scholarly journals Sensing Catalytic Converters and Filters at Work Using Radio Frequencies

Proceedings ◽  
2018 ◽  
Vol 2 (13) ◽  
pp. 1101
Author(s):  
Ralf Moos ◽  
Stefanie Walter ◽  
Carsten Steiner ◽  
Gunter Hagen
Keyword(s):  
Pressure Sensors ◽  
Cavity Resonator ◽  
The State ◽  
Exhaust Pipe ◽  
Sensing Element ◽  
Particulate Filters ◽  
Exhaust Gas Aftertreatment ◽  
Novel Approach ◽  
Nox Storage Catalysts ◽  
Scr Catalysts

The state of catalysts and filters plays a key role in automotive exhaust gas aftertreatment. The soot or ash loading of particulate filters (GPF or DPF), the oxygen loading of three-way catalysts (TWC), the amount of stored ammonia in SCR catalysts, or the NOx loading degree in NOx storage catalysts (NSC) are important parameters. Today, they are determined indirectly based on models that are calibrated by gas or pressure sensors in the exhaust pipe. This contribution overviews a novel approach that determines directly the state of the devices by a radio frequency based technique. For that purpose, the housing of the devices serves as a cavity resonator. As “sensing” element, one or two simple antennas are mounted in the catalyst canning. This contactless-obtained information correlates very well with the catalyst or filter state.

CMOS-MEMS Based Current Mirror MOSFET Embedded Pressure Sensor for Healthcare and Biomedical Applications

2013 ◽  
Vol 647 ◽  
pp. 315-320 ◽  
Author(s):  
Pradeep Kumar Rathore ◽  
Brishbhan Singh Panwar
Keyword(s):  
Pressure Sensor ◽  
Biomedical Applications ◽  
Circuit Simulation ◽  
Applied Pressure ◽  
Pressure Sensors ◽  
Cmos Technology ◽  
Current Mirror ◽  
Sensing Element ◽  
Pressure Sensing ◽  
Cmos Mems

This paper reports on the design and optimization of current mirror MOSFET embedded pressure sensor. A current mirror circuit with an output current of 1 mA integrated with a pressure sensing n-channel MOSFET has been designed using standard 5 µm CMOS technology. The channel region of the pressure sensing MOSFET forms the flexible diaphragm as well as the strain sensing element. The piezoresistive effect in MOSFET has been exploited for the calculation of strain induced carrier mobility variation. The output transistor of the current mirror forms the active pressure sensing MOSFET which produces a change in its drain current as a result of altered channel mobility under externally applied pressure. COMSOL Multiphysics is utilized for the simulation of pressure sensing structure and Tspice is employed to evaluate the characteristics of the current mirror pressure sensing circuit. Simulation results show that the pressure sensor has a sensitivity of 10.01 mV/MPa. The sensing structure has been optimized through simulation for enhancing the sensor sensitivity to 276.65 mV/MPa. These CMOS-MEMS based pressure sensors integrated with signal processing circuitry on the same chip can be used for healthcare and biomedical applications.

scholarly journals Density Guarantee on Finding Multiple Subgraphs and Subtensors

2021 ◽  
Vol 15 (5) ◽  
pp. 1-32
Author(s):  
Quang-huy Duong ◽  
Heri Ramampiaro ◽  
Kjetil Nørvåg ◽  
Thu-lan Dam
Keyword(s):  
Lower Bound ◽  
State Of The Art ◽  
The State ◽  
The Other ◽  
Exact Methods ◽  
Practical Solution ◽  
Novel Approach ◽  
Wide Range ◽  
Real World Datasets ◽  
Tensor Data

