nils-herrmann/clean_scirepeval huggingface dataset:
An information system management of assessment of disassembly and recycle

This paper presents an adaptive information management system for product planning and evaluation during the design phase for disassembly and recycling. As part of the product lifecycle management (PLM), a representation of products and processes for planning disassembly shredding and material sorting based on graphs has been developed. By using a disassembly/recycle oriented product model imported from a CAD system, the system provides an information management module so as to support economic and ecological assessment. The method allows open access to the information from all stages of the product life cycle, in the context of concurrent engineering. The framework of the proposed information management system for modeling and assessment is demonstrated comprehensively in disassembly of air-conditioners.
Optimization on the self-aligned growth of carbon nanotube

The principle of gas-flowing assistant growing of carbon nanotube is described in this paper. The effect of gas-flow was analyzed with numerical simulation, which can give some instruction for the self-aligned growth of carbon nanotube. Scanning electronic microscopy (SEM) images demonstrate that the self-aligned carbon nanotube can be realized by a gas-flowing CVD process and the distribution of carbon nanotube can be controlled by the gas-flowing rates. This research will provide a hopeful approach to the fabrication of CNT-based device.
A Simple Low-Cost Shared-Aperture Dual-Band Dual-Polarized High-Gain Antenna for Synthetic Aperture Radars

This paper presents a novel shared-aperture dual-band dual-polarized (DBDP) high-gain antenna for potential applications in synthetic aperture radars (SARs). To reduce the complexity of SAR antennae, a DBDP high-gain antenna based on the concept of Fabry-Perot resonant cavity is designed. This antenna operates in both Cand X-bands with a frequency ratio of 1:1.8. To form two separate resonant cavities, two frequency selective surface layers are employed, leading to high flexibility in choosing desired frequencies for each band. The beam-scanning capability of this proposed antenna is also investigated, where a beam-scanning angle range of ±15° is achieved in two orthogonal polarizations. To verify this design concept, three passive antenna prototypes were designed, fabricated, and measured. One prototype has broadside radiation patterns, while the other two prototypes have frozen beam scanned to +15°. The measured results agree well with the simulated ones, showing that the high gain, high port isolation, and low cross-polarization levels are obtained in both the bands. Compared with the conventional high-gain DBDP SAR antennae, the proposed antenna has achieved a significant reduction in the complexity, mass, size, loss, and cost of the feed network.
Crystal Structures and Computer Screened Inhibitors of Helicobacter pylori Undecaprenyl Pyrophosphate Synthase

Helicobacter pylori colonizes the human gastric epithelium and causes diseases such as gastritis, peptic ulcers, and stomach cancer. Undecaprenyl pyrophosphate synthase (UPPs), which catalyzes consecutive condensation reactions of farnesyl pyrophosphate with eight isopentenyl pyrophosphate to form lipid carrier for bacterial peptidoglycan biosynthesis, represents a potential target for developing new antibiotics. In the present study, X-ray structural analysis and computer virtual screening of inhibitors were performed for H. pylori UPPs. The 3-D structure of H. pylori UPPs was solved, with subtle variations from that of E. coli UPPs. Using the structures, two hits identified from 58,635 compounds through computer virtual screening displayed differential activities against H. pylori and E. coli UPPs.
A novel model for two-dimensional independent TV-Based Quotient image and its application to face recognition

A novel model for Two-Dimensional Independent TV- Based Quotient Image is proposed in this paper, and the new proposed model is applied to face recognition with only one sample per subject on a large scale face database. In our model, an ETVQI model is firstly proposed to overcome drawbacks of the TVQI model. Then, a two-dimensional independent subspace analysis algorithm is proposed to reduce the dimension of face samples normalized by ETVQI model and to extract high-order statistical features of these samples. According to experiments on the CAS-PEAL face database, our proposed model could outperform ICA with architecture II (ICA2), (2D)2PCA and TVQI. And it also confirms that our model is robust not only to illumination, but to other outliers (expression, masking, occlusion etc.) in face recognition.
Research on the Security Solution of the Industry Oriented E-Exchange

