143 research outputs found
Knowledge and data dual-driven channel estimation and feedback for ultra-massive MIMO systems under hybrid field beam squint effect
No full textAcquiring accurate channel state information (CSI) at an access point (AP) is challenging for wideband millimeter wave (mmWave) ultra-massive multiple-input and multiple-output (UMMIMO) systems, due to the high-dimensional channel matrices, hybrid near- and far- field channel feature, beam squint effects, and imperfect hardware constraints, such as low-resolution analogto- digital converters, and in-phase and quadrature imbalance. To overcome these challenges, this paper proposes an efficient downlink channel estimation (CE) and CSI feedback approach based on knowledge and data dual-driven deep learning (DL) networks. Specifically, we first propose a data-driven residual neural network de-quantizer (ResNet-DQ) to pre-process the received pilot signals at user equipment (UEs), where the noise and distortion brought by imperfect hardware can be mitigated. A knowledge-driven generalized multiple measurement vector learned approximate message passing (GMMV-LAMP) network is then developed to jointly estimate the channels by exploiting the approximately same physical angle shared by different subcarriers. In particular, two wideband redundant dictionaries (WRDs) are proposed such that the measurement matrices of the GMMV-LAMP network can accommodate the farfield and near-field beam squint effect, respectively. Finally, we propose an encoder at the UEs and a decoder at the AP by a data-driven CSI residual network (CSI-ResNet) to compress the CSI matrix into a low-dimensional quantized bit vector for feedback, thereby reducing the feedback overhead substantially. Simulation results show that the proposed knowledge and data dual-driven approach outperforms conventional downlink CE and CSI feedback methods, especially in the case of low signal-to-noise ratios
Covid-19 Pandemisinde Hemşirelerde Yaşam Boyu Öğrenme ve Öznel Mutluluk Arasındaki İlişki
No full textAmaç: Bu çalışmada hemşirelerde yaşam boyu öğrenme ile öznel mutluluk arasındaki ilişkinin incelenmesi amaçlanmıştır. Gereç ve Yöntemler: Bu çalışma tanımlayıcı ve kesitseldir. Bu ça- lışma kesitsel tarama modeli kullanılmıştır. Araştırma, Türkiye’de Ağrı ilinde bir eğitim ve araştırma hastanesinde çalışan 222 hem- şire üzerinde yürütülmüştür. Veriler Demografik Veri Formu, Yaşam Boyu Öğrenme Eğilimi Ölçeği (YBÖEÖ) ve Oxford Mutluluk Ölçeği (OMÖ) kullanılarak toplanmıştır. Bulgular: Hemşirelerin YBÖEÖ toplam puan ortalaması 64.74±23.69 ve OMÖ toplam puan ortalaması 92.78±15.04’tür. Hemşirelerin YBÖEÖ ve OMÖ puanları arasında negatif yönde za- yıf bir korelasyon vardı (r=-.380, p<0.05). Sonuç: Hemşirelerin yaşam boyu öğrenmeleri ile öznel mutlulukları arasında pozitif bir ilişki bulunmuştur. Sağlık hizmetlerinde ileri ve yeni teknolojilerin kullanımı, daha iyi sağlık hizmeti beklentisi ve hızla gelişen bilimsel bilginin hemşirelik uygulamalarına yansıması ile birlikte yaşam boyu öğrenmeyi hemşireler için zorunlu bir gerek- sinim haline getirmiştir. Sağlık hizmetlerinde yaşam boyu öğrenme becerisine sahip nitelikli hemşirelerin varlığı, toplumun sağlık so- runlarının çözümüne katkı sağlayacaktır.Aim: The objective of this study was to examine the relationship between lifelong learning and the subjective well-being of nurses. Materials and Methods: The study is descriptive and cross-sectio- nal. This study was carried out on 222 nurses from a training and research hospital in Turkey, Agri Province, as the study populati- on. Data were collected using The Demographic Data Form, Life- long Learning Tendency Scale (LLTS)and Oxford Happiness Scale (OHS). Results: The mean total score LLTS of the nurses was 64.74±23.69 and the mean total OHS score of the nurses was 92.78±15.04. There was a weak negative correlation between the scores of the nurses’ LLTS and OHS scores (r=-.380, p<0.05). Conclusion: A positive relationship was found between nurses’ li- felong learning and their subjective happiness. The use of advanced and new technologies in healthcare services, along with the expec- tation of better healthcare and the reflection of rapidly developing scientific knowledge in nursing practices, have made lifelong lear- ning a compulsory requirement for nurses. The presence of qualified nurses with lifelong learning skills in healthcare services will contri- bute to the resolution of society’s health problems
SSFs dataset: Self-supervised features dataset of the ultrasonic signals of two-phase flow in an S-shaped riser
No full textTitle: SSFs dataset: Self-supervised features dataset of the ultrasonic signals of two-phase flow in an S-shaped riser
Author: Boyu Kuang, [email protected]
Time: 09th March 2023
Description:
The source data of the proposed SSFs dataset comes from: https://doi.org/10.17862/cranfield.rd.11369379.v1
The Self-supervised features (SSFs) dataset is opened to the community along with our latest journal paper entitled:
"Self-supervised learning-based two-phase flow regimen identification using ultrasonic sensors in an S-shape riser".
