bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ultrasound Image Super-Resolution with Two-Stage Zero-Shot CycleGAN
Authors: Ding Jianrui , Zhao Shili , Tang Fenghe , Ning Chunping 
Published: September 2021

Abstract
Medical ultrasound imaging is widely used in clinical diagnosis because of its non-invasive, convenient and quick characteristics. However, due to its low image contrast, multiple artifacts, noise and lack of paired high-resolution and low-resolution image data sets, the task of super-resolution reconstruction of medical ultrasound images is more challenging. In this paper, the Two-Stage GAN network model was adjusted by CycleGAN generation and unsupervised learning methods, and the Two-Stage ZSSR (“Zero-Shot” Super-Resolution) CycleGAN network was proposed. The objective evaluation indexes PSNR and SSIM were raised to 40.8079 and 0.9953. The visual effect was also significantly improved.
An Investigation about All-optical Millimeter Wave Generation Technology for High-speed Communication
Authors: Li Qiwei 
Published: September 2021

Abstract
With the advent of the network information age, users have higher and higher requirements for the bandwidth and capacity of communication systems. Traditional cellular mobile communications can no longer meet the needs of modern communication systems. It is necessary to find a communication system with larger capacity, higher bandwidth and higher transmission rate. Millimeter wave (MMW) communication has high bandwidth, large capacity and high signal transmission rate. Nowadays, all-optical MMW technology generates high-frequency MMW signals in optical domain, which has become a research hotspot of MMW signal generation technology at home and abroad. In this paper, three typical all-optical MMW generation methods are discussed, including direct modulation method, optical heterodyne method and external modulation method. The advantages and disadvantages of each method are analyzed, and the development prospects of the all-optical MMW generation technology are prospected. It is helpful to research new optical MMW technology in the future.
Key Technologies for Beamforming in Millimeter Wave Communication System
Authors: Qian Guanyu , Liu Weikun , Hao Dengfeng , Li Wei 
Published: September 2021

Abstract
Millimeter wave (mmWave) is one of the key technologies of 5G. It can solve the problem of insufficient spectrum resources. However, mmWave links are easily affected by the environment, such as the user equipment (UE) mobility, link blocking, etc. Moreover, the path loss and atmospheric absorption will also cause a great loss to the channel quality. Dealing with these challenges, beamforming is an effective solution. This paper tracks the progress of beamforming in mmWave communication system, including hybrid beamforming structure, mmWave channel state information (CSI) acquisition, and beam management methods during UE movement. We explore the applicability of different beamforming technologies, and discuss the future challenges in this domain.
Automatic Target Recognition of Millimeter-Wave Radar Based on Deep Learning
Authors: Wang Chen Xi , Chen Xin , Zou Han Yu , He Song , Tang Xiao 
Published: September 2021

Abstract
All-day, all-weather wide-area search discovery target capability makes radar become a key piece of equipment in many military and civilian fields, and plays an indispensable role in tasks such as identification and positioning. However, at the same time, the current radar equipment generally relies on complex signal processing systems, and designing artificial feature extraction algorithms based on prior knowledge is both difficult and time-consuming, and it is difficult to fine-grained identify the target. In recent years, deep learning has been widely used in the radar field with its strong adaptability and strong self-learning ability. The paper presents a radar Doppler image based on YOLO v3 algorithm. With Millimeter-Wave radar distance-doppler reflectance image as input and darknet-53 as the feature extraction network, the automatic detection of vehicle millimeter wave radar cars, bicycles, pedestrians and trucks was realized, and the average detection accuracy reached 84.3%, providing new ideas and technical support for the development of intelligent radar and radar target detection.
Comment information extraction based on LSTM and Neural Networks
Authors: Zhang Qingliang , Ma Binning , Zhong Xier , Mei Liangcai , Zhou Youyu 
Published: September 2021

