bluuebunny/crossref_metadata_2025_split huggingface dataset:
Performance analysis of support vector machines with polynomial kernel for sentiment polarity identification: A case study in lecturer’s performance questionnaire
Authors: Pradnyana G A , Darmawiguna I G M , Suditresna Jaya D K S , Sasmita A 
Published: March 2021

Abstract
The lecturers’ performance evaluation process can be carried out using an open questionnaire filled out by students at the end of the semester. In this questionnaire, students can provide an assessment in the form of comments, suggestions, and criticism of the ’lecturer’s performance, which can describe the level of student satisfaction with the lecture process. Conducting assessments or analyses on the open questionnaire entries manually will certainly impact the high costs time and energy. Sentiment polarity identification is a process in sentiment analysis that classifies text into a sentence or document and then determines whether the opinion expressed is positive, negative or neutral. In this research, a sentiment polarity detection system was developed in a lecturer evaluation questionnaire using the Support Vector Machine (SVM) method with a polynomial kernel. The test results showed that the SVM method’s performance with the Polynomial kernel was strongly influenced by the value of the learning rate parameter, the maximum iteration, and the degree, with the optimal parameter values, respectively, 0.001, 200, and 0.3. The use of optimal parameter values in the process of identifying sentiment polarity obtained an accuracy value of 84.88%.
The design of the cse-ucla evaluation model using topsis and ahp methods for optimizing digital library services in badung regency
Authors: Atmaja I M D S , Divayana D G H , Setemen K 
Published: March 2021

Abstract
The Regional Archives and Library Office of Badung Regency must optimize the services provided in order to achieve excellent service quality. In its implementation, the office encountered difficulties in prioritizing aspects of services that require optimization. The purpose of this study was to design a Center for the Study of Evaluation-University of California in Los Angeles (CSE-UCLA) evaluation model using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Analytical Hierarchy Process (AHP) to provide recommendations on which aspects of services need to be optimized. The research method used stages that included problem identification, problem formulation, literature review, data collection, data analysis, design, and conclusions. The TOPSIS and AHP methods had the ability to rank a variety of aspects in the CSE-UCLA model. Aspect with the lowest ranking was considered as the aspect that is prioritized for optimization. That aspects used five service criteria: tangible, reliability, assurance, responsiveness, and empathy, all of which were classified in the “benefit” category. Each criterion had a value of 0.200, 0.200, 0.200, 0.200, 0.200 for the weight values for system assessment, program planning, program implementation, and program improvement, while for program certification: 0.556, 0.111, 0.111, 0.111, 0.111, respectively.
Application of certain Third-order Non-linear Neutral Difference Equations in Robotics Engineering
Authors: Sindhuja S , Daphy Louis Lovenia J , Lavanya A P , Darling Jemima D , Jayabarathy G 
Published: March 2021

Abstract
We have obtained some results on oscillatory behavior of third order nonlinear neutral difference equations of the form

Δ
3

(

y

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1

+
b

y

m
1

−

δ
1

−
c

y

m
1

+

δ
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)

β

=

q

m
1

−
1

y

m
1

−

ρ
1

−
1

γ

−

q

m
1

y

m
1

−

ρ
1

γ

+

p

m
1

−
1

y

m
1

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2

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1

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−

p

m
1

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2

γ

Δ
3

(

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m
1

+
b

y

m
1

−

δ
1

−
c

y

m
1

+

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2

)

β

=

q

m
1

−
1

y

m
1

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ρ
1

−
1

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q

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1

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m
1

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1

y

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1

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2

−
1

y

−

p

m
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y

m
1

+

ρ
2

γ

where β and γ are odd integers with γ ≥ 1. Example is provided to illustrate the results.
RETRACTED: A Review on Graph Theory in Network and Artificial Intelligence
Authors: Narayanan Kannaiyan Geetha , Pappula Bridjesh , Veerubommu Ragavi 
Published: March 2021

Abstract
The Mathematics field assumes crucial function in different fields. One of the significant territories in Mathematics is Graph theory which isutilized in basic models. We give a study of Graph theory utilized in computer sciences. The study comprises of a portrayal of specific themes from the Graph theory of the zone of Computer science where they are utilized. In any case, for each portrayed hypothesis we show the fields where it is utilized. For example in demonstrating and looking through Internet, in Computer science vision, design acknowledgment, information mining, multiprocessor frameworks, factual information bases, and in a few different regions. This paper gives a overview of the application of Graph theory in heterogeneous fields somewhat however chiefly centers around the software engineering applications that utilizations Graph theory ideas. Computer Science and Artificial Intelligence applications and an overview has been presented in this article.
Ethical hacking and penetration testing for securing us form Hackers
Authors: Pradeep I , Sakthivel G 
Published: March 2021