The development of industry informationization and electronic commerce (e-commerce) promote the emergence of electronic market (e-market). One called electronic exchange (e-exchange) is a typical business model. It requires a higher security level for the business operating system. This paper systematically studies the e-exchange security problems from the view of e-commerce security, analyzes the security requirements of e-exchange and discusses the security mechanism and service. Basing on these, the paper proposes a security solution of the e-exchange. Finally the paper elaborates the realization and application of this solution combined with the case of Guangdong Plastics Exchange (GDPE.com).
Reading identification Algorithms of mercury thermometer based on machine vision

Based on machine vision techniques, the reading identification Algorithms of mercury thermometer was presented. According to the Huffman transformation methods, three-time expansion operation combined with three-time erosion operation is used to locate the mercury, mercury pole and the scales. On the basis of performing spatial moment subpixel localization, the temperature value indicated by thermometer is calculated using location information between edge pixels. Experiment results show that these algorithms with accuracy of 0.1°C can meet the practical application.
Direct Localization of Multiple Stationary Narrowband Sources Based on Angle and Doppler

Direct position determination (DPD) is a single-step method that directly localizes transmitters from sensor outputs without estimating intermediate parameters. With a moving array, DPDs are usually performed by implicitly using only angle information. This letter proposes a DPD algorithm for multiple stationary transmitters by exploiting location information embedded in angles and Doppler shifts. We fit all signal subspaces with the space-time steering vectors at all positions of the moving array using the weighted subspace fitting method, and then perform an alternating projection procedure to directly localize transmitters. The simulation results corroborate the good localization performance of the proposed algorithm.
A Hybrid Ant Colony Optimization Algorithm for the Extended Capacitated Arc Routing Problem

The capacitated arc routing problem (CARP) is representative of numerous practical applications, and in order to widen its scope, we consider an extended version of this problem that entails both total service time and fixed investment costs. We subsequently propose a hybrid ant colony optimization (ACO) algorithm (HACOA) to solve instances of the extended CARP. This approach is characterized by the exploitation of heuristic information, adaptive parameters, and local optimization techniques: Two kinds of heuristic information, arc cluster information and arc priority information, are obtained continuously from the solutions sampled to guide the subsequent optimization process. The adaptive parameters ease the burden of choosing initial values and facilitate improved and more robust results. Finally, local optimization, based on the two-opt heuristic, is employed to improve the overall performance of the proposed algorithm. The resulting HACOA is tested on four sets of benchmark problems containing a total of 87 instances with up to 140 nodes and 380 arcs. In order to evaluate the effectiveness of the proposed method, some existing capacitated arc routing heuristics are extended to cope with the extended version of this problem; the experimental results indicate that the proposed ACO method outperforms these heuristics.
Microfabrication of Single-Wall Carbon Nanotube One-Dimensional Unit

A microfabrication method is devised for integration of long single-wall carbon nanotube (SWNT) into one-dimensional unit. This approach involved the synthesis of the aligned SWCNT array and FIB techniques to bridge predefined molybdenum electrodes. As a demonstration, single-wall nanotube device with metallic electrodes was presented. Sample characterization was carried out with SEM pictures and I-V curves, which show that this fabrication strategy finds applications in the development of micro/nano device and system.
An effective way to eliminate the accumulative error of multi-view registration

Error analysis of free-form surfaces is a requirement to assure quality and to reduce manufacturing costs and rework. This paper proposes a new approach and algorithms for eliminate the accumulative error of multi-view registration. The main influence factor of sequential sub-surface registration error is analyzed detailedly. To eliminate accumulated errors of registration, a method based on an overall errors compensation method is proposed, which distributes accumulated errors to each of transformations, depending on a concept that continued registration errors of surfaces in closed form is zero. And, overlapping area can be chose reasonably. Experimental results showed that the proposed method is effective.
Improving the Accuracy of Destructive Earthquake Prediction by Transforming the Small Probability Event to Conditional Probability Event