Dense subregion (subgraph & subtensor) detection is a well-studied area, with a wide range of applications, and numerous efficient approaches and algorithms have been proposed. Approximation approaches are commonly used for detecting dense subregions due to the complexity of the exact methods. Existing algorithms are generally efficient for dense subtensor and subgraph detection, and can perform well in many applications. However, most of the existing works utilize the state-or-the-art greedy 2-approximation algorithm to capably provide solutions with a loose theoretical density guarantee. The main drawback of most of these algorithms is that they can estimate only one subtensor, or subgraph, at a time, with a low guarantee on its density. While some methods can, on the other hand, estimate multiple subtensors, they can give a guarantee on the density with respect to the input tensor for the first estimated subsensor only. We address these drawbacks by providing both theoretical and practical solution for estimating multiple dense subtensors in tensor data and giving a higher lower bound of the density. In particular, we guarantee and prove a higher bound of the lower-bound density of the estimated subgraph and subtensors. We also propose a novel approach to show that there are multiple dense subtensors with a guarantee on its density that is greater than the lower bound used in the state-of-the-art algorithms. We evaluate our approach with extensive experiments on several real-world datasets, which demonstrates its efficiency and feasibility.

A Radical Rethink on Soot Containment from Auto-Rickshaw Exhausts

2014 ◽  
Vol 911 ◽  
pp. 383-387
Author(s):  
S. Ghosh ◽  
R.N. Shah ◽  
A. Goenka
Keyword(s):  
Particulate Filter ◽  
Exhaust Pipe ◽  
Asian Countries ◽  
Cfd Simulations ◽  
Good Efficiency ◽  
Particulate Filters ◽  
Particulate Air Pollution ◽  
The Everyday ◽  
Indian City ◽  
Natural Cycles

The auto-rickshaw has become a predictable part of the everyday lives of Indian city-dwellers. Although this popular means of public transport provides relatively discounted and efficient transportation, the auto-rickshaw is a key source of soot that causes particulate air pollution. These soot emissions infringe the natural cycles of the atmosphere other than their more overt effects on human health. Consequently, their entrapment becomes vital. Though most particulate filters provide a rather good efficiency, once clogged an undesired back pressure may lead to engine and/ or filter failure. Through this study a method is proposed to overcome such impenetrability. Once the particles are confined to narrower streams, smaller filters may be used which even if clogged will allow the easy passage of the exhaust gases out of the exhaust pipe. The most immediate outcome of this research is that the CFD simulations suggest inexpensive design alterations in the diesel particulate filter which can be fabricated easily. With government subsidies this component can be mass manufactured for use in India and other Asian countries where auto-rickshaws are widely used.

scholarly journals Identification of Micro-calcification in Mammogram for Breast Cancer Analysis using SVM Classifier

2018 ◽  
Vol 7 (2.16) ◽  
pp. 29
Author(s):  
Gaurav Makwana ◽  
Lalita Gupta
Keyword(s):  
Breast Cancer ◽  
Clustering Algorithm ◽  
Automatic Segmentation ◽  
Breast Cancer Diagnosis ◽  
The State ◽  
Svm Classifier ◽  
Common Disease ◽  
Test Technique ◽  
Novel Approach ◽  
Breast Calcification

Breast cancer is most common disease in women of all ages. To identify & confirm the state of tumor in breast cancer diagnosis, patients are undergo biopsy number of times to identify malignancy. Early detection of cancer can save the patient. In this paper a novel approach for automatic segmentation & classification of breast calcification is proposed. The diagnostic test technique for detection of breast condition is very costly & requires human expertise whereas proposed method can help in automatically identifying the disease by comparing the data with the standard database. In proposed method a database has been created to define various stage of breast calcification & testing images are pre-processed to resize, enhance & filtered to remove background noise. Clustering is performed by using k-means clustering algorithm. GLCM is used to extract out statistical feature like area, mean, variance, standard deviation, homogeneity, skewness etc. to classify the state of tumor. SVM classifier is used for the classification using extracted feature. 

scholarly journals Multi-hop Reading Comprehension across Documents with Path-based Graph Convolutional Network

