Pub Date : 2020-05-30DOI: 10.5121/csit.2020.100514
T. Yan, In-ho Ra, Na Song, Yu Youhao, Zhicheng Wu, Zhongyu Shi
After analyzing the research status and existing problems of multi-view video coding and bit rate control, we found that in addition to achieving higher coding efficiency, scalability characteristics, and quality consistency, reasonable bit rate control is urgent What needs further research. The paper proposes a multi-view video coding rate control algorithm based on the quadratic rate distortion (RD) model is presented. There are already many rate control algorithms. However, the testing work is very important, and different sequences need to be tested to effectively judge the effectiveness of the algorithm. Experimental simulation results show that the algorithm can effectively control the bit rate of multi-view video coding, while maintaining efficient coding efficiency, compared with the current MVC using JVT with fixed quantization parameters.
{"title":"Advanced Rate Control Technologies for MVC","authors":"T. Yan, In-ho Ra, Na Song, Yu Youhao, Zhicheng Wu, Zhongyu Shi","doi":"10.5121/csit.2020.100514","DOIUrl":"https://doi.org/10.5121/csit.2020.100514","url":null,"abstract":"After analyzing the research status and existing problems of multi-view video coding and bit rate control, we found that in addition to achieving higher coding efficiency, scalability characteristics, and quality consistency, reasonable bit rate control is urgent What needs further research. The paper proposes a multi-view video coding rate control algorithm based on the quadratic rate distortion (RD) model is presented. There are already many rate control algorithms. However, the testing work is very important, and different sequences need to be tested to effectively judge the effectiveness of the algorithm. Experimental simulation results show that the algorithm can effectively control the bit rate of multi-view video coding, while maintaining efficient coding efficiency, compared with the current MVC using JVT with fixed quantization parameters.","PeriodicalId":201467,"journal":{"name":"9th International Conference on Information Technology Convergence and Services (ITCSE 2020)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121265299","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 : 2020-05-30DOI: 10.5121/csit.2020.100522
R. Kanth, Tuomas Korpi, J. Heikkonen
In this article, a Smart Ping Pong Paddle has been introduced as an example of the use of sensor technology in sports. We have devised an accelerometer and a gyroscope sensor for the analyzing purpose and have gathered motion data of the game object to make a real-time 3D replica of the paddle to get an actual orientation of it. Technical details and principles of how to get the digital motion processing data from sensor to microcontroller and again transfer that wirelessly to a 3D modeling software are examined. Technical details are applied in practice, and the working demo of Smart Ping Pong paddle is built. Also, a couple of examples of other similar applications in the realm of object orientation sensing are overviewed.
{"title":"Use of an IoT Technology to Analyse the Inertial Measurement of Smart Ping-pong Paddle","authors":"R. Kanth, Tuomas Korpi, J. Heikkonen","doi":"10.5121/csit.2020.100522","DOIUrl":"https://doi.org/10.5121/csit.2020.100522","url":null,"abstract":"In this article, a Smart Ping Pong Paddle has been introduced as an example of the use of sensor technology in sports. We have devised an accelerometer and a gyroscope sensor for the analyzing purpose and have gathered motion data of the game object to make a real-time 3D replica of the paddle to get an actual orientation of it. Technical details and principles of how to get the digital motion processing data from sensor to microcontroller and again transfer that wirelessly to a 3D modeling software are examined. Technical details are applied in practice, and the working demo of Smart Ping Pong paddle is built. Also, a couple of examples of other similar applications in the realm of object orientation sensing are overviewed.","PeriodicalId":201467,"journal":{"name":"9th International Conference on Information Technology Convergence and Services (ITCSE 2020)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122797565","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 : 2020-05-30DOI: 10.5121/csit.2020.100524
Ngan-Khanh Chau, T. Ma
Preserving and promoting the intangible cultural heritage is one of the essential problems of interest. In addition, the cultural heritage of the world has been accumulated and early respected during the development of human society. For preservation of traditional dances, this paper is one of the significant processed steps in our research sequence to build an intelligent storage repository that would help to manage the large-scale heterogeneous digital contents efficiently, particularly in dance domain. We concentrated on classifying the fundamental movements of Vietnamese Traditional Dances (VTDs), which are the foundations of automatically detecting the motions of the dancer's body parts. Moreover, we also propose a framework to classify basic movements through coupling a sequential aggregation of the DeepCNN architectures (to extract the features) and Support Vector Machine (to classify the movements). In this study, we detect and extract automatically the primary movements of VTDs, we then store the extracted concepts into an ontology that serves for reasoning, queryanswering, and searching dance videos.
