bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Artificial Intelligence Voice Technology in Radio and Television Media
Authors: Hu Meihui , Xiang Zhiwei , Li Kai 
Published: September 2021

Abstract
With the application of artificial intelligence in various fields, more and more people see the contribution of artificial intelligence technology to the development of the industry, and put more energy in the research of artificial intelligence language, and strive to provide better technical support for the development of more industries. In radio and television media, artificial intelligence voice technology can play a very important value, it can effectively improve the efficiency and quality of traditional audio work, optimize the singing system, broadcasting system and retrieval system, so as to provide better service quality for the masses. This paper discusses the application and development of artificial intelligence technology based on the fusion media environment, analyzes the application and development of artificial intelligence technology in promoting production efficiency, intelligent robot writing, intelligent face recognition, intelligent speech semantic recognition, intelligent OCR recognition, automatic broadcast and other aspects. These AI applications provide efficient and secure support for services, greatly improving service efficiency.
Physics-informed neural network for solving coupled Korteweg-de Vries equations
Authors: Xiao Chaohao , Zhu Xiaoqian , Yin Fukang , Cao Xiaoqun 
Published: September 2021

Abstract
The studies of coupled partial differential equations are focus of engineering and applied mathematics. Although traditional numerical methods have been widely used, researchers are still looking for new methods to solve coupled partial differential equations. In this paper, physical information neural network (PINN) is introduced to solve one-dimensional coupled Korteweg-de Vries (cKdV) equations. Compared with the traditional neural network, the innovation of PINN is to embed the physical constraints of the equations into the network loss function. Moreover, within the acceptable relative error range, the solution can take a longer single time step than the presently available. The results revealed that PINN can solve the cKdV equations with reasonable errors only by training a small amount of data.
An improved sine cosine algorithm for assignment problem
Authors: Ye Dan , Liu Yu , Zhang Shan , Yu Fei , Meng Hongyu , Li Bo , Shang Erzhen 
Published: September 2021

Abstract
The assignment problem is a NP-hard combinatorial optimization problem, where assignees are being assigned to perform tasks. This paper presents an improved sine and cosine algorithm (ISCA) to solve this problem. Nonlinear decreasing inertia weight, chaotic map and greedy strategy are added to the original sine cosine algorithm (SCA) to enhance the ability of focusing on optimal and avoiding local optima. Simulation results show that the proposed algorithm can get more competitive solutions when compared with differential evolution (DE), particle swarm optimization (PSO) and original SCA.
K-means clustering algorithm based on bee colony strategy
Authors: Zhang Zhenrong , Lan Jiayi , Zhang Zhenrong 
Published: September 2021

Abstract
The traditional swarm intelligence optimization K-means algorithm has some problems, such as poor global search ability and blind area selection of initial center points, which leads to the reduction of clustering availability. In order to avoid the above limitations, this paper proposed IABC k-means algorithm. Firstly, the employed bees stage in the traditional artificial bee colony ABC algorithm uses the current colony optimal solution information to guide its optimization search. Secondly, this paper wanted to solve the search ability of the employed bees and expand the information sharing range between various individuals, a random guidance mechanism is proposed in the onlookers bees stage. Finally, chaotic sequence is introduced in the scout bee stage to accelerate the convergence speed of the algorithm. IABC algorithm is proposed and applied to K-means clustering algorithm to improve the poor global search ability of K-means algorithm and the random selection of initial center points. Experiments show that the IABC and IABCK-means proposed in this paper effectively improves the clustering availability.
Evaluation method of degradation index based on AdaBoost regression
Authors: Li Pan , Shen Zhongjie , Zhang Xingwu 
Published: September 2021

Abstract
In the field of bearing monitoring, it has always been a difficult problem in the industry to judge the performance of the degradation index. A degradation index evaluation method is proposed based on AdaBoost regression. In this method, AdaBoost regression method is used for the bearing degradation index correlation evaluation criteria. The comprehensive weighted evaluation of degradation characteristics was obtained by the combination with robustness and monotonicity. Features were optimized according to the evaluation score. The analysis of accelerated life experimental data shows that the degradation feature evaluation method based on AdaBoost regression can effectively select the degradation features with good characterization.
Practical Thinking on Neural Network Phishing Website Detection Research Based on Decision Tree and Optimal Feature Selection
Authors: Zhang Qi 
Published: September 2021

