Pub Date : 2018-03-16DOI: 10.1109/CONECCT.2018.8482369
Shalini Tomar, P. Rastogi, B. Bhadoria, S. Bhowmick, A. Agarwal, S. Yogesh Chauhan
Recently two dimensional layer of 8-Pmmn borophene has been successfully fabricated on single crystal Ag(111) substrate and shown to have a tilted anisotropic Diraccone. In this paper we investigate the strain dependent carrier mobility in 8 - Pmmn borophene. We calculate the electronic structure, group velocity and carrier mobility of 8 - Pmmn borophene using density functional theory coupled with Boltzmann transport method using constant relaxation time approximation. Our results show that bandstructure anisotropy results in anisotropic group velocity and mobility. The intrinsic group velocity and mobility at room temperature are calculated to be 2. $17 times 10^{6ms^{-1}}$, 2. $42 times 10^{6ms^{-1}}$ and 1. $82 times 10^{6 cm^{2V^{-1s^{-1}}},2.26times 10^{6 cm^{2V^{-1s^{-1}}}}}$ in $+x, +y$ direction as well as $1.56times 10^{6ms^{-1}}, 2.43times 10^{6ms^{-1}}$ and $9.42times 10^{5} cm^{2}V^{-1}s^{-1}, 2.29times 10^{6 cm^{2V^{-1s^{-1}}}}$, in - x, - y directions, respectively. Both of them are found to be highest under 1% compressive strain.
最近在单晶Ag(111)衬底上成功制备了8-Pmmn硼罗芬的二维层，并证明其具有倾斜的各向异性狄拉克锥。本文研究了8 - Pmmn硼罗芬中载流子迁移率随应变的变化。利用密度泛函理论和恒定松弛时间近似的玻尔兹曼输运方法计算了8 - Pmmn硼罗芬的电子结构、群速度和载流子迁移率。结果表明，各向异性导致了各向异性基团速度和迁移率。计算室温下的本征群速度和迁移率为2。$17 乘以10^{6ms^{-1}}$， 2。$42 乘以10^{6ms^{-1}}$和1。82美元 * 10 ^{6厘米^ {2 V ^ {1 s ^{1}}}, 2.26 * 10 ^{6厘米^ {2 V ^ {1 s ^ {1}}}}} + x美元,美元+ y方向以及1.56美元 * 10 ^ {6 ms ^ {1}}, 2.43 * 10 ^ {6 ms ^{1}} $和$ 9.42 * 10 ^{5}厘米^ {2}V ^ s ^{1}{1}, 2.29 * 10 ^{6厘米^ {2 V ^ {1 s ^{1}}}},美元- x - y方向,分别。在1%的压应变下，两者均达到最高。
{"title":"Strain Dependent Carrier Mobility in 8 − Pmmn Borophene: ab-initio study","authors":"Shalini Tomar, P. Rastogi, B. Bhadoria, S. Bhowmick, A. Agarwal, S. Yogesh Chauhan","doi":"10.1109/CONECCT.2018.8482369","DOIUrl":"https://doi.org/10.1109/CONECCT.2018.8482369","url":null,"abstract":"Recently two dimensional layer of 8-Pmmn borophene has been successfully fabricated on single crystal Ag(111) substrate and shown to have a tilted anisotropic Diraccone. In this paper we investigate the strain dependent carrier mobility in 8 - Pmmn borophene. We calculate the electronic structure, group velocity and carrier mobility of 8 - Pmmn borophene using density functional theory coupled with Boltzmann transport method using constant relaxation time approximation. Our results show that bandstructure anisotropy results in anisotropic group velocity and mobility. The intrinsic group velocity and mobility at room temperature are calculated to be 2. $17 times 10^{6ms^{-1}}$, 2. $42 times 10^{6ms^{-1}}$ and 1. $82 times 10^{6 cm^{2V^{-1s^{-1}}},2.26times 10^{6 cm^{2V^{-1s^{-1}}}}}$ in $+x, +y$ direction as well as $1.56times 10^{6ms^{-1}}, 2.43times 10^{6ms^{-1}}$ and $9.42times 10^{5} cm^{2}V^{-1}s^{-1}, 2.29times 10^{6 cm^{2V^{-1s^{-1}}}}$, in - x, - y directions, respectively. Both of them are found to be highest under 1% compressive strain.","PeriodicalId":430389,"journal":{"name":"2018 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"312 1-2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114010861","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 : 2018-03-16DOI: 10.1109/CONECCT.2018.8482365
P. Rastogi, A. Dasgupta, A. Chauhan
We explore the impact of channel area scaling in InGaAs gate-all-around transistor for circular (CNW), square (SNW) and triangular (TNW) cross-sections using coupled selfconsistent Schrodinger-Poisson solver. We find that, among all three cross-sections, TNW shows the strongest confinement effect for all the considered dimensions. The confinement effects are significant at 10 nm for TNW and at 5 nm for SNW and CNW. We further analyzed the performance figure of merits (threshold voltage, current ON/OFF ratio, sub-threshold slope, ON current and intrinsic delay with cross-section area scaling) for all three cross-sections. Based on the scaling trend we find that CNW with 10 nm diameter is the most optimum among all three crosssections.
