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2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)最新文献

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Adaptive beamforming based on linearly constrained maximum correntropy learning algorithm 基于线性约束最大熵学习算法的自适应波束形成
2017 7th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2017-10-01 DOI: 10.1109/ICCKE.2017.8167926
M. Hajiabadi, H. Khoshbin, G. Hodtani
{"title":"Adaptive beamforming based on linearly constrained maximum correntropy learning algorithm","authors":"M. Hajiabadi, H. Khoshbin, G. Hodtani","doi":"10.1109/ICCKE.2017.8167926","DOIUrl":"https://doi.org/10.1109/ICCKE.2017.8167926","url":null,"abstract":"The Gaussian noise profile has been demonstrated to be an inaccurate model in several antenna beamforming problems. Many available beamformers are based on second-order statistics and their efficiency degrades significantly due to impulsive noise existed in the received signal. Therefore, a demand exists for attention to address beamforming problems under nonGaussian noise environments. According to the robust performance of information theoretic learning (ITL) criteria in nonGaussian environments, we propose a linearly constrained version of maximum correntropy learning algorithm in order to solve beamforming problem in presence of nonGaussian and impulsive noises. Simulation results of the proposed adaptive beamformer are provided to illustrate its accurate and resistant performance in comparison with conventional second-order-moment-based beamformers.","PeriodicalId":151934,"journal":{"name":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"705 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123638518","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}
引用次数: 1
Performance profiling of database systems in Xen Xen中数据库系统的性能分析
2017 7th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2017-10-01 DOI: 10.1109/ICCKE.2017.8167935
Hesam Tajbakhsh, Mostafa Dehsangi, M. Analoui
{"title":"Performance profiling of database systems in Xen","authors":"Hesam Tajbakhsh, Mostafa Dehsangi, M. Analoui","doi":"10.1109/ICCKE.2017.8167935","DOIUrl":"https://doi.org/10.1109/ICCKE.2017.8167935","url":null,"abstract":"In recent years, many database systems have been deployed in virtualized cloud platforms to take advantage of the general benefits of virtualization and cloud computing. However, deploying database systems in such environments poses some challenges that should be addressed. The performance of database systems can degrade due to the various overheads introduced by the virtualization including CPU, memory, disk, and network overheads. In this paper, we evaluate the performance of MySQL in-disk database and DB2 in-memory database in Xen virtualized environment. Our experimental results show that the performance of MySQL degrades dramatically if it runs in Xen while the performance of DB2 in Xen is comparable with that in the native environment. Moreover, the performance of DB2 is much higher than MySQL in Xen environment. These observations indicate that in-memory databases such as DB2 are good candidates to be migrated to Xen-based cloud platforms.","PeriodicalId":151934,"journal":{"name":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122570591","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}
引用次数: 0
Protein's number of beta-sheets prediction using structural features 利用结构特征预测蛋白质的β -片数
2017 7th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2017-10-01 DOI: 10.1109/ICCKE.2017.8167921
Amir Hossein Babolhakami, Behshid Behkamal, Toktam Dehghani, Kobra Etminani, Mahmoud Naghibzadeh
{"title":"Protein's number of beta-sheets prediction using structural features","authors":"Amir Hossein Babolhakami, Behshid Behkamal, Toktam Dehghani, Kobra Etminani, Mahmoud Naghibzadeh","doi":"10.1109/ICCKE.2017.8167921","DOIUrl":"https://doi.org/10.1109/ICCKE.2017.8167921","url":null,"abstract":"A protein is a long one-dimensional amino acid sequence. Some subsequences of this sequence are given names and β-strand in one such subsequence. β-strands are very common and two or more such strands within one protein can form a β-sheet in the secondary structure of proteins. In its natural form, a protein is a three-dimensional entity composed of β-sheets, α-helices, and other types of substructures. Knowing the exact three-dimensional structure of a protein is the key to diagnosing several diseases and producing some drugs. In many proteins, β-sheets are the most common and the dominating substructure. Predicting the number of β-sheets in a given protein sequence is a valuable step in predicting the whole β-sheets structure in the sense that it can reduce the time complexity of the exhaustive search space examination predictors. In this research, a data-mining method for predicting the number of β-sheets is developed. The evaluations show that its performance is highly reliable.","PeriodicalId":151934,"journal":{"name":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129888081","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}
引用次数: 1
Smart home user identification using bag of events approach 智能家居用户身份识别采用事件包方法
2017 7th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2017-10-01 DOI: 10.1109/ICCKE.2017.8167908
Fatemeh Sadat Lesani, F. F. Ghazvini, Hossein Amirkhani
