Pub Date : 2018-11-01DOI: 10.1109/ICSAI.2018.8599366
Haizhou Du, Jingu Qian
Text classification is a fundamental problem in natural language processing. Recently, neural network models have been demonstrated to be capable of achieving remarkable performance in this domain. However, none of existing method can achieve excellent classification accuracy while concerning of computational cost. To solve this problem, we proposed hierarchical gated convolutional networks with multi-head attention which reduces computational cost through its two distinctive characteristics to save considerable model parameters. First, it has a hierarchical structure the same as the hierarchical structure of documents that has word-level and sentence-level, which not only benefits to classification performance but also reduces computational cost significantly by reusing parameters of the model in each sentence. Second, we apply gated convolutional network on both levels that enables our model achieved comparable performance to very deep networks with relatively shallow network depth. To further improve the performance of our model, multi-head attention mechanism is employed to differentiate more or less importance of words or sentences for better construction of document representation. Experiments conducted on the commonly used Yelp reviews datasets demonstrate that the proposed architecture obtains competitive performance against the state-of-the-art methods.
{"title":"Hierarchical Gated Convolutional Networks with Multi-Head Attention for Text Classification","authors":"Haizhou Du, Jingu Qian","doi":"10.1109/ICSAI.2018.8599366","DOIUrl":"https://doi.org/10.1109/ICSAI.2018.8599366","url":null,"abstract":"Text classification is a fundamental problem in natural language processing. Recently, neural network models have been demonstrated to be capable of achieving remarkable performance in this domain. However, none of existing method can achieve excellent classification accuracy while concerning of computational cost. To solve this problem, we proposed hierarchical gated convolutional networks with multi-head attention which reduces computational cost through its two distinctive characteristics to save considerable model parameters. First, it has a hierarchical structure the same as the hierarchical structure of documents that has word-level and sentence-level, which not only benefits to classification performance but also reduces computational cost significantly by reusing parameters of the model in each sentence. Second, we apply gated convolutional network on both levels that enables our model achieved comparable performance to very deep networks with relatively shallow network depth. To further improve the performance of our model, multi-head attention mechanism is employed to differentiate more or less importance of words or sentences for better construction of document representation. Experiments conducted on the commonly used Yelp reviews datasets demonstrate that the proposed architecture obtains competitive performance against the state-of-the-art methods.","PeriodicalId":375852,"journal":{"name":"2018 5th International Conference on Systems and Informatics (ICSAI)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127987690","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 : 2018-11-01DOI: 10.1109/ICSAI.2018.8599457
J. Kalikova, J. Krcál
The article deals with the biometric identification of drivers, using an ear thermogram. Samples are acquired using an IR camera and then further evaluated by an artificial neural network. Input image data is acquired from a standardized distance at 5 different angles and the effect of the settings of the artificial neural network on the result of successful driver identification is studied.
