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Network traffic flows contain a large number of correlated and redundant features that significantly degrade the performance of data-driven network anomaly detection. In this paper, we propose a novel clustering and ranking-based feature selection scheme, termed as CBFS, to reduce redundant features in network traffic, which can greatly improve the efficiency and accuracy of feature-based network anomaly detection. Our proposed CBFS scheme first calculates the distance between feature vectors, merges these feature vectors into different clusters, and selects the center of each cluster as a representative feature vector. The proposed CBFS scheme then integrates the information gain and gain rate of features to further streamline the number of features on the basis of clustering generation. Finally, the proposed CBFS scheme applies the decision-tree-based classifier to the generated subset of features so that the abnormal traffic flows are detected. The experimental results show that our proposed CBFS scheme is effective in reducing feature dimensions across different datasets. The proposed CBFS scheme can achieve feature reduction rates of 20% to 70%, and cost-performance of up to 70% as compared to benchmarking methods.

Background To evaluate the value of preablative stimulated thyroglobulin (ps-Tg) before the first radioactive ablation iodine (RAI) treatment to predict the postoperative metastasis of DTC. Methods A total of 235 DTC patients, who underwent total thyroidectomy and neck lymph node dissection, were enrolled. On the basis of the presence or absence of metastasis, all patients were divided into metastasis (M1) and non-metastasis (M0) groups. Besides, the patients in the M1 group were further divided into two subgroups according to sites of metastasis. These groups included cervical lymph node metastasis and distant metastasis groups. Subsequently, the level of serum ps-Tg was measured 3 - 4 days before the first RAI ablation treatment, whereas 131I whole-body imaging and SPECT/CT tomography were performed 5 - 7 days after radio ablation. Subsequently, the Mann Whitney U test was used to compare the different levels of ps-Tg between the two groups. Additionally, the relationship between ps-Tg and the metastasis of DTC was analyzed through correlation analysis, regression analysis, and the ROC curve. Results The ps-Tg level in the M1 group was higher than that in the M0 group. Further analysis discovered that the ps-Tg in the distant metastasis group was higher than that in the cervical lymph node metastasis and non-metastasis groups. Also, the ps-Tg level was positively correlated with distant metastasis (r = 0.599, p = 0.000). Besides, the results of multivariate logistic regression analysis outlined that the level of ps-Tg was an independent risk factor for the development of distant metastasis (OR = 1.008, p = 0.018). Subsequently, the results from the ROC analysis also showed a good diagnostic performance for ps-Tg in treating distant metastasis (AUC = 0.964, p = 0.000), and the optimal cutoff value was 61.87 ng/mL. Conclusions The ps-Tg in patients with DTC before the first RAI ablation treatment is an independent risk factor and a meaningful indicator in predicting postoperative distant metastasis.

We propose Auth+Track, a novel authentication model that aims to reduce redundant authentication in everyday smartphone usage. By sparse authentication and continuous tracking of the user’s status, Auth+Track eliminates the “gap” authentication between fragmented sessions and enables “Authentication Free when User is Around”. To instantiate the Auth+Track model, we present PanoTrack, a prototype that integrates body and near field hand information for user tracking. We install a fisheye camera on the top of the phone to achieve a panoramic vision that can capture both user’s body and on-screen hands. Based on the captured video stream, we develop an algorithm to extract 1) features for user tracking, including body keypoints and their temporal and spatial association, near field hand status, and 2) features for user identity assignment. The results of our user studies validate the feasibility of PanoTrack and demonstrate that Auth+Track not only improves the authentication efficiency but also enhances user experiences with better usability.

The aim of the study involves examining the effect of heavy oil viscosity on fracture geometry in detail by establishing a heavy oil fracturing model and conventional fracturing model based on thermal–hydraulic–mechanical (THM) coupled theory, Walther viscosity model, and K–D–R temperature model. We consider viscosity and density within the heavy oil fracturing model as functions of pressure and temperature while that as constants within the conventional fracturing model. A heavy oil production well is set as an example to analyze the differences between the two models to account for the thermo-poro-elastic effect. The results show that temperature exhibits the most significant influence on the heavy oil viscosity while the influence of pressure is the least. In addition, a cooling area with a width of 0–1 m and varied length is generated near the fracture. The heavy oil viscosity increases sharply in this area, thereby indicating an area of viscosity increment. The heavy oil viscosity increases faster and is closer to wellbore, and a high viscosity increment reduces the mobility of the heavy oil and prevents the fracturing fluid from entering into the reservoir. The special viscosity distribution results in significant differences in pore pressure, oil saturation, and changing trends between these two models. In the heavy oil reservoir fracturing model, the thermal effect completely exceeds the influence of pore elasticity, and the values of the fracture length, width, and static pressure exceed those calculated in the conventional fracturing model. Thus, a comparison of the measured values indicates that the results obtained by considering viscosity as a function of temperature and pressure are more accurate. Therefore, the results of this study are expected to provide good guidelines for the design of heavy oil fracturing.