Abstract
With the advent of the era of big data, the amount of data has also increased geometrically. People’s ability to obtain effective information has gradually declined. At present, most e-commerce platforms only focus on the sentiment analysis of positive and negative reviews. It is difficult for users and businesses to extract user opinions and views from the massive review data. For the product review data of a certain hard disk, use the LSTM model to train the sentiment classification model. Finally, the neural network is used to find the keywords of the comment data and the word cloud diagram is used to display the analysis results. Through the research, it can be found that LSTM emotion classifier can classify comments with high accuracy and words closely related to comment emotion tendency can be found according to the weight of neural network.
A Channel Selection Algorithm of Power Line Communication Network Base on Double-layer Cascade Artificial Neural Network
Authors: Qu Beibei , Wang Huifang , Chen Zhixiong , Zheng Zhong , Han Zhen , Zhang Lixia 
Published: September 2021

Abstract
A crucial issue in Power Line Communication (PLC) networks is how to improve the performance of power line channel in physical layer. In this paper, a multiple input multiple output (MIMO) PLC channel selection algorithm based on a double-layer cascaded artificial neural network model is proposed. After the model is trained, the best channel combination can be selected directly through the channel estimation information. The results show that compared with the communication system without channel selection, the model can improve the channel by 2-3dB, the probability of selecting the best channel is 95.02%, and the training has fast convergence speed and small amount of calculation.
On the exact solutions for a type of nonlinear Schrödinger equations with a harmonic potential
Authors: Qin Yamei , Wang Hui , Su Tao , Dai Wang , Zhang Tao 
Published: September 2021

Abstract
The nonlinear Schrödinger equation with harmonic potential (NLSE) plays an important role in quantum mechanics, so the exact solutions of this equation is studied in this paper. The NLSE is transformed into the classical nonlinear Schrödinger equation by a new class of traveling wave transformation. Next, the problem of exact solutions is changed into the solutions of ordinary differential equation (ODE) by the method of undetermined function. Then, through low-order sub-ODE method and hyperbolic function method, we get two class of solutions of the ODEs. Finally, a series of new exact solutions of the NLSE are obtained. Meanwhile the related numerical simulations are presented.
Research on Splicing Technology of Large Format Three Dimensional Printing
Authors: Li Qingming , Yao Fengwei 
Published: September 2021

Abstract
With the development and maturity of 3D printing technology, there are new requirements for printing accuracy, clarity, and frame size. This article mainly focuses on large-format printing technology, using projection splicing technology to realize large-format digital light processing projection splicing 3D printing technology. Aiming at the problem of projection distortion, the article implements multiple digital light processing projection distortion correction; Aiming at the problem of image stitching, the article uses secondary Alpha edge fusion to realize image stitching, and gives an experimental environment to compare the results. According to the above steps, combined with actual pictures, a good splicing effect is achieved.
Face occlusion detection algorithm based on yolov5
Authors: Zhao Yuanzhang , Geng Shengling 
Published: September 2021

AbstractThe current face-mask recognition detection algorithm during the epidemic only distinguishes between wearing or not wearing a mask. Such detection often has certain loopholes, such as using other objects to cover their mouths and noses instead of masks to cheat the detection. To address such problems, this paper proposes a YOLOv5 based face occlusion detection algorithm, which is modified based on the YOLOv5 algorithm by improving the loss function as DIoU and increasing the experimental samples by introducing multiple data sets to improve the object detection effect. The experimental results show that the improved YOLOv5 algorithm has improved the object detection effect for different kinds of face occlusions, which verifies the method’s effectiveness.
Differential search algorithm for biojective feature selection
Authors: Du HongJun , Yao JingJun , Sun Gang , Li Ming , Zhou WuMing , Yu HaiYan , Guo ChangBiao , Zhang Shan 
Published: September 2021

