nils-herrmann/clean_scirepeval huggingface dataset:
A graph based approach to the synthesis of multi-chip module architectures

We present a graph based approach to the time (performance) constrained synthesis of multi-chip module (MCM) architectures. System-level partitioning is performed using the Stochastic Evolution heuristic, which is an effective heuristic for solving several combinatorial optimization problems. The partitioning cost function models the scheduling/allocation constraints (including interchip buses) in the form of incompatible sets. Supernodes are created using the scheduling/allocation constraints which in turn reduces the search space for the partitioner. Scheduling and resource allocation is performed for the case of time (performance) constrained synthesis and includes modeling of inter-chip buses, multi-cycle operations, pipelined functional units and functional pipelining. Efficient synthesis results are obtained for the high-level synthesis benchmarks in far less CPU time compared to the integer linear programming based model.
Low Power Design of Double-Edge Triggered Flip-Flop by Reducing the Number of Clocked Transistors

In this paper, a new technique for implementing low energy double-edge triggered flip-flops is introduced. The new technique employs a clock branch shared (CBS) scheme to reduce the number of clocked transistors in the design. As compared to the other state of the art double-edge triggered flip- flop designs, the newly proposed CBSip design has an improvement of up to 20% and 12.4% in view of power consumption and PDP, respectively.
Data fusion framework for sand detection in pipelines

Reliable sand detection is an important component of oil production system. In practice, produced sand in oil pipelines poses a serious problem in many production situations, since a small amount of sand in the produced fluid can result in significant erosion in a very short time stage. A new data fusion framework for sand detection in pipeline is presented. The framework is collecting data from oil pipeline using acoustic sensors (SENACO AS100) and Flow Analyzer (MC-II) in real time. The framework combines two modules: a wireless receiving and transmission (ReT) module and a data fusion module (DaF). The ReT module implementation is based on TinyOS and Crossbow MICAz motes. In order to optimize between the complexity and accuracy needs, DaF module is implemented using two methods; Fuzzy Art (FA) and Maximum Likelihood Estimator (MLE). The results show the efficient number of sensors needed and compare between FA and MLE redundant.
Dynamic fraction control bus: new SOC on-chip communication architecture design

As technology scales toward deeper submicron, the integration of a large number of IP blocks on the same silicon die is becoming technically feasible. The on-chip communication architecture is becoming the bottleneck for these system-on-a-chips (SOC). The conventional communication architectures all have their limitations. This paper presents new communication architectures, static fraction control bus (SFCB) and dynamic fraction control bus (DFCB), to address the shortcomings of these conventional communication architectures.
An efficient adaptive manipulation architecture for real time video coding in Frequency Domain

Motion estimation (ME) consumes approximately up to 70% of the entire video encoder's computations and is it's main exhaustive time consuming process. Frequency-Domain Motion Estimation (FDME) evolved as a technique that would greatly reduce ME computations and the whole encoding time. In Dynamic Padding FDME (DP-FDME), a dynamic padding threshold adaptively selects the proper search area size according to a pre-estimated set of motion vectors. The main drawback of DP is the mismatched transformed search area formed from different consecutive transformed blocks which would lead to inaccurate ME. In this paper, efficient high speed architecture is proposed to implement an adaptive Manipulation Unit Engine (MUE), a main module of DP-FDME system, to forge a matched transformed search area from successive transformed blocks. Implementation results nominate the proposed MUE architecture to those multimedia applications that favors high speed processing as a trade-off to an acceptable increase in area and power. Simulation results project that MUE, when integrated in a whole FDME system, can perform ME for 60 fps of 4CIF video at 172 MHZ.
Leakage sources and possible solutions in nanometer CMOS technologies

Until recent years, dynamic power dissipation contributed the most to the chip's total power dissipation in CMOS digital circuits thus much attention was given to reduce this dynamic power. But as technology advances into the sub-100 nm regime, leakage power dissipation, which is a static power, increases at a much faster rate than dynamic power and it is expected to dominate the chips' total power dissipation. According to the 2004 update of the International Technology Roadmap for Semiconductors (ITRS), the required reduction of dynamic power beyond the reduction already given by technology scaling for a System-On-Chip (SOC) will grow from 0.1 in 2005 up to 8.1 reduction in 2018; at the same time the required reduction of a SOC standby power will exponentially grow from 2.4 in 2005 up to 232 in 20181.
Challenges and opportunities of silicon technology in communications