{"title":"Driver Identification Using Ear Biometrics","authors":"J. Kalikova, J. Krcál","doi":"10.1109/ICSAI.2018.8599457","DOIUrl":"https://doi.org/10.1109/ICSAI.2018.8599457","url":null,"abstract":"The article deals with the biometric identification of drivers, using an ear thermogram. Samples are acquired using an IR camera and then further evaluated by an artificial neural network. Input image data is acquired from a standardized distance at 5 different angles and the effect of the settings of the artificial neural network on the result of successful driver identification is studied.","PeriodicalId":375852,"journal":{"name":"2018 5th International Conference on Systems and Informatics (ICSAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130713492","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 : 2018-11-01DOI: 10.1109/ICSAI.2018.8599468
Xiaonan Li, Guoqiang Liu, Shiqiang Li, H. Xia, Yong Wang
This paper reports the design, fabrication and preliminary tests of lab-built probes for microliter-level NMR spectroscopy (Nuclear Magnetic Resonance). The detection is based on the planar microcoils fabricated on glass substrate by MEMS (Micro Electronic Mechanical System) technology with SU-8 photoresist. The measured Q values are about 20 at 63.89 MHz for the microcoils, i.d. $1000 mu $m, wire width $80 mu $m, 7 turns. The characterization of the lab-built microcoil-based probes has been performed in NMR experiments for 4 g/L CuSO4 samples of $200 mu $L. Using the square microcoil fabricated, with the cone-type container the SNR (Signal-to-Noise Ratio) and the Linewidth at 1.5 Tesla is 101.7 and 450.1 Hz, respectively. And with the tube-type container the SNR and the Linewidth is 17 and 229.6 Hz, respectively. It was shown that the resolution degraded about one-hundred percent due to container-introduced distortion on B0 container. On the other hand a good couple of container shape with the profile of B1 will improve the sensitivity. And the resolution could be improved by optimization on the structure of the probe. Towards nano-liter NMR spectroscopy, the sample volume under detection could be reduced further. Honestly to say, the planar microcoil NMR has unsealed the integration with chip-based microfluidics in the emerging world of micro-Total Analysis Systems ($mu $ TAS).
本文报道了微升级核磁共振探针的设计、制造和初步试验。该检测基于基于SU-8光刻胶的MEMS(微电子机械系统)技术在玻璃基板上制作的平面微线圈。在63.89 MHz下，微线圈的测量Q值约为20,i.d $1000 mu $m，线宽$80 mu $m, 7匝。在$200 mu $L的4 g/L CuSO4样品中，对实验室构建的基于微线圈的探针进行了NMR实验。采用锥形容器制作方形微线圈，在1.5特斯拉时信噪比为101.7 Hz，线宽为450.1 Hz。筒型容器的信噪比为17 Hz，线宽为229.6 Hz。结果表明，由于B0容器上的容器引入畸变，分辨率下降了约100%。另一方面，良好的容器形状与B1轮廓的结合将提高灵敏度。通过对探针结构的优化，可以进一步提高探针的分辨率。在纳米升核磁共振光谱中，被测样品的体积可以进一步减小。坦白地说，平面微线圈核磁共振开启了微全分析系统($mu $ TAS)这一新兴领域与基于芯片的微流控技术的整合。
{"title":"Planar-coil-based Micro-detection in Nuclear Magnetic Resonance Spectroscopy","authors":"Xiaonan Li, Guoqiang Liu, Shiqiang Li, H. Xia, Yong Wang","doi":"10.1109/ICSAI.2018.8599468","DOIUrl":"https://doi.org/10.1109/ICSAI.2018.8599468","url":null,"abstract":"This paper reports the design, fabrication and preliminary tests of lab-built probes for microliter-level NMR spectroscopy (Nuclear Magnetic Resonance). The detection is based on the planar microcoils fabricated on glass substrate by MEMS (Micro Electronic Mechanical System) technology with SU-8 photoresist. The measured Q values are about 20 at 63.89 MHz for the microcoils, i.d. $1000 mu $m, wire width $80 mu $m, 7 turns. The characterization of the lab-built microcoil-based probes has been performed in NMR experiments for 4 g/L CuSO4 samples of $200 mu $L. Using the square microcoil fabricated, with the cone-type container the SNR (Signal-to-Noise Ratio) and the Linewidth at 1.5 Tesla is 101.7 and 450.1 Hz, respectively. And with the tube-type container the SNR and the Linewidth is 17 and 229.6 Hz, respectively. It was shown that the resolution degraded about one-hundred percent due to container-introduced distortion on B0 container. On the other hand a good couple of container shape with the profile of B1 will improve the sensitivity. And the resolution could be improved by optimization on the structure of the probe. Towards nano-liter NMR spectroscopy, the sample volume under detection could be reduced further. Honestly to say, the planar microcoil NMR has unsealed the integration with chip-based microfluidics in the emerging world of micro-Total Analysis Systems ($mu $ TAS).","PeriodicalId":375852,"journal":{"name":"2018 5th International Conference on Systems and Informatics (ICSAI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131173595","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 : 2018-11-01DOI: 10.1109/ICSAI.2018.8599334
Jiandun Li, Pin Lv, Chunlei Ji
In today’s e-commercial websites, product reviews written by genuine users are commonly seen, which play a crucial role as customer feedbacks and planting seeds to trigger much more transactions. However, motivated by profits, fake reviews crafted by spammers are inevitable to promote or demote product reputations whereas misguiding potential buyers to make bad decisions. Until recently, the problem how to distinguish whether a review is fraudulent or a reviewer is a spammer has long been studied, but the question of general review pattern mining is still open. In this paper, we model online product review systems into bipartite networks and adopt a network technique, called the weighted motif to uncover underlying reviewing patterns. Experiments on Amazon’s review dataset show that, our system is feasible and effective.