As we all know, the possibility of heavy earthquake is tiny, however, the destructiveness is serious, so it is important to improving the veracity of predicting destructive earthquake. This paper using the database of the destructive earthquake precursor, by defining the small probability even and estimating the parameter of success rate in small probability event prediction and changing the parameter, to transform the small probability event to conditional probability event. This paper attempts to find a way to improving the possibility of destructive earthquake which belongs to small probability events.
Control system of powered wheelchairs based on tongue motion detection

A new intelligent powered wheelchair is urgently needed for the individuals with tetraplegia and similar impairments who are unable to use the standard joystick. Based on the tongue motion detection, a new control system is introduced in this paper which is helpful for users to operate powered wheelchair efficiently and easily. The tongue motion can be detected with several vibration film sheets that were embedded in the headset and a standard analog signal can be generated with embedded controller to control the wheelchair, which is convenient to be used in almost other wheelchair. The tongue motion drive system integrated into headset was developed and the control of the wheelchair has been tested moving along the designed route. Preliminary results show that the system is simple and convenient to control powered wheelchair with low cost, which has potential application in intelligent control domain.
Indoor location estimation using virtual fingerprint construction and zone-based remedy algorithm

Location based service relies on precise outdoor and indoor positioning technologies. Intuitively, indoor positioning is more difficult than outdoor positioning because of complicated environment. Fingerprint is a technique proposed to sketch the characteristic of every indoor location by adopting time-consuming measurements in offline phase. To minimize overhead, virtual fingerprint construction scheme (VFCS) with smart antenna system (SAS) has been proposed to fast construct the database based on the log-distance path loss model and interpolation scheme. Our experiments reveal that the VFCS may perform worse when the measured received signal strength levels (RSSIs) are unstable. This paper proposes a simple zone-based algorithm for VFCS to first localize potential zone and then estimate the possible location. Experimental results show that the proposed zone-based algorithm for VFCS and SAS indeed promotes the accuracy of indoor location estimation even using extrapolation scheme.
An Improved Approach to Image Segmentation Based on Mumford-Shah Model

In this paper, based on M-S model and level-set method, a new method for initializing level-set function and hierarchical constant segmentation is proposed in order to overcome the shortcomings in the Chan-Vese model. First, by improving the initial level set function, the process of re-initializing level set function in traditional method is eliminated, and the initial conditions are easier to handle. Secondly, this paper presents a hierarchical constant segmentation method for multi-phase segmentations, using estimated energy to determine whether the sub-regions need further segmentations. By evolving only one level set curve at each segmentation stage, our algorithm speeds up the segmentation significantly. Finally, various numerical experiments on both artificial and real images are done to validate the proposed methods
Multi-scale preprocessing model for face recognition

In this paper a novel multi-scale preprocessing model (MSPM) for face recognition is proposed. MSPM removes lighting effects and enhances the image feature in two scales simultaneously. It decomposes the original image using Total Variation model. Then the lighting effects are normalized by self-quotient in the small scale part and equalized in the large scale part. The final fused image is illumination invariant. Using this image could largely improve face recognition performance under low-level lighting conditions. Combined MSPM with high-order Gabor-based methods could further raise face recognition rates under varying imaging conditions. According to the experiments on the large scale CAS-PEAL face database, MSPM outperforms conventional algorithms when they face most artifacts (lighting, expression, masking etc.).
Guest Editors' Introduction to the Special Section on Learning with Shared Information for Computer Vision and Multimedia Analysis

