nils-herrmann/clean_scirepeval huggingface dataset:
Mobile Supply Chain Management: Theory and Method

This paper tries to give a more specific concept for mobile supply chain management, a detailed analyzes of the mobile supply chain management and the main idea, which uses a developmental perspective to summarize the background of mobile supply chain, describes its operation process, six basic functions and mode of administration. This article discusses the advantages of mobile supply chain management in logistics management, supply and marketing, manufacturing, inventory management and other areas, which also focuses on the analysis of its main features, and then trying to outline the basic framework of the mobile supply chain management.
Synthesis of Carbon Nanotubes on Suspending Microstructures by Rapid Local Laser Heating

A chemical vapor deposition (CVD) method using local infrared laser heating is developed for synthesis of carbon nanotubes (CNTs) on suspending microstructures. Adjusting the laser power and the focused beam spot enables local illumination and heating of suspending microstructures to high temperature for CNT growth. Rapid synthesis of multiwalled CNTs on suspending microstructures is successfully achieved. This method provides uniform temperature distribution for self-confined CNT growth, with structure size adaptability. It avoids the need of global heating in conventional CVD synthesis and protects temperature sensitive devices from being damaged. The CNTs are typical in a porous foam manner with the potential in sensor applications.
FPGA authentication header (AH) implementation for Internet appliances

Data integrity assurance and data origin authentication are essential security services in financial transactions, electronic commerce, electronic mail, software distribution, data storage and so on. Nowadays, consumer electronics has been shifted toward Internet or intelligent appliances (IA) with network capability to exchange information through Internet. Therefore, a hardware based security mechanism is essential to be combined into the IA so that security and performance can be both preserved. In the Internet protocol security (IPSec) mechanism, the authentication header (AH) is an important portion. The two authentication algorithms specified for AH are MD5 and SHA-1 which have been implemented and evaluated in FPGA. With the proposed enhanced (register usage and concurrent statement) operation core design, a 6% improvement for slice utilization plus 24% more throughput for MD5 are obtained comparing to the previous one.
Insulation Characteristics of Polyimide as Insulation Material Used in Pancake Tape Coil Structure for Resistive-Type SFCL

Space utilization is very important for the application of a superconducting fault current limiter (SFCL) in a high-voltage power system. Accordingly, for efficient space utilization, a pancake structure in which superconducting tapes are wound into coils should be adopted. However, because neighboring windings are in direct contact with each other in a pancake structure, special measures must be taken to overcome high-voltage insulation safety problems. This paper proposes two methods: 1) lapping polyimide adhesive tapes on superconducting tapes; and 2) coating a very thin layer of polyimide on the surface of superconducting tapes. A comparison is made between the two methods. A special breakdown strength testing platform is manufactured. Using the platform, the breakdown strength and surface flashover voltage are tested. Considering that the edges of superconducting tapes are very sharp, the influence of pre-breakdown partial discharge on insulation is explored. The results will be used to design and optimize the geometrical structure of the SFCL pancake component.
Neural Network Based Self-Learning Control Strategy for Electronic Throttle Valve

Recently, the application of the electronic throttle has been very popular in the automotive industry. However, difficulties in the control of electronic throttle valves exist due to multiple nonlinearities and plant parameter variations. A neural-network-based self-learning control (SLC) strategy that consists of a fuzzy neural network (FNN) controller and a recurrent neural network (RNN) identifier is proposed for electronic throttle valves in this paper. The FNN controller, which combines the semantic transparency of rule-based fuzzy systems with the learning capability of a neural network, is utilized as an SLC scheme and will be robust to plant parameter variations. An RNN identifier is employed to model the plant and provides plant information for the learning of the FNN controller. Both the structure and the learning algorithm of the control system are presented. The proposed controller is verified by computer simulations and experiments.
Power optimization of source encoding and radio transmission in multiuser CDMA systems

We investigate the power consumed by two mobile terminals transmitting compressed source signals to a base station in a CDMA cellular system. The aim is to minimize total power consumption at the terminals by simultaneously adjusting the complexity of source compression and the transmitter power. We find that in general the complexity of source compression should increase with increasing distance between a terminal and the base station. However, the exact configuration of compression and transmitter power depends on the interaction of the two terminals. The optimum operating points of the two terminals are contained in a pair of nonlinear equations. We use the example of a transform coder processing signals from a Gauss-Markov source to explore the advantages of an adaptive system over a system with fixed compression. The analysis can be applied to a variety of source coders and be extended to a system with more than two users per cell.
Research on the difference of architecture color harmony and color preference between observers with and without professional background

