nils-herrmann/clean_scirepeval huggingface dataset:
Design of simulation system about transfer alignment of SINS for shipborne equipment

A simulation system about transfer alignment of strapdown inertial navigation system (SINS) on moving base is designed, aim at the problems of big cost, high risk and worse repetition about the validate of transfer alignment algorithm and evaluation of the accuracy about SINS of shipborne equipment. The system consists of motion model, where the motion manner is set; the ship motion simulation is used to give the ship's motion under the motion model; then the motion is sensed by master and slave IMU respectively, which contains gyros and accelerometers, here the Flexure of the body and lever arm effect are simulated and sensed by the slave IMU only; then SINS algorithm is utilized to compute the navigation message respectively, such as velocity, attitude and position of the body, then by matching the message from master SINS and slave SINS to obtain the measurement message of transfer alignment. The validate and evaluation of many transfer alignment algorithm and transfer alignment filtering can be done based on this system, obtained the advantage of better expandability and high accuracy. The rapid transfer alignment about “velocity plus attitude” is simulated based on this system; validate the exactness and the availability of the presented method.
The exploration and practice of the project-based learning for analog electronics teaching

The problems are analyzed during the teaching process of analog electronics course. To solve these problems the project-based learning method (PBLM) is used to explore the teaching reform theory and practice. In the light of characteristics and requirement of analog electronics course, the five key steps of PBLM is designed and introduced by a practical example. Practice of teaching students shows that PBLM can stimulate their learning interest, train their innovative ability and increase their comprehensive ability.
High performance wireless LAN in 60 GHz band with MIMO transmission

This paper investigates spatial interference for networks in 60 GHz band and presents a integrated 60GHz transmission module. It consists of a serial bus interface that encodes the channel selection, configures the analog parts and manages the power. Narrow beams are essential for overcoming higher path loss and can be implemented using compact electronically steerable antenna arrays. The proposed package utilizes mainstream manufacturing and automated assembly process, it paves the way for the market success of 60 GHz applications. Because low variation in phase shift across process and temperature implies, each element is set phase-shift without any calibration for variations. The direction spread measure is treated with information of the power distribution of the components.
Blind Proxy Signature Scheme Based on Both ECDLP and IFP

After studying blind proxy signature scheme and a group of digital signature schemes based on two hard mathematical problems, a new blind proxy signature scheme based on both Elliptic Curve Discrete Logarithm Problem and Integer Factoring Problem is proposed and its security is analyzed. The analysis results show that the scheme satisfies all necessary security properties of the proxy signature schemes. Furthermore, the original signer can't confirm the proxy signer's identity from an effective proxy signature. This scheme's capability of anti-attacking is improved evidently comparing with existing blind proxy signature schemes based on one mathematical hard problem.
The protection for private keys in distributed computing system enabled by trusted computing platform

Trusted computing technology, as a quickly developing technology in recent years, is helpful to improve the computer security and build a trusted computing environment for not only PC system but also distributed computing system. The core of trusted computing technology is cryptology. The trusted computing hardware provided a trusted root for upper layer applications and a trusted software interface is used to communicate with the trusted hardware. In this paper we analyze the key and credential mechanism which is two basic aspects in the cryptology application of trusted computing. The protection for private keys is based on the trusted computing platform with the trusted platform module. We give an example application to illustrate that the TPM enabled protection for key and credential can improve the security of distributed computer system.
One fuzzy retrieval algorithm for speech navigation system

In this paper, one fuzzy retrieval algorithm is designed to work with LVCSR in the speech navigation system. Inverted indexing as well as other searching skills are utilized to speed up the searching while keeping the performance. Several cell levels are tried instead of just using word. Easily reaching 90% sentence accuracy within normal database, this framework can also handle very large database, as many as millions, while preserving at least 70% accuracy in both Chinese and English.
Design of a 6.25Gb/s adaptive decision feedback equalizer in 0.18µm CMOS technology

This paper presents a 6.25Gb/s adaptive decision feedback equalizer (DFE) for high speed backplane communication, which consists of a high-speed DFE and an adaptation engine based on Sign-Sign LMS algorithm. Half-rate structure and current mode logic are employed to pursue a high operating speed. The adaptation engine is composed of sense amplifiers (SA), a 5-bit up/down counter and a 5-bit DAC, which are implemented in CMOS logic at 781.25MHz. Designed in 0.18μm CMOS process, the equalizer has an area of 0.6×0.55mm2 including I/O pads, and the static power consumption is 45.9mW under 1.8V power supply. Measurement results show that the proposed equalizer can adapt to signals achieved from PCB channels of different lengths, and the data rate can be up to 6.8Gb/s with horizontal eye opening of outputs larger than 0.8UI.
Sliding mode control for a class of time-delay hybrid linear systems with mismatched Markovian jump parameter