{"title":"Uncover Product Review Patterns via Weighted Motifs","authors":"Jiandun Li, Pin Lv, Chunlei Ji","doi":"10.1109/ICSAI.2018.8599334","DOIUrl":"https://doi.org/10.1109/ICSAI.2018.8599334","url":null,"abstract":"In today’s e-commercial websites, product reviews written by genuine users are commonly seen, which play a crucial role as customer feedbacks and planting seeds to trigger much more transactions. However, motivated by profits, fake reviews crafted by spammers are inevitable to promote or demote product reputations whereas misguiding potential buyers to make bad decisions. Until recently, the problem how to distinguish whether a review is fraudulent or a reviewer is a spammer has long been studied, but the question of general review pattern mining is still open. In this paper, we model online product review systems into bipartite networks and adopt a network technique, called the weighted motif to uncover underlying reviewing patterns. Experiments on Amazon’s review dataset show that, our system is feasible and effective.","PeriodicalId":375852,"journal":{"name":"2018 5th International Conference on Systems and Informatics (ICSAI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128149759","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 : 2018-11-01DOI: 10.1109/ICSAI.2018.8599296
Tao Gao, Xiu-rong Ma, Ming-xin Liu
In this paper, we propose a weighted hard-reliability based one step majority-logic decoding algorithm for NON-Binary Low-Density Parity-Check (NB-LDPC) codes. To improve the information reliable of check nodes and the use efficiency of receive message, a weight reliability message method is proposed where only the weight values generated in the decoding initialization are reserved for the iterate decoding process. We also propose a new message reliability updating rule for each iterate decoding, in which only the unreliable variable nodes are updated. Simulation results show that our proposed weighted iterative hard-reliability (WIHRB) algorithm significantly improves the error-floor performance compared to the conventional truncate iterative hard-reliability (TIHRB) algorithms.