{"title":"An Automatic Detection of Fundamental Postures in Vietnamese Traditional Dances","authors":"Ngan-Khanh Chau, T. Ma","doi":"10.5121/csit.2020.100524","DOIUrl":"https://doi.org/10.5121/csit.2020.100524","url":null,"abstract":"Preserving and promoting the intangible cultural heritage is one of the essential problems of interest. In addition, the cultural heritage of the world has been accumulated and early respected during the development of human society. For preservation of traditional dances, this paper is one of the significant processed steps in our research sequence to build an intelligent storage repository that would help to manage the large-scale heterogeneous digital contents efficiently, particularly in dance domain. We concentrated on classifying the fundamental movements of Vietnamese Traditional Dances (VTDs), which are the foundations of automatically detecting the motions of the dancer's body parts. Moreover, we also propose a framework to classify basic movements through coupling a sequential aggregation of the DeepCNN architectures (to extract the features) and Support Vector Machine (to classify the movements). In this study, we detect and extract automatically the primary movements of VTDs, we then store the extracted concepts into an ontology that serves for reasoning, queryanswering, and searching dance videos.","PeriodicalId":201467,"journal":{"name":"9th International Conference on Information Technology Convergence and Services (ITCSE 2020)","volume":"398 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123372411","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}
{"title":"Industrial Duct Fan Maintenance Predictive Approach Based on Random Forest","authors":"M. Maashi, Nujood Alwhibi, Fatima Alamr, Rehab Alzahrani, Alanoud Alhamid, Nourah Altawallah","doi":"10.5121/csit.2020.100516","DOIUrl":"https://doi.org/10.5121/csit.2020.100516","url":null,"abstract":"","PeriodicalId":201467,"journal":{"name":"9th International Conference on Information Technology Convergence and Services (ITCSE 2020)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134272492","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 : 2020-05-30DOI: 10.5121/csit.2020.100520
Mustapha Hedabou, Ali Azougaghe, A. Bentajer
On the past decade, Trusted Platform Modules (TPM) have become a valuable tool for providing a high level of trust on locally executing software. Indeed, in addition to its availability on most commodity computers, TPM are totally free of cost unlike other available Hardware-Based devices while they o er the same level of security. Enhancing trust in SaaS services regarding the security and the privacy of the hosted SaaS application services can turn out to be a pertinent application scope of TMP. In this paper we present a design for a trusted SaaS model that gives cloud users more con dence into SaaS services by leveraging TPM functionalities combined with a trusted source code certifying authority facility. In our design, the cloud computing provider hosting the SaaS services acts as a root of trust by providing nal cloud users insurance on the integrity of the SaaS application service running on its platform. A new mechanism of multisignature is developed for computing a join signature of SaaS service software by the trusted authority and TPM. A prototype implementation of the proposed design shows that the integrity of SaaS application service before and after it was launched on a cloud provider platform is guaranteed at low cost.