The twelve papers in this special section focus on learning systems with shared information for computer vision and multimedia communication analysis. In the real world, a realistic setting for computer vision or multimedia recognition problems is that we have some classes containing lots of training data and many classes containing a small amount of training data. Therefore, how to use frequent classes to help learning rare classes for which it is harder to collect the training data is an open question. Learning with shared information is an emerging topic in machine learning, computer vision and multimedia analysis. There are different levels of components that can be shared during concept modeling and machine learning stages, such as sharing generic object parts, sharing attributes, sharing transformations, sharing regularization parameters and sharing training examples, etc. Regarding the specific methods, multi-task learning, transfer learning and deep learning can be seen as using different strategies to share information. These learning with shared information methods are very effective in solving real-world large-scale problems.
Study on Knowledge Acquisition of the Telecom Customers' Consuming Behaviour Based on Data Mining

As the reform development of telecom industry and the entrance of WTO, the competition among the telecom enterprises is becoming tougher. Nowadays, "customer-oriented" is the new principle of telecom market competition. As the enterprises in telecom industry have much more customers and customer data than those in other industries, the application of customer relationship management (CRM) in telecom industry becomes one of the hottest topics on enterprise informationlization. The thesis discusses the discovery of telecom customer knowledge based on data-mining. In this paper, a customer analysis model is founded by the method of data mining, including customer segmentation analysis, customer churn analysis, customer owing and fraud analysis. In the end, the thesis introduces a real case of a customer segmentation project in a mobile communication company and illustrates the application detail of customer intelligence in this company. In this case, the author uses SPSS Clementine to conduct data-mining. Meanwhile, diverse marketing strategy is also proposed based on the customer segmentation knowledge.
Game-Theoretic Multiple Target Tracking

Video-based multiple target tracking (MTT) is a challenging task when similar targets are present in close vicinity. Because their visual observations are mixed and difficult to segment, their motions have to be estimated jointly. Most existing approaches perform this joint motion estimation in a centralized fashion and involve searching a rather high dimensional space, and thus leading to quite complicated joint trackers. This paper brings a new view to MTT from a game-theoretic perspective, bridging the joint motion estimation and the Nash equilibrium of a game. Instead of designing a centralized tracker, MTT is decentralized and a set of individual trackers is used, each of which tries to maximize its visual evidence for explaining its motion as well as generates interferences to others. Modelling this competition behavior, a special game is designed so that the difficult joint motion estimation is achieved at the Nash Equilibrium of this game where no individual tracker has incentives to change its motion estimate. This paper substantializes this novel idea in a solid case study where individual trackers are kernel-based trackers. An efficient best response updating procedure is designed to find the Nash equilibrium. The powerfulness of this game-theoretic MTT is shown by promising results on difficult real videos.
Methodology to Reduce the Number of Switches in Frequency Reconfigurable Antennas With Massive Switches

This paper proposes a new method for decreasing the complexity of reconfigurable antennas (RAs) with massive switches while increasing their reconfigurability. The proposed method is performed by removing the less important switches of an RA. Therefore, the RA only has a few important switches that have strong influences on the reconfigurability. The importance of a switch is evaluated by the minimum percentage of useful configurations (PUC). A monopole-type omni-directional frequency RA with 85 uniformly-distributed switches is optimized in this paper. For this type of antennas, a reflection coefficient less than −20 dB and a gain greater than 0 dBi at the same frequency makes a useful configuration. After reducing the switch number from 85 to 15, the complexity of the RA is greatly decreased while the reconfigurability is increased by more than 100 times within the band of 2 to 7 GHz. With only 15 optimally deployed switches, the PUC is significantly increased. Therefore, it is easy to find out the states of the switches to let the frequency RA work well at different frequencies. The results show that the proposed method is an efficient way to design RAs with switches in an optimal deployment.
Performance characterization of triple-junction GaAs Solar Cell with double layers AR-coating and Sub-Wavelength AR-coating