Abstract
This article analyzes the detection methods of neural network phishing websites. The research content of this paper includes naive Bayes method, decision tree method, support vector machine method, neural network technology. The author combines the key points of phishing website detection based on decision tree and optimal feature selection to study such as URL feature and HTML feature analysis, website application feature analysis, K-Medoids cluster analysis, feature set screening. The author uses simulation experiments to complete the website performance check. The purpose of this article is to optimize the performance of phishing website detection and improve the security of the website’s operating environment.
Electroencephalogram signal characterization of tinnitus patients based on sample entropy algorithm and wavelet transform
Authors: Mai Jianbiao , Wang Xinzui , Li Zhaobo , Jia Haiyin , Fu Hui 
Published: September 2021

Abstract
Tinnitus is a disembodied, abnormal sound hallucination in the ear or skull, such as buzzing or hissing, in the absence of an external sound source. Tinnitus is a subjective sensation with no objective observable signs, and its causes are extremely complex. This paper explores the differences in sample entropy of EEG signals between tinnitus patients and normal subjects at different electrodes, using the non-parametric test Kruskal-Wallis test to find areas where there are significant differences between the different lateral tinnitus groups and the control group. Thirty tinnitus patients and 10 healthy controls were used to participate in the scalp EEG signal acquisition. The wavelet transform was first chosen to obtain the activity of each frequency band of the EEG, and then the electrophysiological differences between the two experimental groups were investigated by comparing the sample entropy of the EEG of the tinnitus patients with that of the healthy controls. The results reflect significant differences (p<0.05) in tinnitus patients at FT7, T7, C5, C6, TP7 and CP5 electrodes, mainly in the Delta band. These results compare the abnormalities of sample entropy in the resting state of patients with tinnitus on different sides of the ear with those of controls from an electroneuro-physiological perspective, and are expected to be used as a potential characteristic indicator to distinguish normal people from tinnitus patients for the auxiliary diagnosis of tinnitus and to provide physicians with an aid in diagnosing depressed patients.
Simulation of Different Third Harmonic Injected PWM Strategies for 5-Level Diode-Clamped Multilevel Inverter
Authors: Malladi Lakshmi Swarupa , Chapala Shravani , Veluri Sarada 
Published: September 2021

Abstract
Multilevel Inverters (MLI) have widespread use in industrial drive applications, HVDC transmission with Uninterruptable Power Supply systems. They also have applications in the stand-alone and the grid connected renewable energy systems. Multi-level Inverters also find optimum application in Stand-alone and Grid-connected Systems. Majority of losses i.e. switching losses are considered with constrained device rating, the traditional two-level inverters face limits especially when operating at high frequency. The solution which is optimum and appropriate by many power quality researchers is the use of MLIs. Among various MLI topologies the Diode-Clamped Multilevel Inverter (DCMLI) give a promising solution as they can give better voltage performance for different switching frequencies and an improved total harmonic distortion (THD) profile without the use of filter. To meet the voltage and frequency requirement various modulation techniques are applied to MLIs. The additional switching states created by these topologies provide greater flexibility to control more circuit breakers. This paper presents the comparison of a 5-level DCMLIs with several modulation schemes. The simulation results are discussed in detail and the comparison table is presented in terms of Output voltage and THD.
High Performance Wallace Tree Multiplier Using Majority Gate Based Adders
Authors: Mummudi Murasu M , Sujith Sanjana , Anita Angeline A , Sasi Priya P. , Kanchana Bhaaskaran V S 
Published: September 2021

Abstract
An area efficient high performance Wallace Tree Multiplier using Majority Gate based Adders is presented in this paper. The proposed Wallace tree multiplier is designed using 9T majority function based full adder. Design is implemented in Cadence Virtuoso® using a 180nm technology library. The design and analysis of the proposed design offers reduced delay of 33.12% while compared to the conventional wallace tree multiplier design using 16T full adder. The design also offers reduced transistor count of 208 which is minimal compared to that of the conventional design.
Power-efficient Strategies for Sensing in Autonomous Mobile Robots, a critical requirement of I4.0 standard
Authors: Bali Jyoti , Arpitha H , Anushree N , Giriyapur Arunkumar 
Published: September 2021

