In this paper we present a hybrid model for image compression based on segmentation and total variation regularization. The main motivation behind our approach is to offer decode image with immediate access to objects/features of interest. We are targeting high quality decoded image in order to be useful on smart devices, for analysis purpose, as well as for multimedia content-based description standards. The image is approximated as a set of uniform regions: The technique will assign well-defined members to homogenous regions in order to achieve image segmentation. The Adaptive fuzzy c-means (AFcM) is a guide to cluster image data. A second stage coding is applied using entropy coding to remove the whole image entropy redundancy. In the decompression phase, the reverse process is applied in which the decoded image suffers from missing details due to the coarse segmentation. For this reason, we suggest the application of total variation (TV) regularization, such as the Rudin-Osher-Fatemi (ROF) model, to enhance the quality of the coded image. Our experimental results had shown that ROF may increase the PSNR and hence offer better quality for a set of benchmark grayscale images.
{"title":"Image Compression Approach using Segmentation and Total Variation Regularization","authors":"Ahmad Shahin, W. Moudani, Fadi Chakik","doi":"10.46300/9108.2021.15.6","DOIUrl":"https://doi.org/10.46300/9108.2021.15.6","url":null,"abstract":"In this paper we present a hybrid model for image compression based on segmentation and total variation regularization. The main motivation behind our approach is to offer decode image with immediate access to objects/features of interest. We are targeting high quality decoded image in order to be useful on smart devices, for analysis purpose, as well as for multimedia content-based description standards. The image is approximated as a set of uniform regions: The technique will assign well-defined members to homogenous regions in order to achieve image segmentation. The Adaptive fuzzy c-means (AFcM) is a guide to cluster image data. A second stage coding is applied using entropy coding to remove the whole image entropy redundancy. In the decompression phase, the reverse process is applied in which the decoded image suffers from missing details due to the coarse segmentation. For this reason, we suggest the application of total variation (TV) regularization, such as the Rudin-Osher-Fatemi (ROF) model, to enhance the quality of the coded image. Our experimental results had shown that ROF may increase the PSNR and hence offer better quality for a set of benchmark grayscale images.","PeriodicalId":89779,"journal":{"name":"International journal of computers in healthcare","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88068067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, a parallel algorithm to solve the problem of gravitational interaction between N bodies is considered. The peak performance of an 8 × 8 mesh-connected multiprocessor system while implementing the algorithm is evaluated. Further, the mappings of parallel threads of the algorithm onto the multiprocessor are studied based on two criteria for minimizing the communication delay. The corresponding real application performance of the multiprocessor is estimated.
{"title":"Evaluating the Mesh-connected Multiprocessor Running a Parallel Algorithm Representing the Gravitational Interaction Between N Bodies","authors":"Jamil S. Al-Azzeh","doi":"10.46300/9108.2021.15.5","DOIUrl":"https://doi.org/10.46300/9108.2021.15.5","url":null,"abstract":"In this study, a parallel algorithm to solve the problem of gravitational interaction between N bodies is considered. The peak performance of an 8 × 8 mesh-connected multiprocessor system while implementing the algorithm is evaluated. Further, the mappings of parallel threads of the algorithm onto the multiprocessor are studied based on two criteria for minimizing the communication delay. The corresponding real application performance of the multiprocessor is estimated.","PeriodicalId":89779,"journal":{"name":"International journal of computers in healthcare","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87250543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper focuses on identification of helicopter by exploiting the concept of micro-Doppler effect which is prominent in targets containing rotating, oscillating or vibrating parts in it. Radar received signal is analyzed by Short Time Fourier Transform (STFT) to extract the micro Doppler (mD) signature. From the mD signature, the helicopter parameters are estimated. In a multiple helicopters scenario, estimated parameters will be a mixure, pertaining to the multiple helicopters. These parameters are classified further using a machine learning algorithm, namely k-means clustering to classify the helicopters. Simulated results for the synthesized received signal shows the betted estimates of the helicopter parameter through mD signature. Dataset containing basic parameters like number of blades, blade length and rotational rates of the UN-1N helicopter (rotor with 2 blades), the SH-3H helicopter (rotor with 5 blades) and the CH-54B helicopter (rotor with 6 blades) are considered for the classification. Results show a good classification. When analysed with different SNR level in dataset, at lower SNR, observed some ovelapping in the classification.