{"title":"Diameter Scaling in III-V Gate-All-Around Transistor for Different Cross-Sections","authors":"P. Rastogi, A. Dasgupta, A. Chauhan","doi":"10.1109/CONECCT.2018.8482365","DOIUrl":"https://doi.org/10.1109/CONECCT.2018.8482365","url":null,"abstract":"We explore the impact of channel area scaling in InGaAs gate-all-around transistor for circular (CNW), square (SNW) and triangular (TNW) cross-sections using coupled selfconsistent Schrodinger-Poisson solver. We find that, among all three cross-sections, TNW shows the strongest confinement effect for all the considered dimensions. The confinement effects are significant at 10 nm for TNW and at 5 nm for SNW and CNW. We further analyzed the performance figure of merits (threshold voltage, current ON/OFF ratio, sub-threshold slope, ON current and intrinsic delay with cross-section area scaling) for all three cross-sections. Based on the scaling trend we find that CNW with 10 nm diameter is the most optimum among all three crosssections.","PeriodicalId":430389,"journal":{"name":"2018 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115096211","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 : 2018-03-16DOI: 10.1109/CONECCT.2018.8482366
Ch. Aishwarya, Rajshekhar Mukherjee, D. Mahato
Here we have rendered a functional and architectural model of a system that assists the driver of a vehicle to detect, identify and track objects while driving. The objects detected include vehicle type as well as common on-road objects such as pedestrians. Layer structure for the system involves the design of a state-of-the-art deep learning classifier using a novel database for obtaining higher classification accuracy and another layer consisting of a single-frame object detection method to make the system more robust while limiting the processing time involved. Sub-systems integrated to facilitate the driver with relevant real-time information about his driving umwelt include vehicle identifier, number plate recognition system and creation of database consisting of collected information along with time-stamp. Performance degradation under various ambient conditions and variable environments with various synthetic noises being introduced in the video frames have been studied. Trade-off between speed and accuracy of a state-of-the-art real-time detection system implemented on various processing platforms is studied. Layers of deep learning classifier were trained using an optimized dataset consisting of static and dynamic images of vehicles to yield suitable prediction accuracy and this was combined with a system pre-trained on COCO dataset for YOLO. This helped complete the Intelligent Driver Assistant System. This paper also includes the implementation of real-time object detection on a single board computer. This concept can be tapped to create compact and portable driver assistant systems.