AbstractFeature selection (FS) is a complex optimization problem with important real-world applications. Generally, the main target of FS is to reduce the dimensionality of features and enhance the effectiveness of solving problems. Due to the population characteristics, various evolutionary algorithms (EAs) have been proposed to solve feature selection problems over the past decades. However, the majority of them only consider single-objective optimization, while many real-world problems have multiple objectives, therefore, it is need to design more suitable and effective EAs to deal with multi-objective FS. In this paper, a biobjective FS algorithm based on differential search algorithm (DSA) is designed to solve FS problems, which minimizes the number of selected features and maximizes the classification accuracy. The results of simulation experiments and statistical analysis on 15 classification datasets compared with other four state-of-the-art EAs show that the proposed DSA algorithm can not only obtain better optimization performance, but also achieve competitive convergence accuracy.
Heart Failure Prediction with Machine Learning: A Comparative Study
Authors: Wang Jing 
Published: September 2021

Abstract
Heart failure is a worldwide healthy problem affecting more than 550,000 people every year. A better prediction for this disease is one of the key approaches of decreasing its impact. Both linear and machine learning models are used to predict heart failure based on various data as inputs, e.g., clinical features. In this paper, we give a comparative study of 18 popular machine learning models for heart failure prediction, with z-score or min-max normalization methods and Synthetic Minority Oversampling Technique (SMOTE) for the imbalance class problem which is often seen in this problem. Our results demonstrate the superiority of using z-score normalization and SMOTE for heart failure prediction.
Design and simulation of Sierpmski Triangular Fractal Antenna for S-Band
Authors: Vyas Jahanvi H. , Gohil NB , Dwivedi Ved Vyas 
Published: September 2021

Abstract
In current wireless communication scenarios, you need to reduce the size of the antenna and achieve better performance without affecting other antenna settings. A fractal antenna is an antenna that uses a fractal and similar design to maximize the effective length of a material that can transmit and receive electromagnetic radiation in a specific total area, or to augment its environment (internal components or external structures) or the volume. Fractal antennas offer better parameters while providing better performance at many different frequencies. The Sierpinski triangle is a fixed set of fractal attractions. Its general shape is an equilateral triangle, which is recursively divided into smaller equilateral triangles. Sierpinski’s triangular fractal geometry is used to reduce antenna size and improve antenna performance at required frequencies. In this proposed task, a simple technique is used to design a Sierpinski triangular fractal antenna. These antennas are lightweight and small in size. This design covers the S band and is suitable for wireless applications.
Deep Neural Network for Electroencephalogram based Emotion Recognition
Authors: Garg Shruti , Behera Soumyajit , Patro K Rahul , Garg Ashwani 
Published: September 2021

Abstract
Emotion recognition using electroencephalogram (EEG) signals is an aspect of affective computing. The EEG refers to recording brain responses via electrical signals by showing external stimuli to the participants. This paper proposes the prediction of valence, arousal, dominance and liking for EEG signals using a deep neural network (DNN). The EEG data is obtained from the AMIGOS dataset, a publicly available dataset for mood and personality research. Two features, normalized and power and normalized wavelet energy, are extracted using Fourier and wavelet transform, respectively. A DNN with three different activation functions (exponential linear unit, rectified linear unit [ReLU] and leaky ReLU) has been applied for single and combined features. The result of combined features with leaky ReLU is found to be the best, with a classification accuracy of 85.47, 81.87, 84.04 and 86.63 for valence, arousal, dominance and liking, respectively.
Real-time Flow Visualization using Projection Mapping Technique
Authors: Nishanka T , Prajwal D , Nishmitha M , Bhat Vinayambika S 
Published: September 2021

