Special Issue "Intelligent System Innovation"

A special issue of Applied Sciences (ISSN 2076-3417).

Deadline for manuscript submissions: closed (31 December 2019).

Special Issue Editors

Prof. Dr. Teen­-Hang Meen
Website
Guest Editor
Department of Electronic Engineering, National Formosa University, Yunlin 632, Taiwan
Interests: photovoltaic device; dye-sensitized solar cells; nanotechnology
Special Issues and Collections in MDPI journals
Prof. Dr. Wenbing Zhao
Website
Guest Editor
Department of Electrical Engineering and Computer Science, Cleveland State University, Ohio, 44011, USA
Interests: human computer interaction; rehabilitation; computer vision; distributed systems
Special Issues and Collections in MDPI journals
Prof. Dr. Cheng-Fu Yang

Guest Editor

Special Issue Information

Dear Colleagues,

Mechanical engineering and design innovations are both academic and practical engineering fields that involve systematic technological materialization through scientific principles and engineering design. Technological innovation by mechanical engineering includes IT-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanosciences and nanotechnology. These new technologies, which implant intelligence in machine systems, are an interdisciplinary area combining conventional mechanical technology and new information technology.

The main goal of this Special Issue “Intelligent System Innovation” is to discover new scientific knowledge relevant to IT-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanosciences and nanotechnology. We invite investigators to contribute their original research or review articles to this Special Issue.

In addition, our organized conference “The 2nd IEEE International Conference on Knowledge Innovation and Invention 2019” (IEEE ICKII 2019) will be held in Seoul, South Korea on 12–15 July 2019. The authors of the papers which will be presented at IEEE ICKII 2019 are invited to submit their extended versions to this Special Issue after the conference. Submitted papers should be extended to the size of regular research or review articles, with at least a 50% extension of new results.

Potential topics include, but are not limited to:

  • Intelligent mechanical manufacturing systems;
  • Mathematical problems in mechanical system design;
  • Smart electromechanical system analysis and design;
  • Applied materials in nanosciences and nanotechnology;
  • Computer-aided methods for mechanical design procedure and manufacture;
  • Computer and human–machine interaction;
  • Internet technology in mechanical system innovation;
  • Machine diagnostics and reliability;
  • Human–machine interaction/virtual reality and entertainment

Prof. Teen­Hang Meen
Prof. Dr. Wenbing Zhao
Prof. Dr. Cheng-Fu Yang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Smart electromechanical system analysis and design
  • Intelligent mechanical System
  • Applied Materials on Nanosciences and Nanotechnology

Published Papers (32 papers)