{"title":"Multilayer vehicle classification integrated with single frame optimized object detection framework using CNN based deep learning architecture","authors":"Ch. Aishwarya, Rajshekhar Mukherjee, D. Mahato","doi":"10.1109/CONECCT.2018.8482366","DOIUrl":"https://doi.org/10.1109/CONECCT.2018.8482366","url":null,"abstract":"Here we have rendered a functional and architectural model of a system that assists the driver of a vehicle to detect, identify and track objects while driving. The objects detected include vehicle type as well as common on-road objects such as pedestrians. Layer structure for the system involves the design of a state-of-the-art deep learning classifier using a novel database for obtaining higher classification accuracy and another layer consisting of a single-frame object detection method to make the system more robust while limiting the processing time involved. Sub-systems integrated to facilitate the driver with relevant real-time information about his driving umwelt include vehicle identifier, number plate recognition system and creation of database consisting of collected information along with time-stamp. Performance degradation under various ambient conditions and variable environments with various synthetic noises being introduced in the video frames have been studied. Trade-off between speed and accuracy of a state-of-the-art real-time detection system implemented on various processing platforms is studied. Layers of deep learning classifier were trained using an optimized dataset consisting of static and dynamic images of vehicles to yield suitable prediction accuracy and this was combined with a system pre-trained on COCO dataset for YOLO. This helped complete the Intelligent Driver Assistant System. This paper also includes the implementation of real-time object detection on a single board computer. This concept can be tapped to create compact and portable driver assistant systems.","PeriodicalId":430389,"journal":{"name":"2018 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126981416","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 : 2018-03-16DOI: 10.1109/CONECCT.2018.8482385
Nikumani Choudhury, Rakesh Matam, M. Mukherjee
IEEE 802.15.4 devices operating in beacon-enabled mode synchronize their beacon transmissions to restrict collisions and increase network lifetime. Other avenues of conserving energy in these resource constrained networks is via adaptive duty-cycling. This can be achieved by accounting for the idle listening of a coordinator and its associated devices. But, duty-cycling in a synchronized network often results in loss of synchronization and necessitates re-synchronization. In this paper, we first showcase the scope for additional energy savings in a synchronized network that can be accounted for using a adaptive duty-cycling scheme. Thereafter, we present the necessary condition that needs to be met to perform duty-cycling. We analytically determine the associated cost of synchronization in presence of an active duty-cycling mechanism and compare it with the energy conserved by performing the later. The simulation results concur with our findings and emphasize on the need for operation of synchronization and duty-cycling schemes in sync with each other to boost the overall energy savings of the network.
{"title":"Duty-Cycling in Synchronized IEEE 802.15.4 Cluster-Tree Networks","authors":"Nikumani Choudhury, Rakesh Matam, M. Mukherjee","doi":"10.1109/CONECCT.2018.8482385","DOIUrl":"https://doi.org/10.1109/CONECCT.2018.8482385","url":null,"abstract":"IEEE 802.15.4 devices operating in beacon-enabled mode synchronize their beacon transmissions to restrict collisions and increase network lifetime. Other avenues of conserving energy in these resource constrained networks is via adaptive duty-cycling. This can be achieved by accounting for the idle listening of a coordinator and its associated devices. But, duty-cycling in a synchronized network often results in loss of synchronization and necessitates re-synchronization. In this paper, we first showcase the scope for additional energy savings in a synchronized network that can be accounted for using a adaptive duty-cycling scheme. Thereafter, we present the necessary condition that needs to be met to perform duty-cycling. We analytically determine the associated cost of synchronization in presence of an active duty-cycling mechanism and compare it with the energy conserved by performing the later. The simulation results concur with our findings and emphasize on the need for operation of synchronization and duty-cycling schemes in sync with each other to boost the overall energy savings of the network.","PeriodicalId":430389,"journal":{"name":"2018 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133001910","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 : 2018-03-16DOI: 10.1109/CONECCT.2018.8482380
C. S. Asha, A. V. Narasimhadhan
Vehicle counting is a process to estimate the road traffic density to assess the traffic conditions for intelligent transportation systems. With the extensive utilization of cameras in urban transport systems, the surveillance video has become a central data source. Also, real-time traffic management system has become popular recently due to the availability of handheld/mobile cameras and big-data analysis. In this work, we propose video-based vehicle counting method in a highway traffic video captured using handheld cameras. The processing of a video is achieved in three stages such as object detection by means of YOLO (You Only Look Once), tracking with correlation filter, and counting. YOLO attained remarkable outcome in the object detection area, and correlation filters achieved greater accuracy and competitive speed in tracking. Thus, we build multiple object tracking with correlation filters using the bounding boxes generated by the YOLO framework. Experimental analysis using real video sequences shows that the proposed method can detect, track and count the vehicles accurately.