Abstract
Almost all the people around the world are fully equipped with technologies and software’s. But the how many are really using it wisely, we as the creators of all technologies are being governed by such a technology itself. The software’s are being discovered every day and each one provides a new facility and a hidden disadvantage in it. Many people don’t even have the basic knowledge of what they are doing and that’s the main reason for all cyber-crimes and security breaches. It has become responsibility of every citizen who is using a tech to keep their information safe and secure from others. Be aware of what we are doing in mobiles, laptops, PCs, etc.… since a small activity could lead to great crisis.
An Empirical Exploration of Artificial Intelligence in Medical Domain for Prediction and Analysis of Diabetic Retinopathy: Review
Authors: Deshmukh S V , Roy A 
Published: March 2021

Abstract
The country like India, the majority of people suffering from diabetic retinopathy, is caused by diabetes. Diabetic retinopathy may affect the eyesight of diabetic patients. This paper aims to explore the basics to advance artificial intelligence technology uses to detect diabetic retinopathy. The paper focuses on how different artificial intelligence methods will help detect diabetic retinopathy early, and it is more crucial to recover the vision for timely treatment. Various diabetic retinopathy detection methods are available for diabetic retinopathy, different datasets used in different ways some researcher uses primary datasets, and some use secondary datasets like eyepacs, messidor, kaggle, drive, and many more. Many of these datasets acquired by retinal fundus camera, which in the type of images or .cvs, it is again raw and manual annotations. Many machine learning and deep learning algorithms verify the specificity, sensitivity, and accuracy or classify different stages of diabetic retinopathy. The analysis included many retinal datasets; many artificial algorithms that use many methods and apply on different datasets that give different results vary between sensitivity 85% to 95%, specificity 85% to 96%, and accuracy 87% to 99%. This paper describes diabetic retinopathy’s detection with three primary facets; retinal datasets, methods to detect diabetic retinopathy, and performance evaluation metrics. To defeat the research challenges of the researchers that overall study and observations provide the clue in the field of diabetic retinopathy.
Methods of Detecting Image forgery using convolutional neural network
Authors: Leekha Alka , Gupta Arpan , Kumar Amit , Chaudhary Tarun 
Published: March 2021

Abstract
Image Forgery means manipulation of the digital image so as to hide the necessary information or to convert the image into something which can be used for illegal mo-tives.Differentiating between an original image and a tampered image is a strenuous work for a human being. Machines can do that easily for large amount of data with the help of many artificial intelligence technique and mathematical approaches that are used to develop a system which will help in recognizing whether the image is tampered or not. In this paper Various models like CNN , Hashing , DCT, DWT will be discussed.This paper also discussed about the implementation of CNN done on a data set to figure out a model which is best suited for the development of an image forgery detection system.
Hexafunctional Autonomous Robotic Cart (HARC) for Covid Wardsminimizing human contact risk
Authors: Mahore Rupesh , Mahore Gunendra 
Published: March 2021

Abstract
Medical robotics has shown a significant uprising in the era of COVID 19 global pandemic. With the medical and paramedical staff being in the frontline of this deadly virus it is really important disseminate simpler technologies integrated together to protect them and provide nascent solutions to the problem of contact risk in hospitals. In this paper we have proposed and designed a Hexafunctional Autonomous Robotic Cart (HARC) for covid and isolation wards. The design with its simplicity, durability and cost effectiveness offer a great aid to the healthcare system in not only maintaining social distancing and minimising contact risk but also diagnosing the health of patient and establishing active communication with the concerneddoctor.
Diabetes Mellitus and Diabetic Retinopathy Detection using Tongue Images
Authors: Stephen Sagayaraj A. , Kabilesh S K , Anand Kumar A. , Gokulnath S. , Mani T. , Dinakaran K 
Published: March 2021

Abstract
Diabetes Mellitus is a metabolic disorder caused by increasing blood sugar level. This includes invasive test to detect and diagnose. The image processing technology is introduced to diagnose through non-invasive method. Color, texture and geometry features are extracted. Color gamut is extracted to isolate the same kind of features. The color feature is represented from the extracted gamut. The feature based on distances, height, surface area, width are extracted. The SVM classifiers is used to differentiate the diabetes mellitus affected person and healthy person.
Some Results on Prime Cordial Labeling of Lilly Graphs
Authors: Parthiban A. , Sharma Vishally 
Published: March 2021