{"title":"Micro-Doppler Signature Based Helicopter Identification and Classification Through Machine Learning","authors":"S. Iswariya, J. Valarmathi","doi":"10.46300/9108.2021.15.4","DOIUrl":"https://doi.org/10.46300/9108.2021.15.4","url":null,"abstract":"This paper focuses on identification of helicopter by exploiting the concept of micro-Doppler effect which is prominent in targets containing rotating, oscillating or vibrating parts in it. Radar received signal is analyzed by Short Time Fourier Transform (STFT) to extract the micro Doppler (mD) signature. From the mD signature, the helicopter parameters are estimated. In a multiple helicopters scenario, estimated parameters will be a mixure, pertaining to the multiple helicopters. These parameters are classified further using a machine learning algorithm, namely k-means clustering to classify the helicopters. Simulated results for the synthesized received signal shows the betted estimates of the helicopter parameter through mD signature. Dataset containing basic parameters like number of blades, blade length and rotational rates of the UN-1N helicopter (rotor with 2 blades), the SH-3H helicopter (rotor with 5 blades) and the CH-54B helicopter (rotor with 6 blades) are considered for the classification. Results show a good classification. When analysed with different SNR level in dataset, at lower SNR, observed some ovelapping in the classification.","PeriodicalId":89779,"journal":{"name":"International journal of computers in healthcare","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82605408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a novel control algorithm for variable speed wind generators (VSWG), designed to provide support to grid frequency regulation. The proposed control algorithm ensures that VSWG ‘’truly’’ emulates response of a conventional generating unit with non-reheat steam turbine (GUNRST) in the first several seconds after active power unbalance. A systematic method of analysis and synthesis of the new control algorithm is described in detail.
{"title":"Design of Model Reference Controller of Variable Speed Wind Generators for Frequency Regulation Contribution","authors":"E. Becirovic, J. Osmic, M. Kusljugic, N. Peric","doi":"10.46300/9108.2021.15.3","DOIUrl":"https://doi.org/10.46300/9108.2021.15.3","url":null,"abstract":"This paper presents a novel control algorithm for variable speed wind generators (VSWG), designed to provide support to grid frequency regulation. The proposed control algorithm ensures that VSWG ‘’truly’’ emulates response of a conventional generating unit with non-reheat steam turbine (GUNRST) in the first several seconds after active power unbalance. A systematic method of analysis and synthesis of the new control algorithm is described in detail.","PeriodicalId":89779,"journal":{"name":"International journal of computers in healthcare","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87038415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-24DOI: 10.46300/9108.2020.14.13
H. Iqbal, A. B. Nassif, I. Shahin
Breast Cancer (BC) is amongst the most common and leading causes of deaths in women throughout the world. Recently, classification and data analysis tools are being widely used in the medical field for diagnosis, prognosis and decision making to help lower down the risks of people dying or suffering from diseases. Advanced machine learning methods have proven to give hope for patients as this has helped the doctors in early detection of diseases like Breast Cancer that can be fatal, in support with providing accurate outcomes. However, the results highly depend on the techniques used for feature selection and classification which will produce a strong machine learning model. In this paper, a performance comparison is conducted using four classifiers which are Multilayer Perceptron (MLP), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) and Random Forest on the Wisconsin Breast Cancer dataset to spot the most effective predictors. The main goal is to apply best machine learning classification methods to predict the Breast Cancer as benign or malignant using terms such as accuracy, f-measure, precision and recall. Experimental results show that Random forest is proven to achieve the highest accuracy of 99.26% on this dataset and features, while SVM and KNN show 97.78% and 97.04% accuracy respectively. MLP shows the least accuracy of 94.07%. All the experiments are conducted using RStudio as the data mining tool platform.
{"title":"Classifications of Breast Cancer Diagnosis using Machine Learning","authors":"H. Iqbal, A. B. Nassif, I. Shahin","doi":"10.46300/9108.2020.14.13","DOIUrl":"https://doi.org/10.46300/9108.2020.14.13","url":null,"abstract":"Breast Cancer (BC) is amongst the most common and leading causes of deaths in women throughout the world. Recently, classification and data analysis tools are being widely used in the medical field for diagnosis, prognosis and decision making to help lower down the risks of people dying or suffering from diseases. Advanced machine learning methods have proven to give hope for patients as this has helped the doctors in early detection of diseases like Breast Cancer that can be fatal, in support with providing accurate outcomes. However, the results highly depend on the techniques used for feature selection and classification which will produce a strong machine learning model. In this paper, a performance comparison is conducted using four classifiers which are Multilayer Perceptron (MLP), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) and Random Forest on the Wisconsin Breast Cancer dataset to spot the most effective predictors. The main goal is to apply best machine learning classification methods to predict the Breast Cancer as benign or malignant using terms such as accuracy, f-measure, precision and recall. Experimental results show that Random forest is proven to achieve the highest accuracy of 99.26% on this dataset and features, while SVM and KNN show 97.78% and 97.04% accuracy respectively. MLP shows the least accuracy of 94.07%. All the experiments are conducted using RStudio as the data mining tool platform.","PeriodicalId":89779,"journal":{"name":"International journal of computers in healthcare","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78059434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-24DOI: 10.46300/9108.2020.14.14
Abdallah Abushawish, Mohammed Hamadeh, A. B. Nassif
In nowadays industry, most processes are controlled and automated. Interestingly, PID controllers are major contributors to the control process since they were invented and become quite practical. PID controllers are vital component in the industry and enhancing the component will show an echo effect in today’s technology. Their drawbacks are tuning them for an application, and this provides inspiration to develop advanced optimization methods in tuning PID controllers. This survey aims to review metaheuristic optimization methods of PID controller tuning that were published between 2010 and 2018. The paper was constructed based on 22 research papers and found that 8 metaheuristics optimization methods were used with PID tuning on 5 industrial applications. The papers also extensively provided answers to 3 research questions and assessing the quality of the papers based on 6 parameters.