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Research

Open AccessArticle
Control Strategy Development of Driveline Vibration Reduction for Power-Split Hybrid Vehicles
Appl. Sci. 2020, 10(5), 1712; https://doi.org/10.3390/app10051712 - 02 Mar 2020
Cited by 1
Abstract
In order to achieve better performance of fuel consumption in hybrid vehicles, the internal combustion engine is controlled to operate under a better efficient zone and often turned off and on during driving. However, while starting or shifting the driving mode, the instantaneous [...] Read more.
In order to achieve better performance of fuel consumption in hybrid vehicles, the internal combustion engine is controlled to operate under a better efficient zone and often turned off and on during driving. However, while starting or shifting the driving mode, the instantaneous large torque from the engine or electric motor may occur, which can easily lead to a high vibration of the elastomer on the driveline. This results in decreased comfort. A two-mode power-split hybrid system model with elastomers was established with MATLAB/Simulink. Vibration reduction control strategies, Pause Cancelation strategy (PC), and PID control were developed in this research. When the system detected a large instantaneous torque output on the internal combustion engine or driveline, the electric motor provided corresponding torque to adjust the torque transmitted to the shaft mitigating the vibration. To the research results, in the two-mode power-split hybrid system, PC was able to mitigate the vibration of the engine damper by about 60%. However, the mitigation effect of PID and PC-PID was better than PC, and the vibration was able to converge faster when the instantaneous large torque input was made. In the frequency response, the effect of the PID blocking vibration source came from the elastomer was about 75%, while PC-PID additionally reduced 8% by combining the characteristics of the two control methods. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Numerical Investigation of the Effects of Prosthetic Aortic Valve Design on Aortic Hemodynamic Characteristics
Appl. Sci. 2020, 10(4), 1396; https://doi.org/10.3390/app10041396 - 19 Feb 2020
Cited by 1
Abstract
The superior performance of single-point attached commissures (SPAC) molded valve design has been validated by several numerical, in vitro and in vivo animal studies. However, the impacts of the SPAC molded valve design on aortic hemodynamic environments are yet to be investigated. In [...] Read more.
The superior performance of single-point attached commissures (SPAC) molded valve design has been validated by several numerical, in vitro and in vivo animal studies. However, the impacts of the SPAC molded valve design on aortic hemodynamic environments are yet to be investigated. In this study, multiscale computational models were prepared by virtually implanting prosthetic aortic valves with SPAC tubular, SPAC molded and conventional designs into a patient-specific aorta, respectively. The impacts of the valve designs on efferent flow distribution, flow pattern and hemodynamic characteristics in the aorta were numerically investigated. The results showed that despite the overall flow phenomena being similar, the SPAC tubular valve exhibited a suboptimal performance in terms of higher spatially averaged wall shear stress (SAWSS) in ascending aorta (AAo), higher helix grade, stronger secondary flow mean secondary velocity in descending aorta, as well as more complex vortex distribution. The results from the current study extend the understanding of hemodynamic impacts of the valve designs, which would further benefit the optimization of the prosthetic aortic valve. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
A Web Services, Ontology and Big Data Analysis Technology-Based Cloud Case-Based Reasoning Agent for Energy Conservation of Sustainability Science
Appl. Sci. 2020, 10(4), 1387; https://doi.org/10.3390/app10041387 - 19 Feb 2020
Abstract
Energy conservation is one of the important topics for sustainability science, while case-based reasoning is one of the most important techniques for sustainable processing. This study aimed to develop a cloud case-based reasoning agent that integrates multiple intelligent technologies and supports, which can [...] Read more.
Energy conservation is one of the important topics for sustainability science, while case-based reasoning is one of the most important techniques for sustainable processing. This study aimed to develop a cloud case-based reasoning agent that integrates multiple intelligent technologies and supports, which can help users to quickly, accurately, and effectively obtain useful cloud energy-saving information in a timely manner for sustainability science. The system was successfully built with the support of Web services technology, ontology, and big data analytics. To set up this energy-saving case-based reasoning agent, this study reviewed the relevant technologies for building a web services platform and explored how to widely integrate and support the cloud interaction of the energy-saving data processing agent via the technologies. In addition to presenting relevant R&D technologies and results in detail, this study carefully conducted performance and learning experiments to prove the system’s effectiveness. The results showed that the core technology of the case-based reasoning agent achieved good performance and that the learning effectiveness of the overall system was also great. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Application of Support Vector Machine (SVM) in the Sentiment Analysis of Twitter DataSet
Appl. Sci. 2020, 10(3), 1125; https://doi.org/10.3390/app10031125 - 07 Feb 2020
Cited by 2
Abstract
At present, in the mainstream sentiment analysis methods represented by the Support Vector Machine, the vocabulary and the latent semantic information involved in the text are not well considered, and sentiment analysis of text is dependent overly on the statistics of sentiment words. [...] Read more.
At present, in the mainstream sentiment analysis methods represented by the Support Vector Machine, the vocabulary and the latent semantic information involved in the text are not well considered, and sentiment analysis of text is dependent overly on the statistics of sentiment words. Thus, a Fisher kernel function based on Probabilistic Latent Semantic Analysis is proposed in this paper for sentiment analysis by Support Vector Machine. The Fisher kernel function based on the model is derived from the Probabilistic Latent Semantic Analysis model. By means of this method, latent semantic information involving the probability characteristics can be used as the classification characteristics, along with the improvement of the effect of classification for support vector machine, and the problem of ignoring the latent semantic characteristics in text sentiment analysis can be addressed. The results show that the effect of the method proposed in this paper, compared with the comparison method, is obviously improved. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Defect Detection in Striped Images Using a One-Dimensional Median Filter
Appl. Sci. 2020, 10(3), 1012; https://doi.org/10.3390/app10031012 - 04 Feb 2020
Abstract
Defect detection is a key element of quality assurance in many modern manufacturing processes. Defect detection methods, however, often involve a great deal of time and manual work. Image processing has become widely used as a means of reducing the required detection time [...] Read more.
