nils-herrmann/clean_scirepeval huggingface dataset:
A unified aging model of NBTI and HCI degradation towards lifetime reliability management for nanoscale MOSFET circuits

As planar MOSFETs is approaching its physical scaling limitation, FinFET becomes one of the most promising alternative structure to keep on the industry scaling-down trend for future technology generations of 22 nm and beyond. In this paper, we propose a unified reliability model of Negative Bias Temperature Instability (NBTI) and Hot Carrier Injection (HCI) for double-gate and triple-gate FinFETs, towards a practical reliability assessment method for future FinFETs based circuits. The model is based on the reaction-diffusion theory and extends it such that it covers the FinFET specific geometrical structures. Apart of introducing the reliability model we also investigate the circuit performance degradation due to NBTI and HCI in order to create the premises for its utilization for assessing and monitoring the Integrated Circuits (ICs) aging process. To validate our model we simulated NBTI and HCI degradation and compared the obtained Vth shift prediction with the one evaluated based on experimental data. The simulations suggest that our model characterize the NBTI and HCI process with accuracy and it is computationally efficient, which makes it suitable for utilization in reliability-aware architectures as reliability prediction/assesment kernel for lifetime reliability management mechanisms.
Error Injection & Correction: An efficient formal logic restructuring algorithm

Redundancy Addition and Removal (RAR) and ATPG/Diagnosis-based Design Rewiring (ADDR) are both logic restructuring techniques used in the synthesis and optimization of logic designs. However, not every irredundant target wire can be successfully removed due to some limitations in these two approaches. Therefore, this paper proposes an efficient restructuring technique, Error Injection & Correction (EIC), which formally constructs a corresponding rectification network at feasible locations without verification efforts for the injected errors of the wire removal, addition, or gate replacement. We use the EIC to serve as a logic perturbation engine and combine other logic optimization engines to optimize the circuit. The experimental results show that the size of highly optimized circuits can be further reduced with this EIC technique as compared with the configuration using only logic optimization engines.
An efficient domain decomposition method for 3-D finite element analysis of nonlinear electric machine problems

The dual-primal finite element tearing and interconnecting (FETI-DP) method is combined with the Newton-Raphson method to expand the capability and improve the efficiency of three-dimensional finite element analysis (FEA) of nonlinear electromechanical and electric machine problems. Despite its modeling capability and high degree of accuracy, FEA has high computational complexity, especially for nonlinear analysis. The FETI-DP method is a robust domain decomposition method, which is a suitable choice for improving the efficiency of large-scale 3-D nonlinear FEA. The FETI-DP method decomposes the original large-scale problem into multiple subdomains, which can then be handled by parallel computing techniques so that the total computation time is reduced significantly. Linear and nonlinear regions are separated using the FETI-DP method. This further improves simulation efficiency and flexibility. Cubic splines and relaxation techniques are adopted to ensure stable and fast convergence of the Newton-Raphson method.
Integration of multimodal features for video scene classification based on HMM

Along with the advances in multimedia and Internet technology, a huge amount of data, including digital video and audio, are generated daily. Tools for the efficient indexing and retrieval of such data are indispensable. With multi-modal information present in the data, effective integration is necessary and is still a challenging problem. In this paper, we present four different methods for integrating audio and visual information for video classification based on a hidden Markov model (HMM): direct concatenation, product HMM, two-stage HMM, and integration by neural network. Our results have shown significant improvements over using a single modality.
MajorSat: A SAT solver to majority logic

A majority function can be represented as sum-of-product (SOP) form or product-of-sum (POS) form. However, a Boolean expression including majority functions could be more compact compared to SOP or POS forms. Hence, majority logic provides a new viewpoint for manipulating the Boolean logic. Recently, majority logic attracts more attentions than before and some synthesis algorithms and axiomatic system for majority logic have been proposed. On the other hand, solvers for satisfiability (SAT) problem have a tremendous progress in the past decades. The format of instances for the SAT solvers is the Conjunctive Normal Form (CNF). For the instances that are not expressed as CNF, we have to transform them into CNF before running the SAT-solving process. However, for the instances including majority functions, this transformation might be not scalable and time-consuming due to the exponential growth in the number of clauses in the resultant CNF. As a result, this paper presents a new SAT solver-MajorSat, which is for solving a SAT instance containing majority functions without any transformation. Some techniques for speeding up the solver are also proposed. Besides, we also propose a transformation method that can generate the characteristic function of a majority logic gate. The experimental results show that the MajorSat solver can efficiently solve random instances containing majority functions that CNF SAT solvers, like MiniSat or Lingeling, cannot.
Study on the use of alternative fuel made from waste vegetable oil in the diesel engine