Colors play a significant role in Architectural Design. The quality of architectural environment is determined by color combinations applied, which are mainly subject to architects' individual design ideology. This study investigates color selection preference patterns between observers with and without professional background by using NCS color system and architectural models, and investigate the chosen colors precisely to these models to justify the preferences. Results show that the two groups of observers' preferences differ from each other significantly, specifically, the average values of the color harmony and the color preference are opposite between two groups.
Modelling multi-channel slotted ring networks with tunable transmitters and fixed receivers

This study presents a non-preemptive priority queue model to approximate the cell delay of a multi-channel slotted ring network with tunable transmitters and fixed receivers, and one queue for storing cells for each channel at each node. To analyze network performance, this network is translated to the proposed non-preemptive priority queue model. With this model, the approximated analytical cell delay results can be obtained by close-form formulas. This investigation assumes that the cell arrival rate for every destination at each node can be different and the number of nodes equals the number of channels. The accuracy of the model is assessed using the simulation results, and the two are found to be very close.
2-D anisotropic dual-tree complex wavelet packets and its application to image denoising

In this paper, we extend the 2D dual-tree complex wavelet transform (DTCWT) to an adaptive anisotropic dual- tree complex wavelet packets (ADTCWP). The DTCWT subbands are iteratively decomposed into anisotropic complex wavelet packets, generating anisotropic wavelets and increasing the number of wavelets orientations without introducing extra redundancy. Then a basis selection procedure is applied so that the selected complex wavelet packets are well adapted to image characteristics. The effectiveness of ADTCWP is examined in image denoising with a bivariate statistical model. The ADTCWP-based denoising scheme shows better denoising results than several DTCWT-based methods for image with rich directional features. The de-noised images recovered by the proposed scheme are visually more appealing.
Nitrogen effects on the sensitivity of tantalum nitride (Ta/sub x/N) for ion sensing devices

A novel approach was proposed in this work for hydrogen ion sensing with tantalum nitride (Ta/sub x/N). Ta/sub x/N sensing membrane was sputtered by mixture gas which gas ratio was modified during the sputtering, from 6 to 20 % with Ar and nitrogen mixture gas for tantalum (Ta) target. The optimized condition for Ta/sub x/N-EIS structure improved the sensitivity to 50.47 mV/pH under 16% nitrogen mixture gas ratio. However sensitivity of all nitrogen ratio conditions could be improved for several mV/pH after 8 hours R.O. water immersion. Hysteresis width also changed with different nitrogen ratio and the minimum hysteresis was 5mV/pH at 12% nitrogen ratio. Due to the large variation of sensitivity and high linearity, the nitrogen ratio modification sputtering is suitable for employ TaN to high sensitivity ISFET and low sensitivity REFET application respectively.
Cooperative Transmission of Correlated Gaussian Sources

Cooperation of wireless users is known to provide substantial improvements in channel reliability and in end-to- end distortion when nodes have access to independent sources. In this paper we investigate the effect of cooperation and distributed compression when the sources are correlated. For distributed compression, realizing that each compressed stream may not reach the destination due to fading, we first derive the achievable rate-distortion pairs for Gaussian sources to have robust descriptions. Then we show how user cooperation can be coupled with robust distributed compression to further improve the end-to-end distortion for correlated sources.
Active-learning assisted self-reconfigurable activity recognition in a dynamic environment

It is desirable to know a resident's on-going activities before a robot or a smart system can provide attentive services to meet real human needs. This work addresses the problem of learning and recognizing human daily activities in a dynamic environment. Most currently available approaches learn offline activity models and recognize activities of interest on a real time basis. However, the activity models become outdated when human behaviors or device deployment have changed. It is a tedious and error-prone job to recollect data for retraining the activity models. In such a case, it is important to adapt the learnt activity models to the changes without much human supervision. In this work, we present a self-reconfigurable approach for activity recognition which reconfigures previously learnt activity models and infers multiple activities under a dynamic environment meanwhile pursuing minimal human efforts in relabeling training data by utilizing active-learning assistance.
Negative ion measurements in ECR plasmas

The presence of negative ions can have big effects on the plasma potential, spatial plasma profiles and plasma density. Negative ions also serve as the precursor for particle formation. Significant concentrations of negative ions have already been identified in low power-high pressure capacitively coupled fluorocarbon plasmas. The main goal of this study is to determine what conditions (microwave power, pressure, etc.), if any, give rise to significant negative ion densities in fluorocarbon plasma in an ECR tool. For this purpose, a redesigned omegatron mass spectrometer was employed in an ECR etching plasma, operated at pressures of 0.2-5 mTorr. The modified geometry provides differential pumping with pressures inside the omegatron below the 10/sup -4/ Torr range reducing collisional effects and insulating film deposition, while the neutral pressure in the bulk plasma is in a few mTorr range. The main directions of this experiment are (1) to investigate the geometric effect (collector size, location, etc.) to maximize the resolution of the omegatron and (2) to study the microwave power and neutral pressure dependence for the negative ion species in ECR fluorocarbon etching plasmas. Preliminary results show F/sup -/, F/sub 2//sup -/, CF/sup -/, CF/sub 2//sup -/, CO/sup -/ negative ions in CF/sub 4/, 1000 W ECR plasma. Recent experiments which varied pressure and power are described.
Power efficient multimedia communication over wireless channels