Defect detection is a key element of quality assurance in many modern manufacturing processes. Defect detection methods, however, often involve a great deal of time and manual work. Image processing has become widely used as a means of reducing the required detection time and effort in manufacturing. To this end, this study proposes an image-processing algorithm for detecting defects in images with striped backgrounds—defect types include scratches and stains. In order to detect defects, the proposed method first pre-processes images and rotates them to align the stripes horizontally. Then, the images are divided into two parts: blocks and intervals. For the blocks, a one-dimensional median filter is used to generate defect-free images, and the difference between the original images and the defect-free images is calculated to find defects. For the intervals, defects are identified using image binarization. Finally, the method superposes the results found in the blocks and intervals to obtain final images with all defects marked. This study evaluated the performance of the proposed algorithm using 65 synthesized images and 20 actual images. The method achieved an accuracy of 97.2% based on the correctness of the defect locations. The defects that could not be identified were those whose greyscales were very close to those of the background. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Earthquake Shake Detecting by Data Mining from Social Network Platforms
Appl. Sci. 2020, 10(3), 812; https://doi.org/10.3390/app10030812 - 23 Jan 2020
Abstract
This study used social media posts of the related effect of earthquakes to derive seismic shake scale distributions in regions of Taiwan and compared it with the regional seismic scale reported by the Central Weather Bureau (CWB) of Taiwan. This study conducted a [...] Read more.
This study used social media posts of the related effect of earthquakes to derive seismic shake scale distributions in regions of Taiwan and compared it with the regional seismic scale reported by the Central Weather Bureau (CWB) of Taiwan. This study conducted a context searching to scrawl the relationship phrase on the social media network platform, PTT bulletin board system (BBS), to detect the earthquake shake scale using the keywords of the context. In this investigation a decision tree model for analyzing the semantic words from the context of the target event to detect the earthquake shake scale was devised. The results indicate that we can pick out the keywords to use to detect the earthquake shake scale at about 85%. Furthermore, the results of the derived shake scale show that the four studied cases are in a good agreement with the presented news from the CWB of Taiwan. In this study, the author attempted to develop a quick earthquake shake scale detection model by semantic analysis of the collected earthquake disaster information reported on the social media network platform. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Interdisciplinarily Exploring the Most Potential IoT Technology Determinants in the Omnichannel E-Commerce Purchasing Decision-Making Processes
Appl. Sci. 2020, 10(2), 603; https://doi.org/10.3390/app10020603 - 14 Jan 2020
Cited by 1
Abstract
This research has interdisciplinarily employed the “SoLoMo” concept of Intern of Things (IoT) technology, Social Cognitive Theory and the Technological Acceptance Model (TAM) into the hierarchical Analytical Network Process (ANP) model of qualitative analysis in order to concretively construct the most comprehensive IoT [...] Read more.
This research has interdisciplinarily employed the “SoLoMo” concept of Intern of Things (IoT) technology, Social Cognitive Theory and the Technological Acceptance Model (TAM) into the hierarchical Analytical Network Process (ANP) model of qualitative analysis in order to concretively construct the most comprehensive IoT technology model in the purchasing decision-making process of the omnichannel e-commerce model. Statistically, this research not only employed the Factor Analysis (FA) approach of quantitative analysis for systematically assaying the data results from the dispensation of large-scale questionnaires to refine the commonality of each sub-criterion with higher research representativeness and validity but it also applied the Fuzzy Set Theory (FST) and Grey Relation Analysis (GRA) methods of qualitative analyses for in-depth analytically evaluate the data results from the operation of expert’s questionnaires to refine the measured consequences of the ANP model with higher research accuracy and reliability. Conclusively, the “Purchasing Original Intentions” has been the most critical purchasing factors in the omnichannel e-commerce purchasing decision-making processes which means current omnichannel e-commerce consumers have commenced to firstly and rationally think over before making purchasing decisions and actions without any irrational consumptions. Conclusively, “Purchasing Importance-Purchasing Importance (PI)”, “Purchasing Financial Status-Purchasing Financial Status (PFS)” and “Purchaser’s Personality-Purchaser’s Personality (PP)” were the most potential IoT technology determinants in the omnichannel e-commerce purchasing decision-making processes because (1) omnichannel e-commerce consumers have been rationally focused on what they demand without traditional emotional purchasing consumptions, (2) omnichannel e-commerce consumers have rationally considered their financial resources without impulsive purchasing consumptions and (3) omnichannel e-commerce consumers have rationally respected their personal characteristics and individual value without blindly purchasing consumptions. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Implementation of an Obstacle Recognition System for the Blind
Appl. Sci. 2020, 10(1), 282; https://doi.org/10.3390/app10010282 - 30 Dec 2019
Cited by 1
Abstract
The blind encounter commuting risks, such as failing to recognize and avoid obstacles while walking, but protective support systems are lacking. Acoustic signals at crosswalk lights are activated by button or remote control; however, these signals are difficult to operate and not always [...] Read more.
The blind encounter commuting risks, such as failing to recognize and avoid obstacles while walking, but protective support systems are lacking. Acoustic signals at crosswalk lights are activated by button or remote control; however, these signals are difficult to operate and not always available (i.e., broken). Bollards are posts installed for pedestrian safety, but they can create dangerous situations in that the blind cannot see them. Therefore, we proposed an obstacle recognition system to assist the blind in walking safely outdoors; this system can recognize and guide the blind through two obstacles (crosswalk lights and bollards) with image training from the Google Object Detection application program interface (API) based on TensorFlow. The recognized results notify the blind through voice guidance playback in real time. The single shot multibox detector (SSD) MobileNet and faster region-convolutional neural network (R-CNN) models were applied to evaluate the obstacle recognition system; the latter model demonstrated better performance. Crosswalk lights were evaluated and found to perform better during the day than night. They were also analyzed to determine if a client could cross at a crosswalk, while the locations of bollards were analyzed by algorithms to guide the client by voice guidance. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Injection Molding Process Control of Servo–Hydraulic System
Appl. Sci. 2020, 10(1), 71; https://doi.org/10.3390/app10010071 - 20 Dec 2019
Abstract
The present study constructs a servo–hydraulic system to simulate the filling and packing processes of an injection molding machine. Experiments are performed to evaluate the velocity and position control of the system in the filling stage and the pressure control in the packing [...] Read more.
The present study constructs a servo–hydraulic system to simulate the filling and packing processes of an injection molding machine. Experiments are performed to evaluate the velocity and position control of the system in the filling stage and the pressure control in the packing stage. The results demonstrate that the proposed system meets the required performance standards when operated with the proportional-integral–derivative (PID) controller under a sampling frequency of 1000 Hz. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Urban Air Quality Analysis and Forecast Based on Intelligent Algorithm with Parameter Optimization and Decision Rules
Appl. Sci. 2019, 9(24), 5445; https://doi.org/10.3390/app9245445 - 12 Dec 2019
Cited by 2
Abstract
Air pollution has an ongoing devastating impact on the planet, damaging ecosystems, depleting natural resources, and endangering human health. This paper proposes a new intelligent algorithm that includes parameter optimization and decision rules to forecast and analyze of urban air quality. Through analysis [...] Read more.