车辆计数是估计道路交通密度以评估智能交通系统交通状况的过程。随着摄像机在城市交通系统中的广泛应用，监控视频已成为一个中心数据来源。此外，由于手持/移动相机和大数据分析的可用性，实时交通管理系统最近变得流行起来。在这项工作中，我们提出了基于视频的车辆计数方法，用于使用手持摄像机拍摄的高速公路交通视频。视频的处理分为三个阶段:YOLO (You Only Look Once)的目标检测、相关滤波器的跟踪和计数。YOLO在目标检测领域取得了显著的效果，相关滤波器在跟踪方面取得了更高的精度和速度。因此，我们使用YOLO框架生成的边界框构建带有相关过滤器的多目标跟踪。对真实视频序列的实验分析表明，该方法能够准确地检测、跟踪和计数车辆。
{"title":"Vehicle Counting for Traffic Management System using YOLO and Correlation Filter","authors":"C. S. Asha, A. V. Narasimhadhan","doi":"10.1109/CONECCT.2018.8482380","DOIUrl":"https://doi.org/10.1109/CONECCT.2018.8482380","url":null,"abstract":"Vehicle counting is a process to estimate the road traffic density to assess the traffic conditions for intelligent transportation systems. With the extensive utilization of cameras in urban transport systems, the surveillance video has become a central data source. Also, real-time traffic management system has become popular recently due to the availability of handheld/mobile cameras and big-data analysis. In this work, we propose video-based vehicle counting method in a highway traffic video captured using handheld cameras. The processing of a video is achieved in three stages such as object detection by means of YOLO (You Only Look Once), tracking with correlation filter, and counting. YOLO attained remarkable outcome in the object detection area, and correlation filters achieved greater accuracy and competitive speed in tracking. Thus, we build multiple object tracking with correlation filters using the bounding boxes generated by the YOLO framework. Experimental analysis using real video sequences shows that the proposed method can detect, track and count the vehicles accurately.","PeriodicalId":430389,"journal":{"name":"2018 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130182367","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 : 2018-03-16DOI: 10.1109/CONECCT.2018.8482374
P. Rastogi, S. Bhowmick, A. Agarwal, Y. Chauhan
We explore the impact of Silicon (Si) and Germanium (Ge) thickness scaling (from 1 to 5 nm) on their electronic and transport properties using density functional theory. We find that in Ge, the lowest conduction band valley shifts from L in bulk to X in ultrathin slabs, and at 1 nm thickness Ge reduces to a direct band gap semiconductor. On the other hand, Si changes to a direct band-gap semiconductor in the thickness range of 1 to 5 nm, as opposed to its indirect nature in bulk form. We show that the electron-phonon coupling, which is the dominant scattering mechanism in these materials, is found to be very weak in scaled Ge-slabs as compared to Si-slabs. This in combination with drastically reduced longitudinal effective mass in thin Geslabs, leads to very high electron mobility in scaled Ge films, which increases with decreasing thickness. Our reported mobility trend in Ge-slabs is in agreement with the recently reported experimental results. For Si-slabs, we show that 3 nm is the most suitable thickness for future ultrathin Si devices as it has the lowest conduction band deformation potential and highest electron mobility.