As a useful alternative fuel, vegetable oil is a kind of continuous renewed energy sources made from photosynthesis. In the paper, a performance comparison experiment of two kinds of fuel, alternative fuel made from waste vegetable oil and No.0 diesel oil, was conducted in the small type of diesel engine. Results showed that the alternative fuel is fit for the diesel engine. Compared with diesel oil, in the export power of the engine, the WVO is much at one (only reduced 2%), and fuel consumption increased 6%∼12%, exhaust gas temperature decreased 20 °C, CO2, CO, HC concentration emission reduced 10%∼15%,10%∼18%,47% respectively. The theory on searching for alternative fuel using in diesel engine was also provided.
Saliency Inspired Full-Reference Quality Metrics for Packet-Loss-Impaired Video

This paper explores the application of saliency information for perceptual quality assessment of packet-loss-impaired videos. We propose and validate two categories of error measures for full-reference saliency based quality metrics. The first category uses a weighted average of pixel errors between original and distorted videos, where the weight at a pixel depends on its visual saliency determined by Itti's saliency detection method after motion information incorporated. Motivated by the observation that packet-loss induced errors often change the spatial-temporal visual attention and correspondingly the saliency map, the second category measures the spatial deviation in saliency values between the original and distorted videos, and the temporal variation of saliency map of the distorted video, and further uses the products of both measures. We combine multiple error measures from the previous two categories using stepwise linear regression analysis. The final combined model includes three factors and provides significant gain over using the best single factor and other non-saliency based measurements.
Dynamic tracking attention model for action recognition

This paper proposes a dynamic tracking attention model (DTAM), which mainly comprises a motion attention mechanism, a convolutional neural network (CNN) and long short-term memory (LSTM), to recognize human action in a video sequence. In the motion attention mechanism, the local dynamic tracking is used to track moving objects in feature domain and global dynamic tracking corrects the motion in the spectral domain. The CNN is utilized to perform feature extraction, while the LSTM is applied to handle sequential information about actions that is extracted from videos. It effectively fetches information between consecutive frames in a video sequence and has an even higher recognition rate than does the CNN-LSTM. Combining the DTAM with the visual attention model, the proposed algorithm has a recognition rate that is 3.6% and 4.5% higher than that of the CNN-LSTMs with and without the visual attention model, respectively.
Novel Probabilistic Combinational Equivalence Checking

Exact approaches to combinational equivalence checking, such as automatic test pattern generation-based, binary decision diagrams (BDD)-based, satisfiability-based, and hybrid approaches, have been proposed over the last two decades. Recently, we proposed another exact approach using signal probability. This probability-based approach assigns probability values to the primary inputs and compares the corresponding output probability of two networks via a probability calculation process to assert if they are equivalent. The shortcoming of all these exact approaches is that if two networks are too complex to be handled, their equivalence cannot be determined, even with tolerance. An approximate approach, named the probabilistic approach, is a suitable way to give such an answer for those large circuits. However, despite generally being more efficient than exact approaches, the probabilistic approach faces a major concern of a non zero aliasing rate, which is the possibility that two different networks have the same output probability/signatures. Thus, minimizing aliasing rate is substantial in this area. In this paper, we propose a novel probabilistic approach based on the exact probability-based approach. Our approach exploits proposed probabilistic equivalence checking architecture to efficiently calculate the signature of network with virtually zero aliasing rate. We conduct experiments on a set of benchmark circuits, including large and complex circuits, with our probabilistic approach. Experimental results show that the aliasing rate is virtually-zero, e.g., 10-6013. Also, to demonstrate the effectiveness of our approach on error detection, we randomly inject errors into networks for comparison. As a result, our approach more efficiently detects the error than a commercial tool, Cadence LEC, does. Although our approach is not exact, it is practically useful. Thus, it can effectively complement exact methods to improve the efficiency and effectiveness of combination equivalence checking algorithms.
Foreign Particle Inspection for Infusion Fluids via Robust Dictionary Learning

Complicated sequential images acquired from the automatic particle inspection machine are used to extract tiny objects within bottled medical liquid on pharmaceutical production line. We propose a learning-based inspection method based on the theory of sparse representation and dictionary learning, which converts the inspection problem into background modeling. As discussed in the paper, the way of learning the dictionary is critical to the success of background modeling in our method. To build a correct background model when training samples contain foreign particles, illumination variation and outliers, we propose a robust dictionary learning algorithm and use online dictionary update method. It automatically prunes foreign particle pixels out at the learning stage. Experiments in both qualitative and quantitative comparisons with competing methods demonstrate the obtained robustness against background changes and better performance in foreign particle inspection.
Electromagnetic Characteristics of Multiport TSVs Using L-2L De-Embedding Method and Shielding TSVs

