scholarly journals Context Impacts in Accelerometer-Based Walk Detection and Step Counting

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3604 ◽  
Author(s):  
Buke Ao ◽  
Yongcai Wang ◽  
Hongnan Liu ◽  
Deying Li ◽  
Lei Song ◽  
...  
Keyword(s):  
Wearable Devices ◽  
Performance Comparison ◽  
Process Data ◽  
Algorithm Selection ◽  
Practical Applications ◽  
Dynamic Factors ◽  
Recent Emergence ◽  
Step Counting ◽  
Quantitative Performance ◽  
Series Of Experiments

Walk detection (WD) and step counting (SC) have become popular applications in the recent emergence of wearable devices. These devices monitor user states and process data from MEMS-based accelerometers and optional gyroscope sensors. Various algorithms have been proposed for WD and SC, which are generally sensitive to the contexts of applications, i.e., (1) the locations of sensor placement; (2) the sensor orientations; (3) the user’s walking patterns; (4) the preprocessing window sizes; and (5) the sensor sampling rates. A thorough understanding of how these dynamic factors affect the algorithms’ performances is investigated and compared in this paper. In particular, representative WD and SC algorithms are introduced according to their design methodologies. A series of experiments is designed in consideration of different application contexts to form an experimental dataset. Different algorithms are then implemented and evaluated on the dataset. The evaluation results provide a quantitative performance comparison indicating the advantages and weaknesses of different algorithms under different application scenarios, giving valuable guidance for algorithm selection in practical applications.

Ion Beam Induced Interfacial Reactions in Molybdenum Thin Films on Silicon

1981 ◽  
Vol 39 ◽  
pp. 162-163
Author(s):  
L. J. Chen ◽  
L. S. Hung ◽  
J. W. Mayer
Keyword(s):  
Ion Beam ◽  
Chemical Vapor ◽  
Interfacial Reactions ◽  
Practical Applications ◽  
Microelectronic Devices ◽  
Recent Emergence ◽  
Chemical Vapor Deposited ◽  
Atomic Mixing ◽  
Silicon Interface ◽  
Kinetics Of

When an energetic ion penetrates through an interface between a thin film (of species A) and a substrate (of species B), ion induced atomic mixing may result in an intermixed region (which contains A and B) near the interface. Most ion beam mixing experiments have been directed toward metal-silicon systems, silicide phases are generally obtained, and they are the same as those formed by thermal treatment.Recent emergence of silicide compound as contact material in silicon microelectronic devices is mainly due to the superiority of the silicide-silicon interface in terms of uniformity and thermal stability. It is of great interest to understand the kinetics of the interfacial reactions to provide insights into the nature of ion beam-solid interactions as well as to explore its practical applications in device technology.About 500 Å thick molybdenum was chemical vapor deposited in hydrogen ambient on (001) n-type silicon wafer with substrate temperature maintained at 650-700°C. Samples were supplied by D. M. Brown of General Electric Research & Development Laboratory, Schenectady, NY.

scholarly journals Image Segmentation Techniques in Bone Structure Psychiatry

2020 ◽  
Vol 9 (07) ◽  
pp. 25102-25112
Author(s):  
Ajayi Olayinka Adedoyin ◽  
Olamide Timothy Tawose ◽  
Olu Sunday Adetolaju
Keyword(s):  
Image Segmentation ◽  
Bone Structure ◽  
Performance Comparison ◽  
Imaging Systems ◽  
Intrinsic Properties ◽  
X Ray ◽  
Practical Applications ◽  
X Ray Imaging ◽  
Segmentation Algorithms ◽  
Bone Structures

Today, a large number of x-ray images are interpreted in hospitals and computer-aided system that can perform some intelligent task and analysis is needed in order to raise the accuracy and bring down the miss rate in hospitals, particularly when it comes to diagnosis of hairline fractures and fissures in bone joints. This research considered some segmentation techniques that have been used in the processing and analysis of medical images and a system design was proposed to efficiently compare these techniques. The designed system was tested successfully on a hand X-ray image which led to the proposal of simple techniques to eliminate intrinsic properties of x-ray imaging systems such as noise. The performance and accuracy of image segmentation techniques in bone structures were compared and these eliminated time wasting on the choice of image segmentation algorithms. Although there are several practical applications of image segmentation such as content-based image retrieval, machine vision, medical imaging, object detection, recognition tasks, etc., this study focuses on the performance comparison of several image segmentation techniques for medical X-ray images.

A Lightweight Detection Model for SAR Aircraft in a Complex Environment

2021 ◽  
Vol 13 (24) ◽  
pp. 5020
Author(s):  
Mingwu Li ◽  
Gongjian Wen ◽  
Xiaohong Huang ◽  
Kunhong Li ◽  
Sizhe Lin
Keyword(s):  
Spatial Information ◽  
Scattering Mechanism ◽  
Complex Environment ◽  
Average Precision ◽  
Important Indicator ◽  
Practical Applications ◽  
Detection Model ◽  
The Neural Network ◽  
Series Of Experiments ◽  
Aircraft Detection