As Microelectronic (ME) technology advances in speed of light. Ubiquitous computing (UC) is getting closer to reality. The UC dream with its multilife dimensions will be only there through advanced communication technologies (CT) and devices. The CTs are impacting several application areas and industries such as: wired and wireless communication, mobile computing, wearable computers, network of sensors, etc. These applications have been the driving forces behind the semiconductor industry and its multimillion transistors chips. They represent about 60% of the $200 billion semiconductor industry (2004). As the consumer's demands increase especially in the wireless area and with the pressure of the market on the communication quality and variety, the challenges in the ME as enabling technology grew at several levels; devices, circuits, architectures, and algorithms. The ME has to respond to many expectations and needs. For instance, you can already use your mobile phone to browse the Web, take pictures, send email, and play games. But, you expect to have much better quality in the next generation, in addition, you expect to have enough gigabyte of memory to turn your mobile phone into huge photo albums and MP3 music players. In this talk several of the ME challenges will be discussed. Low power, noise tolerant, reliable, small, fast, and cheap are the main attributes microelectronic systems should have as enabling technology. These attributes requires new design techniques and methods in submicron technologies. At the system levels, systems-on-chip and reconfigurable systems are promising paradigms to meet the complexity challenges. The talk will also address the limitations and expectations of the microelectronic technologies.
Arabic text recognition using neural networks

Recognizing multi-font Arabic texts is a difficult task in the area of optical character recognition (OCR) because Arabic is a cursive type language. This paper proposes a hybrid Arabic character recognition system based on Moment Invariants employing an Artificial Neural Network classifier. The feature extraction stage uses a set of moment invariants descriptors which are invariants under shift, scaling, and rotation. The actual classification is done using a multilayer perceptron network with back-propagation learning. As a preprocessing step, a new approach to segmentation of Arabic words is proposed in this paper. The system has been tested and has shown a very high accuracy.<<ETX>>
Highly Accurate Image Reconstruction for Multimodal Noise Suppression Using Semisupervised Learning on Big Data

Impulse noise corruption in digital images frequently occurs because of errors generated by noisy sensors or communication channels, such as faulty memory locations in devices, malfunctioning pixels within a camera, or bit errors in transmission. Although recently developed big data streaming enhances the viability of video communication, visual distortions in images caused by impulse noise corruption can negatively affect video communication applications. In addition, <inline-formula><tex-math notation="LaTeX">${{sparsity}}$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">${{density}}$</tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">${{multimodality}}$</tex-math></inline-formula> in large volumes of noisy images have often been ignored in recent studies, whereas these issues have become important because of the increasing viability of video communication services. To effectively eliminate the visual effects generated by the impulse noise from the corrupted images, this study proposes a novel model that uses a devised cost function involving semisupervised learning based on a large amount of corrupted image data with a few labeled training samples. The proposed model qualitatively and quantitatively outperforms the existing state-of-the-art image reconstruction models in terms of the denoising effect.
Prediction of Material Mechanical Properties with Support Vector Machine

Predicting model which refers to mechanical properties with material composition and techniques can be founded to reduce test times, increase efficiency and realize the optimization of process. This paper proposes to apply the Support Vector Machine to set up the nonlinear mapping from influence factors of material performances to mechanical properties. Taking the wheat straw-reinforced composite for instance, the prediction model based on support vector machine has been built. Besides, the model is used to optimize process parameters of injection molding and find the range of best parameters. The simulation result shows the founded model has preferable learning and generalization capabilities, which performs effectively in predicting mechanical properties. Therefore it is feasible to optimize process parameters and the technology is worthy to be applied and spread in the research of material performance.
Effects of V/III Ratios on the Properties of AlN Grown on Si (111) Substrate by LP-MOCVD

The AlN thin films were deposited on Si(111) substrates by home-made low pressure metalorganic chemical vapor deposition (LP-MOCVD). At the growth temperature of 1100degC, the effects of the different V/III ratios on the surface morphology and structural characteristics of AlN films were systematically studied. The growth rate of about 150 nm/h was determined by the cross-sectional SEM. By the help of X-ray diffraction (XRD) and atomic force microscopy (AFM) measurements, the obvious effects of the specific growth conditions (different V/III ratios) on the surface morphology and crystallinity of the deposited AlN films were investigated. At the V/III ratio of 15000, the preferred (0002) orientated AlN epitaxial film with the relatively smaller RMS roughness (1.422 nm) was obtained. X-ray photoelectron spectroscopy (XPS) was used to analyze the chemical composition and the chemical bonding structure of the AlN film, indicating some Si atoms outdiffusion from the Si substrate occurred
Influences of Li2O–B2O3–SiO2 Glass Addition on Microstructural and Magnetic Properties of LiZnTi Ferrites