{"title":"Smart home user identification using bag of events approach","authors":"Fatemeh Sadat Lesani, F. F. Ghazvini, Hossein Amirkhani","doi":"10.1109/ICCKE.2017.8167908","DOIUrl":"https://doi.org/10.1109/ICCKE.2017.8167908","url":null,"abstract":"In this paper we present an innovative approach to identify people in smart homes. The behavioral pattern of smart home's users can be extracted to distinguish each user from others. In the lowest level, a sequence of sensor events forms an activity. In the higher levels, a combination of activities creates a behavioral pattern. The bag of events can be considered as features. In other hand, the behavior is flexible and can vary in different situations. A bag of activity approach is introduced to overcome the problem of behavior inconsistency. Our experiments confirm that the bag of activity is increased the f-measure of the model to near 98%.","PeriodicalId":151934,"journal":{"name":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127647675","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}
引用次数: 3
Multi-layer Kullback-Leibler-based Complex NMF with LPC error clustering for blind source separation 基于多层kullback - leibler的LPC误差聚类复NMF盲源分离
2017 7th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2017-10-01 DOI: 10.1109/ICCKE.2017.8167890
A. Amiri, Sanaz Seyedin, S. Ahadi
{"title":"Multi-layer Kullback-Leibler-based Complex NMF with LPC error clustering for blind source separation","authors":"A. Amiri, Sanaz Seyedin, S. Ahadi","doi":"10.1109/ICCKE.2017.8167890","DOIUrl":"https://doi.org/10.1109/ICCKE.2017.8167890","url":null,"abstract":"In many applications such as music transcription, audio forensics, and speech source separation, it is needed to decompose a mono recording into its respective sources. These techniques are usually referred to as blind source separation (BSS). One of the methods recently used in BSS is non-negative matrix factorization (NMF) both in supervised and unsupervised learning cases. In this paper, we propose a novel NMF-based algorithm namely, multi-layer KL-CNMF (Kullback-Leibler-Complex NMF) using fuzzy initial clustering to improve the performance of BSS in the unsupervised mode. In addition, we use LPC error clustering as a powerful criterion especially for separating harmonic signals such as certain speech sources from their multi-layer KL-CNMF components. The results on speech mixtures of the TIMIT database based on signal to distortion ratio (SDR) and signal to interference ratio (SIR) show that the proposed system significantly outperforms the baseline system which is an NMF-based BSS with LPC error clustering.","PeriodicalId":151934,"journal":{"name":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129041990","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}
引用次数: 1
Beam switching techniques for millimeter wave vehicle to infrastructure communications 毫米波车辆与基础设施通信的波束交换技术
2017 7th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2017-10-01 DOI: 10.1109/ICCKE.2017.8167901
H. Mohammadi, R. Mohammadkhani
{"title":"Beam switching techniques for millimeter wave vehicle to infrastructure communications","authors":"H. Mohammadi, R. Mohammadkhani","doi":"10.1109/ICCKE.2017.8167901","DOIUrl":"https://doi.org/10.1109/ICCKE.2017.8167901","url":null,"abstract":"Beam alignment for millimeter wave (mm Wave) vehicular communications is challenging due to the high mobility of vehicles. Recent studies have proposed some beam switching techniques at Road Side Unit (RSU) for vehicle to infrastructure (V2I) communications, employing initial position and speed information of vehicles, that are sent through Dedicated Short Range Communications (DSRC) to the RSU. However, inaccuracies of the provided information lead to beam misalignment. Some beam design parameters are suggested in the literature to combat this effect. But how these parameters should be tuned? Here, we evaluate the effect of all these parameters, and propose a beam design efficiency metric to perform beam alignment in the presence of the estimation errors, and to improve the performance by choosing the right design parameters.","PeriodicalId":151934,"journal":{"name":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127349440","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}
引用次数: 2
A spectrum efficient base station switching-off mechanism for green cellular networks 绿色蜂窝网络中频谱高效的基站关闭机制
2017 7th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2017-10-01 DOI: 10.1109/ICCKE.2017.8167917
Fahime Roghani Arvaje, B. S. Ghahfarokhi
{"title":"A spectrum efficient base station switching-off mechanism for green cellular networks","authors":"Fahime Roghani Arvaje, B. S. Ghahfarokhi","doi":"10.1109/ICCKE.2017.8167917","DOIUrl":"https://doi.org/10.1109/ICCKE.2017.8167917","url":null,"abstract":"Growing demands for mobile services in recent years has extraordinary increased the number of cellular operators and consequently the portion of energy that is consumed by cellular networks. Hence, green cellular network has been introduced, which suggests the use of energy optimization methods in cellular networks. One of the solutions to optimize the energy consumption of cellular networks is to switch on/off base stations with low traffic demand. Previous works on cell switching usually do not address the spectrum efficiency and QoS of users in their methods. In this paper, a cell switching method is proposed on the basis of a baseline method which considers the spectrum efficiency and QoS of users in reallocation of radio resources after switching off a base station. The simulation results demonstrate that the proposed method reduces the energy consumption and improves spectrum efficiency compared to baseline method.","PeriodicalId":151934,"journal":{"name":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131052187","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}