In this work, we introduce an approach for minimizing the total power consumption of a mobile transmitter due to source compression, channel coding and transmission subject to a fixed end-to-end source distortion. We illustrate our approach both on an abstract class of sources and channels and on a realistic H.263 video transmission system through a wireless channel. Performance under different channel environments and implementation schemes are investigated. Our numerical analysis shows that optimized settings can reduce the total power consumption by a significant factor and prolong battery life considerably compared with fixed parameter settings.
Nested Graph Cut for Automatic Segmentation of High-Frequency Ultrasound Images of the Mouse Embryo

We propose a fully automatic segmentation method called nested graph cut to segment images (2D or 3D) that contain multiple objects with a nested structure. Compared to other graph-cut-based methods developed for multiple regions, our method can work well for nested objects without requiring manual selection of initial seeds, even if different objects have similar intensity distributions and some object boundaries are missing. Promising results were obtained for separating the brain ventricles, the head, and the uterus region in the mouse-embryo head images obtained using high-frequency ultrasound imaging. The proposed method achieved mean Dice similarity coefficients of 0.87 ±0.04 and 0.89 ±0.06 for segmenting BVs and the head, respectively, compared to manual segmentation results by experts on 40 3D images over five gestation stages.
Layer bargaining: multicast layered video over wireless networks

Wireless video multicast efficiently streams video to multiple receivers. When designing a wireless video multicast system, the system must be able to handle (i) packet losses induced by the underlying wireless channel and (ii) receiver heterogeneity in channel condition in a multicast group. We propose Layer Bargaining, a wireless video multicast design in infrastructure-based wireless networks that simultaneously addresses both of the above problems. To combat packet losses and improve received video quality, we propose a layered hybrid ARQ scheme that provides unequal protection to layered video by exploring light-weight feedback. To deal with receiver heterogeneity, we propose a framework based on Nash bargaining game for operating point selection in a multicast group. Our simulation results show that the layered hybrid ARQ scheme significantly outperforms the conventional hybrid ARQ scheme with single layer video and the layered FEC scheme. The results also show that the game-based operating point selection provides a high overall system performance while facilitating fairness among receivers. We carefully examine the overhead and the computational complexity of our proposed schemes, through both theoretical analysis and OPNET simulation/experiment, and show that Layer Bargaining is practically feasible under representative settings.
Hierarchical Mumford-Shah model for dynamic microPET image segmentation

We proposed an organ-by-organ segmentation method for whole-body rodent dynamic PET images based on our hierarchical Mumford-Shah model for vector-valued image segmentation (HMSMv). First, we extract the shape parameters of time-activity curves (TAC) of a volume of interest(VOI) in a dynamic PET image via a noise-normalized principal component analysis (PCA). Then we segment one organ at a time in two steps. At the first hierarchy, we segment a rough VOI blurred by partial volume, motion, and spillover effects from the background via a level set method. Then, we select a seed voxel that is farthest from the VOI boundary and is least affected by spillover and motion blur. Finally, we perform the second level set based segmentation inside the initial segmented VOI to refine the segmentation result by evolving a sphere centered at the seed voxel. Once an organ is segmented, it is removed from the PET image by assigning zero value to the voxels inside the VOI and the segmentation algorithm will move on to another organ. The segmentation algorithm has only one regularization parameter, which is easy to choose. Segmentation results of computer simulated data of the MOBY mouse phantom and real mouse dynamic PET images are shown.
Efficient Timing Channel Protection for On-Chip Networks

On-chip network is often dynamically shared among applications that are concurrently running on a chip-multiprocessor (CMP). In general, such shared resources imply that applications can affect each other's timing characteristics through interference in shared resources. For example, in on-chip networks, multiple flows can compete for links and buffers. We show that this interference is an attack vector through which a malicious application may be able to infer data-dependent information about other applications (side channel attacks), or two applications can exchange information covertly when direct communications are prohibited (covert channel attacks). To prevent these timing channel attacks, we propose an efficient scheme which uses priority-based arbitration and a static limit mechanism to provide one-way information-leak protection. The proposed technique requires minimal changes to the router hardware. The simulation results show that the protection scheme effectively eliminates a timing channel from high-security to low-security domains with minimal performance overheads for realistic traffic patterns.
An improved scheduling algorithm for weighted round-robin cell multiplexing in an ATM switch

