nils-herrmann/clean_scirepeval huggingface dataset:
Electro-thermal-stress interaction of GaN HEMT breakdown induced by high power microwave pulses

This paper demonstrated electro-thermal- stress interaction of Gallium Nitride (GaN) high electron mobility transistors (HEMTs) breakdown with a high-power microwave (HPM) pulse injected. A series of GaN HEMT-based power amplifiers were designed and measured by using a special HPM system for characterizing their power-to-failure values. The crack area in the field plate of GaN HEMT was also characterized experimentally. Electro-thermal-stress simulation was performed for capturing temperature and stress distributions over the structure so as to understand breakdown mechanism of GaN HEMTs.
Experimental Investigation and Analysis of the LDMOS FET Breakdown Under HPM Pulses

In this paper, thermal breakdown effects in a laterally diffused MOS (LDMOS) FET under the impact of high-power microwave (HPM) pulses are investigated by theoretically analyzing, modeling, and measuring. Experimental investigations of the LDMOS FET-based power amplifier (PA) are performed under different pulse durations. The measurement system consists of an adjustable HPM source, one controller, couplers, limiters, attenuators, one four-channel oscilloscope, and a DUT. By increasing the input pulse power level, electrothermal breakdown is observed. The breakdown temperature is calculated by using a 2-D analytic model based on the measured power to failure data. Then, our developed time-domain finite-element numerical algorithm is used to characterize temperature distribution and transient performance of the LDMOS FET. The energy capability, which defines the maximum energy that the device can handle, is 15.5 mJ under the pulse duration of 1 ms with a breakdown temperature of 605 K.
A Novel Synthesizing Genetic Logic Circuit: Frequency Multiplier

This paper presents a novel synthesizing genetic logic circuit design based on an existing synthetic genetic oscillator, which provides a function of frequency multiplier to synthesize a clock signal whose frequency is a multiple of that of the genetic oscillator. In the renowned literature, the synthetic genetic oscillator, known as a repressilator, has been successfully built in Escherichia coli to generate a periodic oscillating phenomenon through three repressive genes repress each other in a chain. On the basis of this fact, our proposed genetic frequency multiplier circuit utilizes genetic Buffers in series with a waveform-shaping circuit to reshape the genetic oscillation signal into a crisp logic clock signal. By regulating different threshold levels in the Buffer, the time length of logic high/low levels in a fundamental sinusoidal wave can be engineered to pulse-width-modulated (PWM) signals with various duty cycles. Integrating some of genetic logic XOR gates and PWM signals from the output of the Buffers, a genetic frequency multiplier circuit can be created and the clock signal with the integer-fold of frequency of the genetic oscillator is generated. The synthesized signal can be used in triggering the downstream digital genetic logic circuits. Simulation results show the applicability of the proposed idea.
The dynamics of organizational structure, strategy, and innovation — an empirical study of M&As in the Taiwanese electronics industry

An extensive body of research suggests that an organizationpsilas ability to achieve its goal is a function of the congruence between various components. Following the concept ldquostructure follows strategyrdquo, this study suggested that suited strategy-structure fit should enhance pos-acquisition technological performance for the high tech firms. Further, this study also wishes to examine effects of organizational structure and corporate strategy on process, product, and marketing innovation. Results reveal that organizational coordination and differentiation strategy will enhance product innovation; organizational decentralization and cost leadership strategy will enhance process innovation. For the type of M&As, related M&A firms have better innovation performance than firms undertook unrelated diversification.
A flexible tactile sensing array for robot applications

This work presents the development of a reliable capacitive tactile sensing array which will be tailored as the artificial skins for a humanoid robot. The proposed capacitive sensing element include of two sensing electrodes and a common floating electrode. The sensing electrodes as well as the metal interconnect for signal scanning are implemented on the FPCB, while the floating electrode is patterned on one of the PDMS structures. This special design can effectively reduce the complexity of device structure and thus makes the device highly manufacturable. The measured maximum sensitivity is about 14.5%/kPa. Pressure distribution is captured using a scanning circuit. The deployment of the skin on a humanoid robot is also demonstrated.
Channel estimate with PDP assumption and interference RS knowledge in LTE system

In this article, we discuss the LMMSE(linear minimum mean square error) channel estimate methods on OFDM(Orthogonal Frequency Division Multiplexing) in LTE system. To reduce the complexity of LMMSE, a constant assumption PDP(power delay profile) is used with little performance backoff. The influence of different PDP assumption and channel condition is simulated that the proposed algorithm is robust. Then we come to SRS(sounding reference signal) which different users send different sequence in the same time-frequency resources in LTE system. Simulation results show that if user number is not more than 4, the MSE performance nearly equals to single user, that is LMMSE channel estimate can cancel orthogonal RS sequence interference implicitly. DMRS(demodulation RS) estimate in CoMP scenario has also been discussed whose performance can be increased substantially with the knowledge of interference RS sequence.
2-DOF barycenter mechanism for stabilization of fish-robots