NOTE: the journal DOI will be provided after the acceptance.
This dataset is produced using the settings in TABLE I.
Here are some details, and please contact me if you got any issues with using the dataset:
SSFs_dataset: "the root directory of the dataset"
|
|
-- ex: "the SSFs from the experiment group (ex)"
| |
| |
| -- train: "the training set (70%)"
| |
| |
| -- test: "the testing set (15%)"
| |
| |
| -- valid: "the validation set (the rest)"
|
|
-- ctr-A: "the SSFs from the control group (ctr-A)"
| |
| |
| -- train: "the training set (70%)"
| |
| |
| -- test: "the testing set (15%)"
| |
| |
| -- valid: "the validation set (the rest)"
|
|
-- ... ...</p
Precoding matrix indicator in the 5G NR protocol: A tutorial on 3GPP beamforming codebooks
No full textThe Impact of Mahjong on Marital Relationships
Full text linkOne of the national treasures, Mahjong, is a strategic card game originating
from China, played competitively by constructing and optimizing card hands
among four players. In the game, players aim to achieve specific combinations
of cards, known as "winning hands," through actions such as drawing,
discarding, pung, and kong. Mahjong not only tests memory and strategy but also
integrates probability and chance, embodying profound cultural significance and
social attributes. However, as Mahjong becomes a widely popular social
activity, its impact on personal life has gradually become apparent. In this
paper, I delve into the analysis of the effects of playing Mahjong on marital
relationships, particularly the three negative effects it brings to women:
Time Displacement: The uncertainty of Mahjong playing time leads to a
reduction in shared time between spouses. Women may feel neglected due to the
lack of companionship, leading to "Mahjong Panic Syndrome."
Emotional Conflict: Mahjong playing can result in losses, and men may harbor
"resentment from defeat" at the Mahjong table, which could be brought into the
household and spark marital disputes.
Social Isolation: Women may feel excluded from their partner's social circle
if they do not participate in Mahjong activities, experiencing "marginalization
at the card table."
This study not only reveals the potential negative impact of late-night
Mahjong returns on marital relationships but also provides new insights into
communication and empathy between spouses from the perspectives of decision
trees, time series analysis, and game theory. It also finds the optimal
solution through Monte Carlo simulations
Author recognition for Turkish documents
Full text linkGünümüzde, yazar tanıma çalışmaları, teknolojinin gelişmesi ve bilginin yaygınlaşması ile ortaya çıkan bir takım sorunlara çözüm üretmek için yapılmaktadır. Bu sorunlardan bazıları yazarı belli olmayan dokümanların yazarlarının belirlenmesi ve yazarının kim olduğundan tam olarak emin olunamayan metinlerin yazarlarının belirlenmesidir. Bu çalışmada, Türkçe dokümanlar için yazar tanıma sistemleri geliştirilmiştir. Sistemlerin eğitilmesinde ve test edilmesinde kullanılmak üzere, gazetelerden seçilen 6 yazara ait köşe yazıları kullanılmıştır. Yazarların 70?er makalesinden oluşan 420 dokümandan oluşan bir derlem hazırlanmıştır. Bu dokümanlardan 20?şer tanesi eğitim için, 50?şer tanesi test için kullanılmıştır. İlk olarak, 6 yazara ait dokümanlar toplanmış, daha sonra her yazara ait 20 doküman birleştirilerek tek bir doküman haline getirilmiştir. Bu şekilde elde edilen 6 doküman için sözcük, gövde, hece ve karakter n-gramlarının öznitelik vektörleri belirlenmiştir. K-En Yakın Komşu algoritması için öznitelik vektörleri belirlenirken her yazar için vektör uzunlukları 120, 180 ve 240 olarak seçilmiş, oluşan öznitelik vektörleri için K-En Yakın Komşu algoritmasıyla test edilmiştir. En başarılı sonuçlar, vektör boyu 120 olduğunda elde edildiğinden diğer metotlar için de vektör boyu 120 olarak kullanılmıştır. Geliştirilen sistemler eğitildikten sonra test edilerek doğruluk ve F-ölçüsü değerlerine göre birbirleriyle karşılaştırılmıştır.Today, the studies of author recognition have been made for providing the solutions of the problems which occur by developing and growing of information technology. Some of these problems are to specify the authors who the papers are exactly written by. In this study, some