{"title":"Atomistic Study of Acoustic Phonon Limited Mobility in Extremely Scaled Si and Ge Films","authors":"P. Rastogi, S. Bhowmick, A. Agarwal, Y. Chauhan","doi":"10.1109/CONECCT.2018.8482374","DOIUrl":"https://doi.org/10.1109/CONECCT.2018.8482374","url":null,"abstract":"We explore the impact of Silicon (Si) and Germanium (Ge) thickness scaling (from 1 to 5 nm) on their electronic and transport properties using density functional theory. We find that in Ge, the lowest conduction band valley shifts from L in bulk to X in ultrathin slabs, and at 1 nm thickness Ge reduces to a direct band gap semiconductor. On the other hand, Si changes to a direct band-gap semiconductor in the thickness range of 1 to 5 nm, as opposed to its indirect nature in bulk form. We show that the electron-phonon coupling, which is the dominant scattering mechanism in these materials, is found to be very weak in scaled Ge-slabs as compared to Si-slabs. This in combination with drastically reduced longitudinal effective mass in thin Geslabs, leads to very high electron mobility in scaled Ge films, which increases with decreasing thickness. Our reported mobility trend in Ge-slabs is in agreement with the recently reported experimental results. For Si-slabs, we show that 3 nm is the most suitable thickness for future ultrathin Si devices as it has the lowest conduction band deformation potential and highest electron mobility.","PeriodicalId":430389,"journal":{"name":"2018 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116023143","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 : 2018-03-16DOI: 10.1109/CONECCT.2018.8482389
K. K, Ankit Rathore, V. B, P. D. Shenoy, V. R., Vignesh T Prabhu
The infrastructure of the Tor network is completely dependent on the relays voluntarily contributing their bandwidth for the community. Although the network provides a very high level of anonymity to the end user, it is designed such that the anonymity comes at the cost of very high latency. Hence, improving the performance of Tor network is always a very important aspect of the Tor project. Token Bucket algorithm is used in relays to ensure that the packets sent by clients are not lost and the bandwidth limits configured by the relay administrator is respected. In Token bucket algorithm, an important aspect is the Token Bucket Refill Interval which decides on how often the tokens are added to the bucket. In the Tor network, a default value of 100ms is used. This value is vindictive for a network where the majority of the clients are web clients with small download size. But as the bulk clients increase, it is important to understand how the value of Token Bucket Refill Interval impacts the performance of the network. In this paper, we continue on the previous work done to find the optimum value for Token Bucket Refill Interval for different scenarios of Tor network. Based on the simulations, we have found that download size of the clients is inversely related to the Token Bucket Refill Interval for the overall performance of the network. A larger value of Token Bucket Refill Interval gives a much better performance in Tor network when download size is small. However, as the download size increases, lower values of Token Bucket Refill Interval show better performance in Tor network.
{"title":"Optimal Token Bucket Refilling for Tor network","authors":"K. K, Ankit Rathore, V. B, P. D. Shenoy, V. R., Vignesh T Prabhu","doi":"10.1109/CONECCT.2018.8482389","DOIUrl":"https://doi.org/10.1109/CONECCT.2018.8482389","url":null,"abstract":"The infrastructure of the Tor network is completely dependent on the relays voluntarily contributing their bandwidth for the community. Although the network provides a very high level of anonymity to the end user, it is designed such that the anonymity comes at the cost of very high latency. Hence, improving the performance of Tor network is always a very important aspect of the Tor project. Token Bucket algorithm is used in relays to ensure that the packets sent by clients are not lost and the bandwidth limits configured by the relay administrator is respected. In Token bucket algorithm, an important aspect is the Token Bucket Refill Interval which decides on how often the tokens are added to the bucket. In the Tor network, a default value of 100ms is used. This value is vindictive for a network where the majority of the clients are web clients with small download size. But as the bulk clients increase, it is important to understand how the value of Token Bucket Refill Interval impacts the performance of the network. In this paper, we continue on the previous work done to find the optimum value for Token Bucket Refill Interval for different scenarios of Tor network. Based on the simulations, we have found that download size of the clients is inversely related to the Token Bucket Refill Interval for the overall performance of the network. A larger value of Token Bucket Refill Interval gives a much better performance in Tor network when download size is small. However, as the download size increases, lower values of Token Bucket Refill Interval show better performance in Tor network.","PeriodicalId":430389,"journal":{"name":"2018 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116615996","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 : 2018-03-16DOI: 10.1109/CONECCT.2018.8482382
S. Kanaga, Bhuvnesh Kushwah, Gourab Dutta, N. Dasgupta, A. DasGupta
AlInN/GaN metal insulator semiconductor high electron mobility transistor (MIS-HEMT) with high pressure oxidized aluminium as gate dielectric is investigated in this paper. The fabricated MIS-HEMT shows more than six orders of reduction in the gate leakage current in reverse bias and more than three orders of reduction in forward bias compared to the reference HEMT devices also fabricated on same substrates. A maximum drain current of 750 mA/mm was achieved due to improvement in the gate swing for MIS- HEMT. The MIS-HEMT devices also showed good improvement in the subthreshold slope and ID,ON/ID,OFF ratio compared to HEMT devices.
