On quasi-static source models for wire dipole antennas

1990 ◽  
Vol 3 (11) ◽  
pp. 396-398 ◽  
Author(s):  
Danieul J. Janse Rensburg ◽  
Derek A. McNamara
Keyword(s):  
Dipole Antennas ◽  
Static Source ◽  
Source Models

The Role of Computer Modeling in Electrocardiography

1990 ◽  
Vol 29 (04) ◽  
pp. 282-288 ◽  
Author(s):  
A. van Oosterom
Keyword(s):  
Electrical Activity ◽  
Computer Modeling ◽  
Body Surface ◽  
Electrical Current ◽  
The Body ◽  
Volume Conductor ◽  
Current Generator ◽  
Cardiac Electrical Activity ◽  
Source Models

AbstractThis paper introduces some levels at which the computer has been incorporated in the research into the basis of electrocardiography. The emphasis lies on the modeling of the heart as an electrical current generator and of the properties of the body as a volume conductor, both playing a major role in the shaping of the electrocardiographic waveforms recorded at the body surface. It is claimed that the Forward-Problem of electrocardiography is no longer a problem. Several source models of cardiac electrical activity are considered, one of which can be directly interpreted in terms of the underlying electrophysiology (the depolarization sequence of the ventricles). The importance of using tailored rather than textbook geometry in inverse procedures is stressed.

Perbandingan Desain Antena Dipole dan Yagi-Uda Menggunakan Material Aluminium pada Frekuensi 470 – 890 MHz

2017 ◽  
Vol 3 (3) ◽  
pp. 140
Author(s):  
Suci Rahmatia ◽  
Putri Wulandari ◽  
Nurul Khadiko ◽  
Fitria Gani Sulistya
Keyword(s):  
Radiation Pattern ◽  
Daily Activity ◽  
Dipole Antenna ◽  
Antenna Gain ◽  
Communication Tool ◽  
Dipole Antennas ◽  
Gain Bandwidth ◽  
Large Gain ◽  
At Home

<p><em>Abstrak </em><strong> - Antena merupakan alat pemancar yang akrab dengan aktifitas sehari-hari dan mudah sekali dijumpai, di rumah, di gedung, bahkan pada alat komunikasi yang digunakan. Salah satu antena yang sering digunakan adalah antena televisi. Antena televisi yang sering digunakan adalah Yagi-Uda yang biasanya dipakai sebagai outdoor antena dan antena dipole yang biasanya digunakan untuk indoor antena. Masing – masing jenis antena memiliki kriteria dan keuntungan berdasarkan dari kebutuhan penggunaannya. Baik antena dipole maupun antena Yagi-Uda memiliki perbedaan diantaranya adalah besar bandwidth, nilai gain, dan pola radiasi. Pada paper ini dapat diketahui bahwa bandwidth yang dimiliki antena yagi-uda lebih besar daripada antena dipole yakni 0.39943 MHz untuk antena yagi-uda dan 0.16569 MHz untuk antena dipole. Begitupula dengan besar Gain yang dimiliki antena Yagi-Uda (6.64 dBi) lebih besar dibandingkan dengan gain dari antena dipole (2.29 dBi). Perbedaan ini dikarenakan faktor elemen director dan ketebalannya.</strong></p><p><strong><br /></strong></p><p><strong><em>Kata Kunci</em></strong> – <em>Atena Televisi, Atena Yagi-Uda, Atena Dipole, Gain, Bandwidth</em></p><p><em> </em></p><p><em>Abstract</em> <strong>- Antenna is a transmitter tool that is familiar with daily activity and easy to find at home, in the building, even on the communication tool used. One of antenna that is often used is a television antenna. Television antennas are often used is Yagi-Uda which is usually used as an outdoor antenna and dipole antenna that is usually used for indoor antennas. Each type of antenna has the criteria and advantages based on the needs of its use. Both dipole antennas and Yagi-Uda antennas have differences among them are bandwidth, gain, and radiation pattern. In this paper it can be seen that the bandwidth of yagi-uda antenna is bigger than dipole antenna that is 0.39943 MHz for Yagi-Uda antenna and 0.16569 MHz for dipole antenna. Neither the large Gain of the Yagi-Uda antenna (6.64 dBi) is greater than the gain of the dipole antenna (2.29 dBi). This difference is due to element factor of director and its thickness.</strong></p><p><strong><br /></strong></p><p><strong><em>Keywords</em></strong><strong> – </strong><em>Television Antenna, Yagi-Uda Antenna, Dipole Antenna, Gain, Bandwidth</em><strong> </strong></p>

Investigation of e-textile dipole antenna performance based on embroidery parameters

2021 ◽  
pp. 004051752110134
Author(s):  
Daniel Agu ◽  
Rachel J Eike ◽  
Allyson Cliett ◽  
Dawn Michaelson ◽  
Rinn Cloud ◽  
...  
Keyword(s):  
Frequency Band ◽  
Impedance Matching ◽  
Dipole Antenna ◽  
Water Soluble ◽  
Wearable Sensor ◽  
Dipole Antennas ◽  
Antenna Performance ◽  
Large Production ◽  
Lower Transmission ◽  
The Ideal

