Search

A multichannel conflict-avoiding code of length $L$ and weight $w$ for $M$ orthogonal channels, denoted by MC-CAC(M, L, w), is used for deterministic multiple-access without feedback. When the number of simultaneously active users is less than or equal to w, an MC-CAC(M, L, w) is able to provide a hard guarantee that each active user has a successful transmission within every consecutive $L$ time slots. An upper bound on the number of potential users, or codewords, that an MC-CAC(2, L, 3) can support is derived in this paper. By means of (hooked) Skolem sequences, we propose a new construction that can provide a series of optimal MC-CAC(2, L, 3)s in the sense that the code sizes achieve the obtained upper bounds.

We investigate the problem of generating 3D meshes from single free-hand sketches, aiming at fast 3D modeling for novice users. It can be regarded as a single-view reconstruction problem, but with unique challenges, brought by the variation and conciseness of sketches. Ambiguities in poorly-drawn sketches could make it hard to determine how the sketched object is posed. In this paper, we address the importance of viewpoint specification for overcoming such ambiguities, and propose a novel view-aware generation approach. By explicitly conditioning the generation process on a given viewpoint, our method can generate plausible shapes automatically with predicted viewpoints, or with specified viewpoints to help users better express their intentions. Extensive evaluations on various datasets demonstrate the effectiveness of our view-aware design in solving sketch ambiguities and improving reconstruction quality., Comment: Accepted to CVPR 2021

In order to realize the reliability and economy of virtual power plant, landscape theory is applied to the construction of virtual power plant with distributed generation. Firstly, according to the complementarity of intermittent energy output of various distributed power sources, the attractive parameters between different distributed power sources are introduced, and then the matching degree and energy loss degree of the system based on panoramic theory are established. Then, considering the complex operation constraints of various distributed power sources, such as wind power, photovoltaic power, energy storage and electric vehicles, as well as the operation economy and energy loss after aggregation, a multi-objective function virtual power plant building model was constructed. In view of the complexity of the model, the model is transformed into a mixed integer linear single objective optimization model, and GAMS software is used for simulation solution. The simulation results show that the system operation cost is reduced and the output volatility is improved when the distributed power supply is aggregated into virtual power plant.

The time delay between industrial process variables has dynamic characteristics. However, it is quite difficult to estimate and express these dynamic characteristics through traditional methods. In order to deal with this problem, a novel time-delay fuzzy distribution estimation and expression method is presented in this paper. The novel method cuts the target sequence by sliding time window to obtain the target subsequence, then a subsequence that matches the target subsequence by similar calculating in the search sequence can be got, and finally the time-delay sequence information between the two sequences is determined. The fuzzy distribution of the time-delay sequence is calculated by statistical analysis. Then, the improved Data-Driven Fuzzy Time Petri nets (ID-FPNs) are used to describe and express the process information with fuzzy distribution intuitively and effectively. At last, the effectiveness of the method proposed in this paper is validated through a case study.

This paper presents a novel case-based reasoning (CBR) application to crowd-scale deliberation. We propose a CBR approach to facilitating online discussion for crowd-scale deliberation. The objective is to smooth the discussion by avoiding flaming and to efficiently achieve a consensus. Accordingly, several challenging issues are addressed, including case definition and its structure, case creation, and implementation by incorporating with COLLAGREE, a crowd-scale deliberation platform supporting online discussion with the help of facilitators. After introducing an overview of the crowd-scale deliberation and the COLLAGREE, the paper presents the details of the proposed CBR approach for facilitation of online discussion along with some preliminary results. The feasibility of CBR-based facilitation support for crowd-scale deliberations is demonstrated., 2019 IEEE 23rd International Conference on Computer Supported Cooperative Work in Design (CSCWD), May 6-8, 2019, Porto, Portugal, Series: International Conference on Computer Supported Cooperative Work in Design

With the increasing complexity of engines and number of control parameters, optimal engine parameter sets need to be searched in the high dimensionality. Traditional calibration methods are too complicated, expensive and time-consuming. The model-based optimisation is of critical importance for engine fuel efficiency improvement and exhaust emissions reduction. The optimisation highly depends on the model accuracy. In this paper, a multi-layer modelling method is proposed, which can be used to generate the engine model at arbitrary operating points in real time with high accuracy. An enhanced heuristic-algorithm-based optimiser is combined with the real-time modelling method to perform a parallel optimisation. The proposed modelling and optimisation strategy can achieve the minimal fuel consumption fast and accurately. This strategy has been successfully verified using experimental data sets.

