nils-herrmann/clean_scirepeval huggingface dataset:
Fully complex deep neural network for phase-incorporating monaural source separation

Deep neural network (DNN) have become a popular means of separating a target source from a mixed signal. Most of DNN-based methods modify only the magnitude spectrum of the mixture. The phase spectrum is left unchanged, which is inherent in the short-time Fourier transform (STFT) coefficients of the input signal. However, recent studies have revealed that incorporating phase information can improve the quality of separated sources. To estimate simultaneously the magnitude and the phase of STFT coefficients, this work paper developed a fully complex-valued deep neural network (FCDNN) that learns the nonlinear mapping from complex-valued STFT coefficients of a mixture to sources. In addition, to reinforce the sparsity of the estimated spectra, a sparse penalty term is incorporated into the objective function of the FCDNN. Finally, the proposed method is applied to singing source separation. Experimental results indicate that the proposed method outperforms the state-of-the-art DNN-based methods.
PEACH: A Novel Architecture for Probabilistic Combinational Equivalence Checking

This paper describes an approximate approach for combinational equivalence checking. We propose an architecture such that a virtually-zero aliasing rate is obtained in a single-pass probability calculation. Furthermore, the aliasing rate can be easily configured in various precision by designers. We conduct experiments on a set of ISCAS'85 benchmarks. Experimental results show that with virtually-zero aliasing rate, for example, 10-74, our approach is more efficient than those exact approaches
Correctness Analysis and Power Optimization for Probabilistic Boolean Circuits

Traditionally, we expect that circuit designs can be executed without errors. However, for error resilient applications such as image processing, 100% correctness is not necessary. By pursuing less than 100% correctness, power consumption can be significantly reduced. Recently, probabilistic CMOS and probabilistic Boolean circuits (PBCs) have been proposed to deal with power consumption issue. However, to the best of our knowledge, no correctness analysis and power optimization algorithms have been proposed for PBCs. Thus, in this paper, we first propose a statistical approach for evaluating the correctness of PBCs. Then, we propose strategies for power optimization of PBCs. Finally, we integrate these strategies with the correctness analysis as a power optimization algorithm for PBCs. The experimental results show that the proposed correctness analysis method is highly efficient and accurate, and that the power optimization algorithm saves 36% of total power-delay-product on average under a correctness constraint of 90% on a set of International Workshop on Logic and Synthesis (IWLS) 2005 benchmarks.
Bayesian network-based trust model

We propose a Bayesian network-based trust model. Since trust is multifaceted, even in the same context, agents still need to develop differentiated trust in different aspects of other agents' behaviors. The agent's needs are different in different situations. Depending on the situation, an agent may need to consider its trust in a specific aspect of another agent's capability or in a combination of multiple aspects. Bayesian networks provide a flexible method to present differentiated trust and combine different aspects of trust. A Bayesian network-based trust model is presented for a file sharing peer-to-peer application.
Consensus algorithms for linear multi-agent systems with switching topologies by internal mode control

In this paper, consensus algorithms are investigated for networks of continuous-time and discrete-time linear multi-agent systems under switching and directed topologies. These algorithms adopt internal model control technology to guarantee that the consensus for all states in each agent is achieved. And the “virtual state” is also employed to solve the consensus problem. Numerical simulation results are provided to demonstrate the effectiveness of the theoretical results for the consensus for multi-agent systems under switching and directed topologies.
Improved MMSE Vector Precoding Based on the MBER Criterion

A novel vector precoding scheme is proposed for the downlink of a multiuser system equipped with multiple antennas transmitting to single-antenna aided mobile receivers. Our transmit preprocessing scheme first invokes a regularized channel inversion and then superimposes a perturbation vector to directly minimize the Bit Error Ratio (BER) of the system as an improvement to the well-known Minimum Mean-Square- Error (MMSE) vector precoding scheme. Our simulation results demonstrate that the proposed vector precoding scheme acheives the same BER performance as the MMSE vector precoding at the same complexity, when only discrete vector perturbations are allowed. However, the performance of the proposed vector precoding scheme can be further improved based on the MBER criterion, when continuous-valued vector perturbations are car- ried out.
Prediction of renal transplant rejection and acute tubular necrosis in renal transplant based on SVM

Prevention and proper treatment of renal transplant rejection and acute tubular necrosis in kidney are the key to improving the long-term kidney transplant survival rate. Hence, it is important to predict the acute renal graft rejection in early stage. In recent years, there emerged some biomarkers measured through non-invasive techniques that may indicate the acute rejection. In this paper, we apply SVM method to analyze biomarkers, medullary R2* (MR2*) and cortical R2* (CR2*) in transplanted kidney, acquired through BOLD MRI for classification of patients with normally functioning kidney transplants and acute rejection in kidney, including acute allograft rejection and acute tubular necrosis. Furthermore, we use the classification model to predict the acute kidney rejection. The results show that the application of SVM in the analysis of CR2* and MR2* has its potential in prediction of acute rejection in kidney.
Dual-Vth based double-edge explicit-pulsed level-converting flip-flops