Abstract
Flow visualization is a fundamental topic in scientific visualization and has been the subject of active research for a long time. Usually, information begins from numerical simulations, for example, those of computational fluid dynamics, and should be investigated by methods for perception to acquire a comprehension of the flow. With the rapid rise of computational power for simulations, the interest in further developed visualization strategies has thrived. The idea is to attain advanced visualization through the means of projection mapping. When incorporated with the properties of the fluid, whose flow is to be studied, we can create a visual simulation by extracting the real-time variations data through sensors and feed it to the projector, which results in a visualization method in the 3D plane. The complete process is made visible as the image is projected through light and also in space. Real-time Flow Visualization using Projection Mapping methods will help attain the same results as the conventional methods at less cost. As this process is crucial for many industries in the testing and design sectors, the desired output must be obtained within the given time constraint. This method will help to optimize the complete process. The result can be used to derive the necessary conditions for the best design and performance of the object or vehicle.
Influence of pH and salinity on the photocatalytic dye degradation and heavy metal ion reduction with cobalt ferrite photocatalysts
Authors: Chakkunny Anna Heba , Thomas Bintu , Alexander Libu K 
Published: September 2021

Abstract
The magnetic nanoparticle assisted photocatalytic oxidation-reduction is an effective method to remove and detoxify the organic dyes and the heavy metal ions present in the industrial wastewater. In the present study, the photocatalytic degradation of Methyl Orange(MO) dye and Cr(VI) ions in the presence of cobalt ferrite (CoFe2O4) superparamagnetic photocatalysts under visible light illumination are investigated as a function of wide range of pH and salinity conditions. The effect of pH on the photodegradation rates and the dual effect observed in the presence of Cl- ions were discussed. The photocatalytic degradation rates in single and binary impurity systems were also examined and the synergetic effect of MO oxidation and Cr(VI) reduction were established at different salinity and pH conditions.
Simulation Tests of Tokyo Quantum Network
Authors: Ceylan Osman , Yilmaz Ihsan 
Published: September 2021

Abstract
In this modern era where secure communication is imperative, scientists have always been in search of a new solutions for this problem. One of the best solutions discovered in this century, uses the superiorities of the quantum world. This theorem, called no cloning, mainly uses the collapse of quantum state when observing attribute of qubits. In this study, we will examine the Tokyo Quantum Network [1], which is based on the protocols derived from the BB84 [2] and B92 protocols by implementing in three quantum network simulators.
Selection of an efficient wind turbine generator at Government science college premises Chitradurga, India
Authors: Smitha patil G H , Megha R , Ravikiran Y T , Prashantkumar M , Udaykumar K , Kumaraswamy B G 
Published: September 2021

Abstract
Wind speed modelling is very crucial in estimating the potential of wind energy for a particular site. In this paper, the wind energy potential at the premises of Government Science College area [Lat. 14°13’′ N and Long. 76°27′ E] in Chitradurga town (Karnataka State, India) is statistically analyzed for the year 2019 – 2020. The speed of wind has been assessed at the height of 60 m from the ground level at the site. The seasonal and annual wind speed distributions (WSD) have been modelled using Weibull probability distribution functions (WPDF) i.e., shape parameter, k and scale parameters, c. With the use of them, the wind power density (WPD) has been determined. The WPD estimated from Weibull and normal methods has been found to be comparable. Further, at a height of 60 m above the ground, the capacity factors (CPs) of various marketablly useable wind turbine generators have been estimated to achieve the optimal power generation for the chosen site.
Optimized design of hydraulic silicone pad for OCA lamination of bended cover window in OLED display
Authors: Jang Dong-Hoon , Han Kwan-Young 
Published: September 2021

Abstract
In this study, we report the results of a new experiment using a hydraulically enabled silicone pad for OCA bonding in a cover window with three edges bent with 3R curvature. The silicone pad was designed using computer simulation to set eight important parameters in the cross-section of the pad and to optimize the shape according to the change in the curvature and length of the parameters. The compression strength of the designed silicone pad was analysed using simulation based on a hydraulic load. In addition, the hydraulic silicone pad, which was designed and manufactured in an optimized shape, was adhered to a pad plate to enable hydraulic pressure without oil leakage or outflow, and the OCA lamination was performed. Thus, we developed an optimized hydraulic silicone pad lamination method based on computer simulation and experimental results and provided a solution that can overcome the problems.
Undocumented citizens and the making of ID documents in Nigeria: an ethnography of the politics of suspicion in Jos
Authors: Fourchard Laurent 
Published: September 2021