{"title":"Weighted Hard-Reliability Decoding Method for Non-binary LDPC Codes","authors":"Tao Gao, Xiu-rong Ma, Ming-xin Liu","doi":"10.1109/ICSAI.2018.8599296","DOIUrl":"https://doi.org/10.1109/ICSAI.2018.8599296","url":null,"abstract":"In this paper, we propose a weighted hard-reliability based one step majority-logic decoding algorithm for NON-Binary Low-Density Parity-Check (NB-LDPC) codes. To improve the information reliable of check nodes and the use efficiency of receive message, a weight reliability message method is proposed where only the weight values generated in the decoding initialization are reserved for the iterate decoding process. We also propose a new message reliability updating rule for each iterate decoding, in which only the unreliable variable nodes are updated. Simulation results show that our proposed weighted iterative hard-reliability (WIHRB) algorithm significantly improves the error-floor performance compared to the conventional truncate iterative hard-reliability (TIHRB) algorithms.","PeriodicalId":375852,"journal":{"name":"2018 5th International Conference on Systems and Informatics (ICSAI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126032438","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 : 2018-11-01DOI: 10.1109/ICSAI.2018.8599476
Haizhou Du, Keke Zhang, Zhenchen Yang
In recent years, big data analytics frameworks spring up rapidly. Meanwhile, it has become routine for large volumes of data to be generated, stored, and processed across geographically distributed datac enters. Network congestion generated by data transfers between networks becomes a major bottleneck to the overall performance of the system in a geo-distributed environment. Many existing methods usually process network congestion after they occurs, which does not solve the problem fundamentally. In this paper, we focus on the problem of predicting and avoiding network congestion in advance in a geo-distributed environment on Apache Spark, in terms of their job completion times. We formulate this problem as a runtime minimization problem, which is challenging to solve in practice due to a scene with different data centers. To address these challenges, we propose a model based on congestion-aware scheduling. In the model, we exploit SDN(Software-Defined Networking) to detect the data size of the data flow in advance from different data centers and then analyze the data characteristics, which predicts the flow that can generate network congestion in advance, so that we can draft two scheme for different flow. In addition, when we detect the network congestion, we choose a path with a greater bandwidth for the congestion flow. The approach can minimize network congestion, promote network utilization and improve system performance in a geo-distributed environment. As a highlight of this paper, we design and implement our proposed solution as a job scheduler based on Apache Spark, a modern data processing framework.
{"title":"Octopus: Based on Congestion-aware Scheduling on Geo-distributed Big Data Analytics Cluster","authors":"Haizhou Du, Keke Zhang, Zhenchen Yang","doi":"10.1109/ICSAI.2018.8599476","DOIUrl":"https://doi.org/10.1109/ICSAI.2018.8599476","url":null,"abstract":"In recent years, big data analytics frameworks spring up rapidly. Meanwhile, it has become routine for large volumes of data to be generated, stored, and processed across geographically distributed datac enters. Network congestion generated by data transfers between networks becomes a major bottleneck to the overall performance of the system in a geo-distributed environment. Many existing methods usually process network congestion after they occurs, which does not solve the problem fundamentally. In this paper, we focus on the problem of predicting and avoiding network congestion in advance in a geo-distributed environment on Apache Spark, in terms of their job completion times. We formulate this problem as a runtime minimization problem, which is challenging to solve in practice due to a scene with different data centers. To address these challenges, we propose a model based on congestion-aware scheduling. In the model, we exploit SDN(Software-Defined Networking) to detect the data size of the data flow in advance from different data centers and then analyze the data characteristics, which predicts the flow that can generate network congestion in advance, so that we can draft two scheme for different flow. In addition, when we detect the network congestion, we choose a path with a greater bandwidth for the congestion flow. The approach can minimize network congestion, promote network utilization and improve system performance in a geo-distributed environment. As a highlight of this paper, we design and implement our proposed solution as a job scheduler based on Apache Spark, a modern data processing framework.","PeriodicalId":375852,"journal":{"name":"2018 5th International Conference on Systems and Informatics (ICSAI)","volume":"31 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120860196","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 : 2018-11-01DOI: 10.1109/ICSAI.2018.8599504
Jia Cui, Lei Shi, Juan Li, Zhaohui Liu
With rapid development of network technologies, the data accessing paradigm has been transferred from disk-oriented to “on-the-fly” data stream. The string similarity query on data stream has a broad prospect of application, especially in information security area and network monitoring. Due to the characteristics of stream and limitations of computing resources, the current methods based on static dataset cannot support stream efficiently. To solve these challenges, a framework named F2SCQ (framework of string similarity continuous query) based on filtering and verifying approach is pro-posed. It adopts basic window mechanism to update the sliding window, and the improved asymmetric signature (IAS) scheme to extract signature is proposed. Moreover two new filtering algorithms: Pre-Prune Filtering (PPF) and Count Filtering on Stream (CFS) are proposed. The experiments show that F2SCQ achieves high performance over high rates data stream. Compared to q-gram and asymmetric signature scheme, IAS achieves 50% and 20% faster extraction speed and 45% and 9% less storage overhead. The proposed filtering algorithm also achieves faster filtering speed and generates fewer candidates. F2SCQ minimizes the time and space complexity.