Clustered voltage scaling (CVS) systems is an efficient power reduction technique. One of the design challenges in CVS is the efficient level-converting flip-flop (LCFF) with less overhead in power and delay. In this paper, a level converting flip-flop based pass-transisor logic (LCFFBPT) and a static level converting flip-flop (SLCFF) are proposed, respectively. In addition, the two level-converting flip-flops can leverage availability of a second Vth to maintain good speed characteristics and less leakage power consumption. In the terms of the power delay product (PDP), based on simulation results using HSPICE in 45nm CMOS technology, the proposed flip-flops exhibit up to 68% reduction compared to existing level-converting flip-flops.
Major cast detection in video using both audio and visual information

Major casts, for example, the anchor persons or reporters in news broadcast programs and principle characters in movies play an important role in video, and their occurrences provide good indices for organizing and presenting video content. This paper describes a new approach for automatically generating the list of major casts in a video sequence based on multiple modalities, specifically, both speaker and face information. A list of major casts is created and ordered by the accumulative temporal and spatial presence of corresponding casts. Preliminary simulation results show that the detected major casts are meaningful and the proposed approach is promising.
Evaluation of the Role of Deep Trap State Using Analytical Model in the Program/Erase Cycling of NAND Flash Memory and Its Process Dependence

A method to analyze the kinetics of the charge accumulation in the tunnel oxide by the nand flash memory program and erase (P/E) cycling is proposed. Both electron trapping and detrapping processes are required to be considered owing to the oxide high electric field during P/E cycles. Consequently, the electron trapping in the deep trap state is concluded, whose trap energy (<inline-formula> <tex-math notation="LaTeX">$\text{E}_{\text {trap}}$ </tex-math></inline-formula>) is more than 3.5 eV. Furthermore, the as-grown trap state density (<inline-formula> <tex-math notation="LaTeX">${\text{N}}_{e}$ </tex-math></inline-formula>), the trapping capture cross section (<inline-formula> <tex-math notation="LaTeX">$\sigma $ </tex-math></inline-formula>), and the number of trapped positive charges can also be extracted to explain the tunneling current modulation and the <inline-formula> <tex-math notation="LaTeX">$\text{V}_{\text {T}}$ </tex-math></inline-formula> shift by oxide-trapped charges under the P/E stress. The trapped electrons are mainly distributed in the center of tunnel oxide, and the distributed area extends as the P/E bias increases. In addition, the dependence of oxidation process is also shown. Both thermal dry and plasma oxidation have almost the same value of <inline-formula> <tex-math notation="LaTeX">$\sigma $ </tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">$\sim {4} \times {10}^{ {-17}}$ </tex-math></inline-formula> cm<sup>2</sup>). However, 30% reduction of <inline-formula> <tex-math notation="LaTeX">${\text{N}}_{e}$ </tex-math></inline-formula> is shown in plasma oxidation (<inline-formula> <tex-math notation="LaTeX">$\sim {1.25} \times {10}^{ {19}}$ </tex-math></inline-formula> cm<sup>−3</sup>) when compared with thermal dry oxidation (<inline-formula> <tex-math notation="LaTeX">$\sim {1.88} \times {10}^{ {19}}$ </tex-math></inline-formula> cm<sup>−3</sup>).
Multiple Description Coding for Video Delivery

Multiple description coding (MDC) is an effective means to combat bursty packet losses in the Internet and wireless networks. MDC is especially promising for video applications where retransmission is unacceptable or infeasible. When combined with multiple path transport (MPT), MDC enables traffic dispersion and hence reduces network congestion. This work describes principles in designing MD video coders employing temporal prediction and presents several predictor structures that differ in their tradeoffs between mismatch-induced distortion and coding efficiency. The paper also discusses example video communication systems integrating MDC and MPT.
One-Dimensional Photonic Crystal-Based Multichannel Filters Using Binary Phase-Only Sampling Approach

For one-dimensional (1-D) photonic crystals, the amplitude reversal in refractive index profile is defined as an equivalent pi phase shift. With these defined pi phase shifts, the binary phase-only sampling approach can be implemented to design 1-D photonic crystal-based multichannel filters. Such filters exhibit high-count channels and excellent channel uniformity, which is identical with the phenomena obtained in sampled fiber Bragg gratings (SFBGs). Simulations of a nine-channel filter are given out and the distribution of reflection peaks is consistent with that of SFBGs. Then, the impact of structural parameters on filtering characteristics (especially the peak-trough contrast ratio) is discussed, such as optical length of unit cell, optical thickness ratio of alternate dielectric layers, and apodization technique.
Cardiac autonomic neuropathy evaluated by time asymmetric analysis for heart rate variability in patients with peritoneal dialysis

