2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS)最新文献

Temperature and noise cancellation for Carbon Nanotube ISFET Sensor 碳纳米管ISFET传感器的温度和噪声消除

2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS) Pub Date : 2021-06-07 DOI: 10.1109/DTS52014.2021.9498193

Ahmed Gaddour, W. Dghais, B. Hamdi, M. Ali

引用次数: 0

Combining of TD-GC-MS and home developed electronic nose for road traffic air monitoring 将TD-GC-MS与国内研制的道路交通空气监测电子鼻相结合

2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS) Pub Date : 2021-06-07 DOI: 10.1109/DTS52014.2021.9498110

M. Moufid, C. Tiebe, N. El Bari, M. Bartholmai, B. Bouchikhi

{"title":"Combining of TD-GC-MS and home developed electronic nose for road traffic air monitoring","authors":"M. Moufid, C. Tiebe, N. El Bari, M. Bartholmai, B. Bouchikhi","doi":"10.1109/DTS52014.2021.9498110","DOIUrl":"https://doi.org/10.1109/DTS52014.2021.9498110","url":null,"abstract":"In this work, we demonstrate the ability of an electronic nose system based on an array of six-semiconductor gas sensors for outdoor air quality monitoring over a day at a traffic road in downtown of Meknes city (Morocco). The response of the sensor array reaches its maximum in the evening of the investigated day which may due to high vehicular traffic or/and human habits resulting in elevated concentrations of pollutants. Dataset treatment by Principal Component Analysis and Discriminant Function Analysis shows a good discrimination between samples collected at different times of the day. Moreover, Support Vector Machines were used and reached a classification success rate of 97.5 %. Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS) technique was used to validate the developed e-nose system by identifying the composition of the analyzed air samples. The discrimination obtained by e-nose system was in good agreement with the TD-GC-MS results. This study demonstrates the usefulness of TD-GC-MS and e-nose, providing high accuracy in discriminating outdoor air samples collected at different times. This demonstrates the potential of using the e-nose as a rapid, easy to use and inexpensive environmental monitoring system.","PeriodicalId":158426,"journal":{"name":"2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124376321","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

Classification and Identification of Alzheimer Disease With Fuzzy Logic Method 模糊逻辑方法在阿尔茨海默病分类识别中的应用

2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS) Pub Date : 2021-06-07 DOI: 10.1109/DTS52014.2021.9498257

Ikbel Haouas, Mourad Moussa, A. Douik

引用次数: 2

An efficient FPGA-based design for the AVMF filter 基于fpga的高效AVMF滤波器设计

2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS) Pub Date : 2021-06-07 DOI: 10.1109/DTS52014.2021.9498232

A. Atitallah

引用次数: 0

An autonomous acoustic collar to quantify the severity of covid-19 effects by analyzing the vibratory components of vocal and respiratory systems 一种自主声学项圈，通过分析声音和呼吸系统的振动成分来量化covid-19影响的严重程度

2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS) Pub Date : 2021-06-07 DOI: 10.1109/DTS52014.2021.9498235

V. Elias, A. Rabih, S. Bin, H. Aziz, G. Nassar

引用次数: 0

A Two-stage Area-efficient High Input Impedance CMOS Amplifier for Neural Signals 一种用于神经信号的两级面积高效高输入阻抗CMOS放大器

2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS) Pub Date : 2021-06-07 DOI: 10.1109/DTS52014.2021.9498105

Erwin H. T. Shad, M. Molinas, T. Ytterdal

{"title":"A Two-stage Area-efficient High Input Impedance CMOS Amplifier for Neural Signals","authors":"Erwin H. T. Shad, M. Molinas, T. Ytterdal","doi":"10.1109/DTS52014.2021.9498105","DOIUrl":"https://doi.org/10.1109/DTS52014.2021.9498105","url":null,"abstract":"In this article, a two-stage area-efficient high input impedance neural amplifier is proposed. It has been shown that two single-stage amplifiers with low gain will consume less area in comparison with a single-stage high gain amplifier for capacitively coupled amplifiers. Besides, splitting a high gain amplifier into two single-stages in this structure leads to achieving a higher input impedance at the end. Furthermore, it helps to boost the input impedance at a higher frequency. The robustness of the proposed structure is investigated by process and mismatch Monte Carlo simulations. All the simulations are run using in a commercially available 0.18 μm CMOS technology. Based on post-layout simulation, the proposed two-stage amplifier has 53 dB mid-band gain in the bandwidth of 5 Hz to 10 kHz. The input impedance is 2.8 GΩ and 56 MΩ at 1 kHz and 10 kHz, respectively. In comparison to a single-stage amplifier, the proposed structure boosted the input impedance at frequencies up to 1 kHz by a factor of 10 while the power consumption increased only 0.5 μW. Furthermore, the proposed two-stage neural amplifier area consumption is 0.02 mm2 without pads which decreased area consumption by a factor of 3.","PeriodicalId":158426,"journal":{"name":"2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128823442","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

Towards Autonomous Node Sensors: Green Versus RF Energy Harvesting 自主节点传感器:绿色与射频能量收集

2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS) Pub Date : 2021-06-07 DOI: 10.1109/DTS52014.2021.9498247

Bilel Maamer, Nesrine Jaziri, S. Kaziz, F. Tounsi

引用次数: 2

Novel Capacitive MEMS Logic Gates For Logic Circuits and Systems 用于逻辑电路和系统的新型电容式MEMS逻辑门

2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS) Pub Date : 2021-06-07 DOI: 10.1109/DTS52014.2021.9498255

H. Samaali, Mohamed Amin Ben Hassena, F. Najar

引用次数: 0

Comparison of machine learning algorithms to predict daily water consumptions 预测日常用水量的机器学习算法比较

2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS) Pub Date : 2021-06-07 DOI: 10.1109/DTS52014.2021.9498103

Aida Boudhaouia, P. Wira

{"title":"Comparison of machine learning algorithms to predict daily water consumptions","authors":"Aida Boudhaouia, P. Wira","doi":"10.1109/DTS52014.2021.9498103","DOIUrl":"https://doi.org/10.1109/DTS52014.2021.9498103","url":null,"abstract":"This paper focuses on a comparison of machine learning algorithms for predicting the cumulative daily water consumption. The data are collected from an internet-based platform that provides usable data. A pre-processing has been designed for checking the integrity of data, i.e., detecting missing data and abnormal consumptions. In order to optimize the water uses in distribution networks, monitoring and forecasting consumption are good solutions. Five models, namely the Polynomial Regression (PR), Nonlinear AutoRegressive (NAR), Support Vector Regression (SVR), MultiLayer Perceptron (MLP) and Long Short-Term Memory (LSTM) are designed and compared to find the most accurate solution to forecast daily water consumption. The performance of these models is based on the Root Mean Square Error (RMSE) calculated from desired values. The water consumption for the next five days is predicted with no prior information but only centralized past measurements. Results show a predicting precision with NAR of about 5 and 23 l/day in respectively domestic and industrial installations where up to 1500 and 2700 l/day can be used.","PeriodicalId":158426,"journal":{"name":"2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117038631","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

DCT -II Transform Hardware-Based Acceleration for VVC Standard 基于DCT -II变换硬件的VVC加速标准

2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS) Pub Date : 2021-06-07 DOI: 10.1109/DTS52014.2021.9498196

Werda Imen, Belghith Fatma, Maraoui Amna, N. Masmoudi

引用次数: 8