The effects of Li<sub>2</sub>O-B<sub>2</sub>O<sub>3</sub>-SiO<sub>2</sub> (LBS) glass additive on the microstructural development and gyromagnetic properties of low-temperature sintered LiZnTi ferrites were investigated. The aim was to assess the potential applications of LiZnTi ferrites in low-temperature cofired ceramic (LTCC) technology, and to produce LTCC phase shifters. The selected parameters including saturation flux density (B<sub>s</sub>), squareness ratio (B<sub>r</sub>/B<sub>s</sub>), coercivity (H<sub>c</sub>), and ferromagnetic resonance linewidth (ΔH) at 9.3 GHz were measured as a function of doping content, and their relationships with the phase composition and microstructures were discussed. The results show that the LBS glass addition can effectively promote the grain growth and the sintering of LiZnTi ferrites via liquid phase sintering. Meanwhile, the samples with 0.6 wt.% LBS glass addition prepared by a new thermal cycle sintering method, exhibit high B<sub>s</sub> and low ΔH due to improving the microstructures.
Adaptive 3D facial deformation based on personal characteristics

With the vigorous development of 3D graphics and the Internet platform, the research of personal face deformation and face modeling of high quality is more and more important. In this paper, some experiments are made aiming at the process that is to create personalized model from the neutral face model by data matching and automatic deformation. We use Laplacian mesh editing as the mathematical method, and the deformation of facial mesh based on Laplacian differential coordinates is realized based on the personal characteristics obtained manually or from the photo.
Research and application of the management and control platform oriented the cloud manufacturing services

Under the background of manufacturing service, the rapid development of this new technology: cloud computing make the emergence and formation of cloud manufacturing. This paper introduces the current research status of cloud manufacturing at home and abroad, and analyzes the characteristics and design principle of the management and control platform facing the cloud manufacturing services, puts forward several aspects of the principle which from the system cost, the convenience of resources using, system security and service. We put forward the system design functions of management and control platform of cloud manufacturing. Finally, taking the heat treatment furnace cloud monitoring service system for example, we realize the development of the management and control platform for cloud manufacturing services.
Intra-Vehicle UWB Channel Measurements and Statistical Analysis

Ultra-wideband (UWB) technique attracts attention from automotive manufacturers as a potential way to construct intra-vehicle wireless sensor network. This paper reports our preliminary effort in measuring and modeling the UWB propagation in the commercial vehicle environment. Two cases of time domain channel measurement results are reported. In one case, the antennas are inside the engine compartment. In the other case, both antennas are beneath the chassis. It is observed that clustering phenomenon exists in the former case but not in the latter one. Different channel models are used to describe UWB propagation in the two cases and model parameters are found by statistically analyzing the impulse responses.
Product Supervisor for Fuzzy Discrete Event Systems

Fuzzy discrete event systems, as a generalization of crisp discrete event systems have been introduced recently in order to represent possibility arising from the states and dynamics of a system effectively. Supervisory control theory with fuzzy event systems has already established. As a continuation, the supervisory control related to the product structure of fuzzy discrete event systems is investigated. Two cases of the supervisor existence condition are presented in this paper, which illustrates the relationship between the component systems and the overall system.
Camera mathematic model of the molten steel level detection in the strip casting process

A CCD system was designed to detect the molten steel level in the strip casting process. According to the image computing method, camera mathematic model of the molten steel level detection was established. Then an experiment was carried out to calibrate the model parameters and the precision of the mathematic model was tested. The result illustrates that the camera mathematic model and calibrate method of the molten steel level are feasible, which show high levels of precision and can be applied in the industrial line for the strip casting.
Analysis of ultra wideband signal interference to DSSS receiver

The ultra wideband (UWB) interference to direct sequence spread spectrum (DSSS) receiver is analyzed. Two popular UWB modulation schemes, the time hopping pulse position modulation (TH-PPM) and time hopping pulse amplitude modulation (TH-PAM), are considered. The pulse repetition rate (PRR) of UWB signal and the frequency band of the DSSS play the primary roles in the BER performance of the DSSS receiver in the presence of UWB interference. The UWB signal parameters raising the interference to the DSSS receiver are discussed. The characteristics of an aggregation of multiple UWB signals are somehow different from that of a single UWB device, especially for the TH-PPM scheme, where discrete spectral lines maybe exist in the band of the DSSS receiver. The system parameters of TH-PPM such as the modulation index and maximum shift incurred by the time hopping code determine the amplitude of the discrete spectral lines. In the multiuser case of TH-PPM, sometimes one discrete spectral line leads to serious BER performance. It is observed from both theoretical analysis and computer simulations that the interference with the DSSS receiver from the UWB device is very little in common cases.
Hydrothermal synthesis and magnetic properties of Hexagonal Sr3Co2Fe24O41 particles

Hexagonal Z-type Sr3Co2Fe24O41 ferrite particles are prepared in this study by hydrothermal method. The effects of synthesis condition on the phase transformation, microstructure, and magnetic properties of the particle are investigated. SEM, FTIR spectroscopy, and vibrating sample magnetometry are used for characterization. Magnetic measurement results show that the coercive field remains lower than that of bulk specimens which is probably due to the easy reversal of magnetic moments caused by the shape of particles while the remanent specific magnetization and saturation specific magnetization are close to those of a ceramic hexaferrite.
A fast integrity algorithm for the ultra-tight coupled GPS/INS system