Air pollution has an ongoing devastating impact on the planet, damaging ecosystems, depleting natural resources, and endangering human health. This paper proposes a new intelligent algorithm that includes parameter optimization and decision rules to forecast and analyze of urban air quality. Through analysis of 24-h daily air quality data provided by the Beijing Air Quality Monitoring Station, simulated annealing (SA) and a decision tree (DT) emerge as the key factors. We prove that in the investigated algorithm, SA and DT can be used to make decision rules and achieve better accuracy for classification. We find that SA can be used to adjust the best parameter settings for the DT. Simulation results show that the accuracy of the proposed algorithm for classification is far better than other existing approaches. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Study on the Improvement of a Collision Avoidance System for Curves
Appl. Sci. 2019, 9(24), 5380; https://doi.org/10.3390/app9245380 - 09 Dec 2019
Cited by 1
Abstract
Conventional autonomous emergency braking (AEB) systems derive the relative distance of a curve using a curvature calculated through an in-vehicle sensor. However, as the AEB system cannot reflect geometric factors of a curve with variable curvature, it does not accurately estimate relative distances, [...] Read more.
Conventional autonomous emergency braking (AEB) systems derive the relative distance of a curve using a curvature calculated through an in-vehicle sensor. However, as the AEB system cannot reflect geometric factors of a curve with variable curvature, it does not accurately estimate relative distances, based on which the AEB performance is evaluated. Accordingly, an AEB system reflecting the geometric information of curves needs to be considered and developed to improve the AEB performance for curves. This study proposes a method to improve the performance of AEB systems for curves through curvilinear coordinate conversion, which is used to reflect the geometric information of roads for the navigation of an autonomous vehicle. Both the host and target vehicles are located by means of curvilinear coordinate conversion. The positions thus identified are used to calculate the relative distance and lanes. Finally, the hazard risk criterion—that is, time-to-collision (TTC)—is derived using the proposed AEB system. To demonstrate the effectiveness of the proposed AEB system, this study compares it with the conventional AEB system by analyzing the collision avoidance performance on curves through relative distances and TTC. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Using Real-Time Dynamic Prediction to Implement IoV-Based Collision Avoidance
Appl. Sci. 2019, 9(24), 5370; https://doi.org/10.3390/app9245370 - 09 Dec 2019
Abstract
For some IoV-based collision-avoidance architectures, it is not necessary that all vehicles have communication abilities. Hence, they need some particular designs and extra components. In the literature, one of them uses a camera mounted onto the infrastructure at an intersection to realize collision [...] Read more.
For some IoV-based collision-avoidance architectures, it is not necessary that all vehicles have communication abilities. Hence, they need some particular designs and extra components. In the literature, one of them uses a camera mounted onto the infrastructure at an intersection to realize collision detection. Consequently, technologies for real-time object detection and dynamic prediction are required for the purposes of collision avoidance. In this paper, we propose an interesting method to predict the future position of a vehicle based on a well-known, real-time object detection project, YOLOv3. Our algorithm utilizes the concept of vehicle dynamics and the confidence region to predict the future position on vehicles. This will help us to realize real-time dynamic prediction and Internet of Vehicles (IoV)-based collision detection. Lastly, in accordance with the experimental results, our design shows the performance for predicting the future position of a vehicle. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
A Study of the Influence of Career Counseling Perception on the Employment Competencies of Design Students in Central Taiwan
Appl. Sci. 2019, 9(23), 5072; https://doi.org/10.3390/app9235072 - 24 Nov 2019
Abstract
In recent years, many advanced countries have been outsourcing their lower-skilled jobs to other countries for manufacturing. As a result, employment opportunity has been declining for younger generations in advanced countries. Moreover, the extensive application of production technologies also leads to the replacement [...] Read more.
In recent years, many advanced countries have been outsourcing their lower-skilled jobs to other countries for manufacturing. As a result, employment opportunity has been declining for younger generations in advanced countries. Moreover, the extensive application of production technologies also leads to the replacement of labors by automatic machines. The employment opportunity of young adults has also gradually been deprived. It has become more difficult for students to make a career decision during college. After graduation, students also encounter the difficult choice of getting a job or going to graduate school. Therefore, career counseling for a student is critical to his/her career development. It is required to assist students in developing a correct career concept so that they can make an appropriate choice for their career. College students who are studying in design-related departments in central Taiwan were selected as the research target in this study. A total of 460 questionnaire copies were dispatched and 378 valid questionnaire copies were returned with a rate of response of 82%. The result of this research is threefold, as follows. 1. Career counseling has a significant positive influence on the vocational self-concept. 2. Vocational self-concept has a significantly positive influence on the employment competencies. 3. Career counseling has a significantly positive influence on employment competencies. We proposed recommendations based on the results of the investigation and analysis. It is expected that, the result can help schools provide appropriate and proper career counseling in order to assist and guide students into making proper career choices. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
An Automatic Chinese Medicine Dispensing Machine Using Shelf-Based Mechanism
Appl. Sci. 2019, 9(23), 5060; https://doi.org/10.3390/app9235060 - 23 Nov 2019
Abstract
Chinese medicine is a time-honored and deeply valued medical skill in the Chinese community. Although currently the scientific Chinese medicine powder is prevalent, its varieties are numerous and have similar appearance, color, and odor, resulting in difficulties in being distinguished. Moreover, dosages are [...] Read more.
Chinese medicine is a time-honored and deeply valued medical skill in the Chinese community. Although currently the scientific Chinese medicine powder is prevalent, its varieties are numerous and have similar appearance, color, and odor, resulting in difficulties in being distinguished. Moreover, dosages are still weighed and mixed manually, rather than being automated; therefore, the workload for each Chinese medicine pharmacist is heavy, leading to it being easy for the wrong medicine to be administered due to human negligence. An innovative shelf-based automatic powder dispensing machine is therefore presented in this paper in order to promote the quality and efficiency of powder dispensing. This machine consists of linear guide mechanisms, weighing mechanisms, retractable mechanisms, gallipot base discharge mechanisms, and a lifting platform mechanism, and offers several innovative or important features that are beneficial to Chinese medicine. It can automatically and accurately dispense different powders in the correct weights, reducing the possibility of human error. Each gallipot is equipped with one low-cost gallipot base, which can be controlled by the weighing mechanism to discharge powder with the desired weight. Powder cross-contamination among different gallipots can also be avoided. Stepping motors are used in the presented machine for easy control, low cost, and durability. A parabolic type of S mode speed control for stepping motor is implemented, providing faster and more stable moving speed and accuracy than the traditional trapezoidal mode. Hardware and software are integrated and tested. The error of the weighed powder is reduced to +/−0.2 g. The dispensing process is very efficient, the moving speed of the weighing mechanism reaches 23.89 cm/s, and the discharge speed is up to 0.22 g/s. The system is indeed able to improve the accuracy and efficiency of powder dispensing for Chinese medicine. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Using Unmanned Aerial Vehicle Remote Sensing and a Monitoring Information System to Enhance the Management of Unauthorized Structures
