This study was conducted using a drone with advanced mobility to develop unified sensor and communication system as new platform for in situ atmospheric measurements. As major cause of air pollution, particulate matter (PM) has been attracting attention globally. We developed small, lightweight, simple, cost-effective multi-sensor multiple measurements phenomena related environmental information. For local area measurements, we used long-range wireless module real-time monitoring visualizing...

This study proposes an object detector for apple trees as a first step in developing agricultural digital twins. An original dataset of orchard images was created and used to train Single Shot MultiBox Detector (SSD) You Only Look Once (YOLO) models. Performance evaluated using mean Average Precision (mAP). YOLO significantly outperformed SSD, achieving 91.3% mAP compared the SSD’s 46.7%. Results indicate YOLO’s Darknet-53 backbone extracts more complex features suited tree detection. work...

Coexisting SO2 considerably enhanced the catalytic activity of Ir/SiO2 for NO reduction with CO in presence O2 because formation a cis-type coordinated species and to one iridium atom ([formula: see text]), possible reaction intermediate leading N2 formation.

This study was conducted to develop robot prototypes of three models that navigate mallards achieve high-efficiency rice-duck farming. We examined two robotics navigation approaches based on imprinting and feeding. As the first approach, we used applied baby mallards. They exhibited follow behavior our prototype after imprinting. Experimentally obtained observation results revealed importance providing immediately up one week hatching. another feed placed top second prototype. showed adult...

This paper presents an unsupervised learning-based method for selection of feature points and object category classification without previous setting the number categories. Our consists following procedures: 1) detection description features using a Scale-Invariant Feature Transform (SIFT), 2) target One Class-Support Vector Machines (OC-SVMs), 3) generation visual words all SIFT descriptors histograms in each image selected Self-Organizing Maps (SOMs), 4) formation labels Adaptive Resonance...

In this paper, we propose an advanced adaptive cruise control to evaluate the collision risk between adjacent vehicles and adjust distance them seeking improve driving safety. As a solution for preventing crashes, autopilot vehicle has been considered. near future, technique forecast dangerous situations automatically speed prevent can be implemented real vehicle. We have attempted realize predict future positions of vehicles. Several previous studies investigated similar approaches;...

Abstract. This paper presents a sensor system to predict behavior patterns that occur when patients leave their beds. We originally developed plate-shaped sensors using piezoelectric elements. Existing such as clip and mat require restraint of patients. Moreover, these present privacy problems. The features our are they no power supply or patient restraint. evaluated basic experiment seven patterns. obtained result predicted related bed-leaving only six installed under bed. Especially, can...

This paper presents an adaptive and incremental learning method to visualize series data on a category map. We designate this as Adaptive Category Mapping Networks (ACMNs). The architecture of ACMNs comprises three modules: codebook module, labeling mapping module. module converts input features into codebooks low-dimensional vectors using Self-Organizing Maps (SOMs). creates labels candidate categories based the Resonance Theory (ART). visualizes spatial relations among map Counter...

This paper presents a digital hardware Back- Propagation (BP) model for real-time learning in the field of video image processing. The is layer parallel architecture with 16-bit fixed point specialized We have compared our standard BP that used double-precision floating point. Simulation results show has equal capabilities to those model. implemented on an FPGA board we originally designed and developed experimental use as platform Experimental performed 100,000 epochs/frame corresponds 90...

Proposes a segmentation method for quantitative image diagnosis as means of realizing an objective the frontal lobe atrophy. From data obtained on grade membership, fractal dimensions cerebral tissue [cerebral spinal fluid (CSF), gray matter, and white matter] contours are estimated. The mutual relationship between degree atrophy dimension has been analyzed based estimated dimensions. Using sample 42 male female cases, ranging In age from 50's to 70's, it concluded that can be quantified by...

This paper presents a method for classification and recognition of behavior patterns based on interest from human trajectories at an event site. Our creates models using Hidden Markov Models (HMMs) each trajectory quantized One-Dimensional Self-Organizing Maps (1D-SOMs). Subsequently, we apply Two-Dimensional SOMs (2D-SOMs) unsupervised features according to the distance between models. Furthermore, use Unified Matrix (U-Matrix) visualizing category boundaries Euclidean weights 2D-SOMs....

This paper presents an unsupervised category classification method for time-series images that combines incremental learning of Adaptive Resonance Theory-2 (ART-2) and self-mapping characteristic Counter Propagation Networks (CPNs). Our comprises the following procedures: 1) generating visual words using Self-Organizing Maps (SOM) from 128-dimensional descriptors in each feature point a Scale-Invariant Feature Transform (SIFT), 2) forming labels ART-2, 3) creating classifying categories on...

This paper presents a sensor system that predicts behavior patterns occur when patient leaves bed.We originally developed plate-shaped sensors using piezoelectric elements.Existing such as clip and mat require patients be restrained.The features of our are they no power supply or restraint for privacy problems.Moreover, we machine-learning algorithms to predict without setting thresholds.We evaluated ten subjects at an experimental environment constructed in reference clinical site.The mean...

Abstract Ink‐jet and a‐Si TFT technologies are the best combination for fabricating a large‐sized low‐cost OLED display. We developed 2.1‐inch, full‐color polymer AM‐OLED display driven by new current‐programmed method using a‐Si:H TFTs showing more than 450 cd/m 2 brightness, 100:1 contrast with real black about 5 % deviation of half‐tone uniformity, which were achieved structure inserting interlayer into conventional 2‐layer LEP structure.

Drones equipped with a global navigation satellite system (GNSS) receiver for absolute localization provide high-precision autonomous flight and hovering. However, the GNSS signal reception sensitivity is considerably lower in areas such as those between high-rise buildings, under bridges, tunnels. This paper presents drone method based on acoustic information using microphone array GNSS-denied areas. Our originally developed comprised 32 microphones installed cross-shaped configuration....

Classification, segmentation, and recognition techniques based on deep-learning algorithms are used for smart farming. It is an important challenging task to reduce the time, burden, cost of annotation procedures collected datasets from fields crops that changing in a wide variety ways according growing, weather patterns, seasons. This study was conducted generate crop image semantic segmentation style transfer using generative adversarial networks (GANs). To assess data-augmented...