The sliding mode control problem of a class of uncertain time-delay hybrid linear systems with mismatched Markovian jump parameter is considered. Under the assumptions of known upper bounds mismatched system uncertainties, the sufficient conditions is proposed to guarantee the mean exponentially stability of reduced-order sliding mode system. Under the condition of mismatched system uncertainties, robust sliding mode control law is proposed. The control methods guarantees that the trajectory of system arrives at the sliding surface in finite time interval and is kept here thereafter. It has been shown that the sliding mode control problem for the Markovian jump systems is solvable if a set of linear matrix inequalities(LMIs) have solution. Latsly a simulation is given to illustrate the effectiveness of the proposed approach.
Thermal management in high performance computers by use of heat Pipes and vapor chambers, and the challenges of global warming and environment

The trend of the computer processors performance and power consumption has been increased significantly each year. Heat dissipation has been increased but in contrast the size of die on the processor has been reduced or remained the same size due to nano-size circuit technology and thus the heat flux is critically high. The extreme high performance processors heat flux can be over 100 W/cm2, which is likely 10 times higher than the surface of the household standard clothes iron. The intention of this paper is to provide insight into various thermal management solution using heat pipes and vapor chambers as heat transfer devices. This paper includes designs, data, and discussions of various fan sink air cooling designs showing how the design changes to push the limit of the air cooling capability. The utilization of the two-phase fluid phenomena to spread the heat was a key factor to be the leader of extending the air cooling limit capability for high performance computers.
A robust and accurate method for visual hull computation

A novel method for computing visual hull mesh from a sequence of silhouettes is addressed in this paper. Firstly we use genetic algorithm to estimate the bounding box of the scene object from the silhouettes. Secondly, we develop a method for computing the octree of visual hull through a new projection test strategy to determine whether a voxel locating outside, on or inside the visual hull. The projection test depends on a fact that the projection of a voxel in an image is the same as the convex hull of the projections of the cube's 8 vertices. Finally, the visual hull can be extracted from the Octree. In order to get smooth visual hull mesh, we compute the 2D distance to the silhouette, and use it to evaluate the 3D distance to the real visual hull surface. Experiments with several real data sets are presented to validate our algorithm.
Channel Modification Strategy for Capacity of MIMO Channels with Channel Estimation Error

Multiple input multiple output (MIMO) systems provide dramatic capacity gain through an increased spatial dimension. However, the capacity gain is reduced if the channel state information (CSI) is not perfect. The more exact the CSI is, the higher capacity gain we can obtain. In order to obtain higher capacity gain, this paper analyzes the two factors which mainly affect the reliability of CSI: the quality of channel estimation and the feedback delay, and proposes a channel modification strategy, which can optimally reduce the effect of the two factors and obtain more exact CSI. Simulation shows that the channel modification strategy is effective.
Global Dynamic Modular Innovation Networks: A New Industrial Architecture Supporting Global Dispersive Innovation Synergy

In the age of globalization and innovation dispersing, globalization of manufacturing and innovation has changed the global innovation paradigm, industrial structure and enterprise competition roadmap dramatically. The amalgamation trend of global innovation networks is transforming the global and local innovation trajectory from centralized control orientation to orderly dispersive collaboration orientation. So it is vital for nations, local industrial clusters and enterprises to build the core competences for sustainable development through efficiently catching, utilizing and integrating global dispersive innovation resources. Global modular innovation mechanism is a more and more significant pattern for linking global manufacturing networks and dispersive local innovation resources such as creative design, R&D, valuable marketing originality, effective synergic innovation mechanism in local clusters, and so on. This paper develops a conceptual framework that explore the concept, structure, advantages and characters of a new emerged global innovation pattern, namely global dynamic modular innovation network GDMIN, and explain an the mechanism and structure of GDMIN pattern.
Research on optimization of power grid voltage class series based on rapid load growth

This paper investigate the present situation and history of voltage class series of major city power grids at home and abroad. The technical and economic characteristic of 35 kV and 110 kV is analyzed. The advantage of 110 kV is demonstrated. With the increase of load density, the power supply capacity of 500/220/110/10kV is obviously improved, and the advantages of economy are more prominent. For areas with 35kV power supply, the development and transition of 110kV should be considered as the load density increases.
A Planning-Based Method of Risk Process Modeling for Information Security

To evaluate the information security risk, an approach called PISRPMA is proposed to model the risk process of Information Security. PISRPMA describes risk domain and risk problem in PDDL language, reasons all exploitation paths using relative algorithms and builds a Planning Exploitation Graph to model the risk process. The experiment shows that this method has the features of formalization and scalability, and is a good solution for risk process modeling for information security.
Dynamic Attention-Controlled Cascaded Shape Regression Exploiting Training Data Augmentation and Fuzzy-Set Sample Weighting