{"title":"TPM Based Design for Enhanced Trust in SaaS Services","authors":"Mustapha Hedabou, Ali Azougaghe, A. Bentajer","doi":"10.5121/csit.2020.100520","DOIUrl":"https://doi.org/10.5121/csit.2020.100520","url":null,"abstract":"On the past decade, Trusted Platform Modules (TPM) have become a valuable tool for providing a high level of trust on locally executing software. Indeed, in addition to its availability on most commodity computers, TPM are totally free of cost unlike other available Hardware-Based devices while they o er the same level of security. Enhancing trust in SaaS services regarding the security and the privacy of the hosted SaaS application services can turn out to be a pertinent application scope of TMP. In this paper we present a design for a trusted SaaS model that gives cloud users more con dence into SaaS services by leveraging TPM functionalities combined with a trusted source code certifying authority facility. In our design, the cloud computing provider hosting the SaaS services acts as a root of trust by providing nal cloud users insurance on the integrity of the SaaS application service running on its platform. A new mechanism of multisignature is developed for computing a join signature of SaaS service software by the trusted authority and TPM. A prototype implementation of the proposed design shows that the integrity of SaaS application service before and after it was launched on a cloud provider platform is guaranteed at low cost.","PeriodicalId":201467,"journal":{"name":"9th International Conference on Information Technology Convergence and Services (ITCSE 2020)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128914753","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 : 2020-05-30DOI: 10.5121/csit.2020.100518
Ankit Kamboj, Nilesh U. Powar
Safety is of predominant value for employees who are working in an industrial and construction environment. Real time Object detection is an important technique to detect violations of safety compliance in an industrial setup. The negligence in wearing safety helmets could be hazardous to workers, hence the requirement of the automatic surveillance system to detect persons not wearing helmets is of utmost importance and this would reduce the labor-intensive work to monitor the violations. In this paper, we deployed an advanced Convolutional Neural Network (CNN) algorithm called Single Shot Multibox Detector (SSD) to monitor violations of safety helmets. Various image processing techniques are applied to all the video data collected from the industrial plant. The practical and novel safety detection framework is proposed in which the CNN first detects persons from the video data and in the second step it detects whether the person is wearing the safety helmet. Using the proposed model, the deep learning inference benchmarking is done with Dell Advanced Tower workstation. The comparative study of the proposed approach is analysed in terms of detection accuracy (average precision) which illustrates the effectiveness of the proposed framework.
{"title":"Safety Helmet Detection in Industrial Environment using Deep Learning","authors":"Ankit Kamboj, Nilesh U. Powar","doi":"10.5121/csit.2020.100518","DOIUrl":"https://doi.org/10.5121/csit.2020.100518","url":null,"abstract":"Safety is of predominant value for employees who are working in an industrial and construction environment. Real time Object detection is an important technique to detect violations of safety compliance in an industrial setup. The negligence in wearing safety helmets could be hazardous to workers, hence the requirement of the automatic surveillance system to detect persons not wearing helmets is of utmost importance and this would reduce the labor-intensive work to monitor the violations. In this paper, we deployed an advanced Convolutional Neural Network (CNN) algorithm called Single Shot Multibox Detector (SSD) to monitor violations of safety helmets. Various image processing techniques are applied to all the video data collected from the industrial plant. The practical and novel safety detection framework is proposed in which the CNN first detects persons from the video data and in the second step it detects whether the person is wearing the safety helmet. Using the proposed model, the deep learning inference benchmarking is done with Dell Advanced Tower workstation. The comparative study of the proposed approach is analysed in terms of detection accuracy (average precision) which illustrates the effectiveness of the proposed framework.","PeriodicalId":201467,"journal":{"name":"9th International Conference on Information Technology Convergence and Services (ITCSE 2020)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122546839","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 : 2020-05-30DOI: 10.5121/csit.2020.100502
Grace Kobusinge
Due to their renowned great information processing and dissemination power, Health information systems (HIS) can readily avail past patient medical information across the continuum of care in order to facilitate ongoing treatment. However, a number of existing HIS are designed as vertical silos with no interoperability onuses and therefore, cannot exchange patient information. At the same time, there is limited knowledge about the intricacies and factors that surround HIS’ interoperability implementations. This study therefore, employs an institutional lens perspective to investigate contextual factors influencing HIS’ interoperability designing. Through this perspective, seven contextual factors were arrived at institutional autonomism, intended system goals, existing health-information-systems, national HIS implementation guidelines, interoperability standards, policy and resources in terms of money and labour. A further study implication is the use of institutional lens in making sense of the institutions’ context of integration in order to discover salient factors that might influence health-information-systems’ interoperability designing.
