Efficient CFD Evaluation of Small Device Locations with Automatic Local Remeshing

2008 ◽  
Author(s):  
Yasushi Ito ◽  
Mitsuhiro Murayama ◽  
Kazuomi Yamamoto ◽  
Alan Shih ◽  
Bharat Soni
Keyword(s):  
Small Device

scholarly journals Computational design and optimization of electro-physiological sensors

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Aditya Shekhar Nittala ◽  
Andreas Karrenbauer ◽  
Arshad Khan ◽  
Tobias Kraus ◽  
Jürgen Steimle
Keyword(s):  
Form Factors ◽  
Computational Design ◽  
Quantitative Agreement ◽  
Physiological Data ◽  
High Signal ◽  
Signal Acquisition ◽  
Design And Optimization ◽  
Graphical Tool ◽  
Small Device ◽  
Physiological Sensors

AbstractElectro-physiological sensing devices are becoming increasingly common in diverse applications. However, designing such sensors in compact form factors and for high-quality signal acquisition is a challenging task even for experts, is typically done using heuristics, and requires extensive training. Our work proposes a computational approach for designing multi-modal electro-physiological sensors. By employing an optimization-based approach alongside an integrated predictive model for multiple modalities, compact sensors can be created which offer an optimal trade-off between high signal quality and small device size. The task is assisted by a graphical tool that allows to easily specify design preferences and to visually analyze the generated designs in real-time, enabling designer-in-the-loop optimization. Experimental results show high quantitative agreement between the prediction of the optimizer and experimentally collected physiological data. They demonstrate that generated designs can achieve an optimal balance between the size of the sensor and its signal acquisition capability, outperforming expert generated solutions.

scholarly journals A method for large scale implantation of 3D microdevice ensembles into brain and soft tissue

2020 ◽  
Author(s):  
Stefan A. Sigurdsson ◽  
Zeyang Yu ◽  
Joonhee Lee ◽  
Arto Nurmikko
Keyword(s):  
Polyethylene Glycol ◽  
High Throughput ◽  
Large Scale ◽  
Soft Tissues ◽  
Tissue Injury ◽  
Physiological Activity ◽  
Medical Diagnostics ◽  
Sensors And Actuators ◽  
Small Device ◽  
Minimal Damage

AbstractWireless networks of implantable electronic sensors and actuators on the microscale (sub-mm) are being explored for monitoring and modulation of physiological activity for medical diagnostics and therapeutic purposes. Beyond the requirement of integrating multiple electronic or chemical functions within small device volumes, a key challenge is the development of high-throughput methods for implantation of large numbers of microdevices into soft tissues with minimal damage. To that end, we have developed a method for high-throughput implantation of ∼100-200 μm size devices which are here simulated by proxy microparticle ensembles. While generally applicable to subdermal tissue, our main focus and experimental testbed is the implantation of microparticles into the brain. The method deploys a scalable delivery tool composed of a 2-dimensional array of polyethylene glycol tipped microneedles which confine the microparticle payloads. Upon dissolution of the bioresorbable polyethylene glycol, the supporting array structure is retrieved and the microparticles remain embedded in the tissue, distributed spatially and geometrically according to the design of the microfabricated delivery tool. We first evaluated the method in an agarose testbed in terms of spatial precision and throughput for up to 1000 passive spherical and planar microparticles acting as proxy devices. We then performed the same evaluations of particles implanted into the rat cortex under acute conditions and assessed the tissue injury produced by our method of implantation under chronic conditions.

scholarly journals PROGRAMMABLE LOGIC CONTROLLER TRAINING STANDS FOR EDUCATIONAL PURPOSES

2020 ◽  
pp. 274-280
Author(s):  
Michal Kelemen ◽  
Peter Ján Sinčák
Keyword(s):  
Programmable Logic Controller ◽  
Future Application ◽  
Programmable Logic ◽  
Training Set ◽  
Controlled System ◽  
Small Device ◽  
Logical State ◽  
Machine Interface ◽  
Practical Experiences ◽  
Application Developers