Semantic information is important in video encryption. However, existing image quality assessment (IQA) methods, such as the peak signal to noise ratio (PSNR), are still widely applied to measure the encryption security. Generally, these traditional IQA methods aim to evaluate the image quality from the perspective of visual signal rather than semantic information. In this paper, we propose a novel semantic-level full-reference image quality assessment (FR-IQA) method named Semantic Distortion Measurement (SDM) to measure the degree of semantic distortion for video encryption. Then, based on a semantic saliency dataset, we verify that the proposed SDM method outperforms state-of-the-art algorithms. Furthermore, we construct a Region Of Semantic Saliency (ROSS) video encryption system to demonstrate the effectiveness of our proposed SDM method in the practical application.

The well development of e-retail market directly constraint the performance of innovative businesses. Compared with USA, UK, and India, this systematically researches and summarizes the main characteristics of Chinese e-retail market with five representative indicators such as the size, product category, purchase frequency and monetary, concentration ratio, and regional characteristics, concluding that the size of Chinese e-retail market is large and developing rapidly, middle and small cities, even the central and western regions and rural areas will be the potential areas for the development of e-retail. However, the purchase frequency and monetary are low, the structure of consumption is imbalanced, and the concentration ratio will slow down.

The characteristics of retail market directly constraint and affect the performance of businesses innovation and the effectivity of the national policy of expanding domestic demand. This article systematically researches and summarizes the main characteristics of China retail market from the perspective of international comparison with five representative indices as the size, growth, consumption rate, consumption structure, concentration of China retail market. The conclusion is that the size of China retail market is large and the growing trend is strong, however, the rate of consumption and the degree of concentration are in a low level, and the structure of consumption is imbalanced.

Online retailing contains enterprises with highly innovative characteristics. In this paper, taking the online retail business of Alibaba China as the case study sample, the global value chain (GVC) innovation theory is used to research the innovative practices of Alibaba's online retail business based on the literature research regarding the online retail business innovation theory. Through selection of major innovation events about online retail business of Alibaba Taobao, we carry out content analysis according to the GVC innovation theory, and deeply analyze the innovation system of Taobao from five perspectives which includes innovation goals, process innovation, product innovation, functional innovation and chain innovation.

Global financial crisis has produced a direct and significant impact on retailers. This paper made a case study on the innovation strategy of Hangzhou Tower Shopping Center in the context of global economic crisis based on retail innovation and global value chain theories. The article proposed: under the background of global financial crisis, an importance strategy which retailers should take is to set up and carry out global value chain innovation strategy system, in order to promote the position in the global value chain and strengthen its global value chain words power and control power.

Taking Target Corporation U.S. as a case, this paper researches its innovation system based on the theory of global value chain innovation. Considered as an innovative retailer, Target tries to innovate, in order to establish its own empire in the highly competitive retail industry in USA. This paper classifies and analyses the innovation events of Target, then comprehensively analyses the innovation system of Target from five aspects: innovation goal, process innovation, product innovation, functional innovation and chain innovation. Target's successful innovations are helpful to Chinese retailers in retail innovation.

Retailing running to high-value-added-end is a more visible trend, which attracts lots of attention from researchers or practitioners. This paper tries to explain this with the theory of Global Value Chains(GVCs). After literature review on GVCs and innovation strategy, this paper analyzes the global value chains of 7–11, IKEA, Wal-Mart and PPR separately. Then some comparisons is done to analyze the respective characteristics of the global value chain model of the four from ten angles, so as to build retailer's innovation strategy on GVCs. As a result, some advices are given to Chinese retailers for their developing.

Abstract Oil-gas field development is a complicated system, and it is a difficult to make a decision of optimal development project. In this paper, a new method which is called fuzzy-grey-element relational decision-making analysis was proposed for evaluating and optimizing oil-gas field development project based on the fuzzy matter-element analysis combined with the grey system theory. Its gist is described as the fundamental element of project by the orderly three element group consisting of "a project, an index, whiten fuzzy-grey-quantity". This group is called the fuzzy-grey-element of project. The merits and demerits of various sorts of technical and economic indexes among the projects are considered comprehensively to appraise and optimize the development projects of oil-gas field, a good effect is acquired. A case study for optimizing gas development project in China showed that the result has a good agreement with practice. Therefore, this method is a general tool and can be used in other areas of petroleum, too. P. 649