{"title":"Contextual Factors Influencing the Design and Management of Health Information Systems’ Interoperability","authors":"Grace Kobusinge","doi":"10.5121/csit.2020.100502","DOIUrl":"https://doi.org/10.5121/csit.2020.100502","url":null,"abstract":"Due to their renowned great information processing and dissemination power, Health information systems (HIS) can readily avail past patient medical information across the continuum of care in order to facilitate ongoing treatment. However, a number of existing HIS are designed as vertical silos with no interoperability onuses and therefore, cannot exchange patient information. At the same time, there is limited knowledge about the intricacies and factors that surround HIS’ interoperability implementations. This study therefore, employs an institutional lens perspective to investigate contextual factors influencing HIS’ interoperability designing. Through this perspective, seven contextual factors were arrived at institutional autonomism, intended system goals, existing health-information-systems, national HIS implementation guidelines, interoperability standards, policy and resources in terms of money and labour. A further study implication is the use of institutional lens in making sense of the institutions’ context of integration in order to discover salient factors that might influence health-information-systems’ interoperability designing.","PeriodicalId":201467,"journal":{"name":"9th International Conference on Information Technology Convergence and Services (ITCSE 2020)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128356673","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 : 2020-05-30DOI: 10.5121/csit.2020.100507
Abdullah Aref, Rana Husni Al Mahmoud, Khaled Taha, Mahmoud Al-Sharif
The aim of sentiment analysis is to automatically extract the opinions from a certain text and decide its sentiment. In this paper, we introduce the first publicly-available Twitter dataset on Sunnah and Shia (SSTD), as part of a religious hate speech which is a sub problem of the general hate speech. We, further, provide a detailed review of the data collection process and our annotation guidelines such that a reliable dataset annotation is guaranteed. We employed many stand-alone classification algorithms on the Twitter hate speech dataset, including Random Forest, Complement NB, DecisionTree, and SVM and two deep learning methods CNN and RNN. We further study the influence of word embedding dimensions FastText and word2vec. In all our experiments, all classification algorithms are trained using a random split of data (66% for training and 34% for testing). The two datasets were stratified sampling of the original dataset. The CNN-FastText achieves the highest F-Measure (52.0%) followed by the CNN-Word2vec (49.0%), showing that neural models with FastText word embedding outperform classical feature-based models.
{"title":"Hate Speech Detection of Arabic Shorttext","authors":"Abdullah Aref, Rana Husni Al Mahmoud, Khaled Taha, Mahmoud Al-Sharif","doi":"10.5121/csit.2020.100507","DOIUrl":"https://doi.org/10.5121/csit.2020.100507","url":null,"abstract":"The aim of sentiment analysis is to automatically extract the opinions from a certain text and decide its sentiment. In this paper, we introduce the first publicly-available Twitter dataset on Sunnah and Shia (SSTD), as part of a religious hate speech which is a sub problem of the general hate speech. We, further, provide a detailed review of the data collection process and our annotation guidelines such that a reliable dataset annotation is guaranteed. We employed many stand-alone classification algorithms on the Twitter hate speech dataset, including Random Forest, Complement NB, DecisionTree, and SVM and two deep learning methods CNN and RNN. We further study the influence of word embedding dimensions FastText and word2vec. In all our experiments, all classification algorithms are trained using a random split of data (66% for training and 34% for testing). The two datasets were stratified sampling of the original dataset. The CNN-FastText achieves the highest F-Measure (52.0%) followed by the CNN-Word2vec (49.0%), showing that neural models with FastText word embedding outperform classical feature-based models.","PeriodicalId":201467,"journal":{"name":"9th International Conference on Information Technology Convergence and Services (ITCSE 2020)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133538491","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 : 2020-05-30DOI: 10.5121/csit.2020.100511
D. Wyld, Outcome Predictions, Emilia Apostolova, Joe Morales, I. Koutroulis
While there has been considerable progress in building deep learning models based on clinical time series data, overall machine learning (ML) performance remains modest. Typical ML applications struggle to combine various heterogenous sources of Electronic Medical Record (EMR) data, often recorded as a combination of free-text clinical notes and structured EMR data. The goal of this work is to develop an approach for combining such heterogenous EMR sources for time-series based patient outcome predictions. We developed a deep learning framework capable of representing free-text clinical notes in a low dimensional vector space, semantically representing the overall patient medical condition. The free-text based time-series vectors were combined with time-series of vital signs and lab results and used to predict patients at risk of developing a complex and deadly condition: acute respiratory distress syndrome. Results utilizing early data show significant performance improvement and validate the utility of the approach.
