2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)最新文献
Pub Date : 2021-11-24DOI: 10.1109/SNPD51163.2021.9704961
Takuya Nakata, Sinan Chen, Masahide Nakamura
In advanced smart systems, heterogeneous distributed services are integrated dynamically, based on various contexts in cyber/physical worlds. Currently, the logic of such service integration is implemented specifically in each application. Thus, as the way of integration becomes sophisticated, the complexity and development effort of the application become quite expensive. In this research, we propose a service, called Uni-messe (Unified Rule-based Message Delivery Service), which provides context-aware service integration in an application-neutral manner. Based on ECR (Event-Condition-Routing) rules, Uni-messe routes an event message from an application to a designated application based on a specified condition. We first present the architecture of Uni-messe with publish/subscribe messaging platform. We then propose the data model of the ECR rules based on 6W1H (Who/Whom/When/Where/What/Why/How) event model. Finally, we define the condition evaluation and routing behaviors. Using the implementation of Uni-messe, we demonstrate automatic curtain control and daily routine automation in a smart home. Since Uni-messe de-couples the rule-based service integration from individual applications, it allows developers and users to implement and reuse flexible integration efficiently.
{"title":"Developing Event Routing Service to Support Context-Aware Service Integration","authors":"Takuya Nakata, Sinan Chen, Masahide Nakamura","doi":"10.1109/SNPD51163.2021.9704961","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9704961","url":null,"abstract":"In advanced smart systems, heterogeneous distributed services are integrated dynamically, based on various contexts in cyber/physical worlds. Currently, the logic of such service integration is implemented specifically in each application. Thus, as the way of integration becomes sophisticated, the complexity and development effort of the application become quite expensive. In this research, we propose a service, called Uni-messe (Unified Rule-based Message Delivery Service), which provides context-aware service integration in an application-neutral manner. Based on ECR (Event-Condition-Routing) rules, Uni-messe routes an event message from an application to a designated application based on a specified condition. We first present the architecture of Uni-messe with publish/subscribe messaging platform. We then propose the data model of the ECR rules based on 6W1H (Who/Whom/When/Where/What/Why/How) event model. Finally, we define the condition evaluation and routing behaviors. Using the implementation of Uni-messe, we demonstrate automatic curtain control and daily routine automation in a smart home. Since Uni-messe de-couples the rule-based service integration from individual applications, it allows developers and users to implement and reuse flexible integration efficiently.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117088225","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 : 2021-11-24DOI: 10.1109/SNPD51163.2021.9704915
H. Nieto-Chaupis
The abundance of dipoles of glucose in the blood stream would give rise to a pushing out of albumin proteins giving origin to the formation of a biolelectric circuit inside renal glomerulus. In the periods of large amounts of glucose and albumin in blood, kidneys might not be able to filter proteins initializing the interaction protein-protein at the renal glomerulus. From this nephrine and albumin interaction can be seen as a capacitor because the anionic and cationic functions of proteins. This paper have paid attention to the physics of renal glomerulus when it is electrically involved due to the presence of albumin that surpasses the different layers of renal glomeulus becoming a strong indicator of the kidney disease.
{"title":"Nephrine-Albumin Interaction and the Spontaneous Apparition of Series Capacitors in the Renal Glomerulus as Indicator of Kidney Disease","authors":"H. Nieto-Chaupis","doi":"10.1109/SNPD51163.2021.9704915","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9704915","url":null,"abstract":"The abundance of dipoles of glucose in the blood stream would give rise to a pushing out of albumin proteins giving origin to the formation of a biolelectric circuit inside renal glomerulus. In the periods of large amounts of glucose and albumin in blood, kidneys might not be able to filter proteins initializing the interaction protein-protein at the renal glomerulus. From this nephrine and albumin interaction can be seen as a capacitor because the anionic and cationic functions of proteins. This paper have paid attention to the physics of renal glomerulus when it is electrically involved due to the presence of albumin that surpasses the different layers of renal glomeulus becoming a strong indicator of the kidney disease.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127040991","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}
Industrial big data analysis has received a bunch of attentions in recent decades. There are several famous machine learning or deep learning frameworks used in different scenarios. However, we lack a stable and easy-to-operate pipeline framework. In this paper, the purpose is to propose an algorithm pipeline integration framework to help industrial AI systems deal with loads, scheduling and automatic operations.
