nils-herrmann/clean_scirepeval huggingface dataset:
Computer-Aided Risk Management Research on Construction Techniques

With the rapid development of economic and technology in China, structural forms are becoming more and more complicated, which requires more rigorous construction technology and construction management. However, the risk management in our country is still in its infancy, and managers are short of awareness of risks and lack of ability to manage risks. Study on risk management methods mode of conventional construction process shows that only relying on the qualitative analysis by perfecting manage system and engineering experience cannot satisfy the construction requirement of the complicated structures. Thus, integrating the ideal, characteristics, procedure and goal of risk management meanwhile combining the achievements of computer simulation technology in building structures, this paper presents a new construction technology risk management model, takes overall lifting of steel gallery engineering project of Shaoxing World Financial Center as an example and validates its applicability of the management mode to engineering projects construction.
Data integration and visualization: Dealing with massive and multi-dimensional marine spatial data

Marine observation has entered the era of three-dimensional observation at the present time. More and more spatial data is got form marine observing with no sophisticated visualization and analysis software for marine spatial data (MSD) either. Based on the analysis of data types and the acquisition methods in MSD, the paper proposed a data model for massive and multi-dimensional MSD. Then the procedure and implementation of MSD visualization is designed with the model. In addition, two applications for massive and multi-dimensional data visualization are presented.
A Novel Multitemporal InSAR Model for Joint Estimation of Deformation Rates and Orbital Errors

Orbital errors, characterized typically as longwavelength artifacts, commonly exist in interferometric synthetic aperture radar (InSAR) imagery as a result of inaccurate determination of the sensor state vector. Orbital errors degrade the precision of multitemporal InSAR products (i.e., ground deformation). Although research on orbital error reduction has been ongoing for nearly two decades and several algorithms for reducing the effect of the errors are already in existence, the errors cannot always be corrected efficiently and reliably. We propose a novel model that is able to jointly estimate deformation rates and orbital errors based on the different spatial-temporal characteristics of the two types of signals. The proposed model is able to isolate a long-wavelength ground motion signal from the orbital error even when the two types of signals exhibit similar spatial patterns. The proposed algorithm is efficient and requires no ground control points. In addition, the method is built upon wrapped phases of interferograms, eliminating the need of phase unwrapping. The performance of the proposed model is validated using both simulated and real data sets. The demo codes of the proposed model are also provided for reference.
Complex method of comprehensively evaluation and fault diagnosis in gun control system based on fuzzy reasoning

Aiming at the character and difficulty of comprehensively evaluation and fault diagnosis in gun control system, based on fuzzy analytic hierarchy process(F-AHP), the evaluating indicator architecture is established. Membership functions of voltage signal, current signal, flux signal, and I/O signal are proposed, and the weight of each quality is calculated. Based on the difference weight and fuzzy mathematic theory, the process of fault diagnosis is optimized, at the same time the performance is evaluated. Finally, the system is applied successfully in practice.
A 150GHz injection-locked frequency divider with 19.8% locking range based on adjustable inductor tuning method in 65-nm CMOS

A newly structured 150GHz divider-by-2 injection-locked frequency (ILFD) is designed in a 65-nm CMOS technology. This ILFD uses a new adjustable inductor tuning technique and time-interleaved dual-injection method to improve the frequency division range. A 1-bit binary-weighted switch-capacitor is also used to widen the locking range. From the post-layout simulation result we can see that four self-resonance frequencies are 70.5GHz, 73.5GHz, 76.5GHz, and 79.5GHz, respectively. The locking range is from 135.2GHz to 165GHz with less than 0dBm input power, implying a locking range as wide as 19.8%. The ILFD consumes 4.7mW from a supply of 1.2V excluding output buffers.
An Improved MMAS Algorithm for Path Optimization in Emergency Rescue

Traveling Sales Problem is one of the NP complete problems. The TSP Problem is transformed into a minimized optimal problem without being constrained. The Ant Colony Optimal algorithm has a good effect in solving the TSP problem. This paper discusses the application of the NAX-MIN ant system in the path search of the earthquake emergency rescue. We construct a mathematical model which is based on the earthquake disasters. Then according to the specific characteristics of the model, we improved the max-min ant system that executes the rescue path search, use the mixed-update strategy of global iterative and global iterative and confine the ants to limited entries. So the optimized algorithm can overcome the shortcomings of conventional algorithms, such as slow convergence, easily trapped in local optimum, etc.
A Novel Equivalent Definition of Modified Bessel Functions for Performance Analysis of Multi-Hop Wireless Communication Systems