AbstractIn a production environment, there are several challenges in meeting the Industry 4.0 (I4.0) standard requirements. Energy efficiency is an essential area of focus. In the production setup, the critical and real-time control systems need to be very efficient while implementing functions, namely, accurate sensing, fast processing and precise actuation. Automated Guided vehicles (AGVs) and Automated Guided Vehicles are an integral part of modern and intelligent manufacturing systems. Power consumption in such systems is directly proportional to the performance level achieved. However, there is a need to evolve strategies to reduce power consumption and attain optimal performance. Field Programmable Gate Array(FPGA) based controller solutions can provide competent performance at optimized power consumption. The proposed work discusses the requirements of I4.0 concerning energy efficiency infrastructures for the intelligent manufacturing setup. The need to develop efficient subsystems for sensing, decision-making and actuation based on FPGA is stressed. Thus the focus is on the FPGA based power-efficient models used for sensor fusion technique in Autonomous Mobile Robots. The fundamentals of sensor fusion technique and the need to fuse sensor data for improved decision making and actuation are emphasized.
Mathematical model and analysis of PV Converter - Inverter System
Authors: Pushpa K R , Geetha R S 
Published: September 2021

Abstract
Photo Voltaic (PV) system is commonly preferred renewable energy source for most of the residential, commercial as well as for utility applications. Photo Voltaic systems are extensively used for standalone and grid tied applications. To utilize the PV generated power to the best possible extent, control and conversion of power in PV systems plays an important role. In this paper, mathematical model of the complete PV system that comprises of solar panel, DC-DC Boost converter and a H bridge inverter is developed. The developed model is validated for constant load condition at varying irradiation levels and at fixed duty cycle. The performance analysis of the PV system in terms of efficiency is carried out for 200W resistive load.
RETRACTED: A Novel approach in Hybrid Median Filtering for Denoising Medical images
Authors: Seetharaman R. , Tharun M. , Anandan K. 
Published: September 2021

Abstract
Image denoising is a key pre-processing step in medical image analysis. At current, deep learning-based models have shown a great promise, which outperformed many conventional methods over the past three decades. Speckle noise removal is a major issue in preserving all the delicate details and the edges in ultrasound image processing as it degrades the visual evaluation of ultrasound images. The multiplicative behavior of speckle-noise is converted into additive by using log transform as the additive noise removal is easy as compared to multiplicative noise. An innovative approach for denoising highly distorted images affected by speckle noise is proposed. This paper presents a result of significant work in image denoising and exploring several thresholding methods of denoising images such as SureShrink, VisuShrink and BayesShrink. The results of different approaches of wavelet-based image denoising methods are tabulated to find the best method. The main aim is to show the result of wavelet coefficients on a new basis, so that the noise can be minimized or removed from the data.
Fruit Classification Comparison Based on CNN and YOLO
Authors: Raj Riyanshu , Nagaraj S S , Ritesh Saurav , Thushar T A , Aparanji V M 
Published: September 2021

Abstract
Today, agriculture has become more of science than art. The demand for fresh produce is growing, while availability of field workers is diminishing. Also, Farmers keep investing in land, irrigation, and labor, and much of the fruit is left hanging on the trees because there are not enough people to pick it when it is ripe. Automation in the agricultural field using modern information and Communication Technology can increase the efficiency, reliability, and precision; and reduces the need of human intervention. Thus, to meet solution to this problem is by reducing the costs for farmers and increasing the yield of crops which can be achieved by classifying of fruit by using modern technique in the field of Deep Neural Networking that involves CNN, YOLO etc. which provides a helping hand to farmers to optimize their farming patterns and boost yields by allowing them to grow taller fruit trees that can be harvested by classifying based on the condition of fruit and saving significant labour cost. In conclusion, the proposed methods are highly acceptable and recognizing the necessity, and unresolved classifications.
Power Allocation Scheme for Non-Orthogonal Multiple Access System
Authors: Seetharaman R. , Tharun M. , Gayathri S. , Anandan K. 
Published: September 2021