Online discussion systems have recently attracted great attention as an enabling approach of realizing collective intelligence. During online discussions, human facilitators are introduced in order to help these discussions to proceed more efficiently and productively. However, there are a number of challenges such as human bias and time restriction that need to be solved in the human facilitator-based online discussion systems. As a result, automated facilitation becomes necessary in order to overcome these shortcomings. This paper proposes a novel approach for automated facilitation that utilizes case based reasoning (CBR) in order to imitate the human facilitator thinking style. The proposed approach works in issue based information system (IBIS) discussion style where complex problems are designed as a conversation amongst several stockholders. These stockholders, in turn, bring their expertise in order to resolve the discussion point. Experimental results show the ability of the proposed approach to improve the performance of online discussion systems, and to guide the online discussion towards consensus and towards gathering wisdom efficiently.

The detection of pulmonary nodules is a very important research field in computer-aided diagnosis. In order to help doctors to identify pulmonary nodules more conveniently, especially for some small pulmonary nodules, a method based on RGB channel superposition to detect pulmonary nodules is proposed in this paper. We put the same ROI (region of interest) from three sequential lung CT slices into RGB channels to gain a pseudo-color image for deep learning. AlexNet and GoogLeNet is used as the deep learning network. We use 10000 patches of healthy tissues and 12000 patches of pulmonary nodules in LIDC-IDRI dataset for training and get a prediction model. The model is tested on 176 patients’ CT images and gain the sensitive of 95.0% at 5.62 false positives per scan. The experimental results show that the proposed method can improve the detection rate of pulmonary nodules compared with some traditional feature extraction methods.

The wavelength switchable Er-doped fiber laser based on nonlinear polarization rotation was studied. Wavelength tuning was realized based on polarization controlling, and stable dual-wavelength operation and wavelength switchable was achieved. The central output wavelength was between 1560nm and 1593nm, and the wavelength spacing is about 10–16.5nm with a side-band suppression ration beyond 45dB, and the wavelength deviation is less than 0.05nm.

We experimentally investigate a diode-pumped passively Q-switched Yb:YAG laser with a Nd,Cr:YAG as saturable absorber. The minimum pulse width of 52ns is obtained, and the maximum of average power is 770mW. The repetition rate of the pulse train increases with the pump power increasing. The maximum of repetition is 3.6kHz.

The current density of GaN-based light emitting diode (LED) plays a strong impact on the light output and heat transfer performances. In this paper, the finite element simulation software ANSYS is used to simulate the thermoelectric performance of LED chip with different electrode structures. The conventional LED chip and the flip-chip (FC) LED with bumps are compared in terms of the current density and the temperature distribution. To improve the thermoelectric property of FC-LED, a structure of FC-LED with vias is proposed and simulated by the electrothermal-coupled. To improve the uniformity of current density of the FC-LED with vias, the electrode structure is optimized with symmetrical electrode. The simulated results show that the optimized structure obtains a better uniform temperature distribution, lower highest temperature and lower temperature difference. To confirm the relationship between the current density uniformity and the temperature distribution, the current density uniformity of different chip structures are quantitatively analyzed. The results show that the optimized FC-LED with vias shows the most uniform current density, indicating that the thermal properties are closely related to the uniformity of current density.

Modeling dependent defaults is a key issue in risk measurement and management. In this paper, we introduce a Markovian infectious model to describe the dependent relationship of default processes of credit entities. The key idea of the proposed model is based on the concept of common shocks adopted in the insurance industry. We compare the proposed model to both one-sector and two-sector models considered in the credit literature using real default data. A log-likelihood ratio test is applied to compare the goodness-of-fit of the proposed model. Our empirical results reveal that the proposed model outperforms both the one-sector and two-sector models.