A statistical model is derived for the equivalent signal-to-noise ratio of the Source-to-Relay-to-Destination (S-R-D) link for Amplify-and-Forward (AF) relaying systems that are subject to block Rayleigh-fading. The probability density function and the cumulated density function of the S-R-D link SNR involve modified Bessel functions of the second kind. Using fractional-calculus mathematics, a novel approach is introduced to rewrite those Bessel functions (and the statistical model of the S-R-D link SNR) in series form using simple elementary functions. Moreover, a statistical characterization of the total receive-SNR at the destination, corresponding to the S-R-D and the S-D link SNR, is provided for a more general relaying scenario in which the destination receives signals from both the relay and the source and processes them using maximum ratio combining (MRC). Using the novel statistical model for the total receive SNR at the destination, accurate and simple analytical expressions for the outage probability, the bit error probability, and the ergodic capacity are obtained. The analytical results presented in this paper provide a theoretical framework to analyze the performance of the AF cooperative systems with an MRC receiver.
A Cloud Manufacturing Service Management Model and Its Implementation

From the actual needs of small and medium-sized enterprises, this paper presents a cloud manufacturing services management model. With the transaction mode for multi-party collaboration, the workflows and core functionalities of this cloud manufacturing model were designed. Some key issues, such as intelligent matching engine for supply and demand, and transaction coordinating logic engine were discussed, which implement management of whole process for cloud manufacturing. As an example, we developed a cloud manufacturing service management platform for the industry of automobile and motorcycle, which effectively integrates manufacturing service resources in this field through online services and offline services, and achieves an effective management of manufacturing services.
A minimum variance beamformer with linear and quadratic constraints based on uniform linear antenna arrays

A novel adaptive beamforming algorithm is proposed based on a uniformly spaced linear antenna array by constraining its weight vector to a specific conjugate symmetric form. Two sets of constraints (linear and quadratic) are imposed on the beamformer while minimizing its output variance. Compared to the traditional linearly constrained minimum variance (LCMV) beamforming algorithm, the proposed one can achieve a faster convergence speed and a higher steady state SINR (signal to interference plus noise ratio) and is less sensitive to the change of its stepsize in terms of the final output SINR. Simulation results verify the effectiveness of the proposed algorithm.
Accelerating mobile web browsing with screen scrolling

During the past decade, we have witnessed the pervasive penetration of mobile smart devices such as smartphones, tablets, and wearable devices, which significantly enrich Internet applications and improve user experience. In the foreseeable future, mobile smart devices are predicted to take up over 50% of global devices/connections and surpass 4/5 of mobile data traffic by 2021 . Such mobile smart devices as smartphones, phablets, and tablets, undoubtedly reshape the way that users access Internet services, e.g., web browsing. Different from traditional desktop applications, in which users interact via interfaces like large displays, keyboards, and mouses, mobile applications require users to enter the inputs through touch screens and allow them to view the outputs on limited size of displays. This distinct feature introduced by mobile hardware interfaces brings both challenges and opportunities to mobile-based Internet applications. On one hand, mobile service providers should prepare multiple copies of media contents with different resolutions and even multiple versions of application UI layouts to fit various sizes of screens on heterogeneous devices. On the other hand, as media contents are usually organized in certain order in mobile-based Internet applications, it is possible to predict the viewing region (referred as viewport hereafter) given the user inputs and the fixed size of display.
A Direct Web Page Templates Detection Method

Currently, a large number of web sites are generated from web templates so as to improve the productivity of web sites construction. However, the prevalence of web templates has a negative impact on the efficiency of search engine in many aspects, including the relevance judgment of web IR and resource usage of analysis tool. In this paper, we present a direct and fast method to detect pages of the same template by DOM tree characteristics. After analyzing and compressing DOM tree nodes of the HTML page, our method generates a hash value digest, also called fingerprint, for each page to identify its DOM structure. In addition, we also introduce some other page features to aid in judging the page template type. Through experimental evaluations over thirty thousand sub-domains, we show that our approach can obtain the analysis results rapidly but with a high accuracy rate above 95 percents.
A lexica family with small semantic gap

Defining a lexicon of high-level concepts is the first step for data collection and model construction in concept-based image retrieval. Differences of semantic gaps among concepts are well worth considering. By measuring consistency in visual space and textual space, concepts with small semantic gap can be obtained. Considering so many diverse concepts in large-scale image dataset, we construct a lexica family of high-level concepts with small semantic gap based on different low-level features and different consistency measurements. In this lexica family, the lexica are independent to each other and mutually complementary. It provides helpful suggestions about data collection, feature selection and search model construction for large-scale image retrieval.
A QoS Pre-Configure Mechanism on DiffServ Mobile IPv6 Networks