Abstract
Since there exists a principal power-defer tradeoff in the NOMA framework, power proficiency additionally becomes basic for Ultra-Reliable Low Latency Communication (URLLC), particularly where countless gadgets are battery-fueled. Joining these contemplations, we reproduce Dynamic Power Allocation (DPA) for power area non-symmetrical different access (PD-NOMA) with client versatility. The exhibition of the DPA is contrasted and Static Power Allocation under client versatility. The characterization of clients in (NOMA) depends on power, while it depends on schedule, recurrence and code in Orthogonal Multiple Access (OMA). Since there exists an essential force defer tradeoff in the NOMA framework, power effectiveness likewise becomes basic for Ultra-Reliable Low Latency Communication (URLLC), particularly where countless gadgets are battery-controlled. Consolidating these contemplations, we reenact Dynamic Power Allocation (DPA) for power area non-symmetrical numerous entrance (PD-NOMA) with client portability. Force effectiveness becomes basic particularly for little and cumbersome battery-controlled IoT gadgets. Further, adaptability is additionally critical to speak with different machine-type gadgets just as human clients while meeting an assortment of nature of administration (QoS) prerequisites. The presentation of the DPA is contrasted and Static Power Allocation under client portability.
Design and preliminary test of a 105/140 GHz dual-frequency MW-level gyrotron
Authors: HU Linlin , SUN Dimin , HUANG Qili , ZHUO Tingting , MA Guowu , JIANG Yi , GONG Shenggang , ZENG Zaojin , GUO Zixing , DU Chaohai , LI Fanhong , CHEN Hongbin , MENG Fanbao , MA Hongge 
Published: September 2021

Abstract
A dual-frequency (105/140 GHz) MW-level continuous-wave gyrotron was developed for fusion application at Institute of Applied Electronics, China Academy of Engineering Physics. This gyrotron employs a cylindrical cavity working in the TE18,7 mode at 105 GHz and the TE24,9 mode at 140 GHz. A triode magnetron injection gun and a built-in quasi-optical mode converter were designed to operate at these two frequencies. For the proof-test phase, the gyrotron was equipped with a single-disk boron nitride window to achieve radio frequency output with a power of ∼500 kW for a short-pulse duration. In the preliminary short-pulse proof-test in the first quarter of 2021, the dual-frequency gyrotron achieved output powers of 300 kW at 105 GHz and 540 kW at 140 GHz, respectively, under 5 Hz 1 ms continuous pulse-burst operations. Power upgrade and pulse-width extension were hampered by the limitation of the high-voltage power supply and output window. This gyrotron design was preliminarily validated.
Do home adaptation interventions help to reduce emergency fall admissions? A national longitudinal data-linkage study of 657,536 older adults living in Wales (UK) between 2010 and 2017
Authors: Hollinghurst Joe , Daniels Helen , Fry Richard , Akbari Ashley , Rodgers Sarah , Watkins Alan , Hillcoat-Nallétamby Sarah , Williams Neil , Nikolova Silviya , Meads David , Clegg Andy 
Published: September 2021

Abstract

Background
falls are common in older people, but evidence for the effectiveness of preventative home adaptations is limited.

Aim
determine whether a national home adaptation service, Care&Repair Cymru (C&RC), identified individuals at risk of falls occurring at home and reduced the likelihood of falls.

Study Design
retrospective longitudinal controlled non-randomised intervention cohort study.

Setting
our cohort consisted of 657,536 individuals aged 60+ living in Wales (UK) between 1 January 2010 and 31 December 2017. About 123,729 individuals received a home adaptation service.

Methods
we created a dataset with up to 41 quarterly observations per person. For each quarter, we observed if a fall occurred at home that resulted in either an emergency department or an emergency hospital admission. We analysed the data using multilevel logistic regression.