systems about author recognition for Turkish documents have been developed. For generating the systems, we have used the columns which belong to six authors in some newspapers. A corpus which includes totally 420 documents is constructed for training and testing of the systems. Each author has seventy documents. Twenty documents of every author are used for training operation. But, the other documents are utilized for testing stage. The features of word, stem, syllable, character and their n-grams are decided for each documents of these six author. Author recognition systems have been developed with the methods as K-Nearest Neighbor, Support Vector Machine, Multi-Layer Perceptron and Learning Vector Quantization. The feature vectors? lengths of the systems developed by K-Nearest Neighbor have been chosen as 120, 180 and 240. Because the most successful results are obtained as the length of the feature vectors is 120, we have used this length for the other methods. After the developed systems are trained the methods, the systems have been tested and evaluated according to accuracy and F-measure values
Examining Changes in the Democratic Progressive Party from 2008 to 2014 with Harmel and Janda\ue2s Integrated Theory of Party Change
No full textUsing Harmel and Janda\ue2s integrated theory of party change, the author examines the changes within the Democratic Progressive Party\ue3(DPP)\ue3from 2008-2014. In this thesis, the author specifically explores how the three main independent variables \ue2 chairperson change, dominant faction displacement, and external stimuli \ue2 are related to the changes observed in DPP which is considered a vote-seeking party.
The research finds that changes within the DPP including organization, ideology, strategies, constitution, and policy changes can be attributed to numerous factors such as \ue2 changes in DDP\ue2s chairperson, external stimuli and external shocks such as electoral system change, jurisdictional changes in Taiwan\ue2s local government structure, the Sunflower protest movement in early 2014, and others. Despite these changes, DPP factional structure have not changed substantially. The changes observed in the DPP in this thesis corroborates Harmel and Janda\ue2s integrated theory of party change
Design of optoacoustic imaging system for care medical diagnostics
No full textThis report presents what the author have done for the Final Year Project. Firstly, involved the design of a palm size laser diode driver circuit board which later on could be used in the photoacoustic imaging system for driving a low power laser diode. Electrical circuit design, circuit simulation on LTSpice, PCB layout design and hands on experiments were also performed.
Secondly, studied the photoacoustic effect and furthermore a photoacoustic imaging system was implemented to achieve high spatial resolution and good contrast image.
Last but not least, had a basic understanding of photoacoustic effects, coupled with the research study on PA-SAW devices, a PA-SAW based particle sensing system was designed to effective enhance the sensing signal.Bachelor of Engineerin
Research on the Optimal Machine Learning Classifier for Traffic Signs
No full textNow autonomous driving is a hot topic, and the identification of traffic signs is also extremely important for autonomous driving. This paper mainly compares the difference of the Support Vector Machine (SVM), Multilayer Perceptron (MLP), and Logistic Regression (LR) Classifier in the traffic sign classification. The effect of the initial image processing on classification accuracy is also studied. The paper found that sharpening the image significantly improved the accuracy of the image classification. Based on the results of various situations, the author found that, in this paper, SVM is the classifier with the best classification effect, but the effect of LR classifier is not much worse than that of SVM when the image is sharpened
Fast pyrolysis kinetics of waste tires and its products studied by a wireless-powered thermo-balance
Full text linkFunding Information: Authors appreciate the financial support from the Liao Ning Revitalization Talents Program (grant number: XLYC2007179 ). Publisher Copyright: © 2023 The AuthorsPeer reviewe
- …