Appl. Sci. 2019, 9(22), 4954; https://doi.org/10.3390/app9224954 - 18 Nov 2019
Abstract
In this research, we investigated using unmanned aerial vehicle (UAV) photographic technology to prevent the further expansion of unauthorized construction and thereby reduce postdisaster losses. First, UAV dynamic aerial photography was used to obtain dynamic digital surface model (DSM) data and elevation changes [...] Read more.
In this research, we investigated using unmanned aerial vehicle (UAV) photographic technology to prevent the further expansion of unauthorized construction and thereby reduce postdisaster losses. First, UAV dynamic aerial photography was used to obtain dynamic digital surface model (DSM) data and elevation changes of 2–8 m as the initial sieve target. Then, two periods of dynamic orthophoto images were superimposed for human–computer interaction interpretation, so we could quickly distinguish buildings undergoing expansion, new construction, or demolition. At the same time, mobile geographic information system (GIS) software was used to survey the field, and the information gathered was developed to support unauthorized construction detection. Finally, aerial images, interpretation results, and ground survey information were integrated and released on WebGIS to build a regulatory platform that can achieve accurate management and effectively prevent violations. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Hyperspectral Image Classification Based on Spectral and Spatial Information Using Multi-Scale ResNet
Appl. Sci. 2019, 9(22), 4890; https://doi.org/10.3390/app9224890 - 14 Nov 2019
Cited by 2
Abstract
Hyperspectral imaging (HSI) contains abundant spectrums as well as spatial information, providing a great basis for classification in the field of remote sensing. In this paper, to make full use of HSI information, we combined spectral and spatial information into a two-dimension image [...] Read more.
Hyperspectral imaging (HSI) contains abundant spectrums as well as spatial information, providing a great basis for classification in the field of remote sensing. In this paper, to make full use of HSI information, we combined spectral and spatial information into a two-dimension image in a particular order by extracting a data cube and unfolding it. Prior to the step of combining, principle component analysis (PCA) is utilized to decrease the dimensions of HSI so as to reduce computational cost. Moreover, the classification block used during the experiment is a convolutional neural network (CNN). Instead of using traditionally fixed-size kernels in CNN, we leverage a multi-scale kernel in the first convolutional layer so that it can scale to the receptive field. To attain higher classification accuracy with deeper layers, residual blocks are also applied to the network. Extensive experiments on the datasets from Pavia University and Salinas demonstrate that the proposed method significantly improves the accuracy in HSI classification. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Design of Novel Fiber Optical Flexible Routing System
Appl. Sci. 2019, 9(22), 4763; https://doi.org/10.3390/app9224763 - 07 Nov 2019
Abstract
In this paper, we propose a new versatile routing device that utilizes arrayed waveguide gratings (AWGs), optical switches, and optical circulators to implement reconfigurable optical add/drop multiplexers (ROADMs), optical interleavers, and optical cross-connect (OXC). With the development of dense wavelength division multiplexing (DWDM) [...] Read more.
In this paper, we propose a new versatile routing device that utilizes arrayed waveguide gratings (AWGs), optical switches, and optical circulators to implement reconfigurable optical add/drop multiplexers (ROADMs), optical interleavers, and optical cross-connect (OXC). With the development of dense wavelength division multiplexing (DWDM) technology, ROADM and OXC technologies have also been put into practical use. Thus, the optical signal can be routed directly in the optical network according to its wavelength without the need for optical-electrical-optical (OEO) conversion. Although different optical network units (ONUs) have different bandwidth requirements, the use of optical interleavers has successfully solved the connection problem between old and new systems. According to the numerical experiments of static characteristics, the proposed routing device can effectively implement three different functionalities, thereby providing greater flexibility for fiber optic network applications. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Impacts of Internal Carotid Artery Revascularization on Flow in Anterior Communicating Artery Aneurysm: A Preliminary Multiscale Numerical Investigation
Appl. Sci. 2019, 9(19), 4143; https://doi.org/10.3390/app9194143 - 03 Oct 2019
Cited by 3
Abstract
The optimal management strategy of patients with concomitant anterior communicating artery aneurysm (ACoAA) and internal carotid artery (ICA) stenosis is unclear. This study aims to evaluate the impacts of unilateral ICA revascularization on hemodynamics factors associated with rupture in an ACoAA. In the [...] Read more.
The optimal management strategy of patients with concomitant anterior communicating artery aneurysm (ACoAA) and internal carotid artery (ICA) stenosis is unclear. This study aims to evaluate the impacts of unilateral ICA revascularization on hemodynamics factors associated with rupture in an ACoAA. In the present study, a multiscale computational model of ACoAA was developed by coupling zero-dimensional (0D) models of the cerebral vascular system with a three-dimensional (3D) patient-specific ACoAA model. Distributions of flow patterns, wall shear stress (WSS), relative residence time (RRT) and oscillating shear index (OSI) in the ACoAA under left ICA revascularization procedure were quantitatively assessed by using transient computational fluid dynamics (CFD) simulations. Our results showed that the revascularization procedures significantly changed the hemodynamic environments in the ACoAA. The flow disturbance in the ACoAA was enhanced by the resumed flow from the affected side. In addition, higher OSI (0.057 vs. 0.02), prolonged RRT (1.14 vs. 0.39) and larger low WSS area (66 vs. 50 mm2) in ACoAA were found in the non-stenotic case. These acute changes in hemodynamics after revascularization may elevate the rupture risk of ACoAA. The preliminary results validated the feasibility of predicting aneurismal hemodynamics characteristics in revascularization procedures by using multiscale CFD simulations, which would benefit the management of this group of patients. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Intelligent Neural Network Schemes for Multi-Class Classification
Appl. Sci. 2019, 9(19), 4036; https://doi.org/10.3390/app9194036 - 26 Sep 2019
Cited by 1
Abstract
Multi-class classification is a very important technique in engineering applications, e.g., mechanical systems, mechanics and design innovations, applied materials in nanotechnologies, etc. A large amount of research is done for single-label classification where objects are associated with a single category. However, in many [...] Read more.