Recently, deep learning has been widely used in synthetic aperture radar (SAR) aircraft detection. However, the complex environment of the airport—consider the boarding bridges, for instance—greatly interferes with aircraft detection. Besides, the detection speed is also an important indicator in practical applications. To alleviate these problems, we propose a lightweight detection model (LDM), mainly including a reuse block (RB) and an information correction block (ICB) based on the Yolov3 framework. The RB module helps the neural network extract rich aircraft features by aggregating multi-layer information. While the RB module brings more effective information, there is also redundant and useless information aggregated by the reuse block, which is harmful to detection precision. Therefore, to accurately extract more aircraft features, we propose an ICB module combining scattering mechanism characteristics by extracting the gray features and enhancing spatial information, which helps suppress interference in a complex environment and redundant information. Finally, we conducted a series of experiments on the SAR aircraft detection dataset (SAR-ADD). The average precision was 0.6954, which is superior to the precision values achieved by other methods. In addition, the average detection time of LDM was only 6.38 ms, making it much faster than other methods.

scholarly journals Application of Color Featuring and Deep Learning in Maize Plant Detection

2020 ◽  
Vol 12 (14) ◽  
pp. 2229
Author(s):  
Haojie Liu ◽  
Hong Sun ◽  
Minzan Li ◽  
Michihisa Iida
Keyword(s):  
Deep Learning ◽  
False Negative ◽  
Color Space ◽  
Performance Comparison ◽  
Maize Plant ◽  
Detection Accuracy ◽  
Learning Technology ◽  
Practical Applications ◽  
Feature Based ◽  
Detection Speed

Maize plant detection was conducted in this study with the goals of target fertilization and reduction of fertilization waste in weed spots and gaps between maize plants. The methods used included two types of color featuring and deep learning (DL). The four color indices used were excess green (ExG), excess red (ExR), ExG minus ExR, and the hue value from the HSV (hue, saturation, and value) color space, while the DL methods used were YOLOv3 and YOLOv3_tiny. For practical application, this study focused on performance comparison in detection accuracy, robustness to complex field conditions, and detection speed. Detection accuracy was evaluated by the resulting images, which were divided into three categories: true positive, false positive, and false negative. The robustness evaluation was performed by comparing the average intersection over union of each detection method across different sub–datasets—namely original subset, blur processing subset, increased brightness subset, and reduced brightness subset. The detection speed was evaluated by the indicator of frames per second. Results demonstrated that the DL methods outperformed the color index–based methods in detection accuracy and robustness to complex conditions, while they were inferior to color feature–based methods in detection speed. This research shows the application potential of deep learning technology in maize plant detection. Future efforts are needed to improve the detection speed for practical applications.

scholarly journals Round table: AI and Big Data: Ethical Challenges and Health Opportunities

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
Keyword(s):  
Big Data ◽  
Digital Health ◽  
Rapid Development ◽  
Open Data ◽  
Wearable Devices ◽  
Good Evidence ◽  
Electronic Patient Records ◽  
Ethical Challenges ◽  
Data Movement ◽  
Recent Emergence

Abstract The recent emergence of Big Data in healthcare (including large linked data from electronic patient records (EPR) as well as streams of real-time geolocated health data collected by personal wearable devices, etc.) and the open data movement enabling sharing datasets are creating new challenges around ownership of personal data whilst at the same time opening new research opportunities and drives for commercial exploitation. A balance must be struck between an individual’s desire for privacy and their desire for good evidence to drive healthcare, which may sometimes be in conflict. With the increasing use of mobile and wearable devices, new opportunities have been created for personalized health (tailored care to the needs of an individual), crowdsourcing, participatory surveillance, and movement of individuals pledging to become “data donors” and the “quantified self” initiative (where citizens share data through mobile device-connected technologies). These initiatives created large volumes of data with considerable potential for research through open data initiatives. In this workshop we will hear from a panel of international speakers working across the digital health, Big Data ethics, computer science, public health divide on how they have addressed the challenges presented by increased use of Big Data and AI systems in healthcare with insights drawn from their own experience to illustrate the new opportunities that development of these movements has opened up. Key messages The potential of open access to healthcare data, sharing Big Data sets and rapid development of AI technology, is enormous - so as are the challenges and barriers to achieve this goal. Policymakers, scientific and business communities should work together to find novel approaches for underlying challenges of a political and legal nature associated with use of big data for health.

Comparison of Feature Performance and its Application to Feature Combination in Off-Line Handwritten Korean Alphabet Recognition

1998 ◽  
Vol 12 (02) ◽  
pp. 251-261 ◽  
Author(s):  
Kukhwan Seo ◽  
Jongyeol Kim ◽  
Jongmin Yoon ◽  
Kyusik Chung
Keyword(s):  
Performance Improvement ◽  
Recognition Rate ◽  
Performance Comparison ◽  
Experimental Results ◽  
The Other ◽  
Feature Combination ◽  
Topological Features ◽  
Quantitative Performance ◽  
Combination Approach ◽  
Neural Network Classifiers

This paper presents (1) a quantitative performance comparison of the features used in off-line handwritten Korean alphabet recognition, and (2) some experimental results based on the feature combination approach. We classified the features into three: geometrical/topological, statistical and global. For each class, we selected four or five features and performed recognition experiments with PE92 database using neural network classifiers. We compared their recognition performances and selected the top four among those thirteen features: Up Down Left Right Hole, Gradient, Structure, and Mesh. With the combination of some or all of the four features, we repeated recognition experiments. Experimental results show that (1) as a whole, geometrical/topological features outperform the other two feature classes in terms of the recognition rate, and (2) UDLRH and Gradient features in geometrical/topological feature class outperform the other features, (3) the feature combination approach can result in performance improvement.

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