{"title":"Pipeline Manager: A Flexible Semi-automatic Dataflow Analysis Framework","authors":"Cheng-Hui Chen, Huai-Che Hong, Yu-Shiang Hong, Hsiao Yu Wang, Shyr-Shen Yu","doi":"10.1109/SNPD51163.2021.9704972","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9704972","url":null,"abstract":"Industrial big data analysis has received a bunch of attentions in recent decades. There are several famous machine learning or deep learning frameworks used in different scenarios. However, we lack a stable and easy-to-operate pipeline framework. In this paper, the purpose is to propose an algorithm pipeline integration framework to help industrial AI systems deal with loads, scheduling and automatic operations.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127406792","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 : 2021-11-24DOI: 10.1109/SNPD51163.2021.9704978
You Cheng Lu, Chia-Wei Chen, Xuan Jie Gong, Kan-Rong Lee, Chung‐Jen Tseng
Energy conservation in buildings open doors for innovative techniques for thermal comfort. Recently, Simulation of smart building energy management (SBEM) has gained attention for energy conservation and efficient utilization in buildings. In this study, we proposed a conceptual framework to achieve thermal comfort inside a low-energy smart building (LESB) with real-time environmental conditions by computational fluid dynamics (CFD) simulation. CFD simulations are performed in natural ventilation mode at five different time periods to understand the climatic conditions inside the LESB in summer solstice. Heat energy entering the room at noon is effectively blocked by a special air layer of the roof. In summer, comfort inside the LESB is limited in natural ventilation mode. So, the indoor thermal comfort can be maintained with air conditioners (AC). In this study, predicted mean vote (PMV) is adopted to predict the thermal comfort with different AC position inside the LESB for energy conservation. AC installation away from the center of the wall avoids short circulation and the air flows to farther distance. The farther air flow helps to maintain uniform temperature inside room. This work helps in understanding the parameters to be considered in designing an LESB with good thermal comfort.
{"title":"CFD Simulations for Thermal Comfort and Energy Saving","authors":"You Cheng Lu, Chia-Wei Chen, Xuan Jie Gong, Kan-Rong Lee, Chung‐Jen Tseng","doi":"10.1109/SNPD51163.2021.9704978","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9704978","url":null,"abstract":"Energy conservation in buildings open doors for innovative techniques for thermal comfort. Recently, Simulation of smart building energy management (SBEM) has gained attention for energy conservation and efficient utilization in buildings. In this study, we proposed a conceptual framework to achieve thermal comfort inside a low-energy smart building (LESB) with real-time environmental conditions by computational fluid dynamics (CFD) simulation. CFD simulations are performed in natural ventilation mode at five different time periods to understand the climatic conditions inside the LESB in summer solstice. Heat energy entering the room at noon is effectively blocked by a special air layer of the roof. In summer, comfort inside the LESB is limited in natural ventilation mode. So, the indoor thermal comfort can be maintained with air conditioners (AC). In this study, predicted mean vote (PMV) is adopted to predict the thermal comfort with different AC position inside the LESB for energy conservation. AC installation away from the center of the wall avoids short circulation and the air flows to farther distance. The farther air flow helps to maintain uniform temperature inside room. This work helps in understanding the parameters to be considered in designing an LESB with good thermal comfort.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134152852","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 : 2021-11-24DOI: 10.1109/SNPD51163.2021.9704985
Amit Singh, Chun-Yu Lin, Chung-I Huang, Fang-Pang Lin
Traffic congestion is one of the major issues in urban areas, particularly when traffic loads exceed the road’s capacity, resulting in higher petrol consumption and carbon emissions as well as delays and stress for road users. In Asia, the traffic situation can be further deteriorated by road sharing of scooters. How to control the traffic flow to mitigate the congestion has been one of the central issues in transportation research. In this study, we employ a quantum annealing approach to optimize the traffic signals control at a real-life intersection with mixed traffic flows of vehicles and scooters. Considering traffic flow is a continuous and emerging phenomenon, we used quadratic unconstrained binary optimization (QUBO) formalism for traffic optimization, which has a natural equivalence to the Ising model and can be solved efficiently on the quantum annealers, quantum computers or digital annealers. In this article, we first applied the QUBO traffic optimization to artificially generated traffic for a simple intersection, and then we used real-time traffic data to simulate a real "Dongda-Keyuan" intersection with dedicated cars and scooter lanes, as well as mixed scooter and car lanes. We introduced two types of traffic light control systems for traffic optimization: C-QUBO and QUBO. Our rigorous QUBO optimizations show that C-QUBO and QUBO outperform the commonly used fixed cycle method, with QUBO outperforming C-QUBO in some instances. It has been found that QUBO optimization significantly relieves traffic congestion for the unbalanced traffic volume. Furthermore, we found that dynamic changes in traffic light signal duration greatly reduce traffic congestion.