IPv6 is the next generation IP protocol to solve the lack of IP address problem and it has been widely used on Internet. The future wireless network would be based on IPv6 to provide services for more users. Mobile IPv6 is proposed to remain a device reachable even when the device roams away from one network to another on single-hop wireless networks. Mobile IPv6 is a best-effort services model and QoS solutions for real-time mobile applications are needed. A QoS pre-configure mechanism (QoSPCM) is contributed to guarantee quality of service (QoS) on DiffServ based mobile IPv6 networks. SIP is extended to perform AAA processes and distribute QoS parameters. QoSPCM uses differentiated service (DiffServ) to guarantee QoS on wired backbone. Roaming users can keep communications with QoS guaranteed right after it performed handover. Voice software and DiffServ mobile IPv6 test-bed are implemented to demonstrate the validity of QoSPCM. Experiment results shown that it is necessary to guarantee QoS for real-time applications on crowded networks, and mobile user could get the same QoS guaranteed after it performed handover on QoSPCM
An efficient memorization scheme for relevance feedback in image retrieval

We propose a novel approach to memorizing content relevance information accumulated in relevance feedback sessions (historical relevance feedback) in image retrieval. It is based on the idea that by storing identification numbers of several representative images for each positive image after a query session, it is possible to provide more precise and diverse retrieval results when this image is used later as a query in a new search session. To do so, a criterion for a "good" buddy image is proposed. Based on such criterion, an algorithm is designed to maximize the space spanned by the selected buddy images. Since the proposed approach requires only a constant storage space for each image, it has good scalability for a large size of image database. Experimental results on a database of 10,000 images show the high efficiency and good scalability of the proposed memorization scheme.
Approximation of canonical sets and their applications to 2D view simplification

Given a set of patterns and a similarity measure between them, we would present an optimization framework to approximate a small subset, known as a canonical set, whose members closely resemble the members of the original set. We would present a combinatorial formulation of the canonical set problem in terms of quadratic optimization integer programming, present a relaxation through semidefinite programming, and propose a bounded performance rounding procedure for its approximation solution in polynomial time. Through a set of experiments we would investigate the application of canonical sets for computing a summary of views from a dense set of 2D views computed for a 3D object.
A practical 4G sites planning scheme based on 3G multi-dimensional data analysis

When making 4G sites planning scheme, telecom operators prefer to reuse the existing 2G/3G site resources to reduce capital and operating expenditure. However, 4G is a typical co-frequency interference network with characteristics of hard handover and mode 3 interference. Thus, it is of great significance to identify the high-risk original 2G/3G sites which may cause interference problem. Based on the purpose, a novel 4G site reusability scheme considering both site attribute and coverage efficiency is proposed to improve 4G network planning accuracy. And we demonstrate the feasibility of the proposed model by quantitative correlation analysis. The prediction results indicate the proposed scheme can achieve great performance and help to improve 4G network quality effectively.
A Sparse Embedding and Least Variance Encoding Approach to Hashing

Hashing is becoming increasingly important in large-scale image retrieval for fast approximate similarity search and efficient data storage. Many popular hashing methods aim to preserve the kNN graph of high dimensional data points in the low dimensional manifold space, which is, however, difficult to achieve when the number of samples is big. In this paper, we propose an effective and efficient hashing approach by sparsely embedding a sample in the training sample space and encoding the sparse embedding vector over a learned dictionary. To this end, we partition the sample space into clusters via a linear spectral clustering method, and then represent each sample as a sparse vector of normalized probabilities that it falls into its several closest clusters. This actually embeds each sample sparsely in the sample space. The sparse embedding vector is employed as the feature of each sample for hashing. We then propose a least variance encoding model, which learns a dictionary to encode the sparse embedding feature, and consequently binarize the coding coefficients as the hash codes. The dictionary and the binarization threshold are jointly optimized in our model. Experimental results on benchmark data sets demonstrated the effectiveness of the proposed approach in comparison with state-of-the-art methods.
A Generic Optical Router Design for Photonic Network-on-Chips

Photonic network-on-chip (NoC) architectures are emerging as a new paradigm to interconnect a large number of processing cores at chip level, meeting the pressing demand for extremely high bandwidth and low power consumption. Optical routers, which are typically composed of silicon waveguides and optical switches, play a key role in an on-chip photonic interconnection network. In this paper, we propose a micro-ring-resonator (MRR)-based, scalable, and non-blocking passive optical router design, namely the generic wavelength-routed optical router (GWOR). We first introduce the four 4 × 4 GWOR router structures and then show how to construct GWORs of larger sizes by using the proposed 4 × 4 GWORs as the primitive building blocks. The number of MRRs used in the proposed GWOR is the least among the existing passive router designs for the same network size. In addition, we show that the power loss experienced on GWORs is lower than other comparative designs. Furthermore, to improve the bandwidth and fault tolerance capability of the GWORs, the redundant GWOR (RGWOR) structure is presented. RGWOR can provide multiple routing paths between each pair of input-output ports by cascading different types of GWORs.
Comparative study on tracking techniques for motion targets