In this study we attempt to quantify the correlations between time asymmetric index (TAI) and physiological/ pathological measurements in order to predict the status of cardiac autonomic neuropathy (CAN) in patients with end-stage renal disease. The TAI can explore non-equilibrium dynamics that conventional time and frequency domain indices fail to consider. For comparing the effectiveness and applicability, traditional time-domain and frequency-domain heart rate variability (HRV) indices were also evaluated. To validate the use of TAI, this study investigates 65 DM patients (22 men and 43 women) and divides the data into two subgroups by HbAlc. The HRV indices such as PNN50 and nLF exhibit a positive correlation with CTR in HbAlc+ subgroup, while SDANN and nLHR show a positive correlation between P and Caphos, respectively. In particular, TAI exhibits a significant negative correlation with TNF-alpha, HbAlc, Caphos, and GLUAC in HbAlc+ subgroup, which overcomes the limitation that a single index can be only correlated to one measurement for conventional time-domain and frequency-domain HRV indices. These results manifest that TAI is an integrated HRV index that contains more information than traditional HRV analysis. Moreover, TAI provides a useful and quantified method in evaluation of the cardiac autonomic neuropathy in patients with ESRD. A large cohort study with TAI analysis is in need for potential cardiovascular outcome prediction.
Image Coding using 2-D Anisotropic Dual-Tree Discrete Wavelet Transform

We propose an image coding scheme using 2-D anisotropic dual-tree discrete wavelet transform (DDWT). First, we extend 2-D DDWT to anisotropic decomposition, and obtain more directional subbands. Second, an iterative projection-based noise shaping algorithm is employed to further sparsify anisotropic DDWT coefficients. At last, the resulting coefficients are rearranged to preserve zero-tree relationship so that they can be efficiently coded with SPIHT. Experimental results show that our proposed scheme outperforms JPEG2000 and SPIHT at low bit rates despite the redundancy of DDWT.
Application of the LU Recombination Method to the FETI-DP Method for Solving Low-Frequency Multiscale Electromagnetic Problems

The LU recombination method is applied within a dual-primal finite element tearing and interconnecting (FETI-DP) framework to solve low-frequency multiscale electromagnetic problems. The FETI-DP method, a robust domain decomposition method, is adopted to deal with the large-scale linear system resulting from finite element modeling of multiscale problems. When frequency decreases or a highly nonuniform mesh is used, the FETI-DP method encounters a low-frequency breakdown problem. The LU recombination method is adopted to identify and eliminate dependent degrees of freedom (DOFs), so that nearly singular finite element matrices are regularized. Since it deals with matrices directly, the LU recombination method is easily combined with different types and orders of basis functions. A nested scheme is adopted to apply LU recombination within the FETI-DP framework. The proposed algorithm is applied to large-scale eddy-current, switched reluctance motor, and logging-while-drilling tool problems. With the LU recombination method, the FETI-DP method is extended down to DC, making it possible to deal with a variety of problems of practical interest.
Application of FIB-SEM and Raman spectroscopy for investigating conductive carbon particles in epoxy encapsulation of IC

We report investigation about three types of conductive carbon particles viz. pure carbon particles, SiO2 filler mixed carbon particles, and SiO2@C core-shell particles in epoxy encapsulations of IC. SEM, EDX, FIB voltage contrast imaging, and Raman spectroscopy are used to characterize conductive carbon particles, and to identify their potential origin.
Selection of Materialized View Based on Information Weight and Using Huffman-Tree on Spatial Data Warehouse

We propose the method of selecting materialized views on a spatial data warehouse and focus on selecting spatial tuples. The selecting considerations include query frequency, source data and spatial complexity, so we introduce information content and density-based selective materialization, which is different from object-based selective materialization. We present proofs showing that the algorithms are guaranteed to provide a solution that is fairly close to the optimal solution
Green media: the future of wireless multimedia networks [Guest Editorial]