{"title":"Quantum Annealing Approach for the Optimal Real-time Traffic Control using QUBO","authors":"Amit Singh, Chun-Yu Lin, Chung-I Huang, Fang-Pang Lin","doi":"10.1109/SNPD51163.2021.9704985","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9704985","url":null,"abstract":"Traffic congestion is one of the major issues in urban areas, particularly when traffic loads exceed the road’s capacity, resulting in higher petrol consumption and carbon emissions as well as delays and stress for road users. In Asia, the traffic situation can be further deteriorated by road sharing of scooters. How to control the traffic flow to mitigate the congestion has been one of the central issues in transportation research. In this study, we employ a quantum annealing approach to optimize the traffic signals control at a real-life intersection with mixed traffic flows of vehicles and scooters. Considering traffic flow is a continuous and emerging phenomenon, we used quadratic unconstrained binary optimization (QUBO) formalism for traffic optimization, which has a natural equivalence to the Ising model and can be solved efficiently on the quantum annealers, quantum computers or digital annealers. In this article, we first applied the QUBO traffic optimization to artificially generated traffic for a simple intersection, and then we used real-time traffic data to simulate a real \"Dongda-Keyuan\" intersection with dedicated cars and scooter lanes, as well as mixed scooter and car lanes. We introduced two types of traffic light control systems for traffic optimization: C-QUBO and QUBO. Our rigorous QUBO optimizations show that C-QUBO and QUBO outperform the commonly used fixed cycle method, with QUBO outperforming C-QUBO in some instances. It has been found that QUBO optimization significantly relieves traffic congestion for the unbalanced traffic volume. Furthermore, we found that dynamic changes in traffic light signal duration greatly reduce traffic congestion.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114235143","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 : 2021-11-24DOI: 10.1109/SNPD51163.2021.9704954
Chia-Ju Lin, Ruey-Maw Chen
The data preprocess directly affects the classification results in various applications. In the field of intrusion detection, less research raised the problems or solutions of unequal metrics in data attributes. This study proposes an effective data preprocessing method for network packets with unequal metrics in packet attributes. A standard deviation standardization was first applied to standardize each attribute of KDDCUP'99 dataset, followed by quantizing it to the range of 0 to 255 interval for afterward use of the image. Meanwhile, the Zigzag arrangement coding and IDCT (Inverse Discrete Cosine Transform) were then used to convert the quantized data into images. Experimental results demonstrate that a more than 94% recall rate of the overall intrusion detection classifier can be yielded by the proposed preprocess method even without a complicated network model. Meanwhile, intrusion detection performance can be guaranteed by using small-size images of packet attributes.
{"title":"An Effective Preprocess for Deep Learning Based Intrusion Detection","authors":"Chia-Ju Lin, Ruey-Maw Chen","doi":"10.1109/SNPD51163.2021.9704954","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9704954","url":null,"abstract":"The data preprocess directly affects the classification results in various applications. In the field of intrusion detection, less research raised the problems or solutions of unequal metrics in data attributes. This study proposes an effective data preprocessing method for network packets with unequal metrics in packet attributes. A standard deviation standardization was first applied to standardize each attribute of KDDCUP'99 dataset, followed by quantizing it to the range of 0 to 255 interval for afterward use of the image. Meanwhile, the Zigzag arrangement coding and IDCT (Inverse Discrete Cosine Transform) were then used to convert the quantized data into images. Experimental results demonstrate that a more than 94% recall rate of the overall intrusion detection classifier can be yielded by the proposed preprocess method even without a complicated network model. Meanwhile, intrusion detection performance can be guaranteed by using small-size images of packet attributes.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121625787","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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