Results
compared to the control group, C&RC clients had higher odds of falling, with an odds ratio (OR [95% confidence interval]) of 1.93 [1.87, 2.00]. Falls odds was higher for females (1.44 [1.42, 1.46]), older age (1.07 [1.07, 1.07]), increased frailty (mild 1.57 [1.55, 1.60], moderate 2.31 [2.26, 2.35], severe 3.05 [2.96, 3.13]), and deprivation (most deprived compared to least: 1.16 [1.13, 1.19]). Client fall odds decreased post-intervention; OR 0.97 [0.96, 0.97] per quarter. Regional variation existed for falls (5.8%), with most variation at the individual level (31.3%).

Conclusions
C&RC identified people more likely to have an emergency fall admission occurring at home, and their service reduced the odds of falling post-intervention. Service provisioning should meet the needs of an individual and need varies by personal and regional circumstance.
Making progress: but a way to go—the age and ageing care-home collection
Authors: Gordon Adam L , Bennett Chloe , Goodman Claire , Achterberg Wilco P 
Published: September 2021

Abstract
Care homes enable people with advanced physical and cognitive impairment to live well with 24-h support from staff. They are a feature of care systems in most countries. They have proved pivotal to the coronavirus disease 2019 (COVID-19) response.
We searched Age and Ageing for care-home articles published since 2015. From these we collated 42 into the Age and Ageing care-home collection. This collection draws together important papers that show how Age and Ageing is helping to shape and grow care-home research.
The collection outlines the technical issues that researchers face by grouping together important feasibility trials conducted in the sector. It looks at the challenges of measuring quality of life and working with routine data in care homes. It brings together observational studies considering loneliness, functional dependency, stroke outcomes, prescribing and acute deterioration. Health services research in care homes is represented by two studies that demonstrate realist evaluation as a way to make sense of service innovations.
Papers are included that consider: non-pharmacological strategies for residents with dementia, end-of-life care, sexuality and intimacy and the care-home workforce. Given the importance of the COVID-19 pandemic in care homes, all of the care home COVID-19 papers published in Age and Ageing to date are included.
Finally, a group of papers that present innovative approaches to research in care homes, each of which give voice to residents and/or staff, are collated and presented as a way of moving towards a more resident and care home centred research agenda.
An Evaluation of Cardiac Health in the Spontaneously Hypertensive Rat Colony: Implications of Evolutionary Driven Increases in Concentric Hypertrophy
Authors: Holjak Emma J B , Savinova Iryna , Nelson Victoria L , Ogilvie Leslie M , Ng Anabelle M , Edgett Brittany A , Platt Mathew J , Brunt Keith R , Ask Kjetil , Simpson Jeremy A 
Published: September 2021

Abstract

Background
The Spontaneously Hypertensive Rat (SHR) Colony was established in 1963 and is the most commonly used rodent model for studying heart failure (HF). Ideally, animal models should recapitulate the clinical disease as closely as possible. Any drift in a genetic model may create a new model that no longer adequately represents the human pathology. Further, instability overtime may lead to conflicting data between laboratories and/or irreproducible results. While systolic blood pressure (SBP) is closely monitored during inbreeding, the sequelae of HF (e.g., cardiac hypertrophy) are not. Thus, the object of this review was to investigate whether the hypertension-induced sequelae of HF in the SHR have remained stable after decades of inbreeding.

Methods
A systematic review was performed to evaluate indices of cardiovascular health in the SHR over the past 60 years. For post hoc statistical analyses, studies were separated into 2 cohorts: Initial (mid to late 1900s) and Current (early 2000s to present) Colony SHRs. Wistar-Kyoto rats (WKY) were used as controls.

Results
SBP was consistent between Initial and Current Colony SHRs. However, Current Colony SHRs presented with increased concentric hypertrophy (i.e., elevated heart weight and posterior wall thickness) while cardiac output remained consistent. Since these changes were not observed in the WKY controls, cardiac-derived changes in Current Colony SHRs were unlikely due to differences in environmental conditions.

Conclusions
Together, these data firmly establish a cardiac-based phenotypic shift in the SHR model and provide important insights into the beneficial function of concentric hypertrophy in hypertension-induced HF.