{"title":"An Efficient Framework for String Similarity Continuous Query on Data Stream","authors":"Jia Cui, Lei Shi, Juan Li, Zhaohui Liu","doi":"10.1109/ICSAI.2018.8599504","DOIUrl":"https://doi.org/10.1109/ICSAI.2018.8599504","url":null,"abstract":"With rapid development of network technologies, the data accessing paradigm has been transferred from disk-oriented to “on-the-fly” data stream. The string similarity query on data stream has a broad prospect of application, especially in information security area and network monitoring. Due to the characteristics of stream and limitations of computing resources, the current methods based on static dataset cannot support stream efficiently. To solve these challenges, a framework named F2SCQ (framework of string similarity continuous query) based on filtering and verifying approach is pro-posed. It adopts basic window mechanism to update the sliding window, and the improved asymmetric signature (IAS) scheme to extract signature is proposed. Moreover two new filtering algorithms: Pre-Prune Filtering (PPF) and Count Filtering on Stream (CFS) are proposed. The experiments show that F2SCQ achieves high performance over high rates data stream. Compared to q-gram and asymmetric signature scheme, IAS achieves 50% and 20% faster extraction speed and 45% and 9% less storage overhead. The proposed filtering algorithm also achieves faster filtering speed and generates fewer candidates. F2SCQ minimizes the time and space complexity.","PeriodicalId":375852,"journal":{"name":"2018 5th International Conference on Systems and Informatics (ICSAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126086449","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 : 2018-11-01DOI: 10.1109/ICSAI.2018.8599287
Weizhi Ying, Bin Sun, Aoyun Shen, Haifeng Xu, Liangyu Zhong
This paper aims to establish a nonlinear speeding optimizing model for minimizing the fuel consumption. Considering the fuel consumption of the vessel both in sailing and mooring, the traditional speeding optimizing model with fuel consumption only in sailing consideration is improved. Not only the relationship between fuel consumption and speed in sailing is fitted by a power function, but also a linear function was used to fit the relationship between fuel consumption and time in mooring. Based on the two functions above, a new speeding calculating formula which is more practical is proposed. The simulation experiments prove the speeding optimizing model and formula proposed can reduce the fuel consumption and emission more effectively.
{"title":"Speeding optimization considering the fuel consumption in the mooring period","authors":"Weizhi Ying, Bin Sun, Aoyun Shen, Haifeng Xu, Liangyu Zhong","doi":"10.1109/ICSAI.2018.8599287","DOIUrl":"https://doi.org/10.1109/ICSAI.2018.8599287","url":null,"abstract":"This paper aims to establish a nonlinear speeding optimizing model for minimizing the fuel consumption. Considering the fuel consumption of the vessel both in sailing and mooring, the traditional speeding optimizing model with fuel consumption only in sailing consideration is improved. Not only the relationship between fuel consumption and speed in sailing is fitted by a power function, but also a linear function was used to fit the relationship between fuel consumption and time in mooring. Based on the two functions above, a new speeding calculating formula which is more practical is proposed. The simulation experiments prove the speeding optimizing model and formula proposed can reduce the fuel consumption and emission more effectively.","PeriodicalId":375852,"journal":{"name":"2018 5th International Conference on Systems and Informatics (ICSAI)","volume":"239 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126814110","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 : 2018-11-01DOI: 10.1109/ICSAI.2018.8599466
Gangmin Li, Jian Gu, Xuming Bai
Cancer plays a leading role in causing morbidity and mortality worldwide. Several treatments have been developed and practiced for fighting against cancer. Totally Implantable Venous Access Port Drug Supply (TIVAPDS) treatment is a new method utilizing Totally Implantable Venous Access Port (TIVAP) delivery method, which is one kind of Intrathecal Drug Delivery System (IDD) with lower side effects, to increase patient’s quality of life. This paper reports our study aiming to evaluate the effectiveness of TIVAPDS treatment in order to make contributions to generalize this treatment in China. Our data samples come from The Second Affiliated Hospital of Suzhou University, a forerunner of TIVAPDS practices in China and with patients’ agreement. The data statistics summary results and the relationships between each two identified attributes are analyzed. Based on the results, 2 predictive models utilizing C4.5 decision tree and logistic regression algorithms are adopted for prediction. The results are used as reference to assess individual treatment cases, so that the effectiveness of the treatment can be achieved and if possible, to improve the efficiency of TIVAPDS treatment.