{"title":"PID Controller Gains Tuning Using Metaheuristic Optimization Methods: A survey","authors":"Abdallah Abushawish, Mohammed Hamadeh, A. B. Nassif","doi":"10.46300/9108.2020.14.14","DOIUrl":"https://doi.org/10.46300/9108.2020.14.14","url":null,"abstract":"In nowadays industry, most processes are controlled and automated. Interestingly, PID controllers are major contributors to the control process since they were invented and become quite practical. PID controllers are vital component in the industry and enhancing the component will show an echo effect in today’s technology. Their drawbacks are tuning them for an application, and this provides inspiration to develop advanced optimization methods in tuning PID controllers. This survey aims to review metaheuristic optimization methods of PID controller tuning that were published between 2010 and 2018. The paper was constructed based on 22 research papers and found that 8 metaheuristics optimization methods were used with PID tuning on 5 industrial applications. The papers also extensively provided answers to 3 research questions and assessing the quality of the papers based on 6 parameters.","PeriodicalId":89779,"journal":{"name":"International journal of computers in healthcare","volume":"67 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80253380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-22DOI: 10.46300/9108.2020.14.12
J. Borcsok, M. Schwarz, Waldemar Muller, M. Abdelawwad
Using electronic systems to control complex applications has found its way into nearly all technical and industrial areas during the last four decades. Today, in addition to system size, reduced system costs, optimized energy consumption and high reliability or safety, the aspects of functional safety are increasingly in the focus of many applications. Especially concerning safe embedded cyber-physical systems, which is favored by increasing integration of components, these aspects are of central importance. This article describes a consistently safety 1oo2 SoC architecture model (a miniaturized safety system on a chip) based on a modified software comparator architecture. The design and realization of the safety SoC, according to IEC 61508, are also presented.
{"title":"Approach for a Safe-SoC for Cyber-physical Application according to IEC 61508","authors":"J. Borcsok, M. Schwarz, Waldemar Muller, M. Abdelawwad","doi":"10.46300/9108.2020.14.12","DOIUrl":"https://doi.org/10.46300/9108.2020.14.12","url":null,"abstract":"Using electronic systems to control complex applications has found its way into nearly all technical and industrial areas during the last four decades. Today, in addition to system size, reduced system costs, optimized energy consumption and high reliability or safety, the aspects of functional safety are increasingly in the focus of many applications. Especially concerning safe embedded cyber-physical systems, which is favored by increasing integration of components, these aspects are of central importance. This article describes a consistently safety 1oo2 SoC architecture model (a miniaturized safety system on a chip) based on a modified software comparator architecture. The design and realization of the safety SoC, according to IEC 61508, are also presented.","PeriodicalId":89779,"journal":{"name":"International journal of computers in healthcare","volume":"240 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82885366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-22DOI: 10.46300/9108.2020.14.10
M. Abdelawwad, M. Schwarz, Malte Drabesch, J. Borcsok
The importance of human-robot collaboration systems in industrial applications has increased due to the orientation towards the smart factory approach. To ensure the safety of such systems, collision avoidance techniques based on millimeter-wave radar sensors are used. Safe communication between the robot and the radar sensor is ensured by using the safety system on a chip based on 1oo2D architecture. The design and prototyping of a multi-channel communication FPGA-based development board is presented. Furthermore, the FPGA implementation of SoC with multiple Ethernet MAC interfaces based on various soft cores is demonstrated.
