Structure and microwave dielectric properties of La(2−x)/3Nax(Mg1/2W1/2)O3

The structure evolution, sintering behavior and microwave dielectric properties of La_(2−x)/3Na_x(Mg_1/2W_1/2)O₃ (x = 0–0.5) were investigated in this paper. The X-ray diffraction (XRD) results show that all samples exhibit single phase, and the structure changed from orthorhombic when 0 ≤ x < 0.3 to monoclinic phase when 0.3 ≤ x ≤ 0.5. The size and ordering degree of A/B-site domains decrease with the increase in x value. The sintering temperature of the Na-doped samples increased compared to the pure La_2/3(Mg_1/2W_1/2)O₃ (LMW) due to the estimated decrease in the concentration of A-site vacancies. The addition of Na⁺ ion does not affect the dielectric permittivity greatly. The Q × f value decreases with the increase in x value, although the estimated concentration of A-site vacancies decreases with increasing x, which may be ascribed to the decrease of A/B-site ordering and domain size with the increase in x. The temperature coefficient of resonant frequency changed from negative values into positive values with the increase in x value.     

Two possible emission mechanisms involved in the arc discharge method of carbon nanotube preparation

By investigating the morphologies and microstructures of the cathode deposits prepared by self-sustained arc discharge between graphite rods, we consider that there are two electron emission mechanisms occurring on the cathode: field emission and thermionic emission. The former occurs mainly on the edge of the growing surface, by which we can explain the formation of the outer hard shell of the cathode deposit; while the latter occurs mainly on the growing surface except for the edge area and it is the main cause for the growth of carbon nanotubes.     

Coupling-and-decoupling: A hierarchical model for occlusion-free object detection

Handling occlusion is a very challenging problem in object detection. This paper presents a method of learning a hierarchical model for X-to-X occlusion-free object detection (e.g., car-to-car and person-to-person occlusions in our experiments). The proposed method is motivated by an intuitive coupling-and-decoupling strategy. In the learning stage, the pair of occluding X?s (e.g., car pairs or person pairs) is represented directly and jointly by a hierarchical And–Or directed acyclic graph (AOG) which accounts for the statistically significant co-occurrence (i.e., coupling). The structure and the parameters of the AOG are learned using the latent structural SVM (LSSVM) framework. In detection, a dynamic programming (DP) algorithm is utilized to find the best parse trees for all sliding windows with detection scores being greater than the learned threshold. Then, the two single X?s are decoupled from the declared detections of X-to-X occluding pairs together with some non-maximum suppression (NMS) post-processing. In experiments, our method is tested on both a roadside-car dataset collected by ourselves (which will be released with this paper) and two public person datasets, the MPII-2Person dataset and the TUD-Crossing dataset. Our method is compared with state-of-the-art deformable part-based methods, and obtains comparable or better detection performance.     

A fuzzy neural network approach for online fault detection in waste water treatment process

In this paper, an effective strategy for fault detection of sludge volume index (SVI) sensor is proposed and tested on an experimental hardware setup in waste water treatment process (WWTP). The main objective of this fault detection strategy is to design a system which consists of the online sensors, the SVI predicting plant and fault diagnosis method. The SVI predicting plant is designed utilizing a fuzzy neural network (FNN), which is trained by a historical set of data collected during fault-free operation of WWTP. The fault diagnosis method, based on the difference between the measured concentration values and FNN predictions, allows a quick revealing of the faults. Then this proposed fault detection method is applied to a real WWTP and compared with other approaches. Experimental results show that the proposed fault detection strategy can obtain the fault signals of the SVI sensor online.     

Efficient object detection based on selective attention

In this paper, we make use of biologically inspired selective attention to improve the efficiency and performance of object detection under clutter. At first, we propose a novel bottom-up attention model. We argue that heuristic feature selection based on bottom-up attention can stably select out invariant and discriminative features. With these selected features, performance of object detection can be improved apparently and stably. Then we propose a novel concept of saccade map based on bottom-up attention to simulate the saccade (eye movements) in vision. Sliding within saccade map to detect object can significantly reduce computational complexity and apparently improve performance because of the effective filtering for distracting information. With these ideas, we present a general framework for object detection through integrating bottom-up attention. Through evaluating on UIUC cars and Weizmann–Shotton horses we show state-of-the-art performance of our object detection model.     

Recent climate variability and its impact on precipitation,temperature, and vegetation dynamics in the Lancang River headwater area of China

The alpine ecosystem is one of the most fragile ecosystems threatened by global climate change. The impact of climate variability on the vegetation dynamics of alpine ecosystems has become important in global change studies. In this study, spatially explicit gridded data, including the Moderate Resolution Imaging Spectroradiometer (MODIS) land-surface temperature (LST) product (MOD11A1/A2), the Tropical Rainfall Measuring Mission (TRMM) rainfall product (3B43), and MODIS net primary productivity (NPP) product (MOD17A3), together with meteorological observation data, were used to explore the spatio-temporal pattern of climate variability and its impact on vegetation dynamics from 2000 to 2012 in the Lancang River headwater area. We found that the variation patterns of LST, precipitation, and NPP in the study area showed remarkable spatial differences. From the northwest to the southeast the spatial variation of average annual LST exhibited a decreasing–increasing–decreasing–increasing pattern. At the same time, most of the study area exhibited an increasing LST during the growing season. The annual precipitation increased in the semi-arid northern part, whereas it decreased in the semi-humid southern part. The precipitation variability during the growing season has a pattern similar to the annual precipitation variability. Although the majority of the regions have seen an NPP increase from 2000 to 2012, the responses of the vegetation to the varied climate factors were spatially heterogeneous. The alpine–subalpine meadows in the high-altitude areas were more sensitive to climate variability in the growing season. It is argued that satellite remote-sensing products have great potential in investigating the impact of climate variability on vegetation dynamics at the finer scale, especially for the Lancang River headwater area with complex surface heterogeneity.     

A general transformation from KP-ABE to searchable encryption

Users are inclined to share sensitive data in a remote server if no strong security mechanism is in place. Searchable encryption satisfies the need of users to execute a search encrypted data. Previous searchable encryption methods such as “public key encryption with keyword search (PEKS)” restricted the data access to certain users, because only the assigned users were able to search the encrypted data. In this paper we will discuss the relation between Attribute Based Encryption (ABE) and searchable encryption and define a weak anonymity of the ABE scheme, named “attribute privacy”. With this weak anonymity, we propose a general transformation from ABE to Attribute Based Encryption with Keyword Search (ABEKS) and a concrete attribute private key-policy ABE (KP-ABE) scheme. We present an ABEKS scheme based on this KP-ABE scheme and permit multi-users to execute a flexible search on the remote encrypted data.