引用次数: 1
BER performance of uplink massive MIMO with low-resolution ADCs 低分辨率adc下上行海量MIMO的误码率性能
2017 7th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2017-10-01 DOI: 10.1109/ICCKE.2017.8167895
A. Azizzadeh, R. Mohammadkhani, S. Makki
{"title":"BER performance of uplink massive MIMO with low-resolution ADCs","authors":"A. Azizzadeh, R. Mohammadkhani, S. Makki","doi":"10.1109/ICCKE.2017.8167895","DOIUrl":"https://doi.org/10.1109/ICCKE.2017.8167895","url":null,"abstract":"Massive multiple-input multiple-output (MIMO) is a promising technology for next generation wireless communication systems (5G). In this technology, Base Station (BS) is equipped with a large number of antennas. Employing high resolution analog-to-digital converters (ADCs) for all antennas may cause high costs and high power consumption for the BS. By performing numerical results, we evaluate the use of low-resolution ADCs for uplink massive MIMO by analyzing Bit Error Rate (BER) performance for different detection techniques (MMSE, ZF) and different modulations (QPSK, 16-QAM) to find an optimal quantization resolution. Our results reveal that the BER performance of uplink massive MIMO systems with a few-bit resolution ADCs is comparable to the case of having full precision ADCs. We found that the optimum choice of quantization level (number of bits in ADCs) depends on the modulation technique and the number of antennas at the BS.","PeriodicalId":151934,"journal":{"name":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132786484","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}
引用次数: 12
GLCM features and fuzzy nearest neighbor classifier for emotion recognition from face 基于GLCM特征和模糊最近邻分类器的人脸情感识别
2017 7th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2017-10-01 DOI: 10.1109/ICCKE.2017.8167879
M. Imani, G. Montazer
{"title":"GLCM features and fuzzy nearest neighbor classifier for emotion recognition from face","authors":"M. Imani, G. Montazer","doi":"10.1109/ICCKE.2017.8167879","DOIUrl":"https://doi.org/10.1109/ICCKE.2017.8167879","url":null,"abstract":"An emotion recognition method from the face images is proposed in this paper, which can recognize seven emotions of human, i.e., six basic expressions in addition to neutral. The proposed method uses the GLCM approach for feature extraction and the nearest neighbor (NN) for classification. The fuzzy Euclidean distance is used. GLCM provides the texture characteristics of an input image through the second order statistical measurements. Because of existence of vagueness and uncertainty in the discriminant features extracted from different emotional face images, the fuzzy measure is involved in the NN classifier to recognize the emotions of faces with more accuracy. The experiments show the good efficiency of the introduced recognition method compared to some other feature extraction and facial emotion recognition methods.","PeriodicalId":151934,"journal":{"name":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131803157","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}
引用次数: 5
Modeling intra-label dynamics in connectionist temporal classification 连接主义时态分类中标签内动态建模
2017 7th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2017-10-01 DOI: 10.1109/ICCKE.2017.8167906
Ashkan Sadeghi Lotfabadi, Kamaledin Ghiasi-Shirazi, A. Harati
{"title":"Modeling intra-label dynamics in connectionist temporal classification","authors":"Ashkan Sadeghi Lotfabadi, Kamaledin Ghiasi-Shirazi, A. Harati","doi":"10.1109/ICCKE.2017.8167906","DOIUrl":"https://doi.org/10.1109/ICCKE.2017.8167906","url":null,"abstract":"Most sequence processing tasks can be cast as a problem of mapping a sequence of observations into a sequence of labels. This is a very difficult problem since the association between input data sequences and output label sequences is not given at the frame level. Recurrent neural networks (RNNs) equipped with connectionist temporal classification (CTC) are among the best tools devised to handle this problem and have been used to achieve state of the art results in many handwritten and speech recognition tasks. The reason that RNNs are used instead of feedforward networks in combination with CTC is that CTC does not model the dynamics of sequences. Specifically, the long short term memory (LSTM) RNN, which is excellent at memorizing information for a long time, is used in combination with CTC to overcome the limitations of CTC in modeling the dynamics of sequences. In this paper, we propose to model each label with a sequence of hidden sub-labels at the CTC level. The proposed framework allows CTC to learn the intra-label relations which transfers part of the load of learning dynamical sequences from RNN to CTC. Our experiments on handwriting recognition tasks show that the proposed method outperforms standard CTC in terms of accuracy.","PeriodicalId":151934,"journal":{"name":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121278425","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}
引用次数: 1
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