2020 ◽  
Author(s):  
Zeyun Tang ◽  
Yongliang Shen ◽  
Xinyin Ma ◽  
Wei Xu ◽  
Jiale Yu ◽  
...  
Keyword(s):  
Reading Comprehension ◽  
Human Performance ◽  
The State ◽  
Ensemble Model ◽  
Human Reasoning ◽  
Convolutional Network ◽  
Gating Mechanism ◽  
Novel Approach ◽  
Multiple Documents ◽  
State Of Art

Multi-hop reading comprehension across multiple documents attracts much attentions recently. In this paper, we propose a novel approach to tackle this multi-hop reading comprehension problem. Inspired by the human reasoning processing, we introduce a path-based graph with reasoning paths which extracted from supporting documents. The path-based graph can combine both the idea of the graph-based and path-based approaches, so it is better for multi-hop reasoning. Meanwhile, we propose Gated-GCN to accumulate evidences on the path-based graph, which contains a new question-aware gating mechanism to regulate the usefulness of information propagating across documents and add question information during reasoning. We evaluate our approach on WikiHop dataset, and our approach achieves the the-state-of-art accuracy against previous published approaches. Especially, our ensemble model surpasses the human performance by 4.2%.

scholarly journals Tie-Bar Elongation Based Filling-To-Packing Switchover Control and Prediction of Injection Molding Quality

Polymers ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1168 ◽  
Author(s):  
Jian-Yu Chen ◽  
Chun-Ying Liu ◽  
Ming-Shyan Huang
Keyword(s):  
Injection Molding ◽  
Pressure Sensors ◽  
Clamping Force ◽  
Cavity Pressure ◽  
Testing Specimen ◽  
Injection Speed ◽  
Novel Approach ◽  
Pressure Profiles ◽  
Molded Parts ◽  
Short Shot

Filling-to-packing switchover (also called V/P switchover) is critical for assuring injection molding quality. An improper V/P switchover setting may result in various defects of injection-molded parts, such as excessive residual stress, flash, short shot, and warpage, etc. To enhance a consistent molding quality, recent V/P switchover approaches adopt cavity pressure profiles requiring sensors embedded in mold cavities, which is invasive to mold cavities and more expensive. Instead of using cavity pressure sensors, by working with the most popular screw position switchover control, this study hereby proposes a novel approach of tuning V/P switchover timing using a tie-bar elongation profile. In this investigation, a dumbbell testing specimen mold is applied to verify the feasibility of the method proposed. The results show that the mold filling and packing stages can be observed along the tie-bar elongation profile, detected by mounting strain gauges on the tie bars. Also, the characteristics of the cavity pressure are similar to those of the tie-bar elongation profile under a proper clamping force condition. Moreover, the varying process parameter settings which include injection speed, V/P switchover point, and holding pressure, can be reflected in these profiles. By extracting their characteristics, the application of the V/P switchover is proved to be realistic. This research conducted an experiment to verify the proposed V/P switchover decision method based on the tie-bar elongation profile. The result showed that the fluctuation of the part’s weight corresponding to a slight change of the barrel’s temperature from 210 °C to 215 °C can be successfully controlled with this method. Besides, the maximum clamping force increment extracted from the tie-bar elongation profile was found to be a good indicator for online monitoring of the reground material variation.

Design of a Flow Reactor for Testing Multi-Brick Catalyst Systems Using Rapid Exhaust Gas Composition Switches

2009 ◽  
Author(s):  
Stefan Klinkert ◽  
John W. Hoard ◽  
Sakthish R. Sathasivam ◽  
Dennis N. Assanis ◽  
Stanislav V. Bohac
Keyword(s):  
Flow Reactor ◽  
Combustion Engine ◽  
Synergistic Effects ◽  
Control Program ◽  
Exhaust Gas ◽  
Gas Composition ◽  
Lean Burn ◽  
Exhaust Gas Aftertreatment ◽  
Scr Catalysts ◽  
Catalyst Systems

