Farmland in the Fukushima region of Japan experienced serious radioactive contamination as a result of the Fukushima Nuclear Power Plant disaster in 2011. A large number of farm-fields have been decontaminated by replacing the top surface soil with non-contaminated soil. This preliminary study investigated the potential of high spatial- and temporal-resolution micro-satellite Venμs and ground-based hyperspectral sensing techniques for assessment of soil fertility and rice productivity in the region to assist the agricultural recovery. Results suggested that these variables would be estimated in a regional scale by remote sensing approaches.

Since hyperspectral data is composed of many spectral bands, it is used for classification with high accuracy. Various studies using spatial information as well as spectral information have been conducted to improve accuracy. However, in recent years pixel-based methods have been reviewed for purposes such as anomaly detection, which is originally expected for hyperspectral data. In this work, we applied one of the time-frequency analysis techniques, wavelet transform, to improve the information extraction capability from hyperspectral data in both classification and regression tasks. As the result, the proposed method showed higher accuracy for classification compared to the conventional methods without spatial information. Also, it was confirmed that the proposed method was effective even for small size classes. For regression, we compared various regression models and confirmed the effectiveness of the proposed method for almost all models.

The advent of satellite constellation has been rapidly increasing the acquisition frequency of remote sensing imagery. In spite of widespread use of constellation satellite imagery in various applications, the assessments of these imagery are still limited. To assess the quality of constellation imagery, we compared imagery of the constellation satellite, Planet, with imagery of the conventional satellite, VENμS, by using three methodologies. Our research revealed that constellation satellites have the advantage of being less blured and the disadvantage of being noisy. Also, we denoted that relative indices, such as NDVIs, should be used in data fusion application. Based on these analysis, we performed land cover mapping of fused time-series satellite imagery by making a use of the result of these assessments.

Drone-based remote sensing has a great potential for spatial diagnostics of crops and soils in the information-based agricultural management (smart farming). This paper reports an advanced drone-based remote sensing system, integrated data processing, algorithms, and applications to smart farming. The system is equipped with higher-performance drone and three imaging modules, i.e., multispectral, thermal, and visible video imagers. The algorithms for diagnostic information derived from hyperspectral and thermal data were validated with drone-based sensing data. 3D models were also derived semi-automatically from the spectral, thermal, and video imagery. Drone-based remote sensing would be useful for timely and efficient acquisition of diagnostic information for smart faming.

Although many wearable sensors have been developed or commercialized for gait analysis, ambulatory force sensors and motion sensors were rarely integrated to implement complete human dynamics analysis. Three dimensional (3D) lower limb kinematic and kinetic analysis based on ambulatory measurements is introduced in this paper. We developed a wireless sensor system composed of a mobile force plate system, 3D motion analysis units and a wireless data logger. 3D motions of body segment and triaxial ground reaction force (GRF) could be simultaneously measured using the system, and the data obtained from sensor units on thighs, shanks and feet could be transferred to a personal computer by wireless local area network (LAN). A stick-chain model was built to visually analyze lower limb postures and joint trajectories, and an inverse dynamics method was adopted to calculate triaxial joint moments. We conducted application experiments on volunteers to visualize and analyze 3D segment orientations and joint moments during successive gait for level ground walking, treadmill walking, and stair climbing. Experiment results showed that 3D segment orientations and joint trajectories could be shown and analyzed using the stick chain model, and that joint loads for different walking conditions could be compared in each gait cycle.

Numerous rehabilitation robots have been developed to deliver therapy for hemiplegic patients with a unilateral-disabled limb or for aged persons with motor-function degenerated limbs. Recently, much attention has been paid to the development of robots that support bilateral arm training in various patterns. It has been proved that the coordination of two limbs can reduce hypertonia and abnormal synergies compared to unilateral limb training. However, traditional robots realized different modes with the robot providing a corresponding force for the impaired limb. This paper proposes a novel bimanual training system. A subject controls master and slave terminal handles with his/her two limbs. The less impaired limb provides a corresponding force for the more impaired limb to achieve different training patterns. No matter in which mode, the two limbs accomplish symmetric movement. An experimental prototype was built. Frequency response test and training tests on 9 healthy subjects in active-resisted and active-assisted modes were performed. Experimental results confirm that the system can correctly respond a subject's commands if velocity was changed within the frequency range of 30 Hz. For each training mode, the average position error, and RMS (root mean square) values of position errors and velocity errors that between the reference values and actual values of a motion tracking task were reduced after practice. This proves the effectiveness of the system for self-assisted rehabilitation training.