Urgency of the research. Programmable logic controller are devices for controlling of various systems also in industry. If controlled device is complicated, it is problem to debug application, because of risk of its damage. For this purpose is better to use hardware training stand for testing of your designed application. Target setting. Training stand is as compact small device which is easy to move to another place. Also it allows to connect other hardware device for testing. Logical state hardware simulator is also designed for simulation of logic system with any user inputs with buttons or switches and also witch coloured lights for visualisation of output state.Actual scientific researches and issues analysis. Training set allows to make simulation of control system with real parts before its practical use with expensive controlled system, where any mistake can cause a huge economist loses, but errors occurred during the simulation on training set only make warning and shows the weak place on design. Uninvestigated parts of general matters defining. The questions of the networked structure of programmable logic controller structures are uninvestigated, so the next research will be focused to this. The research objective. The main goal is to create a compact device for training future application developers with a programmable logic controller, but it is also usable for developers from practice, who need to debug the program before installing it into real operation. The statement of basic materials. Existing training sets are large and expensive devices that are not easy to carry and cannot be expanded. Working with such devices is quite complicated. The designed training stand is a flexible and easily portable device. Conclusions. Main contribution is that students will gain practical experiences and skills that are essential for PLC programmers. This device supports also own creativity of students, because it allows to modify hardware composition. It uses the DIN rail system similar as in real installation cabinet. The stand also includes the human-machine interface for training of practical using of these devices.

Integrating Mobile Learning in an Undergraduate Course

2015 ◽  
pp. 1333-1350 ◽  
Author(s):  
Fawzi Ishtaiwa
Keyword(s):  
Mobile Learning ◽  
Mobile Technology ◽  
Situated Learning ◽  
Structured Interviews ◽  
Negative Attitudes ◽  
Small Device ◽  
Technology Affordances ◽  
Research Questions ◽  
The Impact ◽  
The Relationship

This study investigated students' perceptions towards the affordances and challenges of integrating mobile learning (m-learning) into an undergraduate course. It also examined the impact of students' gender on their perceived affordances and challenges. The relationship between students' perceived affordances and perceived challenges of m-learning was also explored. Questionnaires distributed to 76 students and semi-structured interviews conducted with 17 students were used for collecting data to answer the research questions. The results revealed that students' perceptions towards the affordances of m-learning were particularly positive. They indicated that m-learning can provide an active, flexible, contextualised, and situated learning environment. However, several challenges are associated with m-learning integration. Most notable are: distraction, small device screens, plagiarism, cost, and parents' negative attitudes toward m-learning. The study also revealed that students' gender significantly impacted on the perceived affordances and challenges of m-learning. Finally, a negative significant correlation was found between mobile technology affordances and challenges.

scholarly journals A Smart WiFi Multi-Sensor Node for Fire Detection Mechanism Based on Social Network

2018 ◽  
Vol 14 (10) ◽  
pp. 4
Author(s):  
Anekwong Yoddumnern ◽  
Roungsan Chaisricharoen ◽  
Thongchai Yooyativong
Keyword(s):  
Sensor Node ◽  
Finite Impulse Response ◽  
Fire Detection ◽  
Sensor Data ◽  
Sensor Calibration ◽  
Sensing Element ◽  
Detection Mechanism ◽  
Small Device ◽  
Home Area ◽  
Calibration Time

<p class="0abstract">A small device with WiFi multi-sensing element is very important under a social digital century<strong>.</strong> This study aims to implement the hardware and the power of the algorithm with WiFi technologies. Especially, the multi-sensors have to reinforce around a home area and support to any requirement in the term of digital society. This study focus to care the home security— on going to the fire detection with applying several technologies based on a Cloud. Firstly, the multi-sensor calibration has used calibration time and self-calibration as the Finite Impulse Response (FIR). Next, the Full-Scale Kalman Filter (FSKF) helps to fill data and estimate the accuracy data. After that, the fire detection mechanism has used Fuzzy logic to detect and send alert messages over an IFTTT process. There are changed following event-- the data range of fire proportion inside the home. Furthermore, The OFF-Mode has reduced the power consumption suddenly the WiFi module is sent the sensor data to the Cloud. Finally, the WiFi multi-sensor node will use more than one sensor as the same detector will be a high stability and high accuracy.</p>

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