In recent years, diesel exhaust gas aftertreatment has become a core combustion engine research subject because of both increasingly stringent emission regulations and incentives toward more fuel-efficient propulsion systems. Lean NOX traps (LNT) and selective catalytic reduction (SCR) catalysts represent two viable pathways for the challenging part of exhaust gas aftertreatment of lean burn engines: NOX abatement. It has been found that the combination of LNT and SCR catalysts can yield synergistic effects. Switches in the operation mode of the engine, temporarily enriching the mixture, are required to regenerate the LNT catalyst and produce ammonia for the SCR. This paper describes the design of a catalyst flow reactor that allows studying multi-brick catalyst systems using rapid exhaust gas composition switches and its initial validation. The flow reactor was designed primarily to study the potential of combining different aftertreatment components. It can accommodate two sample bricks at a time in two tube furnaces, which allows for independent temperature control. Moreover, the flow reactor allows for very flexible control of the composition and flow rate of the synthetic exhaust, which is blended using mass flow controllers. By using a two-branch design, very fast switches between two exhaust gas streams, as seen during the regeneration process of a LNT catalyst, are possible. The flow reactor utilizes a variety of gas analyzers, including a 5-Hz FTIR spectrometer, an emissions bench for oxygen and THC, a hydrogen mass spectrometer, and gas chromatographs for HC speciation. An in-house control program allows for data recording, flow reactor control, and highly flexible automation. Additionally, the hardware and software incorporate features to ensure safe testing. The design also has provisions for engine exhaust sampling.

scholarly journals Learning to Transfer Relational Representations through Analogy

2019 ◽  
Vol 33 ◽  
pp. 10015-10016
Author(s):  
Gaetano Rossiello ◽  
Alfio Gliozzo ◽  
Michael Glass
Keyword(s):  
State Of The Art ◽  
Relation Extraction ◽  
Knowledge Bases ◽  
The State ◽  
Large Set ◽  
Relational Information ◽  
Siamese Network ◽  
Distant Supervision ◽  
Novel Approach ◽  
Art Methods

We propose a novel approach to learn representations of relations expressed by their textual mentions. In our assumption, if two pairs of entities belong to the same relation, then those two pairs are analogous. We collect a large set of analogous pairs by matching triples in knowledge bases with web-scale corpora through distant supervision. This dataset is adopted to train a hierarchical siamese network in order to learn entity-entity embeddings which encode relational information through the different linguistic paraphrasing expressing the same relation. The model can be used to generate pre-trained embeddings which provide a valuable signal when integrated into an existing neural-based model by outperforming the state-of-the-art methods on a relation extraction task.

scholarly journals Initial Development of a Master-Slave Controller for a Five-Fingered Robotic Hand Design by Using Pressure Sensors Comparator Technique

2018 ◽  
Vol 7 (4.35) ◽  
pp. 765
Author(s):  
Syed Zainal Abidin Syed Kamarul Bahrin ◽  
Khairul Salleh Mohamed Sahari
Keyword(s):  
Pressure Sensors ◽  
Robotic Hand ◽  
Robotic Hands ◽  
Initial Finding ◽  
Initial Development ◽  
Future Developments ◽  
Physiological Diversity ◽  
Advanced Technologies ◽  
Novel Approach ◽  
Similar Appearance

There are numerous robotic hand designs but the five-fingered robotic hand design is the most dexterous robotic hand design due to its similar appearance and motions with the human hands. The five-fingered robotic hands are commonly controlled or governed through a master-slave system that can be accomplished by using simple preset motions or other complicated and advanced technologies. However, a five-fingered robotics hand can also be controlled by a novel approach known as pressure sensors comparator technique. This technique compares the values from the pressure sensors that are strategically located at the glove (master) and robotic hand (slave). If the values differ, the actuators will generate motions accordingly. The initial finding based on the master and slave prototypes showed that applying this technique is very challenging due to the humans' physiological diversity. Nevertheless, a solution was proposed for further studies and future developments by introducing an offset.

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