Fuzzy geographically weighted clustering using artificial bee colony: An efficient geo-demographic analysis algorithm and applications to the analysis of crime behavior in population

Geo-demographic analysis is an essential part of a geographical information system (GIS) for predicting people’s behavior based on statistical models and their residential location. Fuzzy Geographically Weighted Clustering (FGWC) serves as one of the most efficient algorithms in geo-demographic analysis. Despite being an effective algorithm, FGWC is sensitive to initialize when the random selection of cluster centers makes the iterative process falling into the local optimal solution easily. Artificial Bee Colony (ABC), one of the most popular meta-heuristic algorithms, can be regarded as the tool to achieve global optimization solutions. This research aims to propose a novel geo-demographic analysis algorithm that integrates FGWC to the optimization scheme of ABC for improving geo-demographic clustering accuracy. Experimental results on various datasets show that the clustering quality of the proposed algorithm called FGWC-ABC is better than those of other relevant methods. The proposed algorithm is also applied to a decision-making application for analyzing crime behavior problem in the population using the US communities and crime dataset. It provides fuzzy rules to determine the violent crime rate in terms of linguistic labels from socioeconomic variables. These results are significant to make predictions of further US violent crime rate and to facilitate appropriate decisions on prevention such the situations in the future.     

Robust control via concave minimization local and global algorithms

This paper is concerned with the robust control problem of linear fractional representation (LFT) uncertain systems depending on a time-varying parameter uncertainty. Our main result exploits a linear matrix inequality (LMI) characterization involving scalings and Lyapunov variables subject to an additional essentially nonconvex algebraic constraint. The nonconvexity enters the problem in the form of a rank deficiency condition or matrix inverse relation on the scalings only. It is shown that such problems, but also more generally rank inequalities and bilinear constraints, can be formulated as the minimization of a concave functional subject to LMI constraints. First of all, a local Frank and Wolfe (1956) feasible direction algorithm is introduced in this context to tackle this hard optimization problem. Exploiting the attractive concavity structure of the problem, several efficient global concave programming methods are then introduced and combined with the local feasible direction method to secure and certify global optimality of the solutions. Computational experiments indicate the viability of our algorithms, and in the worst case, they require the solution of a few LMI programs     

Adaptive robust fuzzy control for path tracking of a wheeled mobile robot

This paper proposes an adaptive robust fuzzy control scheme for path tracking of a wheeled mobile robot with uncertainties. The robot dynamics including the actuator dynamics is considered in this work. The presented controller is composed of a fuzzy basis function network (FBFN) to approximate an unknown nonlinear function of the robot complete dynamics, an adaptive robust input to overcome the uncertainties, and a stabilizing control input. The stability and the convergence of the tracking errors are guaranteed using the Lyapunov stability theory. When the controller is designed, the different parameters for two actuator models in the dynamic equation are taken into account. The proposed control scheme does not require the accurate parameter values for the actuator parameters as well as the robot parameters. The validity and robustness of the proposed control scheme are demonstrated through computer simulations. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Efficient screen-space approach to high-quality multiscale ambient occlusion

We present a new screen-space ambient occlusion (SSAO) algorithm that improves on the state-of-the-art SSAO methods in both performance and quality. Our method computes ambient occlusion (AO) values at multiple image resolutions and combines them to obtain the final, high-resolution AO value for each image pixel. It produces high-quality AO that includes both high-frequency shadows due to nearby, occluding geometry and low-frequency shadows due to distant geometry. Our approach only needs to use very small sampling kernels at every resolution, thereby achieving high performance without resorting to random sampling. As a consequence, our results do not suffer from noise and excessive blur, which are common of other SSAO methods. Therefore, our method also avoids the expensive, final blur pass commonly used in other SSAO methods. The use of multiple resolutions also helps reduce errors that are caused by SSAO’s inherent lack of visibility checking. Temporal incoherence caused by using coarse resolutions is solved with an optional temporal filtering pass. Our method produces results that are closer to ray-traced solutions than those of any existing SSAO methods, while running at similar or higher frame rates than the fastest ones.     

Preparation of an exponentially rising optical pulse for efficient excitation of single atoms in free space

We report on a simple method to prepare optical pulses with exponentially rising envelope on the time scale of a few ns. The scheme is based on the exponential transfer function of a fast transistor, which generates an exponentially rising envelope that is transferred first on a radio frequency carrier, and then on a coherent cw laser beam with an electro-optical phase modulator. The temporally shaped sideband is then extracted with an optical resonator and can be used to efficiently excite a single (87)Rb atom.     

