2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA)最新文献

Localization and mobility of underwater acoustic sensor nodes 水声传感器节点的定位与移动

2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA) Pub Date : 2016-10-14 DOI: 10.1109/CT-IETA.2016.7868249

Vignesh Mandalapa Bhoopathy, Mohamed Ben Haj Frej, Steve Richard Ebenezer Amalorpavaraj, Imran K. Shaik

{"title":"Localization and mobility of underwater acoustic sensor nodes","authors":"Vignesh Mandalapa Bhoopathy, Mohamed Ben Haj Frej, Steve Richard Ebenezer Amalorpavaraj, Imran K. Shaik","doi":"10.1109/CT-IETA.2016.7868249","DOIUrl":"https://doi.org/10.1109/CT-IETA.2016.7868249","url":null,"abstract":"The Underwater Acoustic Sensor Network (UASN) is a network which consists of underwater wireless sensor nodes distributed randomly over the certain area of observation and communicate with each other using acoustic signals. UASN can be used in a wide variety of underwater applications, ranging from marine biology surveillance to earthquake and tsunami alert applications. Despite the fact that sensor networks are meant to collect data, in some applications, collection of data without a location of the occurrence becomes incoherent. Hence, localization for UASN has become an enthralling research topic in the recent years. However, there are several disadvantages of acoustic channel like propagation delay, limited energy sources, high bit error rate, and limited harvesting techniques underwater make the localization of UASN very challenging. Therefore, in this paper we have proposed a distributed localization scheme which employs two-way time of arrival estimation method to calculate distance and avoid the requirement of time synchronization","PeriodicalId":223031,"journal":{"name":"2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125749802","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: 10

Hybrid evolutionary designer of modular robots 模块化机器人的混合进化设计

2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA) Pub Date : 2016-10-01 DOI: 10.1109/CT-IETA.2016.7868256

Reem Alattas

引用次数: 2

Deep neural network combined posteriors for speakers' age and gender classification 深度神经网络结合说话人的后验进行年龄和性别分类

2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA) Pub Date : 2016-10-01 DOI: 10.1109/CT-IETA.2016.7868251

Arafat Abumallouh, Zakariya Qawaqneh, B. Barkana

{"title":"Deep neural network combined posteriors for speakers' age and gender classification","authors":"Arafat Abumallouh, Zakariya Qawaqneh, B. Barkana","doi":"10.1109/CT-IETA.2016.7868251","DOIUrl":"https://doi.org/10.1109/CT-IETA.2016.7868251","url":null,"abstract":"Various applications depend on speakers' age and gender to satisfy their customer needs. The age and gender information of a speaker are concealed in the speech signal, which is vary in time duration and is exposed to background noise. These effects make the speakers' age and gender prediction one of the most challenging problems in the field of speech processing. Recently, remarkable developments have been achieved in the neural network field. DNN is considered as one of the state-of-art classifiers. Due to the success of DNN in many speech applications, we propose combined posteriors of the softmax and last hidden layer for class model representation based on a trained DNN. DNN is used in this work to extract the softmax and last hidden layer posteriors from the concatenated frames for each utterance. The outputs of the combined posteriors for each frame in the training database are accumulated to form a new model for each class. Our experimental results showed that the proposed class model is capable of representing speakers age and gender for new utterances. The performance of the proposed work is evaluated by using GMM-UBM model on a publicly available Age-Annotated Database of a German Telephone Speech Database (aGender). The proposed work outperforms the baseline system by approximately 6% in terms of overall accuracy.","PeriodicalId":223031,"journal":{"name":"2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130240776","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

Theoretical modelling for enhancing contact-separation triboelectric nanogenerator performance 提高接触分离摩擦纳米发电机性能的理论建模

2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA) Pub Date : 2016-10-01 DOI: 10.1109/CT-IETA.2016.7868259

Ayman Abdelwahed, Mayssa Amin, M. Elosairy, N. Abbasy

{"title":"Theoretical modelling for enhancing contact-separation triboelectric nanogenerator performance","authors":"Ayman Abdelwahed, Mayssa Amin, M. Elosairy, N. Abbasy","doi":"10.1109/CT-IETA.2016.7868259","DOIUrl":"https://doi.org/10.1109/CT-IETA.2016.7868259","url":null,"abstract":"Triboelectric Nanogenerator (TENG) is a device which collects mechanical energy naturally wasted through ordinary daily human activities and converts it into useful electrical energy. Although extensive practical investigations have been made aiming at achieving better performance, theoretical studies have not taken its share of importance yet. In the present work a theoretical model for contact-separation mode TENG is presented and demonstrated. This model could be helpful in improving the performance of TENG through controlling its parameters. Previous theoretical work has mainly focused on optimizing the delivered maximum instantaneous power to the load and has not given much attention to the delivered energy. However, delivered energy to the load is very important aspect in any electrical device as it decides its efficiency. In this work a theoretical model is presented to predict the performance and different output characteristics including charge, current, potential difference and power of the TENG. This model can be used to optimize and enhance the performance of the TENGs by adjusting the load resistance, the average velocity of the moving electrode, the thicknesses of the electrodes and the relative permittivity to deliver maximum energy to the load. Numerical application is given through a case study to realize the effectiveness of the suggested model.","PeriodicalId":223031,"journal":{"name":"2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127781761","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