{"title":"soc-approach for Safety-oriented Multi-channel Communication in Industrial Application of Human-robot-collaboration (HRC)","authors":"M. Abdelawwad, M. Schwarz, Malte Drabesch, J. Borcsok","doi":"10.46300/9108.2020.14.10","DOIUrl":"https://doi.org/10.46300/9108.2020.14.10","url":null,"abstract":"The importance of human-robot collaboration systems in industrial applications has increased due to the orientation towards the smart factory approach. To ensure the safety of such systems, collision avoidance techniques based on millimeter-wave radar sensors are used. Safe communication between the robot and the radar sensor is ensured by using the safety system on a chip based on 1oo2D architecture. The design and prototyping of a multi-channel communication FPGA-based development board is presented. Furthermore, the FPGA implementation of SoC with multiple Ethernet MAC interfaces based on various soft cores is demonstrated.","PeriodicalId":89779,"journal":{"name":"International journal of computers in healthcare","volume":"41 7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89244741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-22DOI: 10.46300/9108.2020.14.11
R. Thum, J. Borcsok
Autonomous guided vehicles have great advantages over rigidly track-guided conveyor technology, as they can react flexibly to changes in the application area. Temporary obstacles can be easily avoided. The vehicles can circumnavigate bottlenecks and areas at risk of congestion switch to alternative routes. To avoid accidents, safety-relevant position detection is necessary in many areas. The current speed is derived from this driven trajectory and this is safely reduced in the working areas. Minimum distances can also be safely maintained. Therefore it is necessary to permanently control the measured position with regard to disturbance variables and to monitor the reliability of the position detection in real time.
{"title":"Reliability Monitoring of Laser Scanner Based Navigation","authors":"R. Thum, J. Borcsok","doi":"10.46300/9108.2020.14.11","DOIUrl":"https://doi.org/10.46300/9108.2020.14.11","url":null,"abstract":"Autonomous guided vehicles have great advantages over rigidly track-guided conveyor technology, as they can react flexibly to changes in the application area. Temporary obstacles can be easily avoided. The vehicles can circumnavigate bottlenecks and areas at risk of congestion switch to alternative routes. To avoid accidents, safety-relevant position detection is necessary in many areas. The current speed is derived from this driven trajectory and this is safely reduced in the working areas. Minimum distances can also be safely maintained. Therefore it is necessary to permanently control the measured position with regard to disturbance variables and to monitor the reliability of the position detection in real time.","PeriodicalId":89779,"journal":{"name":"International journal of computers in healthcare","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80817237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A strong and insightful interpretation of scientific knowledge and practice must take into consideration how human cognitive skills and constraints enable as well restrict the scientific enterprise's activities and products. While existing deep learning systems are outstanding in functions such as object classification, language processing, and gameplay but few can create or transform a complex system like a Frame Pyramid. Assume that what these systems lack is a "Cognitive Inductive Prejudice": an ability to justify inter-object relationships and make decisions about an organized description of the incident. In order to assess this premise, this paper concentrated on a work involving stapling together stacks of frames to balance a castle and quantify how well hominids are doing. Then for analyzing contraption capability, our work introduce the Significant Stimulus Learning Tool that utilizes object-and interactioncentered scene and policy representations, these apply to the task. Our results shows that these structural portrayals enable the tool to perform both hominids and contraption for more naive methods, indicating that cognitive inductive effect is a significant element in solving structured reasoning issues and building more intelligent also flexible for machines.
{"title":"Cognitive Inductive Prejudice For Corporal Edifice In Hominids And Contraption","authors":"Chandra Bhim Bhan Singh","doi":"10.46300/9108.2020.14.8","DOIUrl":"https://doi.org/10.46300/9108.2020.14.8","url":null,"abstract":"A strong and insightful interpretation of scientific knowledge and practice must take into consideration how human cognitive skills and constraints enable as well restrict the scientific enterprise's activities and products. While existing deep learning systems are outstanding in functions such as object classification, language processing, and gameplay but few can create or transform a complex system like a Frame Pyramid. Assume that what these systems lack is a \"Cognitive Inductive Prejudice\": an ability to justify inter-object relationships and make decisions about an organized description of the incident. In order to assess this premise, this paper concentrated on a work involving stapling together stacks of frames to balance a castle and quantify how well hominids are doing. Then for analyzing contraption capability, our work introduce the Significant Stimulus Learning Tool that utilizes object-and interactioncentered scene and policy representations, these apply to the task. Our results shows that these structural portrayals enable the tool to perform both hominids and contraption for more naive methods, indicating that cognitive inductive effect is a significant element in solving structured reasoning issues and building more intelligent also flexible for machines.","PeriodicalId":89779,"journal":{"name":"International journal of computers in healthcare","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76519559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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