Differential Cytotoxicity of Curcumin-Loaded Micelles on Human Tumor and Stromal Cells

Although curcumin in the form of nanoparticles has been demonstrated as a potential anti-tumor compound, the impact of curcumin and nanocurcumin in vitro on normal cells and in vivo in animal models is largely unknown. This study evaluated the toxicity of curcumin-loaded micelles in vitro and in vivo on several tumor cell lines, primary stromal cells, and zebrafish embryos. Breast tumor cell line (MCF7) and stromal cells (human umbilical cord vein endothelial cells, human fibroblasts, and human umbilical cord-derived mesenchymal stem cells) were used in this study. A zebrafish embryotoxicity (FET) assay was conducted following the Organisation for Economic Co-operation and Development (OECD) Test 236. Compared to free curcumin, curcumin PM showed higher cytotoxicity to MCF7 cells in both monolayer culture and multicellular tumor spheroids. The curcumin-loaded micelles efficiently penetrated the MCF7 spheroids and induced apoptosis. The nanocurcumin reduced the viability and disturbed the function of stromal cells by suppressing cell migration and tube formation. The micelles demonstrated toxicity to the development of zebrafish embryos. Curcumin-loaded micelles demonstrated toxicity to both tumor and normal primary stromal cells and zebrafish embryos, indicating that the use of nanocurcumin in cancer treatment should be carefully investigated and controlled.     

Applying Wide & Deep Learning Model for Android Malware Classification

Android malware has exploded in popularity in recent years, due to the platform’s dominance of the mobile market. With the advancement of deep learning technology, numerous deep learning-based works have been proposed for the classification of Android malware. Deep learning technology is designed to handle a large amount of raw and continuous data, such as image content data. However, it is incompatible with discrete features, i.e., features gathered from multiple sources. Furthermore, if the feature set is already well-extracted and sparsely distributed, this technology is less effective than traditional machine learning. On the other hand, a wide learning model can expand the feature set to enhance the classification accuracy. To maximize the benefits of both methods, this study proposes combining the components of deep learning based on multi-branch CNNs (Convolutional Network Neural) with wide learning method. The feature set is evaluated and dynamically partitioned according to its meaning and generalizability to subsets when used as input to the model’s wide or deep component. The proposed model, partition, and feature set quality are all evaluated using the K-fold cross validation method on a composite dataset with three types of features: API, permission, and raw image. The accuracy with Wide and Deep CNN (WDCNN) model is 98.64%, improved by 1.38% compared to RNN (Recurrent Neural Network) model.     

SMA-16路面改性沥青压实温度对比研究

施工温度对SMA-16改性沥青混合料路面的性能影响很大。为了给SMA-16沥青路面压实技术在工程中的应用提供有价值的数据和理论依据,采用合格的矿料级配以及油石比、纤石比和粉石比分别为6.1%,0.31%和10%,模拟施工压实温度变异性对SMA-16路面性能的影响,对不同压实温度下沥青混合料的路用性能进行试验分析。结果表明:SMA混合料最佳压实温度为160℃,初始压实温度不该低于150℃。     

The effect of postharvest 1-MCP treatment and storage atmosphere on ‘Cripps Pink’ apple phenolics and antioxidant activity

This study investigated the effect of a postharvest 1-methylcyclopropene (1-MCP) treatment, controlled atmosphere and storage time on the total antioxidant activity (TAA) and phenolic compounds in the peel and flesh of ‘Cripps Pink’ apples (Malus domestica Borkh.). Preclimacteric apples were harvested and treated with 1-MCP then stored in normal atmosphere (NA) or controlled atmosphere (CA) at 0 °C for up to 160 days. In general, the level of phenolics decreased by 9% in the peel and significantly increased twofold in the flesh during cold storage, regardless of storage atmosphere or 1-MCP treatment. However, treatment with 1-MCP resulted in significantly lower concentrations of chlorogenic acid and procyanidin B2 in apple flesh, and catechin and epicatechin in the peel compared to the control fruits. There was no significant effect of CA on the phenolic compounds during long-term storage, except for quercetin 3-galactoside and quercetin 3-glucoside, which both significantly increased under CA storage. Total antioxidant activity (TAA) is an important nutritional attribute of apples in the human diet. The results showed that TAA in the peel tissue was about eight times higher than that of the flesh, with mean values of 4.75 g TE/kg FW and 0.56 TE/kg FW, respectively. The TAA in both the peel and flesh tissue increased significantly during storage by 40% and 70%, respectively. The storage atmosphere did not significantly affect TAA in either the peel or flesh, whilst the 1-MCP treatment significantly reduced the TAA in the peel tissue only. These results show the beneficial combined effects of pre-storage 1-MCP treatment and CA on ‘Cripps Pink’ apple phenolic composition and antioxidant capacity during long term storage.     

One-point-plus for 5-DOF localization of vehicle-mounted omnidirectional camera in long-range motion

This paper proposes a method for localization of vehicle using one point plus an edge matching region of monocular vision in wide urban environments. The five degree of freedom (5-DoF) localization estimated by monocular omnidirectional camera improves the planar motion assumption in most of conventional researches. In recent year, the car-like motion model with planar motion is often investigated to reduce the requirements of correspondence until one point. However, in the real application of long-range motion in outdoor scene, the motion may not satisfy this condition. This leads to the inaccurate vehicle localization. In this proposed method, the car-like model is also utilized for 5-DoF localization however the requirements of correspondence are reduced to only one point plus an edge matching region which is much simpler than the conventional 5-point RANSAC. The cumulative errors of visual odometry are excluded by using global positioning system (GPS) correction under equation of maximum likelihood estimation in Extended Kalman Filter (EKF) frame work. The real application in hills and mountainous regions demonstrates the accuracy of vehicle localization using this proposed method.