{"title":"AlInN/GaN MIS-HEMTs with High Pressure Oxidized Aluminium as Gate Dielectric","authors":"S. Kanaga, Bhuvnesh Kushwah, Gourab Dutta, N. Dasgupta, A. DasGupta","doi":"10.1109/CONECCT.2018.8482382","DOIUrl":"https://doi.org/10.1109/CONECCT.2018.8482382","url":null,"abstract":"AlInN/GaN metal insulator semiconductor high electron mobility transistor (MIS-HEMT) with high pressure oxidized aluminium as gate dielectric is investigated in this paper. The fabricated MIS-HEMT shows more than six orders of reduction in the gate leakage current in reverse bias and more than three orders of reduction in forward bias compared to the reference HEMT devices also fabricated on same substrates. A maximum drain current of 750 mA/mm was achieved due to improvement in the gate swing for MIS- HEMT. The MIS-HEMT devices also showed good improvement in the subthreshold slope and ID,ON/ID,OFF ratio compared to HEMT devices.","PeriodicalId":430389,"journal":{"name":"2018 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122678506","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 : 2018-03-16DOI: 10.1109/CONECCT.2018.8482379
Priyanka Saha, S. Sarkhel, Pritha Banerjee, S. Sarkar
This paper aims to develop a physics based 3Danalytical modeling of potential prof ile and electric field distribution of a newly proposed dual material trigate (DMTG) Silicon On Nothing (SON) TFET with SiO2/HfO2 stacked gate oxide to reap the dual benefits of gate material and dielectric engineering techniques. Based on the derived electric field, drain current is obtained using Kane’s tunneling model. An overall comparative performance analysis of the present structure is done to establish the functional efficiency of the model over its SMTG equivalent in terms of surface potential, electric field, ON current and ambipolar conduction. The analytical results obtained are verified with 3DATLAS device simulator data to substantiate the accuracy of the derived model.
{"title":"3D Modeling based Performance Analysis of Gate Engineered Trigate SON TFET with SiO2/HfO2 stacked gate oxide","authors":"Priyanka Saha, S. Sarkhel, Pritha Banerjee, S. Sarkar","doi":"10.1109/CONECCT.2018.8482379","DOIUrl":"https://doi.org/10.1109/CONECCT.2018.8482379","url":null,"abstract":"This paper aims to develop a physics based 3Danalytical modeling of potential prof ile and electric field distribution of a newly proposed dual material trigate (DMTG) Silicon On Nothing (SON) TFET with SiO2/HfO2 stacked gate oxide to reap the dual benefits of gate material and dielectric engineering techniques. Based on the derived electric field, drain current is obtained using Kane’s tunneling model. An overall comparative performance analysis of the present structure is done to establish the functional efficiency of the model over its SMTG equivalent in terms of surface potential, electric field, ON current and ambipolar conduction. The analytical results obtained are verified with 3DATLAS device simulator data to substantiate the accuracy of the derived model.","PeriodicalId":430389,"journal":{"name":"2018 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126759031","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 : 2018-03-16DOI: 10.1109/CONECCT.2018.8482372
Abin M Abraham, N. Kulkarni, Nikhil Clement, Lakshmeesha Bhat, Nikita Misale, Thwaha Hussain, S. Mohalik, Badrinath Ramamurthy
As IoT devices proliferate, platforms and programming environments to develop IoT-based systems are becoming commonplace. However, the current models of development will soon prove to be inadequate due to the exploding scale, variety and dynamism in the IoT ecosystems, which is making it imperative that these systems manage and operate themselves in an autonomous fashion. Specifically, IoT-based systems must be able to adapt themselves intelligently to changes in the device hardware and software, the context and context-dependent policies and continue delivering to the requirements. Unfortunately, current IoT platforms and programming environments do not have any native support for such intelligence. In order to address this lacuna, we suggest additional components and APIs that can support intelligent autonomy based on the MAPE-K (Monitor, Analyze, Plan, Execute, Knowledge) architecture. The solution is demonstrated through a couple of concrete case studies implemented using IoT sensors and actuators on Raspberry Pi boards, openHAB - a popular IoT automation environment, Metric-FF - a well-known search-based AI planner and Leshan, an LwM2M platform for providing the sensing and actuation interfaces of the IoT devices.
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