This paper discusses current integrity algorithms to deal with ultra-tight coupled GPS/INS system failures. Using the simulated output of the aircraft based INS and GPS receiver, current integrity algorithms are evaluated. A new algorithm based on detection of the growth rate of a typical test statistic is presented. Results show that the new algorithm detects slowly growing ramp-type failures faster than the current methods. This will enable early detection of such errors for enhanced integrity performance.
Circular metasurface based on SSPP and application on beam width enhancement of slot antenna

A circular metasurface that consists of twelve gradually increasing two-sided metallic grooves and an ultra-thin flexible dielectric film is theoretically and experimentally demonstrated based on the s poof surface plasmon polaritons (SSPPs) in the microwave frequency. The dispersion characteristics of the SSPPs structure are analyzed by the length of grooves study. The circular metasurface provides a way to convert spatial propagating waves to the SSPP waves. For application, we design a novel and attractive waveguide slot antenna loaded with the circular metasurface to enhance the beam width. To demonstrate the design, a metasurface waveguide slot antenna device easily implemented using common printed circuit board fabrication method is fabricated and measured, and measurement agrees well with simulation.
Research on the construction of the sustainable development system for tourism in the Daocheng Yading Scenic Spot

Based on the investigation of the sustainable development system and conceptual framework for tourism, this paper presents that the sustainable development of tourism in the Daocheng Yading Scenic Spot is confronted with a great many challenges such as tourist resource security, tourist ecological environment security, tourist human landscape security and tourist management security, and builds up a sustainable tourism development system for the Daocheng Yading Scenic Spot which is comprised of the resource protection system, ecological environment protection system, tourist products planning system, tourism assessment indexes system, tourist sales system, tourist management system and tourist theory system for the sustainable development of tourism in the Daocheng Yading Scenic Spot.
Evaluation strategies for automatic linguistic indexing of pictures

With the rapid technological advances in machine learning and data mining, it is now possible to train computers with hundreds of semantic concepts for the purpose of annotating images automatically using keywords and textual descriptions. We have developed a system, the automatic linguistic indexing of pictures (ALIP) system, using a 2-D multiresolution hidden Markov model. The evaluation of such approaches opens up challenges and interesting research questions. The goals of linguistic indexing are often different from those of other fields including image retrieval, image classification, and computer vision. In many application domains, computer programs that can provide semantically relevant keyword annotations are desired, even if the predicted annotations are different from those of the gold standard. In this paper, we discuss evaluation strategies for automatic linguistic indexing of pictures. We provide both objective and subjective evaluation methods. Finally, we report experimental results using our ALIP system.
Infrequent Item Mining in Multiple Data Streams

The problem of extracting infrequent patterns from streams and building associations between these patterns is becoming increasingly relevant today as many events of interest such as attacks in network data or unusual stories in news data occur rarely. The complexity of the prob- lem is compounded when a system is required to deal with data from multiple streams. To address these problems, we present a framework that combines the time based associa- tion mining with a pyramidal structure that allows a rolling analysis of the stream and maintains a synopsis of the data without requiring increasing memory resources. We apply the algorithms and show the usefulness of the techniques.
Image classification by a two dimensional hidden Markov model

Traditional block-based image classification algorithms, such as CART and VQ based classification, ignore the statistical dependency among image blocks. Consequently, these algorithms often suffer from over-localization. In order to benefit from the inter-block dependency, an image classification algorithm based on a hidden Markov model (HMM) is developed. An HMM for image classification, a two dimensional extension from the one dimensional HMM used for speech recognition, has transition probabilities conditioned on the states of neighboring blocks from both directions. Thus, the dependency in two dimensions can be reflected simultaneously. The HMM parameters are estimated by the EM algorithm. A two dimensional version of the Viterbi algorithm is also developed to classify optimally an image based on the trained HMM. An application of the HMM algorithm to document image and aerial image segmentation shows that the algorithm performs better than CART.
Learning Features and Parts for Fine-Grained Recognition

This paper addresses the problem of fine-grained recognition: recognizing subordinate categories such as bird species, car models, or dog breeds. We focus on two major challenges: learning expressive appearance descriptors and localizing discriminative parts. To this end, we propose an object representation that detects important parts and describes fine grained appearances. The part detectors are learned in a fully unsupervised manner, based on the insight that images with similar poses can be automatically discovered for fine-grained classes in the same domain. The appearance descriptors are learned using a convolutional neural network. Our approach requires only image level class labels, without any use of part annotations or segmentation masks, which may be costly to obtain. We show experimentally that combining these two insights is an effective strategy for fine-grained recognition.