{"title":"Free-text and Structured Clinical Time Series for Patient Outcome Predictions","authors":"D. Wyld, Outcome Predictions, Emilia Apostolova, Joe Morales, I. Koutroulis","doi":"10.5121/csit.2020.100511","DOIUrl":"https://doi.org/10.5121/csit.2020.100511","url":null,"abstract":"While there has been considerable progress in building deep learning models based on clinical time series data, overall machine learning (ML) performance remains modest. Typical ML applications struggle to combine various heterogenous sources of Electronic Medical Record (EMR) data, often recorded as a combination of free-text clinical notes and structured EMR data. The goal of this work is to develop an approach for combining such heterogenous EMR sources for time-series based patient outcome predictions. We developed a deep learning framework capable of representing free-text clinical notes in a low dimensional vector space, semantically representing the overall patient medical condition. The free-text based time-series vectors were combined with time-series of vital signs and lab results and used to predict patients at risk of developing a complex and deadly condition: acute respiratory distress syndrome. Results utilizing early data show significant performance improvement and validate the utility of the approach.","PeriodicalId":201467,"journal":{"name":"9th International Conference on Information Technology Convergence and Services (ITCSE 2020)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129749429","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 : 2020-05-30DOI: 10.5121/csit.2020.100505
Shaodi Li, Junmin Wu
Communication between parallel programs is an indispensable part of parallel computing. SW26010 is a heterogeneous many-core processor used to build the Sunway TaihuLight supercomputer, which is well suited for parallel computing. Our team is designing and implementing a coroutine scheduling system on SW26010 processor to improve its concurrency, it is very important and necessary to achieve communication between coroutines for the coroutine scheduling system in advance. Therefore, this paper proposes a communication system for data and information exchange between coroutines on SW26010 processor, which contains the following parts. First, we design and implement a producer-consumer mode channel communication based on ring buffer, and designs synchronization mechanism for condition of multi-producer and multi-consumer based on the different atomic operation on the MPE (management processing element) and the CPE (computing processing element) of SW26010. Next, we design a wake-up mechanism between the producer and the consumer, which reduces the waiting of the program for communication. At last, we test and analyse the performance of channel in different numbers of producers and consumers, draw the conclusion that when the number of producers and consumers increases, the channel performance will decrease.
{"title":"Communication between Coroutines on Sunway Many-core Platform","authors":"Shaodi Li, Junmin Wu","doi":"10.5121/csit.2020.100505","DOIUrl":"https://doi.org/10.5121/csit.2020.100505","url":null,"abstract":"Communication between parallel programs is an indispensable part of parallel computing. SW26010 is a heterogeneous many-core processor used to build the Sunway TaihuLight supercomputer, which is well suited for parallel computing. Our team is designing and implementing a coroutine scheduling system on SW26010 processor to improve its concurrency, it is very important and necessary to achieve communication between coroutines for the coroutine scheduling system in advance. Therefore, this paper proposes a communication system for data and information exchange between coroutines on SW26010 processor, which contains the following parts. First, we design and implement a producer-consumer mode channel communication based on ring buffer, and designs synchronization mechanism for condition of multi-producer and multi-consumer based on the different atomic operation on the MPE (management processing element) and the CPE (computing processing element) of SW26010. Next, we design a wake-up mechanism between the producer and the consumer, which reduces the waiting of the program for communication. At last, we test and analyse the performance of channel in different numbers of producers and consumers, draw the conclusion that when the number of producers and consumers increases, the channel performance will decrease.","PeriodicalId":201467,"journal":{"name":"9th International Conference on Information Technology Convergence and Services (ITCSE 2020)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131354829","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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