Multi-class classification is a very important technique in engineering applications, e.g., mechanical systems, mechanics and design innovations, applied materials in nanotechnologies, etc. A large amount of research is done for single-label classification where objects are associated with a single category. However, in many application domains, an object can belong to two or more categories, and multi-label classification is needed. Traditionally, statistical methods were used; recently, machine learning techniques, in particular neural networks, have been proposed to solve the multi-class classification problem. In this paper, we develop radial basis function (RBF)-based neural network schemes for single-label and multi-label classification, respectively. The number of hidden nodes and the parameters involved with the basis functions are determined automatically by applying an iterative self-constructing clustering algorithm to the given training dataset, and biases and weights are derived optimally by least squares. Dimensionality reduction techniques are adopted and integrated to help reduce the overfitting problem associated with the RBF networks. Experimental results from benchmark datasets are presented to show the effectiveness of the proposed schemes. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Design of Micro-Phasor Measurement System to Identify Phasor of Distribution Transformers
Appl. Sci. 2019, 9(18), 3831; https://doi.org/10.3390/app9183831 - 12 Sep 2019
Abstract
In this paper, the micro-phasor measurement system is developed to support phasor identification of distribution transformers for the distribution mapping management system (DMMS) of Taiwan Power Company (TPC). The one pulse per second signal (1PPS) from the global positioning system (GPS) is used [...] Read more.
In this paper, the micro-phasor measurement system is developed to support phasor identification of distribution transformers for the distribution mapping management system (DMMS) of Taiwan Power Company (TPC). The one pulse per second signal (1PPS) from the global positioning system (GPS) is used to synchronize the voltage sampling between reference and measurement sides. By receiving 1PPS from GPS, the phasor measurement of three-phase voltage at the reference site of the substation is stored in the master station with a time-stamp. This paper proposes a timing synchronous module with an embedded temperature compensated crystal oscillator (TCXO) to generate highly accurate timing for field measurement of underground distribution facilities. Mobile communication network is used to compare measurement results between reference and field sides of voltage angle that define distribution transformer phasor. This paper also designs and develops an application for mobile devices by importing DMMS database, which is used to search the attributes of the distribution transformers for measurement at the field. After the transformer phasor is identified, the results are stored in the mobile device to update the attributes of distribution transformers in DMMS. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Non-Touch Sign Word Recognition Based on Dynamic Hand Gesture Using Hybrid Segmentation and CNN Feature Fusion
Appl. Sci. 2019, 9(18), 3790; https://doi.org/10.3390/app9183790 - 10 Sep 2019
Cited by 6
Abstract
Hand gesture-based sign language recognition is a prosperous application of human– computer interaction (HCI), where the deaf community, hard of hearing, and deaf family members communicate with the help of a computer device. To help the deaf community, this paper presents a non-touch [...] Read more.
Hand gesture-based sign language recognition is a prosperous application of human– computer interaction (HCI), where the deaf community, hard of hearing, and deaf family members communicate with the help of a computer device. To help the deaf community, this paper presents a non-touch sign word recognition system that translates the gesture of a sign word into text. However, the uncontrolled environment, perspective light diversity, and partial occlusion may greatly affect the reliability of hand gesture recognition. From this point of view, a hybrid segmentation technique including YCbCr and SkinMask segmentation is developed to identify the hand and extract the feature using the feature fusion of the convolutional neural network (CNN). YCbCr performs image conversion, binarization, erosion, and eventually filling the hole to obtain the segmented images. SkinMask images are obtained by matching the color of the hand. Finally, a multiclass SVM classifier is used to classify the hand gestures of a sign word. As a result, the sign of twenty common words is evaluated in real time, and the test results confirm that this system can not only obtain better-segmented images but also has a higher recognition rate than the conventional ones. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
A Novel Bidirectional Wireless Power Transfer System for Mobile Power Application
Appl. Sci. 2019, 9(18), 3769; https://doi.org/10.3390/app9183769 - 09 Sep 2019
Abstract
This paper presents a bidirectional wireless power transfer system for mobile power applications. A novel 2-switch bidirectional wireless power transfer system with dual-side control is proposed for mobile power applications. Although only two switches are adopted, the energy can be transferred from the [...] Read more.
This paper presents a bidirectional wireless power transfer system for mobile power applications. A novel 2-switch bidirectional wireless power transfer system with dual-side control is proposed for mobile power applications. Although only two switches are adopted, the energy can be transferred from the transmitter side to the receiver side and vice versa. The term bidirectional means that the power-flow is bidirectional and also that the transmitter is also a receiver and the receiver is also a transmitter. The output energy can be easily controlled by the duty ratios of the two switches. Thus, the proposed bidirectional power transfer system uses only one circuit to achieve bidirectional power transfer. Hence, the system cost and volume can be reduced so that the system is small and convenient for mobile power systems, portable and/or wearable electronic devices. A prototype system is constructed and the experimental results verify the validity of the proposed bidirectional wireless power transfer system. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Failure-Robot Path Complementation for Robot Swarm Mission Planning
Appl. Sci. 2019, 9(18), 3756; https://doi.org/10.3390/app9183756 - 08 Sep 2019
Cited by 1
Abstract
Currently, unmanned vehicles are widely used in different fields of exploration. Due to limited capacities, such as limited power supply, it is almost impossible for one unmanned vehicle to visit multiple wide areas. Multiple unmanned vehicles with well-planned routes are required to minimize [...] Read more.
Currently, unmanned vehicles are widely used in different fields of exploration. Due to limited capacities, such as limited power supply, it is almost impossible for one unmanned vehicle to visit multiple wide areas. Multiple unmanned vehicles with well-planned routes are required to minimize an unnecessary consumption of time, distance, and energy waste. The aim of the present study was to develop a multiple-vehicle system that can automatically compile a set of optimum vehicle paths, complement failed assignments, and avoid passing through no-travel zones. A heuristic algorithm was used to obtain an approximate solution within a reasonable timeline. The A* Search algorithm was adopted to determine an alternative path that does not cross the no-travel zone when the distance array was set, and an improved two-phased Tabu search was applied to converge any initial solutions into a feasible solution. A diversification strategy helped identify a global optimal solution rather than a regional one. The final experiments successfully demonstrated a group of three robot cars that were simultaneously dispatched to each of their planned routes; when any car failed during the test, its path was immediately reprogrammed by the monitoring station and passed to the other cars to continue the task until each target point had been visited. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
A Cloud-Based Real-Time Mechanism to Protect End Hosts against Malware
Appl. Sci. 2019, 9(18), 3748; https://doi.org/10.3390/app9183748 - 08 Sep 2019
Cited by 1
Abstract