We present a new Cascaded Shape Regression (CSR) architecture, namely Dynamic Attention-Controlled CSR (DAC-CSR), for robust facial landmark detection on unconstrained faces. Our DAC-CSR divides facial landmark detection into three cascaded sub-tasks: face bounding box refinement, general CSR and attention-controlled CSR. The first two stages refine initial face bounding boxes and output intermediate facial landmarks. Then, an online dynamic model selection method is used to choose appropriate domain-specific CSRs for further landmark refinement. The key innovation of our DAC-CSR is the fault-tolerant mechanism, using fuzzy set sample weighting, for attention-controlled domain-specific model training. Moreover, we advocate data augmentation with a simple but effective 2D profile face generator, and context-aware feature extraction for better facial feature representation. Experimental results obtained on challenging datasets demonstrate the merits of our DAC-CSR over the state-of-the-art methods.
Numerical analysis on the reliability of space tracking, telemetering and command system based on the sparse matrix storage schemes

Space tracking, telemetry and command (TT&C) system is essentially a dynamic structure system with multiple mission phases. When there are a large number of equipments in a system, the transition matrix of the Markov model of the system is a large sparse matrix whose solution is hard to gain directly. This paper suggests a Runge Kutta method based on the sparse matrix storage scheme to numerically solve and analyze the reliability model. Examples with numerical results show the effectiveness of the solution method. The efficiency of the proposed method is also proved through an analysis on its storage space and solving time.
Semantic cooperative editing based on FLoDL

This paper brings forward an ontology description structure called FLoDS (Four-layer ontology Description Structure) which contains object layer, attribute layer, definition layer, and relation layer. Then an ontology description language called FLoDL (Four-layer ontology Description Language) based on FLoDS is also presented. We use knowledge description methods of frame theory in semantic level and XML specifications in grammar level in FLoDL. Based on FLoDS and FLoDL, the architecture of semantic cooperative editing system is proposed. It has the ability of keeping semantic consistency of the shared document. It also can provide the semantic personalized services for different users and maintain the users' semantic intentions. The algorithm of the server side of the architecture is also given.
Low-Power Area-Efficient Decimation Filters in Sigma-Delta ADCs

The performances of different structures for Sine filters were analyzed and compared in this paper. To reduce their power consumption and chip area, a new optimum method was proposed. And it was implemented in poly-phase structure and direct-realization structure respectively for verification. In addition, the low-power area-efficient optimization scheme for decimation filters in Sigma-Delta ADCs was also discussed. All simulation results were obtained under supply voltage of 1.62 V using TSMC 0.18 mum CMOS technology. The results showed that, compared to CIC, 36% area and 50% power were saved for poly-phase structure and 64% power consumption was reduced for direct-realization structure.
Effects of DiLong oblatum on free radical oxidative injury after EMP radiation

The preventive and therapeutic effects of DiLong oblatum are observed on free radical oxidative injury in mouse brain and testis after EMP radiation. Activity of SOD was detected by NBT method and content of MDA was detected by TBA method. Compared with control group, activity of SOD in brain and testis decreased significantly and content of MDA in brain and testis increased significantly after EMP radiation. The activity of SOD in brain and testis increased significantly and content of MDA in brain and testis decreased significantly if DiLong oblatum was administered to mouse before EMP radiation. The activity of SOD in brain increased significantly and content of MDA in brain decreased significantly if DiLong oblatum was administered to mouse after EMP radiation. DiLong oblatum had some preventive and therapeutic effects on free radical oxidative injury in mouse brain after EMP radiation. DiLong oblatum had some preventive effects on free radical oxidative injury in mouse testis after EMP radiation
On-demand broadcast for mobile real-time multi-item requests

On-demand broadcast is an effective data dissemination approach for mobile computing. Currently most of recent studies on on-demand broadcast consider a restrictive case of single-item requests of mobile clients. In this paper, we extend on-demand broadcast to cater for multi-item requests with timing constraints. We argue for the case of aggregation of data requests to minimize the broadcast bandwidth and deadline miss rate. We present several aggregation algorithms and discuss their strengths and weaknesses. Our preliminary simulation results show that the aggregation algorithms perform much better than the algorithms without aggregation.
Hookworm Detection in Wireless Capsule Endoscopy Images With Deep Learning