Two-DOF barycenter mechanism and its control are proposed. The mechanism by means of the moved balancing masses along two axes changes the center of gravity of fish's body. The projected torques on x and y axes propel pitch and roll angles to the desired values. Merging the pitching and rolling models with fish-tail and rigid-body models, the fish robot motion and maneuverability can be achieved in three dimensions. The 3-D motion has been derived based on three basic behaviors as swimming, orientating, and stabilizing. Lastly, simulation results of the barycenter stabilization system and the robot motion are given and feasibility of the realization is discussed.
Group decision support system: workflow and models in GDSS based on coordination MAS

GDSS is a popular and attractive topic in the decision field. It is reasonable to combine multi-agent technology and GDSS because they are both distributed systems and support interaction in group members. We define the workflow of group-decision as cognitive, group organizing, decision-making by coordination, feedback and adjust decision, conduce consensus decision by negotiation, knowledge management and repository evolution, explain the process of every part, and propose models to describe character of agent and issue in GDSS.
Robust Active Vibration Control for Rail Vehicle Pantograph

This paper deals with vibration control for a light rail vehicle's pantographs. The concepts of force cancellation, skyhook damper, and contact wire-following spring are jointly applied to constitute an effective controller for vibration suppression. Performance of the control system is evaluated on the basis of variations of displacement and acceleration between the pantograph and contact wire. An active control law is developed by means of a linear quadratic regulator design to derive a stabilizing control law for the pantograph system with the time-varying contact force between the pantograph shoe and catenary. A systematic optimization process with Pareto set and variable weights for the design of active suspension parameters of the pantograph using a constrained multiobjective evolutionary algorithm is developed. Extensive simulations are well performed to verify our proposed design.
SiC reversely switched dynistor (RSD) for pulse power application

This paper reports the world's first SiC reversely switched dynistor (RSD) work. The device structure of 1200V SiC RSD is designed. The two-dimensional numerical model of SiC RSD is established with full consideration of the SiC material parameters and the important physical effects in power device. The blocking characteristics and turn-on characteristics are simulated. The operation principle based on the turn-on controlled by the reverse plasma injection is explained. The influence factors on the switching performance, especially on the residual voltage, including the device parameters and the external conditions, are discussed. The experiment reports the high di/dt pulse output acquired recently based on Si RSD integrated module. The di/dt of 8.85kA/μs is acquired at 1500V discharge voltage, with the peak current of
PISA: Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures with Spatial Priors

Driven by recent vision and graphics applications such as image segmentation and object recognition, assigning pixel-accurate saliency values to uniformly highlight foreground objects becomes increasingly critical. More often, such fine-grained saliency detection is also desired to have a fast runtime. Motivated by these, we propose a generic and fast computational framework called PISA - Pixel wise Image Saliency Aggregating complementary saliency cues based on color and structure contrasts with spatial priors holistically. Overcoming the limitations of previous methods often using homogeneous super pixel-based and color contrast-only treatment, our PISA approach directly performs saliency modeling for each individual pixel and makes use of densely overlapping, feature-adaptive observations for saliency measure computation. We further impose a spatial prior term on each of the two contrast measures, which constrains pixels rendered salient to be compact and also centered in image domain. By fusing complementary contrast measures in such a pixel wise adaptive manner, the detection effectiveness is significantly boosted. Without requiring reliable region segmentation or post-relaxation, PISA exploits an efficient edge-aware image representation and filtering technique and produces spatially coherent yet detail-preserving saliency maps. Extensive experiments on three public datasets demonstrate PISA's superior detection accuracy and competitive runtime speed over the state-of-the-arts approaches.
Immune Clonal Selection Optimization Method with Mixed Mutation Strategies

In artificial immune optimization algorithm, the mutation of immune cells has been considered as the key operator that determines the algorithm performance. Traditional immune optimization algorithms have used a single mutation operator, typically a Gaussian. A mixed mutation strategy may be more efficient than a single one. In view of this, a mixed mutation strategy using Gaussian and Cauchy mutations is presented, and a novel clonal selection optimization method based on clonal selection principle is proposed also. The experimental results show the mixed strategy can obtain the same performance as the best of pure strategies or even better in some cases.
A general class of sliding surface for sliding mode control