By 2015, with the proliferation of wireless multimedia applications and services (e.g., mobile TV, video on demand, online video repositories, immersive video interaction, peer to peer video streaming, and interactive video gaming), and anytime anywhere communication, the number of smartphones and tablets will exceed 6.5 billion as the most common web access devices. Data volumes in wireless multimedia data-intensive applications and mobile web services are projected to increase by a factor of 10 every five years, associated with a 20 percent increase in energy consumption, 80 percent of which is multimedia traffic related. In turn, multimedia energy consumption is rising at 16 percent per year, doubling every six years. It is estimated that energy costs alone account for as much as half of the annual operating expenditure. This has prompted concerted efforts by major operators to drastically reduce carbon emissions by up to 50 percent over the next 10 years. Clearly, there is an urgent need for new disruptive paradigms of green media to bridge the gap between wireless technologies and multimedia applications.
A Type-2 Fuzzy Switching Control System for Biped Robots

In this paper, a type-2 fuzzy switching control system is proposed for a biped robot, which includes switched nonlinear system modeling, type-2 fuzzy control system design, and a type-2 fuzzy modeling algorithm. A new switched system model is proposed to represent the continuous-time dynamic and discrete-event dynamic of a walking biped as a whole, which is helpful to analyze the closed-loop stability of the biped locomotion. A type-2 fuzzy switching control system is proposed for the switched system model to guarantee the gait stability and to achieve a robust control performance with a simplified control scheme. Finally, we propose a new fuzzy c-mean variance algorithm for the type-2 fuzzy system modeling to capture the variance of each clustering means, which can translate random uncertainties of original data into rule uncertainties. Simulation results are reported to show the performance of the proposed control system model and algorithms.
Multi-Track Joint Detection for Shingled Magnetic Recording on Bit Patterned Media With 2-D Sectors

Shingled writing on bit patterned media (BPM) is a promising technology to further increase the areal density beyond 1 Tbit/in2 without drastic changes in writer design. In this paper, a shingled writer is modeled for writing a 2-D sector on BPM, and in particular, we investigate the potential benefit of leaving the last track in the 2-D sector untrimmed, making it fatter than the other tracks in that 2-D sector. During detection, the more reliable information from the last untrimmed (i.e., the fat) track is used as a priori information for detecting the data in the other tracks in that 2-D sector. The simulation results indicate that for 2-D sector with ten tracks (at 3.64 Tbits/in2 channel bit density) and 5% media noise and at a target bit error rate of 10-3, using the fat track information, 2-D equalizer + 2-D target + symbol-based pattern-dependent noise-predictive detector detecting a single track can provide about 2.9 dB SNR gain compared with that with the same joint detection method using uniform tracks at the same areal density. However, the latency increases due to the decision feedback detection. We can reduce this latency penalty by detecting three tracks at a time, but the SNR gain then reduces to 0.9 dB.
Development of ultra-low capacitance through-silicon-vias (TSVs) with air-gap liner

This paper presents the development of ultra-low capacitance TSVs using air-gap to replace conventional SiO2 as the insulating liners. Two polymer sacrificial technologies, including Benzocyclobutene (BCB) etching and Propylene Carbonate (PPC) pyrolysis, have been developed to successfully realize the air-gap TSVs. The capacitance-voltage (C-V) characteristics and the leakage current have been measured to evaluate the electrical performances of the air-gap TSVs, and the thermal-mechanical stress has been studies with ANSYS. The measurement results show that the air-gap TSVs have a capacitance density around 0.6 nF/cm2 at the maximum depletion region, and the leakage current is less than 1×10-1 A at 20 V biased voltage, indicating that air-gaps are able to achieve low capacitance and good insulating property. The simulation results show that the air-gap is effective to reduce the thermal stresses in the silicon substrate, which is beneficial for devices performance.
A Simple and Practical Duty Cycle Modulated Direct Torque Control for Permanent Magnet Synchronous Motors

This paper proposes a simple and practical duty cycle modulated direct torque control (DDTC) for permanent magnet synchronous motors. The duty cycle of active vector is obtained using a duty cycle generator according to the torque error and motor speed, which can avoid the complex calculation process associated with conventional DDTC. The design details about the duty cycle generator are illustrated, and the stability of the proposed DDTC is analyzed, which ensures the reliable operation of the motor system. Experimental results are presented to validate the effectiveness of the proposed DDTC. Furthermore, the comparative evaluation of the proposed DDTC and conventional DDTC is conducted to verify the superiority of the proposed DDTC.
Perceptual quality of video with quantization variation: A subjective study and analytical modeling

This work investigates the impact of temporal variation of quantization stepsize (QS) on perceptual video quality. Among many dimensions of QS variation, as a first step we focus on videos in which two QS's, alternate over fixed intervals. We present subjective test results, and analyze the influence of several factors (including the QS difference, QS ratio, changing intervals, and video content). According the observation and data analysis, we propose analytical models that relate the perceived quality with the two QS's. Such quality assessment and modeling are essential in making video adaptation decisions when delivering video over dynamically changing wireless links.