The reflective spectrum and the incident angle effects of double-layers AR-coating and Sub-Wavelength AR-coating on the triple-junction GaAs Solar Cell are characterized by short-circuit current (I<sub>sc</sub>), open-circuit voltage (V<sub>oc</sub>), and conversion efficiency (η).
InGaAs/InP DHBTs in a Dry-Etched Refractory Metal Emitter Process Demonstrating Simultaneous $f_{\tau}/f_{\max} \sim \hbox{430/800}\ \hbox{GHz}$

We report an InPZIn<sub>0.53</sub>Ga<sub>0.47</sub>As/InP double heterojunction bipolar transistor (DHBT) demonstrating simultaneous 430-GHz f<sub>τ</sub> and 800-GHz f<sub>max</sub>. The devices were fabricated using a triple mesa process with dry-etched refractory metals for emitter contact formation. The devices incorporate a 30-nm-thick InP emitter semiconductor which enables a wet-etch emitter process demonstrating 270-nm-wide emitter-base junctions. At peak RF performance, the device is operating at 30 mW/μm<sup>2</sup> with J<sub>c</sub> = 18.4 mA/μm<sup>2</sup> and V<sub>ce</sub> = 1.64 V. The devices show a peak DC common-emitter current gain (β) ~ 20 and V<sub>BR,CEO</sub> = 2.5 V.
InGaAs-InP mesa DHBTs with simultaneously high f/sub /spl tau// and f/sub max/ and low C/sub cb//I/sub c/ ratio

We report an InP-InGaAs-InP double heterojunction bipolar transistor (DHBT), fabricated using a conventional triple mesa structure, exhibiting a 370-GHz f/sub /spl tau// and 459-GHz f/sub max/, which is to our knowledge the highest f/sub /spl tau// reported for a mesa InP DHBT-as well as the highest simultaneous f/sub /spl tau// and f/sub max/ for any mesa HBT. The collector semiconductor was undercut to reduce the base-collector capacitance, producing a C/sub cb//I/sub c/ ratio of 0.28 ps/V at V/sub cb/=0.5 V. The V/sub BR,CEO/ is 5.6 V and the devices fail thermally only at >18 mW//spl mu/m/sup 2/, allowing dc bias from J/sub e/=4.8 mA//spl mu/m/sup 2/ at V/sub ce/=3.9 V to J/sub e/=12.5 mA//spl mu/m/sup 2/ at V/sub ce/=1.5 V. The device employs a 30 nm carbon-doped InGaAs base with graded base doping, and an InGaAs-InAlAs superlattice grade in the base-collector junction that contributes to a total depleted collector thickness of 150 nm.
Optimal design and implementation of an energy-efficient, semi-active biped

In this paper, a semi-active biped which combines the merits of both powered and passive bipeds is proposed. The semi-activeness of the biped is due to the fact that, during most of a walking cycle, only half of the joints are actuated, and the other half remain unactuated, but have passive joint springs to induce their motions. To devise a systematic design methodology for the biped, its dynamics as well as the walking constraints are carefully studied. Furthermore, an optimization procedure is proposed to compute the optimal trajectories for the actuated joints and spring constants which can lead to minimum energy consumption. The feasibility of the proposed biped is verified by hardware implementation. Experiments indicate that the semi-active biped consumes 80% less the electrical power of the powered biped that performs the same gait and is more energy-efficient than several state-of-the-art bipeds.
Query Driven Localized Linear Discriminant Models for Head Pose Estimation

Head pose appearances under the pan and tilt variations span a high dimensional manifold that has complex structures and local variations. For pose estimation purpose, we need to discover the subspace structure of the manifold and learn discriminative subspaces/metrics for head pose recognition. The performance of the head pose estimation is heavily dependent on the accuracy of structure learnt and the discriminating power of the metric. In this work we develop a query point driven, localized linear subspace learning method that approximates the non-linearity of the head pose manifold structure with piece-wise linear discriminating subspaces/metrics. Simulation results demonstrate the effectiveness of the proposed solution in both accuracy and computational efficiency.