This paper presents an L-2L de-embedding method for characterizing the electromagnetic properties of through-silicon-vias (TSVs) in 3-D ICs. To the best of our knowledge, this is the first paper that discusses the use of de-embedding method for multiport TSVs. The L-2L de-embedding structure and the analysis algorithm are first introduced. Then, the techniques for meeting two crucial requirements in accurately applying the method on multiport TSVs are proposed. To meet these two requirements, the de-embedding structure is designed to enhance the symmetry and the shielding TSVs are used to decrease the mutual admittance. The simulation results show that with the appropriate design, the shielding TSVs are able to greatly reduce the mutual admittance with little impact on TSVs and RDLs. Finally, the performance of the designed structures with and without shielding TSVs is examined via both full-wave simulation and the measurements. With the full-wave simulation results of TSVs as reference, it turns out that the de-embedding accuracy is significantly improved with the shielding TSVs. Moreover, the de-embedding results based on the measurements show good agreements with those of the simulation ones.
Media Transmission by Cooperation of Cellular Network and Broadcasting Network

Future media transmission as a consistent target is pursued by both next mobile communication system (5G) and advanced digital terrestrial television system. High data rate and flexibility are major considerations for future media transmission. Broadcasting network facilitates high-efficiency transmission of popular or live video in large area, and while, cellular network tends to provide personalized and localized services with a unicast/multicast model. The broadcast-like scheme emerges in 5G to resolve the high demand for bandwidth. However, it requires high deployment cost and imposes much interference on unicast/multicast services. In this paper, a cooperative structure of cellular network and broadcasting network using cloud radio access network (C-RAN) is proposed. The expenses of constructing hybrid network can be significantly cut down by applying the centralization and virtualization of C-RAN. Besides, technical approaches for 3GPP and ATSC cooperation in physical layer is detailed. Dedicated return channel (DRC) of broadcasting network is proposed to enable seamless interaction between broadcasters and few users in a remote area with high expense of cellular tower deployment. To loosen the real-time physical layer pipes period restriction of DRC system, three alternative periods are investigated to provide more flexibility to broadcasters.
Substream Trading: Towards an open P2P live streaming system

We consider the design of an open P2P live-video streaming system. When designing a live video system that is both open and P2P, the system must include mechanisms that incentivize peers to contribute upload capacity. We advocate an incentive principle for live P2P streaming: a peerpsilas video quality is commensurate with its upload rate. We propose substream trading, a new P2P streaming design which not only enables differentiated video quality commensurate with a peerpsilas upload contribution but can also accommodate different video coding schemes, including single-layer coding, layered coding, and multiple description coding. Extensive trace-driven simulations show that substream trading has high efficiency, provides differentiated service, low start-up latency, synergies among peers with different Internet access rates, and protection against free-riders.
Non-invasive optoelectronic transforming inspection technique on medical device applications

This article reported on the pixel flaw detection properties of amorphous In-Ga-Zn-O-based active thin film transistors on flexible medical panel substrate application, which is using the non-invasive optoelectronic transforming inspection technique. The experimental data exactly showed good flaw detection rate > 90% and stable uniformity < 5%. Currently, it is a popular method with electrical testing and detection with advantages of ultrahigh resolution and small-pixel-sized medical panel, and no contact damaged to the application of flexible medical panel substrates.
A spontaneous preference aware service composition framework for Message-Oriented Pervasive systems

Current trends suggest that the Pervasive systems should be adaptive and flexible. Many Message-Oriented Pervasive systems have been proposed to support on-line self-composition of services in reaction to changing contexts. However, most existing service composition mechanisms either do not consider user preferences or use proprietary typing systems. In this paper, we propose an extensible ontology-based autonomous service composition framework for Message-Oriented Pervasive systems. System developers can reconfigure this framework according to their application domains by overriding default hook functions. Experimental results show that the superiority1 of the proposed approach become obvious along with increasing number of nodes.
Improved parabolic prediction-based fractional search for H.264/AVC video coding

In this study, the authors propose an efficient fractional pixel search algorithm for H.264/AVC video coding to reduce the computational complexity in half/quarter-pixel motion estimation. A prediction for the optimal motion vector is derived under the assumption that the sum of absolute transform differences error surface is a symmetric parabolic function. With the optimal region, a decision rule for half-pixel search is proposed. The experimental result shows that approximately two search points are required. Based on the half-pixel search, a hierarchical quarter-pixel search is described and an extra three search points, on average, are consumed for each quarter-pixel search. Experimental results show that significant reduction in computation can be achieved, while maintaining high coding efficiency.
Degrees of freedom region of the MIMO two-transmit, two-receive network with General message sets