Priority as well as constant delay are both important performance criteria in an isochronous scheduler design such as the one in ATM switches. Weighted round-robin (WRR) multiplexing has been proven to be an effective and simple method to implement for priority traffic. The authors present an improved scheduling algorithm based on WRR cell multiplexing to ease the delay jitter problems. The impact of smoothness of the proposed scheduler design is thoroughly presented. The mean response time and its standard deviation are analyzed. The solutions show better performance results than previous work, especially when requested bandwidths are uniformly allocated.<<ETX>>
An Approach to the Transformer Faults Diagnosing Based on Rough Set and Artificial Immune System

Aiming at the shortages of the diagnosing efficiency, applicability and knowledge acquisition ability in traditional transformer fault diagnosing methods, an immune model for diagnosing transformer fault is established in this paper by combining the strong ability of recognition and learning in the artificial immune system (AIS) with the attributes' objectively reduction of the rough set theory (RST) together. The optimal coding of the antibodies and the antigents based on RST, the algorithm in the immune model for diagnosing and learning is analyzed in detail. Finally, the experimental results confirmed that this model has high diagnosis accuracy, strong robustness and good learning ability.
Comparative Study on Residual Current Signal Processing Method of AC/DC Sensitive Residual Current Transformer

AC/DC sensitive residual current transformer (AC/DC RCT) is used to detect residual sinusoidal alternating currents, residual pulsating direct currents or residual smooth direct currents and the characteristics of AC/DC RCT is of great significance for residual current protection under complicated waveform conditions. An AC/DC sensitive residual current transformer based on magnetic modulation principle as well as its Mathematical simulation model is proposed. Based on this, different signal processing methods which are about the simulation of residual current waveform signal are studied and compared. Firstly, based on the analysis of operation principle of AC/DC RCT, a computer based simulation model is established. Secondly, based on the Fourier transform, Spectrum analysis about five typical residual current signals, which include full-wave signal, half-wave signal, quarter-wave signal ,135° wave signal and smooth direct currents signal and comparison about the spectrum are obtained. Thirdly, Approaches of signal processing on the complex waveforms, which is represented the actual residual current on the protected circuit, have been studied. And the FIR low-pass digital filter with suitable parameters is concluded to be the most suitable method for the signal processing of AC/DC sensitive residual current transformer. Finally, conclusion that FIR low-pass digital filter is the most suitable device to process the residual current signal of AC/DC sensitive residual current transformer has been reached.
Experimental study on acoustic emission characteristics of the damage process of concrete under uniaxial compression in different ages

A total of 18 specimens damage processes of concretes under uniaxial compression in 1d, 3d, 5d, 7d, 14d and 28d age are monitored by acoustic emission technique, the development of axial compression strength and corresponding typical acoustic emission characteristics are summarized. Acoustic emission characteristic parameters which in higher correlation with the development of mechanical properties for concrete in early age are given.
Semi-Supervised Positioning Algorithm in Indoor WLAN Environment

In Wireless Local Area Network (WLAN) positioning system, the most popular solution for RSS-based positioning is the fingerprinting architecture. In this paper, we present a novel algorithm, known as Semi-supervised Discriminant Embedding (SDE), to reconstruct a radio map by using real-time signalstrength values received at random points. Instead of deploying dense reference points, our approach takes advantage of less labeled data and partial unlabeled data to transform into lowerdimensional feature signals. Through solving the objective functions optimization, with strong discriminative features in Receive Signal Strength (RSS) are retained in the low-dimensional space. We conducted experiments in our office area with a realistic WLAN environment. Compared to the traditional methods, the experimental results show that the proposed algorithm has considerable accuracy improvement in the same positioning environment. Furthermore, the results also show the size of training samples can be greatly reduced in the proposed algorithm in order to achieve the similar accuracy of traditional approaches. That is, the cost of collecting fingerprints in the offline stage and calibrating database in the online stage are thus reduced.
Novel In-Plane Polarized PZT Film Based Ultrasonic Micro-Acoustic Device

This paper presents the design, fabrication and testing results of a novel in-plane polarized PZT film based micro-acoustic device for ultrasonic applications. The proposed micro-acoustic device with Pt/PZT/TiO2/SiO2 structure can be used for both microphone and microspeaker due to the piezoelectric effect and converse piezoelectric effect of PZT film. The PZT film is polarized along in-plane direction by top square ring shaped interdigitated (IDT) electrodes and works in d33 mode. The fabricated d33-mode micro-acoustic devices have good ultrasonic receiving and transmitting performance, and the resonance frequency is around 44 kHz.