Abstract
For 40 years, Nigeria has separated its citizens into two categories, ‘indigenes’ and ‘non-indigenes’. Indigene citizens can trace their genealogical roots back to a community in a locality. All local governments (LGs) in Nigeria issue certificates of indigene, which give access to the job market and university. This issuance of certificate of indigene has received scant academic attention despite the centrality of the indigeneity issue in Nigeria. In the two last decades, issuing certificates has become part of the political tensions and mass violence in Plateau State (Jos) as politicians and bureaucrats have transformed certificates to exclude most of the population from the local citizenship. Through an ethnographic approach, this article explores how a politics of suspicion can contribute to the growing literature on legal identification. Focusing on local authorities helps in understanding the centrality of suspicion in the making of new undocumented citizens which are not minority groups (foreigners, migrants and asylum seekers) usually targeted by national authorities. The complicated procedures to get certificates and the production of fake ones are an outcome of this politics of suspicion. The article also shows that a locally paper-based bureaucracy could expand at the same time as—and while being disconnected from—biometric identification.
Comprehensive geriatric assessment in newly diagnosed older myeloma patients: a multicentre, prospective, non-interventional study
Authors: Yao Yuan , Sui Wei-Wei , Liao Ai-Jun , Wang Wei , Chen Li-Juan , Chu Xiao-Xia , Bao Li , Cen Xi-Nan , Fu Rong , Liu Hui , Sun Chun-Yan , Jin Feng-Yan , Yan Hua , Wang Lu-Qun , Yuan Cheng-Lu , Gao Guang-Xun , Gao Da , Zhang Jin-Qiao , He Jian-Xia , Hu Jian-Da , Ma Liang-Ming , Zhang Lu , Zhou Dao-Bin , Zou De-Hui , Li Jian 
Published: September 2021

Abstract

Background
Multiple myeloma is a disease of the older people, whose prognoses are highly heterogeneous. The International Myeloma Working Group (IMWG) proposed a geriatric assessment (GA) based on age, functional status and comorbidities to discriminate between fit and frail patients. Given the multidimensional nature of frailty and the relatively recent exploration of frailty in the field of MM, reaching a consensus on the measurement of frailty in MM patients remains challenging.

Objective
We sought to assess the feasibility of performing a comprehensive GA (CGA) in older MM patients in a real-world and multicentre setting and to evaluate their baseline CGA profiles.

Results
We studied 349 older patients with newly diagnosed MM (age range, 65–86 years). Our results showed that a CGA is feasible for older MM patients. Using the IMWG-GA criteria, we identified significantly more frail patients in our cohort comparing to in the IMWG cohort (43% vs 30%, P = 0.002). In the IMWG-GA ‘fit’ group, risk of malnutrition, depression and cognitive impairment remains. The median follow-up time was 26 months (range 1–38). The median overall survival (OS) was 34.7 months, and the estimated 3-year OS rate was 50%. A high MNA-SF score (MNA-SF ≥ 12), low GDS score (GDS ≤ 5) and high CCI score (CCI ≥ 2) can be used to predict the OS of older patients with newly diagnosed MM. This study is registered at www.clinicaltrials.gov (NCT03122327).

Conclusions
Our study justifies the need for a CGA in older patients with newly diagnosed MM.
Twenty-First-Century Jewish Writing and the World
Authors: Goldman Dara E , Kaplan Brett Ashley 
Published: September 2021

Abstract
This introduction situates the essays about twenty-first century Jewish writing and the world in light of the exciting line up of writers who joined us at the University of Illinois for a series bridging fiction and scholarship. Nicole Krauss, Ruby Namdar, David Bezmozgis, and Ayelet Tsabari--Jewish writers from Israel, the U.S., and Canada, span a range of modalities and thematic concerns that ultimately illuminate the complexities of Jewish writing.