Rice is one of the most important and valuable crops in the world. People around the world mainly depend on rice as their daily diet. Therefore, efficient rice fields monitoring is a crucial factor in the improvement of rice crop yield estimation, damage evaluation, budget planning, and agricultural resource management. Synthetic aperture radar (SAR) is an effective tool in monitoring agricultural fields because of its ability to provide high resolution images regardless of weather conditions. However, precision agriculture has put higher requirements for SAR data analysis. In recent years, deep learning methods have achieved great success in various remote sensing applications. In this research, two of the most popular deep learning architectures for time series data, namely convolutional long short-term memory (ConvLSTM) and gated recurrent unit (GRU) have been explored and applied to detect rice fields from SAR images in Taiwan. The experimental results showed that time-series deep learning methods for analyzing SAR data have a great potential for improving the rice fields detection.

While there are several widely used object detection datasets, current computer vision algorithms are still limited in conventional images. Such images narrow our vision in a restricted region. On the other hand, 360° images provide a thorough sight. In this paper, our goal is to provide a standard dataset to facilitate the vision and machine learning communities in 360° domain. To facilitate the research, we present a real-world 360° panoramic object detection dataset, 360-Indoor, which is a new benchmark for visual object detection and class recognition in 360° indoor images. It is achieved by gathering images of complex indoor scenes containing common objects and the intensive annotated bounding field-of-view. In addition, 360-Indoor has several distinct properties: (1) the largest category number (37 labels in total). (2) the most complete annotations on average (27 bounding boxes per image). The selected 37 objects are all common in indoor scene. With around 3k images and 90k labels in total, 360-Indoor achieves the largest dataset for detection in 360° images. In the end, extensive experiments on the state-of-the-art methods for both classification and detection are provided. We will release this dataset in the near future.

In recent years, the satellite technique has a tremendous progress. The images captured by satellites contain larger data and dimensions. The higher number of spectral bands increases the complexity of a classification task. Therefore, it is necessary to reduce highly correlated and redundant neighboring bands which cause the huge phenomenon. In this paper, we proposed a hybrid hierarchical approaches that combine the greedy modular eigenspace (GME) and impurity function band prioritization with hotspot analysis. Unfortunately, GME doesn't guarantee to reach a global optimal solution by the greedy algorithm except by the exhaustive search method. In order to mitigate this limitation, we used a particle swarm optimization (PSO) algorithm to cluster the highly correlated bands and hotspot analysis to give weighting to the clustered blocks. The experimental results on two publicly available benchmark dataset demonstrate that the presented approach can select those bands with discriminative information. The effectiveness of the proposed approach is tested on both images with different parameters of PSO. To verify the effectiveness of a hybrid hierarchical approach put forward in this paper, KNN classifier is performed on the selected bands. In MASTER dataset, the proposed method has 90.91% achievement in dimensionality redaction rate with classification accuracy of 95.3%. In Northwest Tippecanoe County (NTC) dataset, the dimensionality reduction rate is 87.7% and the method achieve a classification accuracy of 96.48%.The results clearly show that the proposed method has the better effects both in dimensionality reduction rate and classification accuracy.

Differential Interferometric Synthetic Aperture Radar (DInSAR) is an effective technique to measures the surface displacement caused by strong earthquakes. In our previous work an adaptive local kriging (ALK) was proposed to recover surface deformation associated with the fault zones. The calculation of ALK needs a huge computing power. Thus a high-performance computing is needed. It can not only speedup the interpolation processes of ALK but also handle large volumes of widely distributed remote sensing dataset. As a result, a parallel image interpolation approach, referred to as the graphics processing unit (GPU) based ALK method, to the slant range motion maps derived by DInSAR is proposed in this paper. It makes use of the performance profiling to analyze the serial version of ALK and perform a parallel GPU computation for reducing the computation time efficiently. By employing the NVIDIA TITAN GPU, the proposed method achieves a speedup of 77.86× compared to its CPU counterpart part.

Flash memory has been widely utilized in embedded systems and consumer electronics, because of its low-power consumption, high-performance access, non-volatility, and shock resistance. A flash-memory device is different from a typical hard-disk device and requires a sophisticated management method to improve the reliable endurance and provide the efficient storage management. To improve the reliable endurance and provide the efficient storage management, the previous works have demonstrated that the identification of the frequently used data and the least recently used data is a key point. In this paper, we will propose a hotness filter of files to calculate how the files are accessed (i.e., reads and writes) intensively. The proposed filter is designed specifically to distinguish between hot and cold files by considering the characteristics of non-volatile memory systems and Android systems. In the experiments, we have implemented the hotness filter in a real Android system (e.g., Asus Nexus 7) and demonstrated that the proposed filter can correctly identify hot and cold files without significant overhead.