As one of the most common human helminths, hookworm is a leading cause of maternal and child morbidity, which seriously threatens human health. Recently, wireless capsule endoscopy (WCE) has been applied to automatic hookworm detection. Unfortunately, it remains a challenging task. In recent years, deep convolutional neural network (CNN) has demonstrated impressive performance in various image and video analysis tasks. In this paper, a novel deep hookworm detection framework is proposed for WCE images, which simultaneously models visual appearances and tubular patterns of hookworms. This is the first deep learning framework specifically designed for hookworm detection in WCE images. Two CNN networks, namely edge extraction network and hookworm classification network, are seamlessly integrated in the proposed framework, which avoid the edge feature caching and speed up the classification. Two edge pooling layers are introduced to integrate the tubular regions induced from edge extraction network and the feature maps from hookworm classification network, leading to enhanced feature maps emphasizing the tubular regions. Experiments have been conducted on one of the largest WCE datasets with  $440K$  WCE images, which demonstrate the effectiveness of the proposed hookworm detection framework. It significantly outperforms the state-of-the-art approaches. The high sensitivity and accuracy of the proposed method in detecting hookworms shows its potential for clinical application.
Topology Optimization of the Loader Hood Structure Based on SIMP Theory

The FEA model was built and modal analysis was executed for the loader hood structure. The mathematical model of topology optimization on continuum structures was established based on the solid isotropic material with penalization (SIMP) theory. A new layout of the ribs of loader hood was gotten through topology optimization using OptiStruct software. The results show that the improved design of the hood not only reduces the structural weight but also meets the dynamic characteristics requirements.
Routing algorithm based on social relations in opportunistic networks

In this paper, we design a social-relations-based routing algorithm (SRBRA). Firstly, by analyzing the real-time data from mobile nodes in the network, we summarize and extract factors that affect social relations between these mobile nodes. Then make inference and evaluation for the complexity and dynamic of these factors from multiple angles, calculate the social-relations values between each sensor node from these factors. Finally, based on the values of social relations, we sort out the network topology information of the neighbours, and select the best next hop relay node for information routing. Simulation experiments show that SRBRA is cost effective and has high delivery ratio.
Network security situation awareness model based on heterogeneous multi-sensor data fusion

Network security situation awareness (NSSA) is an emerging technique in the Held of network security and it helps security analysts to be aware of the actual security situation of their networks. In this paper we presented a novel NSSA model based on multi-sensor data fusion and multi-class support vector machines. In our model, we adopted Snort and NetFlow as two sensors to gather data from network traffic. We employed multi-class support vector machines as fusion engine of our model in combination with an efficient feature reduction approach to fuse the gathered data from heterogeneous sensors. Furthermore, we discussed the alert aggregation algorithm and the security situation awareness generation techniques detailedly. Our model is proved to be feasible and effective through a series of experiments.
Novel active FET circular patch antenna arrays for quasi-optical power combining

This paper discusses two-dimensional planar arrays of weakly coupled active circular patch antennas suitable for quasi-optical power combiners. A novel radiating element that has low cross-polarization is described. A two-dimensional array analysis was developed to address radiation pattern and phase problems. Equivalent isotropic radiated power levels of 1.5 W for a two by two FET array and 3.8 W for a two by four FET array have been obtained at X-band.
Adaptive control based dynamic Real-time resource management

In open, largely unpredictable environments, Quality of service (QoS) has recently become an important focus for real-time research. The cost of performing such measurements is a significant hurdle to the wide-spread deployment of open QoS-aware software components. In this paper, we describe the design and implementation of Adaptive Control middleware, a middleware QoS-control architecture based on Adaptive control theory, motivated by the needs of performance-assured distributed application. It uses adaptive behavior to meet timeliness requirements in the face of restrictions in processing power and network bandwidth. This paper gives an overview of our implementation on a Real-time CORBA platform.
An Attribute Reduction Algorithm of the Information System Based on DNA-Sticker Model

Aiming at the attribute reduction problems of the information system, a new algorithm based on DNA-sticker model is proposed in this paper. Firstly, the dependency matrix of the information system is established, which could convert the problem of attribute reduction to set cover problem. Then, the all true solution can be achieved by using DNA-sticker model. Finally, through the example the conclusion is drawn that this method is feasible, simple, and effective.
An Estimation Rotation Factor PTS Scheme with Superimposed Training Sequence for PAPR Reduction in OFDM System

Orthogonal Frequency Division Multiplexing (OFDM) technology is a high-speed information transmission technology with multi-path resistance, one greatest drawback for it is existing high peak power and average power ratio (Peak-to-Average Power Ratio, PAPR). Partial Transmit Sequence (PTS) method is an effective algorithm to reduce PAPR of the OFDM system, and it will not bring about any distortion for the signals. In this paper, we propose a kind of improved PTS scheme which combines superimposed training sequence method on the basis of researching the traditional PTS method of PTS, in which the rotation factor of PTS scheme is using the rotation factor with good performance obtaining from the method of estimating rotation factor. Through simulating the performance of the improved scheme, the results show that: the proposed scheme has good compromise between the PAPR reductions and lowering the computational complexity for the system, at the same time, there is no significant effect on system performance.