E-textile antennas have the potential to be the premier on-body wearable sensor. Embroidery techniques, which can be applied to produce e-textile antennas, assist in large production volumes and fast production speeds. This paper focuses on the effects of three commonly used embroidery parameters, namely stitch type, conductive thread location, and stabilizer, on the performance of embroidered dipole antennas in order to determine the ideal embroidery combination for optimal antenna performance. Fifty-four dipole antenna samples were fabricated and measured at the industrial, scientific, and medical (ISM) frequency band of 2.45 GHz. The results of this study show that machine-embroidered antenna designs with satin stitches resonate at a lower frequency and exhibit a lower transmission gain compared with those made with contour stiches, and the conductive thread location in the bobbin location plus the use of a water-soluble stabilizer can help improve impedance matching.

scholarly journals Induced network-based transfer learning in injection molding for process modelling and optimization with artificial neural networks

2021 ◽  
Vol 112 (11-12) ◽  
pp. 3501-3513
Author(s):  
Yannik Lockner ◽  
Christian Hopmann
Keyword(s):  
Injection Molding ◽  
Transfer Learning ◽  
Injection Molding Process ◽  
Process Data ◽  
Molding Process ◽  
Melt Temperature ◽  
Processing Industry ◽  
Source Models ◽  
Plastics Processing ◽  
Artificial Neural

AbstractThe necessity of an abundance of training data commonly hinders the broad use of machine learning in the plastics processing industry. Induced network-based transfer learning is used to reduce the necessary amount of injection molding process data for the training of an artificial neural network in order to conduct a data-driven machine parameter optimization for injection molding processes. As base learners, source models for the injection molding process of 59 different parts are fitted to process data. A different process for another part is chosen as the target process on which transfer learning is applied. The models learn the relationship between 6 machine setting parameters and the part weight as quality parameter. The considered machine parameters are the injection flow rate, holding pressure time, holding pressure, cooling time, melt temperature, and cavity wall temperature. For the right source domain, only 4 sample points of the new process need to be generated to train a model of the injection molding process with a degree of determination R2 of 0.9 or and higher. Significant differences in the transferability of the source models can be seen between different part geometries: The source models of injection molding processes for similar parts to the part of the target process achieve the best results. The transfer learning technique has the potential to raise the relevance of AI methods for process optimization in the plastics processing industry significantly.

scholarly journals Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule

2021 ◽  
Vol 13 (8) ◽  
pp. 1424
Author(s):  
Lucas Terres de Lima ◽  
Sandra Fernández-Fernández ◽  
João Francisco Gonçalves ◽  
Luiz Magalhães Filho ◽  
Cristina Bernardes
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Coastal Management ◽  
Google Earth ◽  
Environmental Data ◽  
Planetary Scale ◽  
Bruun Rule ◽  
Source Models ◽  
Google Earth Engine ◽  
Bathtub Model

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence of free and open-source models to estimate the sea-level impact can contribute to improve coastal management. This study aims to develop and validate two different models to predict the sea-level rise impact supported by Google Earth Engine (GEE)—a cloud-based platform for planetary-scale environmental data analysis. The first model is a Bathtub Model based on the uncertainty of projections of the sea-level rise impact module of TerrSet—Geospatial Monitoring and Modeling System software. The validation process performed in the Rio Grande do Sul coastal plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses the Bruun rule formula implemented in GEE and can determine the coastline retreat of a profile by creatting a simple vector line from topo-bathymetric data. The model shows a very high correlation (0.97) with a classical Bruun rule study performed in the Aveiro coast (NW Portugal). Therefore, the achieved results disclose that the GEE platform is suitable to perform these analysis. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific community.

scholarly journals Enhanced Bug Prediction in JavaScript Programs with Hybrid Call-Graph Based Invocation Metrics

Technologies ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 3
Author(s):  
Gábor Antal ◽  
Zoltán Tóth ◽  
Péter Hegedűs ◽  
Rudolf Ferenc
Keyword(s):  
Software Maintenance ◽  
Positive Impact ◽  
Source Code ◽  
Code Analysis ◽  
Static Source ◽  
Static Code Analysis ◽  
Function Calls ◽  
Hybrid Code ◽  
Code Metrics ◽  
Scripting Language

Bug prediction aims at finding source code elements in a software system that are likely to contain defects. Being aware of the most error-prone parts of the program, one can efficiently allocate the limited amount of testing and code review resources. Therefore, bug prediction can support software maintenance and evolution to a great extent. In this paper, we propose a function level JavaScript bug prediction model based on static source code metrics with the addition of a hybrid (static and dynamic) code analysis based metric of the number of incoming and outgoing function calls (HNII and HNOI). Our motivation for this is that JavaScript is a highly dynamic scripting language for which static code analysis might be very imprecise; therefore, using a purely static source code features for bug prediction might not be enough. Based on a study where we extracted 824 buggy and 1943 non-buggy functions from the publicly available BugsJS dataset for the ESLint JavaScript project, we can confirm the positive impact of hybrid code metrics on the prediction performance of the ML models. Depending on the ML algorithm, applied hyper-parameters, and target measures we consider, hybrid invocation metrics bring a 2–10% increase in model performances (i.e., precision, recall, F-measure). Interestingly, replacing static NOI and NII metrics with their hybrid counterparts HNOI and HNII in itself improves model performances; however, using them all together yields the best results.

A note on source models for speech traffic

2007 ◽  
Vol 35 (3) ◽  
pp. 22-24 ◽  
Author(s):  
Michael Menth ◽  
Andreas Binzenhöfer ◽  
Stefan Mühleck
Keyword(s):  
Source Models
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