In this paper, we propose an integrated Mobile WiMAX and free space optics (FSO) broadband access network where the FSO network is used to provide high capacity backhaul for the Mobile WiMAX front end. The integrated network extends the coverage of Mobile WiMAX networks to larger areas in applications where the fiber network is expensive and difficult to deploy. We present a unified EAP-based security framework, and we evaluate and compare the performance of EAP-TLS and EAP-TTLS for this integrated FSO-WiMAX access network. Furthermore, we evaluate the impact of the point-to-point FSO link in the integrated access network. Our measurement shows that compared to EAP-TLS, EAP-TTLS provides a more flexible, efficient, and secure way to protect the integrated FSO-WiMAX access network. Our experiment also demonstrates that the point-to-point FSO link does not degrade the performance of EAP authentication in the integrated network.

Color database is a very important part for fashion design management and trend forecasting work. Traditional color database have a large number of presswork and product object which are not easy for search and view. This color database is based on computer intelligence and digital graphics processing technique. It not only provides a convenient information system but also can raise the utilization rate of images and accuracy of forecasting. This database includes 3 important processes: (1) color information selecting and arrange. (2) Color information transfer and processing. (3) Color data optimization. This computer assisted color database can help color image understanding and offer reliable data for fashion color forecasting.

Fashion color forecasting is more and more important to product development now. It is a creative work combined sense with sensibility and based on huge color resource analysis. In traditional color resource management, different kind of information is usually mixed together and designers can hardly compare accumulated resources and make trend prediction just from picture information. It not only wastes lots of useful information but also affects the accuracy of prediction. This system of color resource management aimed at supporting fashion color forecasting is very helpful and can be carried out by computer intelligence. It divides color resource management into 3 processes: (1) Color resource selecting and classifying. (2) Color resource numeration. (3) Color data optimization. This supposed system can let the color resource management more efficient and scientific and provide more practical data to fashion color forecasting.

In order to evaluate the coordinated development of a system, a method named Synchronous Coordination Judgment (SCJ) is designed, which involves such five procedures as following. Firstly, a system is divided into several subsystems and a number of elements are chosen. Then, based on some criteria these elements are divided into three ranks. Secondly, in each subsystem the number of the elements in each rank is calculated, which is used to determine the state degree of the subsystem. The third step is to determine the line of Ideally Coordinated Development (ICD) and the state point (Q) of system in a specific state space. Fourthly, two distances----the vertical distance (d1) from Q to the line of ICD, and the distance (d2) between Q and the origin, can be calculated. Finally, based on the two distances, both the coordinated development between subsystems and the optimum degree of the system are evaluated. This method is adopted to evaluate the coordinated development between three subsystems (tourism, eco-environment and social economy subsystem) in Nanjing. The results indicate that the subsystems had been approaching coordinated development during 1996-2007. The paper suggests the SCJ method can be applied to evaluate the coordinated development of many subsystems.

A full automatic framework for segmentation of brain image is proposed in this paper. The method is able to segment MRI images, corrects for MRI signal inhomogeneities, and incorporates contextual information by means of Markov random filed. The framework consists of three-step segmentation procedures. First, non-brain structures removal by level set method. Then, the non-uniformity correction method is based on computing estimates of tissue intensity variation. Finally, it uses a statistical model based on Markov random filed (MRF) for MRI brain image segmentation. The brain tissue can be classified into cerebrospinal fluid (CSF), white matter (WM) and gray matter (GM). The efficacy of the proposed method is demonstrated by extensive segmentation experiments using both simulated and real MR images.

Level set method requires the definition of a speed function that governs model deformation. Classical method only used image gradient, edge strength, and region intensity to define the speed function. In this paper, a new speed function for level set framework is proposed. This method combines the region intensity and gradient information instead of spatial image gradient information. The new method is robust to noise and poor edges. We illustrate the performance of the new algorithm on various images. The experimental results show that incorporating region intensity information and gradient information into the level set framework, an accurate and robust segmentation can be achieved.

An automatic approach is presented to isolate and remove the electrocardiogram and respiration waveform artifacts from the electroencephalogram (EEG) recordings. The collected signals from the laboratory rabbit model of intracranial pressure increased are decomposed linearly into independent components by the extended-ICA. The artifactual components can be identified automatically by spectrum analysis. The approach is able to process a long period of data continuously with successive data segments, which can create artifact-reduced EEG signals. To evaluate the performance, the power spectra and the relative wavelet energy (RWE) were calculated, which show the approach can identify the artifacts correctly and suppress them strongly.