Moving target tracking algorithm is one of the most heated topic in the field of computer vision. The purpose of the target tracking technique is to figure out the displacement, moving speed, and the quantity as well as the moving trail of the moving targets through analyzing the image sequence. Target tracking has potential applications in civilian and military has been widely used in many fields, such as smart monitoring system, human-computer interaction, image compression, automatic navigation. In this article, the usual tracking ways in the moving target tracking are divided into three types: the tracking based on the model matching, the tracking based on the region matching and the one based on the feature matching, which compares the applicable scope, superiorities and inferiorities of different methods. It provides references for how to choose appropriate way in various occasion, and at the same time analyses the future development tendency research of the target tracking techniques.
A Novel $ {\rm x}$-ploiting Strategy for Improving Performance of Test Data Compression

A precomputed core test set contains a large number of don't cares (x's) that can be effectively exploited to improve test data compression (TDC). Extending pattern run-length coding, we present a novel strategy that propagates the x's of a reference pattern to a new reference pattern in such a way that the reference pattern is xor-ed with the pattern to be encoded. The x -propagating strategy can increase the probability of a reference pattern being coding-compatible with the pattern to be encoded, and its validity can be established by filling some x's of the already encoded patterns in backtracing way. How our strategy is used for TDC is demonstrated. Experimental results for large ISCAS89 benchmarks show that, compared to the recently proposed schemes, our technique can effectively improve compression and simplify on-chip decoder, and work better when used for core-unified TDC.
Automatic foreground extraction in video

This paper presents an automatic and efficient system for extracting dynamic objects of interest from videos. We take advantage of a saliency map and an optimization-based segmentation algorithm to extract the foreground objects automatically in some key frames. Then, the segmentation results in those key frames are propagated to other frames via an error map-based propagation scheme. Finally, a Bayesian matting-based refinement approach is employed to to handle the topology changes. Experiments show that our system is able to generate high quality results at a low computation cost.
A Novel Cost-Effective Portable Electronic Nose for Indoor-/In-Car Air Quality Monitoring

With today's competitive and complex environment which results from rapid industrial development, air quality monitoring is becoming a necessity. Devising devices that provide reliable, cost-effective, and fast monitoring of indoor/in-car harmful chemical compounds is of paramount importance for governments as well as individuals. Sensors array systems or commonly called electronic nose (E-nose) systems have been used in various fields of consumer applications. Owing to their versatility and ease of use, these systems can be an adequate alternative for indoor/in-car air quality monitoring. In this study a novel self-made and cost-effective electronic nose aiming at quantifying five indoor/in-car harmful gases (formaldehyde, benzene, CO, NO2, toluene), has been devised and implemented at the college of electronic and communication engineering of Chongqing University, China. A hybrid genetic algorithm support machine vector regression (GA-LSSVMR) model is used for pattern recognition and concentrations estimation. With absolute relative errors of prediction (MAREP) less than 10%, these models outperform those based on hybrid genetic algorithm back-propagation neural network regression (GA-BPNNR). Furthermore, the best regression models were embedded into the system for real-time concentration estimation, our system's predictions mostly agree with those of specific gas detectors. The product will therefore be a good alternative for indoor/in-car air quality monitoring.
A Spatial-Temporal Method to Detect Global Influenza Epidemics Using Heterogeneous Data Collected from the Internet

The 2009 influenza pandemic teaches us how fast the influenza virus could spread globally within a short period of time. To address the challenge of timely global influenza surveillance, this paper presents a spatial-temporal method that incorporates heterogeneous data collected from the Internet to detect influenza epidemics in real time. Specifically, the influenza morbidity data, the influenza-related Google query data and news data, and the international air transportation data are integrated in a multivariate hidden Markov model, which is designed to describe the intrinsic temporal-geographical correlation of influenza transmission for surveillance purpose. Respective models are built for 106 countries and regions in the world. Despite that the WHO morbidity data are not always available for most countries, the proposed method achieves 90.26 to 97.10 percent accuracy on average for real-time detection of global influenza epidemics during the period from January 2005 to December 2015. Moreover, experiment shows that, the proposed method could even predict an influenza epidemic before it occurs with 89.20 percent accuracy on average. Timely international surveillance results may help the authorities to prevent and control the influenza disease at the early stage of a global influenza pandemic.