An innovative delay based algorithm to boost PUF security against machine learning attacks 一种创新的基于延迟的算法，以提高PUF的安全性，防止机器学习攻击

2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA) Pub Date : 2016-10-01 DOI: 10.1109/CT-IETA.2016.7868242

Fathi H. Amsaad, Muhtadi Choudhury, C. Chaudhuri, M. Niamat

引用次数: 4

Emulating grid cell spatial cognition in an FPGA 基于FPGA的网格单元空间认知仿真

2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA) Pub Date : 2016-10-01 DOI: 10.1109/CT-IETA.2016.7868255

Peter J. Zeno

引用次数: 0

Modifying deep neural network structure for improved learning rate in speakers' age and gender classification 修改深度神经网络结构，提高说话人年龄和性别分类的学习率

2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA) Pub Date : 2016-10-01 DOI: 10.1109/CT-IETA.2016.7868252

Zakariya Qawaqneh, Arafat Abumallouh, B. Barkana

{"title":"Modifying deep neural network structure for improved learning rate in speakers' age and gender classification","authors":"Zakariya Qawaqneh, Arafat Abumallouh, B. Barkana","doi":"10.1109/CT-IETA.2016.7868252","DOIUrl":"https://doi.org/10.1109/CT-IETA.2016.7868252","url":null,"abstract":"Speaker's age and gender classification is one of the most challenging problems in the field of acoustic recognition. Although many studies have been done to obtain better results, the classification accuracies are still not satisfactory. Motivated by the success in the deep learning techniques in speech processing field, we developed a DNN architecture to classify speakers' age and gender. In this work, we propose a new data model and we make modifications in GB-RBM and the BB-RBM architectures. This work shows that DNN can be trained by using age and gender real valued data and it will have a solid expressive and distinctive capability to classify the speaker's age and gender if the DNN is skillfully initialized and trained. Experimental results showed that the proposed DNN model and modifications achieved faster learning. To evaluate the proposed model, several experiments were conducted. The dimensional grey scale displays for the activation probability of hidden units, weights and biases histograms, and the MSE metrics were used.","PeriodicalId":223031,"journal":{"name":"2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132914673","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

Optimum allocation of distributed generation units in distribution power grids with line losses and voltage sag considerations 考虑线损和电压暂降的配电网分布式发电机组优化配置

2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA) Pub Date : 2016-10-01 DOI: 10.1109/CT-IETA.2016.7868260

Sahar Abdel Moneim Moussa, Ayman Abdelwahed

引用次数: 2

Improved monostatic pulse radar design using ultra wide band for range estimation 利用超宽带进行距离估计的改进单站脉冲雷达设计

2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA) Pub Date : 2016-10-01 DOI: 10.1109/CT-IETA.2016.7868245

A. V. N. R. Sai Shiva, K. Elleithy, Eman Abdelfattah

引用次数: 3

Hardware-based FIR filter implementations for ECG signal denoising: A monitoring framework from industrial electronics perspective 基于硬件的心电信号去噪FIR滤波器实现:从工业电子角度的监测框架

2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA) Pub Date : 2016-10-01 DOI: 10.1109/CT-IETA.2016.7868243

Salam Al-Khammasi, K. Aboalayon, M. Daneshzand, Misagh Faezipour, M. Faezipour

{"title":"Hardware-based FIR filter implementations for ECG signal denoising: A monitoring framework from industrial electronics perspective","authors":"Salam Al-Khammasi, K. Aboalayon, M. Daneshzand, Misagh Faezipour, M. Faezipour","doi":"10.1109/CT-IETA.2016.7868243","DOIUrl":"https://doi.org/10.1109/CT-IETA.2016.7868243","url":null,"abstract":"This work represents the design and verification of three different finite impulse response (FIR) filter implementations for removing the noise of electrocardiogram (ECG) signals. Generally, ECG signals may be contaminated with different noise sources such as body movement and respiration, electromyography (EMG) interference, power line interference and the baseline wander noise. The FIR filter coefficients are calculated to attenuate the 60 Hz frequencies. The advanced filter design tool available with MATLAB is used to first determine the FIR filter coefficients. These coefficients are then used in three different FIR filter implementations: regular implementation, pipelined implementation and pipelined multiply-accumulate (MAC) implementation. The three implementations are designed using VHDL and the Quartus II design toolset. A test bench is also designed to verify the operation of each filter implementation, and the Modelsim simulator available with Quartus is used to run the tests. The synthesized reports for the three different implementations show the resource utilization and the maximum operating frequency. As a result, the regular (direct) design produces the simplest design but consumes more resources and operates at lower frequencies. The pipelined architecture consumes more resources but it enhances the operating frequency. The pipelined MAC implementation requires the least resources and operates at extremely higher performance, however, the main drawback is its complexity. The hardware implementations can be further viewed as an industrial ECG monitoring framework where system dynamics modeling can be applied to minimize the risks associated with the framework using any of the three implementations.","PeriodicalId":223031,"journal":{"name":"2016 Annual Connecticut Conference on Industrial Electronics, Technology & Automation (CT-IETA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123359456","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: 10