In the conventional sliding mode control, the relative degree of the chosen sliding surface is usually one. This paper addresses a general class of sliding surface whose relative degree is no longer restricted to one. We show that when the relative degree is more than two, it is inevitable that there will exist a limit cycle for the nonlinear sign function. And for the case of relative degree two the system possesses poor phase margin. However, these disadvantages can be remedied remarkably by smoothing out the control nonlinearity in a suitable boundary layer with a saturation function that ensures asymptotic stability of the overall system.
Angular dependence of AC transport losses in stacks of Bi/sub 2/Sr/sub 2/Ca/sub 2/Cu/sub 3/O/sub 10//Ag tapes

In most power applications, the superconducting tapes carry AC transport currents and are exposed to applied AC or/and DC fields with different orientations. Because of the anisotropy of high temperature superconductors, AC losses depend on both the strength and the orientation of the magnetic field. To achieve high current carrying capacity, several tapes are often stacked. Thus an estimation of AC losses in stacked tapes is necessary for the design of superconducting devices. Here, AC transport losses in single, double- and triple-stacked Bi2223/Ag tapes were measured under different magnetic fields. The measurements were carried out at 77 K with the field angle between the tape surface and the direction of magnetic field varied from 0/spl deg/ to 90/spl deg/. The experimental results on the angular dependence of the AC losses are reported and analyzed.
Learning a lightweight deep convolutional network for joint age and gender recognition

This paper proposes a lightweight deep model to recognize age and gender from a face image. Though simple, our network architecture is able to complete the two tasks effectively and efficiently. Moreover, different from existing methods, we simultaneously perform the age and gender recognition tasks via a joint regression model. Specifically, our model employs a multi-task learning scheme to learn shared features for these two correlated tasks in an end-to-end manner. Extensive experimental results on the recent Adience benchmark demonstrate that our model achieves competitive recognition accuracy with the state-of-the-art methods but with much faster speed, i.e., about 10 times faster in the testing phase. Our model can be easily adopted and extended to other facial applications.
Research on Digital Phase-Locked Loop about K/Ka-Band High Precision Receiver

A dual one-way ranging system (DOWR) can provide very high precision ranging between two carrier phase transceiver-receiver systems. In microwave ranging system, the accuracy of inter-satellite ranging is mainly limited by the stability of the oscillator and the accuracy of phase measurement. In K/Ka band, the Micron level ranging requests that the phase measure achieves 0.0006rad measurement precision. This paper presents a novel design of the carrier tracking loop, and analyses the realizability of Micron level ranging in the atomic clock phase noise and channel noise condition.
Interactive CT image segmentation with online discriminative learning

Although interactive image segmentation has been widely exploited, current approaches present unsatisfactory results in medical image processing. This paper proposes a fast method for interactive CT image segmentation in which the tumor regions should be partitioned as foreground against the healthy tissues. In contrast to natural images, we have the following observation on CT images: (1) CT images often include discontinuous silhouette or cluttered spots caused by input devices or patient corporeity; (2) Disease areas often have varying appearance and shape. We thus train a discriminative foreground/background model based on user-placed scribbles. In our method, we extract positive and negative samples according to the foreground and background scribbles respectively, and use dense SIFT descriptors plus gray-level histogram as candidate features. With online learning, segmentation can be fast solved by the Bregman iteration. We test our method on CT liver images and demonstrate the advantage by comparing to state-of-the-art approaches.
Optimal teeth design of the lost mechanisms demonstrating interior planets in antikythera astronomical device

Antikythera Astronomical Device, the oldest calculator with multiple-functions, is driven by gear trains with five subsystems. The authors synthesized four feasible 1-DOF designs of the lost mechanisms for interior planetary motions by a systematic design procedure. The optimal teeth design corresponding to the simplest structure is presented. To compare the ancient astronomical theory, the peak errors respectively for Mercury and Venus are about 0.227 and 0.365 days. It is proved strongly that the reconstruction designs generated by systematic synthesis procedure are feasible.
Network management platform approach and its application-KView II

The rapid adoption of the SNMP standard is creating complex new competitive challenges for the traditional providers of LAN and internet management. An emerging strategy among some system and network vendors, is the adaptation of a platform approach to develop custom applications. Network management platform provides an environment in which network management software can be written quickly, and integrated with other management software easily. This paper describes the management problems in a multivendor environment, user requirements for management, the facilities of a management platform, and introduces an application of the management platform KView II. KView II consists of two main tools: the panel editor, which is a graphic editor system for creating and editing graphical representations of the LAN interconnection devices; and the device manager, a value-added application that tightly integrated with HP Open View, providing the network administrator monitoring and control facilities.<<ETX>>
Attention-Aware Face Hallucination via Deep Reinforcement Learning