This paper describes the application examples of satellite interferometric synthetic aperture radar (InSAR) in exploring potential geo-hazards and mapping geo-related disasters, including earthquakes, landslides, and land subsidence, triggered by natural forces and/or human activities. Satellite images were acquired from the Japan Aerospace Exploration Agency's (JAXA's) ALOS-PALSAR satellite, the Euroeapn Space Agency's (ESA's) Envisat-ASAR satellite, and the German Aerospace Center's (DLR's) TerraSAR-X satellite, covering frequency bands of L, C, and X, respectively. The study areas include Taiwan and Vietnam because both regions are prone to greater risks of geo-hazards and natural disasters. A series of C-band and L-band both ascending and descending mode SAR imagery data were used to map the deformation and subsidence of the environmentally sensitive areas. With the historical information and fast updated data sets, long-term and short-term subsidence patterns can be effectively and efficiently obtained. Excellent agreements were obtained as compared with Global Positioning System (GPS) and leveling measurements. Stacking of dual-beam mode as ascending and descending mode could extract the vertical displacement more easily and reduce the influence from the horizontal displacement. In summary, the advance of satellite radar interferometry provides a vital mapping to detect and identify geo-hazard and potential geo-disaster in general.

Abstract VoIP over WLAN (VoWLAN) gradually has become a popular application with the fast maturing of both WLAN and Voice over IP (VoIP) technology. However there exists one problem that heavily affects the satisfaction of the users which is that the mobility of the mobile host (MH) can disrupt or even intermittently disconnect an ongoing real‐time session. Therefore the issue of how to reduce the handover delay gets more and more important. This paper proposes a Network‐Initiated SimUltaneouS mobility (NISUS) mechanism to facilitate terminal mobility with the session initiation protocol (SIP) in Voice over 3GPP‐WLAN. We design the E2E tunnel state model running on the packet data gateway (PDG) referring to the CAMEL concept. The NISUS is triggered at the PDG by detecting the state transition of the E2E tunnel state model that represents the occurrence of a handover. Then the PDG sends the handover request to notify the Mobility Server (MS) to perform a third party call control (3PCC) and a third party registration on behalf of the MH in parallel for session re‐establishment. With the help of the MS we ensure the lost signaling messages could be correctly re‐sent to moving hosts. Moreover the Master‐Slave Determination procedures derived from H.245 are proposed for the MS in order to handle the racing conditions fairly when two MSs involved in a simultaneous mobility issue 3PCC calls respectively at about the same time. We demonstrate the NISUS works well in the simultaneous and non‐simultaneous movement cases. Analytical results show that the handover delay can be improved significantly by using the NISUS compared with the mobile‐initiated simultaneous/non‐simultaneous mobility. Copyright © 2010 John Wiley & Sons, Ltd.

This paper presents an overview of the current status and data applications of FORMOSAT-2, Taiwanese's first earth observation satellite mission. Highlights of its contributions to monitoring of global natural disasters and earth environmental changes will be illustrated. The FORMOSAT-2 satellite successfully complements existing high spatial resolution imaging satellites such as SPOT-5, IKONOS, and QuickBird, among others, with its unique capability of daily revisits worldwide. The FORMOSAT-2 follow-up program to ensure data continuity to the user community is briefly introduced.

Flash memory has become a popular non-volatile memory technology and is widely used in mobile electronics devices and consumer applications. A flash-memory device is different from typical hard-disk devices and requires sophisticated management to improve the lifetime and the performance. As a result, when a file system is executed on these flash-memory devices, the endurance problem will be an important issue. This is because flash memory could suffer from access errors due to unevenly erase operations on specific locations. In this paper, we will propose a reliable non-volatile memory system by exploiting file-system characteristics. The proposed method can help quick identification of hot and cold files and evenly distribute erase operations over flash-memory devices.When compared to other methods, the proposed method can provide reliable endurance and a more practical solution according to the experimental results.

With high mobility rates of vehicles, there may be frequent occurrences of simultaneous handover. Our work focuses on and straightens out the problems resulting from simultaneous handover in SIP-NEMO. This article proposes a proxy-aided simultaneous handover (PASH) mechanism for the architecture of mobile networks operating on vehicles. The system architecture is modified from SIP-NEMO. We design a Fast Route/local routE re-Establishment (FREE) algorithm capable of re-establishing the optimized routing path fast and ensuring signaling messages buffered in local proxy could be sent to the correct destination without loss. Moreover, the Master- Slave Determination procedures derived from H.245 are introduced to handle the racing conditions fairly when two local proxies involved in a simultaneous handover issue re-INVITE requests at about the same time. Analytical results show that the handover delay can be improved significantly using the PASH, compared with the home-aided simultaneous handover.

In this study, we propose a simple and effective approach to synthesize new motions from a given sequence of continuous motion capture data. First an index function, based on posture features of each motion frame, is introduced to segment the given motion capture data into indexed motion clips. Then based on the fact that motion coherence implies index coherence, a new motion with start frame f/sub start/ and end frame fend can be synthesized by finding a smooth path connecting f/sub start/ to f/sub end/ in the multidimensional index space. Moreover, an algorithm for finding smooth paths is presented and a relevance feedback mechanism is provided to refine the results. The merit of the proposed framework is that it can generate fast prototyping of desired motions with only a small amount of preprocessing time. Experimental results are given to shown the effectiveness of the proposed framework.