{"title":"New Cancer Treatment Evaluation through Big Data Analytics","authors":"Gangmin Li, Jian Gu, Xuming Bai","doi":"10.1109/ICSAI.2018.8599466","DOIUrl":"https://doi.org/10.1109/ICSAI.2018.8599466","url":null,"abstract":"Cancer plays a leading role in causing morbidity and mortality worldwide. Several treatments have been developed and practiced for fighting against cancer. Totally Implantable Venous Access Port Drug Supply (TIVAPDS) treatment is a new method utilizing Totally Implantable Venous Access Port (TIVAP) delivery method, which is one kind of Intrathecal Drug Delivery System (IDD) with lower side effects, to increase patient’s quality of life. This paper reports our study aiming to evaluate the effectiveness of TIVAPDS treatment in order to make contributions to generalize this treatment in China. Our data samples come from The Second Affiliated Hospital of Suzhou University, a forerunner of TIVAPDS practices in China and with patients’ agreement. The data statistics summary results and the relationships between each two identified attributes are analyzed. Based on the results, 2 predictive models utilizing C4.5 decision tree and logistic regression algorithms are adopted for prediction. The results are used as reference to assess individual treatment cases, so that the effectiveness of the treatment can be achieved and if possible, to improve the efficiency of TIVAPDS treatment.","PeriodicalId":375852,"journal":{"name":"2018 5th International Conference on Systems and Informatics (ICSAI)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134013266","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 : 2018-11-01DOI: 10.1109/ICSAI.2018.8599381
Yang Bo
In this paper, using embedded technology, signal processing technology, digital circuit technology and analog circuit technology, and other related technologies, the intelligent and general combustible gas detection system can be designed to detect natural gas, gas, liquefied gas and other combustible gases. The design includes two parts: hardware design and software design. It focuses on the analysis of hardware circuits such as detection, sampling/holding, anti-interference and nonlinear compensation, and introduces the software design of the system. The system design facilitates the expansion of gas detection points and the processing of real-time data. The test results show that the detection precision of the detection system is 0.1% for methane, natural gas and other combustible gases. It has the characteristics of stable detection precision, good linearity, simple circuit and easy to miniaturization.
{"title":"Design of Combustible Gas Concentration Detection System","authors":"Yang Bo","doi":"10.1109/ICSAI.2018.8599381","DOIUrl":"https://doi.org/10.1109/ICSAI.2018.8599381","url":null,"abstract":"In this paper, using embedded technology, signal processing technology, digital circuit technology and analog circuit technology, and other related technologies, the intelligent and general combustible gas detection system can be designed to detect natural gas, gas, liquefied gas and other combustible gases. The design includes two parts: hardware design and software design. It focuses on the analysis of hardware circuits such as detection, sampling/holding, anti-interference and nonlinear compensation, and introduces the software design of the system. The system design facilitates the expansion of gas detection points and the processing of real-time data. The test results show that the detection precision of the detection system is 0.1% for methane, natural gas and other combustible gases. It has the characteristics of stable detection precision, good linearity, simple circuit and easy to miniaturization.","PeriodicalId":375852,"journal":{"name":"2018 5th International Conference on Systems and Informatics (ICSAI)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122905717","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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