Nowadays, antivirus is one of the most popular tools used to protect computer systems. Diverse antivirus vendors are established to protect their customers against malware. However, antivirus is facing some critical problems, such as significant detection windows, vulnerability inside antivirus, and long scanning [...] Read more.
Nowadays, antivirus is one of the most popular tools used to protect computer systems. Diverse antivirus vendors are established to protect their customers against malware. However, antivirus is facing some critical problems, such as significant detection windows, vulnerability inside antivirus, and long scanning time. In this paper, we recommend a cloud-based real-time defense mechanism named Skywalker to allow users to safely utilize antivirus without the above problems. After Skywalker is installed in a host, the host does not need to install any antivirus. However, Skywalker guarantees that the host only executes programs that have been verified by a cloud-based scanner, such as VirusTotal. VirusTotal uses 56 antivirus engines to check whether a program is malware. Research shows that the more antivirus engines are used, the more accurate the result is. Because the above scan is performed right before the execution of every program, Skywalker provides 24/7 real-time protection to a system. Besides, Skywalker eliminates the need to spend a lot of time scanning all files in a host. Experimental results show that after a program has been executed once, it takes Skywalker, at most, 0.47091 s to start the program again. Meanwhile, VirusTotal provides a secure protection to client hosts. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
A Brunnstrom Stage Evaluation System with Fuzzy-Accelerometer
Appl. Sci. 2019, 9(18), 3718; https://doi.org/10.3390/app9183718 - 06 Sep 2019
Abstract
Advances in medical care has reduced the rate of mortality from strokes, but the incidence of stroke has remained stable while the incidence of ministrokes has increased. Most stroke victims require long-term care, imposing a heavy financial and emotional burden on families while [...] Read more.
Advances in medical care has reduced the rate of mortality from strokes, but the incidence of stroke has remained stable while the incidence of ministrokes has increased. Most stroke victims require long-term care, imposing a heavy financial and emotional burden on families while incurring a heavy cost to society. Thus, strokes are a key issue in the context of health care in Taiwan. This paper proposes using VBA (Visual Basic for Applications) to build a system for assessing Brunnstrom stages based on the observation of several obvious rehabilitation features The system calculates features for accelerometer readings, which are then used as input parameters for a fuzzy algorithm to obtain the Brunnstrom action level. Experimental results show the proposed approach effectively assesses Brunnstrom level, and that the approach can be used to assist physical therapists in performing longitudinal assessments of stroke victim progress, thus improving evaluation efficiency. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Investigation of a Promoted You Only Look Once Algorithm and Its Application in Traffic Flow Monitoring
Appl. Sci. 2019, 9(17), 3619; https://doi.org/10.3390/app9173619 - 03 Sep 2019
Cited by 7
Abstract
We propose a high-performance algorithm while using a promoted and modified form of the You Only Look Once (YOLO) model, which is based on the TensorFlow framework, to enhance the real-time monitoring of traffic-flow problems by an intelligent transportation system. Real-time detection and [...] Read more.
We propose a high-performance algorithm while using a promoted and modified form of the You Only Look Once (YOLO) model, which is based on the TensorFlow framework, to enhance the real-time monitoring of traffic-flow problems by an intelligent transportation system. Real-time detection and traffic-flow statistics were realized by adjusting the network structure, optimizing the loss function, and introducing weight regularization. This model, which we call YOLO-UA, was initialized based on the weight of a YOLO model pre-trained while using the VOC2007 data set. The UA-CAR data set with complex weather conditions was used for training, and better model parameters were selected through tests and subsequent adjustments. The experimental results showed that, for different weather scenarios, the accuracy of the YOLO-UA was ~22% greater than that of the YOLO model before optimization, and the recall rate increased by about 21%. On both cloudy and sunny days, the accuracy, precision, and recall rate of the YOLO-UA model were more than 94% above the floating rate, which suggested that the precision and recall rate achieved a good balance. When used for video testing, the YOLO-UA model yielded traffic statistics with an accuracy of up to 100%; the time to count the vehicles in each frame was less than 30 ms and it was highly robust in response to changes in scenario and weather. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Application of Internet of Things in a Kitchen Fire Prevention System
Appl. Sci. 2019, 9(17), 3520; https://doi.org/10.3390/app9173520 - 27 Aug 2019
Cited by 2
Abstract
When using a gas stove to cook, the food or oil in the pot or pan may catch fire because of an excessively high temperature. In addition, people may be uncertain as to whether they have turned off the gas stove before leaving [...] Read more.
When using a gas stove to cook, the food or oil in the pot or pan may catch fire because of an excessively high temperature. In addition, people may be uncertain as to whether they have turned off the gas stove before leaving home and therefore feel compelled to return home to check. To solve these problems, this study has developed a smart kitchen fire prevention system that possesses the following devices and functions. (1) Sensors are installed above the stove top. When they detect flames, high temperature, or a gas leak, they immediately activate the gas shutoff device to turn off the gas supply. (2) The alarm produces a loud sound and flashes to warn the residents. (3) The Line reporting system sends Line messages to notify the residents and the community management center, and the main entrance door is automatically unlocked to allow relevant personnel to enter the house to deal with the accident. (4) An Internet protocol camera is installed in the kitchen to enable the residents to monitor the gas stove on their mobile phones. If they find the gas stove is still turned on, they can activate the gas shutoff device to shut off the gas supply from their phones. The system developed in this study can effectively reduce the loss that results from a kitchen fire. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
The Usability Testing of VR Interface for Tourism Apps
Appl. Sci. 2019, 9(16), 3215; https://doi.org/10.3390/app9163215 - 07 Aug 2019
Cited by 5
Abstract
Virtual reality (VR) is considered to be an emerging technology. This study compared the usability differences of VR travel software, such as Google Street View, VeeR VR, and Sites in VR, for mobile phones. In the pilot study, three post-graduate students and one [...] Read more.
Virtual reality (VR) is considered to be an emerging technology. This study compared the usability differences of VR travel software, such as Google Street View, VeeR VR, and Sites in VR, for mobile phones. In the pilot study, three post-graduate students and one interface expert were invited to participate in the designed experimental tasks to provide opinions on the first draft of the questionnaire. Next, thirty college students were recruited to join the formal experiment. After operating the VR interface, they were asked to fill out the questionnaire, and a semi-structured interview was conducted. The results are described as follows: (1) Intuitive operation is required to allow people to select objects smoothly; (2) the chosen object requires a feedback mode to inform the user that the object has been selected; (3) the speed of the feedback mode should be adjustable to fulfil the needs of most people; (4) the contrast of icon color needs to be improved to ensure the most efficient verification of the operations; and (5) a search button or reminder function can be added to aid first-time users. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Optimal Intrinsic Mode Function Based Detection of Motor Bearing Damages
