| 1. |
- Karlsson, M., et al.
(författare)
-
Wafer-scale epitaxial graphene on SiC for sensing applications
- 2015
-
Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE - The International Society for Optics and Photonics. - 9781628418903
-
Konferensbidrag (refereegranskat)abstract
- The epitaxial graphene-on-silicon carbide (SiC-G) has advantages of high quality and large area coverage owing to a natural interface between graphene and SiC substrate with dimension up to 100 mm. It enables cost effective and reliable solutions for bridging the graphene-based sensors/devices from lab to industrial applications and commercialization. In this work, the structural, optical and electrical properties of wafer-scale graphene grown on 2'™'™ 4H semi-insulating (SI) SiC utilizing sublimation process were systemically investigated with focus on evaluation of the graphene'™s uniformity across the wafer. As proof of concept, two types of glucose sensors based on SiC-G/Nafion/Glucose-oxidase (GOx) and SiC-G/Nafion/Chitosan/GOx were fabricated and their electrochemical properties were characterized by cyclic voltammetry (CV) measurements. In addition, a few similar glucose sensors based on graphene by chemical synthesis using modified Hummer'™s method were also fabricated for comparison.
|
|
| 2. |
- Loni, Mohammad, et al.
(författare)
-
NeuroPower : Designing Energy Efficient Convolutional Neural Network Architecture for Embedded Systems
- 2019
-
Ingår i: Lecture Notes in Computer Science, Volume 11727. - Munich, Germany : Springer. - 9783030304867 ; 11727 LNCS, s. 208-222
-
Konferensbidrag (refereegranskat)abstract
- Convolutional Neural Networks (CNNs) suffer from energy-hungry implementation due to their computation and memory intensive processing patterns. This problem is even more significant by the proliferation of CNNs on embedded platforms. To overcome this problem, we offer NeuroPower as an automatic framework that designs a highly optimized and energy efficient set of CNN architectures for embedded systems. NeuroPower explores and prunes the design space to find improved set of neural architectures. Toward this aim, a multi-objective optimization strategy is integrated to solve Neural Architecture Search (NAS) problem by near-optimal tuning network hyperparameters. The main objectives of the optimization algorithm are network accuracy and number of parameters in the network. The evaluation results show the effectiveness of NeuroPower on energy consumption, compacting rate and inference time compared to other cutting-edge approaches. In comparison with the best results on CIFAR-10/CIFAR-100 datasets, a generated network by NeuroPower presents up to 2.1x/1.56x compression rate, 1.59x/3.46x speedup and 1.52x/1.82x power saving while loses 2.4%/-0.6% accuracy, respectively.
|
|
| 3. |
- Lu, Zhonghai, et al.
(författare)
-
Wearable pressure sensing for lower limb amputees
- 2022
-
Ingår i: BioCAS 2022 - IEEE Biomedical Circuits and Systems Conference. - : Institute of Electrical and Electronics Engineers Inc.. - 9781665469173 ; , s. 105-109, s. 105-109
-
Konferensbidrag (refereegranskat)abstract
- Pressure sensing in prosthetic sockets is valuable as it provides quantified data to assist prosthetists in designing comfortable sockets for amputees. We present a wearable pressure sensing system for lower limb amputees. The full system consists of three essential elements from sensing scheme (wearable sensors, sensor calibration and deployment), electronic measurement system (embedded hardware and software), to time-series database and visualization. The full system has been successfully applied in clinical trials to effectively collect pressure data in real-time.
|
|
| 4. |
- Nikoui, T. S., et al.
(författare)
-
Container-Based Load Balancing and Monitoring Approach in Fog Computing System
- 2022
-
Ingår i: MELECON 2022 - IEEE Mediterranean Electrotechnical Conference, Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9781665442800 ; , s. 1159-1164
-
Konferensbidrag (refereegranskat)abstract
- The Internet of Things has become a fast-growing area and has attracted considerable attention from the research communities. To provide satisfactory performance and efficiency in smart applications, it is inevitable to apply proper and efficient load balancing mechanisms. This paper presents a container-based load balancing and monitoring approach in fog-cloud environments. The presented architecture is composed of application services, message queuing system and online monitoring tools to address fault-detection, reliability, higher efficiency and scalability that are essential requirements of smart applications. In addition, an implementation of the proposed approach by using well-known technologies is presented, and the system is evaluated. Results indicate that using this model satisfies the requirements and can be considered as a practical solution to fog computing applications.
|
|
| 5. |
- Shafaat, Tallat M., et al.
(författare)
-
Handling network partitions and mergers in structured overlay networks
- 2007
-
Ingår i: P2P. - 9780769529868 ; , s. 132-139
-
Konferensbidrag (refereegranskat)abstract
- Structured overlay networks form a major class of peer-to-peer systems, which are touted for their abilities to scale, tolerate failures, and self-manage. Any long-lived Internet-scale. distributed system is destined to face network partitions. Although the problem of network partitions and mergers is highly related to fault-tolerance and self-management in large-scale systems, it has hardly been studied in the context of structured peer-to-peer systems. These systems have mainly been studied under chum (frequent joins/failures), which as a side effect solves the problem of network partitions, as it is similar to massive node failures. Yet, the crucial aspect of network mergers has been ignored. In fact, it has been claimed that ring-based structured overlay networks, which constitute the majority of the structured overlays, are intrinsically ill-suited for merging rings. In this paper we present an algorithm for merging multiple similar ring-based overlays when the underlying network merges. We examine the solution in dynamic conditions, showing how our solution is resilient to churn during the merger something widely believed to be difficult or impossible. We evaluate the algorithm for various scenarios and show that even when falsely detecting a merger the algorithm quickly terminates and does not clutter the network with many messages. The algorithm is flexible as the tradeoff between message complexity and time complexity can be adjusted by a parameter.
|
|