Face hallucination is a domain-specific super-resolution problem with the goal to generate high-resolution (HR) faces from low-resolution (LR) input images. In contrast to existing methods that often learn a single patch-to-patch mapping from LR to HR images and are regardless of the contextual interdependency between patches, we propose a novel Attention-aware Face Hallucination (Attention-FH) framework which resorts to deep reinforcement learning for sequentially discovering attended patches and then performing the facial part enhancement by fully exploiting the global interdependency of the image. Specifically, in each time step, the recurrent policy network is proposed to dynamically specify a new attended region by incorporating what happened in the past. The state (i.e., face hallucination result for the whole image) can thus be exploited and updated by the local enhancement network on the selected region. The Attention-FH approach jointly learns the recurrent policy network and local enhancement network through maximizing the long-term reward that reflects the hallucination performance over the whole image. Therefore, our proposed Attention-FH is capable of adaptively personalizing an optimal searching path for each face image according to its own characteristic. Extensive experiments show our approach significantly surpasses the state-of-the-arts on in-the-wild faces with large pose and illumination variations. The state (i.e., face hallucination result for the whole image) can thus be exploited and updated by the local enhancement network on the selected region. The Attention-FH approach jointly learns the recurrent policy network and local enhancement network through maximizing the long-term reward that reflects the hallucination performance over the whole image. Therefore, our proposed Attention-FH is capable of adaptively personalizing an optimal searching path for each face image according to its own characteristic. Extensive experiments show our approach significantly surpasses the state-of-the-arts on in-the-wild faces with large pose and illumination variations.
Robust wavelet neuro control for linear brushless motors

Design, simulation and experimental implementation of a wavelet basis function network learning controller for linear brushless dc motors (LBDCM) are considered. Stability robustness with position tracking is the primary concern. The proposed controller deals mainly with external disturbances, e.g. nonlinear friction force and payload variation in motion control of linear motors. It consists of two parts, one is a state feedback component, and the other one is a learning feedback component. The state feedback controller is designed on the basis of a simple linear model, and the learning feedback component is a wavelet neural controller. The attenuation effect of wavelet neural networks on friction force is first verified by the numerical method. The learning effect of wavelet neural networks on friction force is also shown in the numerical results. Then, a wavelet neural network is applied on a real LBDCM to on-line suppress the friction force, which may be variable due to the different lubrication. The effectiveness of the proposed control schemes is demonstrated by simulated and experimental results.
An algebraic method for blind FIR channel identification with cumulant matrix decomposition

Blind identification of discrete-time single real FIR channel with nonminimum phase is studied in this paper. A new solution to the single real FIR channel is derived by exploiting four-order cumulant matrix of output signals. It relies only on Cholesky decomposition of the cumulant matrix. This method does not require over parametization which poses consistency difficulties. It can be used either as the final channel estimate or as initial point of other algorithms. We present altogether four hypoalgorithms which can be applied alone or combined together to satisfy different practical conditions. The algorithm is robust to low SNR and short data length circumstance and that it is simple and fast.
Enhanced Light Extraction Using Blue LED Package Consisting of  ${\rm TiO}_{2}$ -Doped Silicone Layer and Silicone Lens

A novel, blue light-emitting diode (LED) packaging structure with improved light and thermal characteristics is presented. The package includes a TiO2-doped silicone layer and silicone lens. This dual-layer graded refractive index structure used for LED encapsulation was fabricated using dispensing technology. In the LEDs doped with TiO2 nanoparticles and a silicone lens, the light scattering capability and average refraction index of silicone were enhanced, thus reducing reflection losses. The LED achieved a light extraction efficiency increase of 24.5% and a junction temperature reduction of 12.1 °C compared with a conventional single-layer encapsulated LED. Consequently, the proposed structure not only improved the LED performance, but also reduced thermal accumulation in the packaging.
A novel algorithm to achieve bandwidth fairness of RED with packet size consideration

Random-early-detection (RED) is widely applied in network nodes for congestion control. It randomly drops packets to prevent congestion from occurring, while keeping high bandwidth utilization at the same time. Unfortunately, RED provides little protection against aggressive flows from consuming most of the bandwidth. BF-RED was introduced in the literature to address the problem, but it calculated packet drop history only in number, ignoring the sizes of the dropped packets. That is, BF-RED still suffers bandwidth unfairness when packet size varies. In this paper, we introduce a new algorithm named bandwidth-fair-considering-packet-size-RED (BF-PS-RED) to further improve bandwidth fairness. Similar to BF-RED, BF-PS-RED raises the dropping probability according to its drop-weight, but it further adjusts dropping probability according to its average packet size. The simulation shows that BF-PS-RED can effectively guarantee fairness not only in packet numbers but also packet sizes.