We establish the degrees of freedom (DoF) region for the multiple-input multiple-output (MIMO) two-transmit, two-receive network which has an arbitrary number of antennas at each of its four terminals. General message sets are considered, from which all possible communication scenarios based on two-transmit, two-receive network can be regarded as special cases. An outer bound is given first and then it is shown to be tight. In particular, we propose a linear precoding scheme that can achieve all the DoF tuples in the region. Time extension and asymmetric complex signaling are utilized when necessary. The scheme works for both constant channel as well as time/frequency varying channel scenarios. From our general result, one can obtain the degrees of freedom region and the corresponding DoF-optimal precoding scheme for the two-transmit, two-receive network with any subset of all possible messages. Some of these DoF regions have been found before, but many are new. Our work sheds light on the optimal message sets design that could take the most advantage of channel resources in a flexible and efficient manner.
T - Vmin addressing mode and an improved equivalent circuit model for ferroelectric liquid crystal displays

The authors describe an improved model for modelling the electro-optical response of a ferroelectric liquid crystal display and discuss its applicability. The model includes the direct coupling of applied electric fields to dielectric permittivity, an effect not accounted for in previous equivalent circuits. Compared with previous models, the new model has more capability in optical response prediction and device setup optimisation when the dielectric biaxiality of ferroelectric liquid crystals is of a relatively high value. In the improved model, different trends of switching time are observed as drive voltage rises in cases of positive anisotropy and negative anisotropy. The bend in tau-V min mode, that is, the minimum pulse area for switching directors, is measured and the mechanism of optical contrast enhancement and switching process complemented by high-frequency ac pulses is clearly explained. Results obtained from the improved model compare favourably with that obtained from numerical models and from testing of a real cell
Methods for extraction of contaminated area using multispectral remote sensing data in Baiyin city, northwestern China

Effective monitoring of the current situation and change of vegetation contamination has become an application of the space remote sensing technology. The long-term exploitation of mines at Baiyin city, which is located in the typical vegetation-cover area, has led to the natural ecological environment of Baiyin very fragile. The object of present study is to investigate the vegetation contamination caused by exploit mineral resources using remote sensing technique, and confirmed that the feasibility of using remote sensing technology to monitor the vegetation contamination surrounding the mineral resources. The extraction of vegetation growth status in minerals areas is carried out by using multispectral remote sensing data (or images), we use the methods of density slice based on vegetation-greenness of rotating planar scanner plots in this study. In the end of the study, we provides some countermeasures and advises in the face of existing environment problems, in the hope of offer the available technology procedure and work ideas to other areas which are fit for remote sensing.
Shingled Magnetic Recording on Bit Patterned Media at 10 ${\rm Tb/in}^{2}$

In this work, we have combined shingled magnetic recording and bit patterned media (BPM) to achieve an areal density of 10 Tb/in<sup>2</sup>. In our design, the gradient of the write field along the cross track direction is as high as 700 Oe/nm. Composite BPM are utilized and the ratio of thermal stability to switching field is optimized accordingly. Assuming 5% switching field distribution, 5% timing error, 5% jitter error and 5% track misregistration, the write field is 7.8 kOe and the BER is 8.0×10<sup>-4</sup> for 10 Tb/in<sup>2</sup> with 5.4 × nm 5.4 nm dots; the write field is 7.9 kOe and the BER is 1.0×10<sup>-3</sup> for 9.6 Tb/in<sup>2</sup> with 4.4 nm 4.4 nm dots.
The design and development of active stereovision system for mobile robot navigation

Sharing mechanisms with biological vision systems, real-time active stereovision system built from component parts was developed for mobile robot autonomous navigation. Firstly, four degrees of freedom of stereo platform with optimal baseline 34 cm, was designed for accomplishing visual tasks independently like pan, tilt and vergence of stereo camera. Secondly, step-motor drive scheme combined with closed loop servo controller was selected for multi-freedom controller in view of motor resolution requirement and system cost. Then, camera parameters controller was highlighted to enhance system adaptability by adjusting aperture, focus and zoom. Finally, stereo camera synchronization was guaranteed with the adoption two independent image-grabbers combined external synchronous signal. The strategies adopted for the design of the system has been proven to be very effective with applications on the pioneer 2-DXE mobile robot.