The study was carried out for agricultural area in Poland for the years 2003-2007. The aim of the project was to examine the impact of soil-vegetation parameters on backscatter calculated from ENVISAT.ASAR under various polarizations and incidence angles. The extensive field measurements have been carried out simultaneously to satellite overpasses. Additionally to microwave acquisitions the optical data from TERRA.ASTER satellite have been used to distinguish different crop types. There has been applied two approaches: (1) for each of the class the equations for calculation of LAI and soil moisture from microwave data have been derived using statistical analyses, and the maps of LAI and soil moisture have been presented; (2) the semi empirical water-cloud model has been applied to describe the contribution of soil moisture and winter wheat descriptor as LAI on backscattering coefficient. The results show that presented methods can be implemented into monitoring of crop growth.

To achieve accurate and efficient interaction with humans, robot training is indispensable to make robot cooperate with different host. We are focusing on development of a human motion analysis system to real-time measure body segment orientations. Imitation control was applied on a biped robot based on measurements of the developed wearable sensor system. Experimental study was implemented to verify the synchronous imitation control method proposed for the biped robot, and verification results proved the feasibility of the proposed control method. Through comparing results obtained from direct imitation control method and improved method based on training algorithm considering the personal motion pattern, we found that the imitation control accuracy was markedly improved, and the three-axial average errors of x- y- and z- moving displacements related to leg length were 12%, 8% and 4% respectively.

Renesas Technology Corp. designers turned to OpenAccess to address the major design challenges with systems on chip for the automotive, wireless, digital consumer and industrial markets. OpenAccess provides Renesas with an industry standard database that has the capacity and performance needed for today's largest designs. The C++ API (C++ application programming interface) facilitates fast access to a unified data model for both logical and physical design. It enables an efficient level of access to the data model to integrate tools developed in-house with commercially available tools for translation free interoperability.

A wearable sensory system for human lower extremity motion analysis is proposed, and an intelligent computation method for this sensory system is presented. The standard method for human motion analysis is the optical motion analysis using high-speed cameras to record human 3D motion, but this method is only limited in the laboratory research, because it requires expensive devices, large space and time-exhausted calibration experiments. In this study, two low-cost human motion analysis systems are constructed, deferent from the conventional 3D motion analysis system based on high-speed camera. These wearable systems incorporate gyroscopes (ENC-05EB) to measure angular velocities of body segments, and two-axis accelerometers (ADXL202) are used to measure the accelerations for the purpose of leg (foot, shank and thigh) motion analysis in every human motion cycle. The first wearable sensor system is designed for only foot motion analysis and the second system can be used for a leg (foot, shank and thigh) motion analysis. Then based on the two sensor systems, a fuzzy inference system (FIS) is developed for the calculation of the gait phases fed by sensors outputs. A digital filter is also designed to eliminate noises from of the output of the fuzzy inference system, which enhances robustness of the system. Finally, experimental study is conducted to validate the wearable sensor systems using an optical motion analysis system (Hi-DCam)

The numeric inversion of water-cloud model of synchronized microwave bands of ERS-2 and JERS satellites gave the possibility of obtaining crop characteristics. Model performance was validated by comparison between backscattering coefficients simulated and measured by satellites. The contribution of various crop characteristics was presented and compared to measured soil-vegetation parameters at the ground level during satellite overpasses.

The objectives of this study were to explore quantitative relationships between remotely sensed signatures and ecosystem variables such as vegetation growth and CO/sub 2/ flux, and to investigate the potential of the synergy between remote sensing and process models. Results showed both thermal and optical remote sensing data could be effectively used for estimating dynamic change of important variables in agricultural ecosystems.

A method is proposed to estimate both green leaf area index (GLAI) and soil moisture (h/sub v/), based on radar measurements at the Ku-band (14.85 GHz) and C-band (5.35 GHz) frequencies. The Ku-band backscatter at large incidence angles was found to be independent of soil moisture conditions and could be used alone to estimate GLAI. Then, the Ku-band estimate of GLAI could be used with a measurement of C-band backscatter in a canopy radiative transfer model to isolate the value of h/sub v/. This concept was demonstrated with a set of Kuand C-band synthetic aperture radar (SAR) backscatter data acquired over agricultural fields in Arizona. The demonstration showed promise for operational application of the method, though several limitations were identified. Since both Ku- and C-band /spl sigma//sub /spl deg// are sensitive to soil roughness, this approach must be applied only to fields of similar soil roughness or row direction. This limitation may be less serious for farm management applications since crop type and cultivation practices are generally well known and can be taken into consideration. Another limitation of the use of Ku- and C-band /spl sigma//spl deg/ is the apparent saturation of the Ku-band signal with increasing GLAI. Operational implementation of this approach will require dual-frequency sensors aboard an aircraft or orbiting satellite.