often unsatisfactory. Previously, we have developed a maximally smooth recovery method for image reconstruction from incomplete LOT coefficients (see Chung and Wang, ibid., vol.9, p.895-908, 1999). The reconstruction quality depends on the LOT basis used. We describe a new LOT-basis design method, which maximizes the weighted average of a coding gain and a reconstruction gain, with the latter being defined according to the maximally smooth recovery method. A coder using the designed basis with a high weighting factor toward the reconstruction gain can achieve significantly better reconstruction quality than a LOT basis that is designed to optimize the coding efficiency only. The newly designed bases are evaluated by their redundancy-rate-distortion performance. Simulation results show that the new bases are more efficient than the bases designed previously by S.S. Hemami (see ibid., vol.6, p.168-81, 1996), in that the new bases require fewer redundancy bits to achieve the same reconstruction quality under the same channel error pattern.
On Robust Stability of Stochastic Genetic Regulatory Networks With Time Delays: A Delay Fractioning Approach

Robust stability serves as an important regulation mechanism in system biology and synthetic biology. In this paper, the robust stability analysis problem is investigated for a class of nonlinear delayed genetic regulatory networks with parameter uncertainties and stochastic perturbations. The nonlinear function describing the feedback regulation satisfies the sector condition, the time delays exist in both translation and feedback regulation processes, and the state-dependent Brownian motions are introduced to reflect the inherent intrinsic and extrinsic noise perturbations. The purpose of the addressed stability analysis problem is to establish some easy-to-verify conditions under which the dynamics of the true concentrations of the messenger ribonucleic acid (mRNA) and protein is asymptotically stable irrespective of the norm-bounded modeling errors. By utilizing a new Lyapunov functional based on the idea of ¿delay fractioning¿, we employ the linear matrix inequality (LMI) technique to derive delay-dependent sufficient conditions ensuring the robust stability of the gene regulatory networks. Note that the obtained results are formulated in terms of LMIs that can easily be solved using standard software packages. Simulation examples are exploited to illustrate the effectiveness of the proposed design procedures.
Performance of multiple description coders on a real channel

We explore the ability of multiple description (MD) source coders to achieve good performance on channels other than ideal MD channels. We examine both the overall system design and compare the performance of a system with MD source coder to that of a more traditional system using a layered source coder. For the memoryless channels we consider, MD source coding cannot achieve acceptable performance for a memoryless Gaussian source without appropriate channel coding. Also, in memoryless channels, a system with MD source coding outperforms a layered source coding system only in very poor channels. The introduction of memory in the channel degrades the performance of both systems equally. Using interleaving to reduce the impact of memory in the channel has more influence on performance than the choice of source coder.
Dealing with user heterogeneity in P2P multiparty video conferencing: Layered coding versus receiver partitioning

Layered coding elegantly handles user bandwidth heterogeneity in video conferencing, however, it incurs rate and complexity overheads. An alternative is partitioning the receiver sets and using non-layered coding for each group. In this paper, we investigate how to maximize the received video quality for both systems under uplink and downlink capacity constraints, while limiting the number of hops that the videos travel by two. Towards this end, we first show that any multicast tree is equivalent to a collection of depth-1 and depth-2 trees, under outbound and inbound flow constraints. For the layered system, we propose an algorithm that simultaneously solves for the number of video layers, the rate and distribution tree of each layer. For the receiver partitioning system, we develop an algorithm for determining the receiver partitions and tree construction for each group. Through numerical comparison study, we show that the receiver partitioning system achieves significantly higher video quality than the layered system, due to its higher coding efficiency.
Color-Guided Depth Recovery From RGB-D Data Using an Adaptive Autoregressive Model

This paper proposes an adaptive color-guided autoregressive (AR) model for high quality depth recovery from low quality measurements captured by depth cameras. We observe and verify that the AR model tightly fits depth maps of generic scenes. The depth recovery task is formulated into a minimization of AR prediction errors subject to measurement consistency. The AR predictor for each pixel is constructed according to both the local correlation in the initial depth map and the nonlocal similarity in the accompanied high quality color image. We analyze the stability of our method from a linear system point of view, and design a parameter adaptation scheme to achieve stable and accurate depth recovery. Quantitative and qualitative evaluation compared with ten state-of-the-art schemes show the effectiveness and superiority of our method. Being able to handle various types of depth degradations, the proposed method is versatile for mainstream depth sensors, time-of-flight camera, and Kinect, as demonstrated by experiments on real systems.
Design of Power Quality Monitoring System Based on LabVIEW

A multifunctional vitual power quality monitoring system is designed and implemented in LabVIEW environment. S-transform is introduced and applied to perform time-frequency analysis on power quality disturbances. The root mean square(RMS) value, the waveforms of three-phase voltage and current, the harmonic components, the total harmonic distortion(THD) and S-transform analysis waveforms of the three-phase voltage and current signals can be calculated and displayed in the system. Furthermore, the remote transfer of measured results is implemented using the AppletVIEW Toolkit in LabVIEW adopting a B/S framework. Measurement results show the feasibility and validity of the system.
Intrusion detection systems adapted from agent-based artificial immune systems

Agent-based artificial immune system (ABAIS) is applied to intrusion detection systems (IDS). A multiagent-based IDS (ABIDS) inspired by the danger theory of human immune system is proposed. The intelligence behind ABIDS is based on the functionality of dendritic cells in human immune systems and the danger theory, while dentritic cells agents (DC agent) are emulated for innate immune subsystem and artificial T-cell agents (TC agent) are for adaptive immune subsystem. Antigens are profiles of system calls while corresponding behaviors are regarded as signals. This ABIDS is based on the dual detections of DC agent for signals and TC agent for antigen, where each agent coordinates with other to calculate danger value (DV). ABAIS is an intelligent system with learning and memory capabilities. According to DVs, immune response for malicious behaviors is activated by either computer host or Security Operating Center (SOC). Multiple agents are ”embedded” to ABIDS, where agents coordinate one another to calculate mature context antigen value (MCAV) and update activation threshold for security responses. Accordingly, computer hosts met with malicious intrusions can be effectively detected via input signals and temporary output signals such as PAMP, danger and safe signals.