Appl. Sci. 2019, 9(13), 2587; https://doi.org/10.3390/app9132587 - 26 Jun 2019
Cited by 2
Abstract
This paper proposes a model which uses the greedy algorithm to select the optimal intrinsic mode functions (IMFs) of the empirical mode decomposition (EMD), namely the greedy empirical mode decomposition (GEMD) model. The optimal IMFs can more sufficiently represent the characteristics of damage [...] Read more.
This paper proposes a model which uses the greedy algorithm to select the optimal intrinsic mode functions (IMFs) of the empirical mode decomposition (EMD), namely the greedy empirical mode decomposition (GEMD) model. The optimal IMFs can more sufficiently represent the characteristics of damage bearings since the proposed GEMD model effectively selects some IMFs not affected by noise. To validate the superiority of the proposed GEMD model, various damage types of motor bearings were shaped by electrical discharge machining (EDM) in this experiment. The measured motor current signals of various types were decomposed to IMFs by using EMD. Then the optimal IMFs can be obtained by using the proposed GEMD model. The results show that the Hilbert–Huang transform (HHT) spectrums when using the optimal IMFs become easier in the detection system than when using all IMFs. Simultaneously, the detection accuracy of motor bearing damages is increased by using the features extracted from the lower complexity HHT spectrum. The average detection accuracy can be also improved from 69.5% to 74.6% by using the features extracted from the GEMD-HHT spectrum even in a noise interference 10dB Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Development of UAV Tracing and Coordinate Detection Method Using a Dual-Axis Rotary Platform for an Anti-UAV System
Appl. Sci. 2019, 9(13), 2583; https://doi.org/10.3390/app9132583 - 26 Jun 2019
Cited by 3
Abstract
The rapid development of unmanned aerial vehicles (UAVs) has led to many security problems. In order to prevent UAVs from invading restricted areas or famous buildings, an anti-UAV defense system (AUDS) has been developed and become a research topic of interest. Topics under [...] Read more.
The rapid development of unmanned aerial vehicles (UAVs) has led to many security problems. In order to prevent UAVs from invading restricted areas or famous buildings, an anti-UAV defense system (AUDS) has been developed and become a research topic of interest. Topics under research in relation to this include electromagnetic interference guns for UAVs, high-energy laser guns, US military net warheads, and AUDSs with net guns. However, these AUDSs use either manual aiming or expensive radar to trace drones. This research proposes a dual-axis mechanism with UAVs automatic tracing. The tracing platform uses visual image processing technology to trace and lock the dynamic displacement of a drone. When a target UAV is locked, the system uses a nine-axis attitude meter and laser rangers to measure its flight altitude and calculates its longitude and latitude coordinates through sphere coordinates to provide drone monitoring for further defense or attack missions. Tracing tests of UAV flights in the air were carried out using a DJI MAVIC UAV at a height of 30 m to 100 m. It was set up for drone image capture and visual identification for tracing under various weather conditions by a thermal imaging camera and a full-color camera, respectively. When there was no cloud during the daytime, the images acquired by the thermal imaging camera and full-color camera provide a high-quality image identification result. However, under dark weather, black clouds will emit radiant energy and seriously affect the capture of images by a thermal imaging camera. When there is no cloud at night, the thermal imaging camera performs well in drone image capture. When the drone is traced and locked, the system can effectively obtain the flight altitude and longitude and latitude coordinate values. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Competition Among the World’s Main Technological Powers to Develop IPs: Cross-National Longitudinal Patentography Over a 9-Year Time Span
Appl. Sci. 2019, 9(12), 2432; https://doi.org/10.3390/app9122432 - 14 Jun 2019
Abstract
Relatively few studies have focused on systematically mining the patent databases of different countries. This study mines the databases of the main ‘technological powers’ using several methods. By using descriptive statistical methods, the study yields key insights regarding patenting activities affecting the succession [...] Read more.
Relatively few studies have focused on systematically mining the patent databases of different countries. This study mines the databases of the main ‘technological powers’ using several methods. By using descriptive statistical methods, the study yields key insights regarding patenting activities affecting the succession and ‘crowding out’ of technologies, the ‘hottest technologies’ and the patent application strategies in these countries. The spectrums of technological strength in these countries are further analysed with Principal Component Analysis (PCA), as two principal components are sufficient to resolve over 92% of the total variance. The US, EU and China are the economies that all technological powers may regard as important; similarities in the application strategies used in these countries are thus further investigated. Another extensive analysis utilising K-means clustering is also performed. Except for the optimal number for patent clustering, surprisingly, the top 10 ‘most important technologies’ are identical to the top 10 hottest ones that were previously identified. The knowledge and insights gained from this study are valuable not only for technological development policy makers, but also for business decision makers seeking suitable markets and areas to enter and invest in. Some data visualization and analysis methods are applied for the first time to this knowledge discovery problem. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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Open AccessArticle
Development of an Assistant System of Clean Intermittent Catheterization for Neurogenic Bladder Dysfunction Patients
Appl. Sci. 2019, 9(7), 1433; https://doi.org/10.3390/app9071433 - 05 Apr 2019
Abstract
Clean intermittent catheterization (CIC) is one of the methods currently used to prevent overdistention of the bladder in patients with neurogenic bladder dysfunction (NBD). It is also helpful in preventing urinary tract infection and retaining the function of the bladder. Voiding diary and [...] Read more.
Clean intermittent catheterization (CIC) is one of the methods currently used to prevent overdistention of the bladder in patients with neurogenic bladder dysfunction (NBD). It is also helpful in preventing urinary tract infection and retaining the function of the bladder. Voiding diary and social behavior are necessary for the patients to maintain their physical and mental health, nevertheless there are currently no good assistant systems to help them achieve these goals. In this study, we propose a CIC assistant system with the functions of recording and tracking the voided volume and accessible lavatory. The aim of this study is to assess the effects from the 12 patients who joined the proposed system. Information collected from participants included their demographics, past medicals, injury characteristics, current and past bladder managements, and any NBD related complications. The results indicate that most patients felt relieved that they could know the voided volume and track their history easily. Moreover, the accessible lavatory function of the proposed system could reduce time consumption by 43.1% in finding the suitable lavatory, thus the desire and willingness of patients to travel increased from 25% to 75% after using the system. The proposed system could help doctors with clinical diagnoses, and help patients to understand more about the history of their catheterization volume and time period. This study provided essential information and design for future investigation. Full article
(This article belongs to the Special Issue Intelligent System Innovation)
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