Abstract
A PCL of G is a bijective map g from V to {1, 2, 3, |V|} in such a way that if an edge st is given label 1 if GCD(g(s), g(t)) = 1 & 0 otherwise, then the edges given 0 & 1 differ by at most 1 i.e; |eg
(0) − eg
(1)| ≤ 1. If a graph permits a PCL, then it is called a PCG. In this paper, we prove that lilly graph admits a PCL. Further, we have shown that lilly graph under some graph operations like switching of a vertex, duplication of a vertex, degree splitting graph and barycentric subdivision admits a PCL which may find its application in the development of artificial intelligence.
Structural damage identification based on dynamic deflection sensitivity of bridge under vehicle loading
Authors: Li Yue , Zhang Kun 
Published: March 2021

Abstract
Based on the concept of dynamic response sensitivity, a method of identifying bridge structural damage by using the dynamic deflection response of bridge under vehicle load is proposed. Firstly, the dynamic equation of vehicle-bridge coupling dynamic system is established. And then, the basic principle and iterative identification process of bridge damage identification based on dynamic deflection response sensitivity are derived. Finally, the effectiveness of the algorithm is verified with a numerical example of three-span continuous beam vehicle-bridge coupling system. The research results show that the proposed algorithm can overcome the influence of measurement noise and initial model error, and realize the damage location and quantification of bridge from dynamic deflections of a few measuring points.
The utility model relates to a system for absorbing, storing and reusing harmful gases in municipal sewer system
Authors: Tan Xiaolong , Tu Mingxi , Tao Menglun , Li Kuangxi 
Published: March 2021

Abstract
With the acceleration of urbanization, the scale of urban sewage drainage systems is also getting larger and larger. The pipeline sewage carries a large amount of domestic garbage and sludge after being decomposed by microorganisms, which produces a large amount of toxic, harmful, flammable and explosive gases, such as methane (CH4) and hydrogen sulfide (H2S). When these gases are concentrated in the drainage pipe, it is a serious safety hazard. If these gases are directly discharged into the atmosphere, it will pollute the environment on the one hand, and waste resources on the other. In order to solve this important problem, this paper designs a system for the absorption, storage and reuse of harmful gases in urban sewage pipelines for hydrogen sulfide and methane. The hydrogen sulfide and methane gas are absorbed by the gas adsorption device, and then the gas is pumped out of the adsorption device by a solar driven pump and stored in the gas storage device.
RETRACTED: Design of life assistance device for the elderly based on artificial intelligence
Authors: Li Wei 
Published: March 2021

Abstract
With the development of the times, China has entered a stage of aging population. Because of the increase of age, the elderly are often hard to finish like bend over, squat such simple actions, which brought great challenge to the basic life of old people. Some basic activities such as walking and the toilet, are very difficult for them. In order to guarantee the basic life of the elderly, a kind of life assistance device for the elderly based on artificial intelligence is designed to help the elderly in walking and toilet. The mechanical structure of the device mainly consists of five parts, namely, walking mechanism, lifting mechanism, rotating seat cushion mechanism, rotating handrail mechanism and pulling rod backrest mechanism. The control part is mainly based on voice recognition technology. The device is simple in structure, convenient in operation and low in cost. Compared with the existing life assistance devices for the elderly, the device has more complete functions, which better solves the difficulties of the elderly in walking and using the toilet, and provides great convenience for the elderly.
Modal parameter identification of rotating machinery based on time domain synchronous averaging
Authors: Zhang Zhuzhu , Wang Ting , Deng Congying , Zhao Yang , Deng Haiyan 
Published: March 2021

AbstractOperational modal analysis (OMA) is an important method of structural dynamic design and mechanical fault diagnosis. It is the application of parameter identification in the field of engineering vibration. Traditional operational modal analysis is based on the random response of white noise. However, when rotating machinery structure is running at high speed, it will produce a lot of harmonic interference, which will affect the identification effect. In this paper, the time domain synchronous averaging technique is used to remove the periodic harmonics in the response. For the random response part, the method of combining NExT and ITD is used to identify the modal parameters.
Elevator group control strategy and software design in high-rise office building
Authors: Wang Yanlin , Jiang Tao 
Published: March 2021

Abstract
Elevators are widely used in high-rise buildings. Especially in high-rise office buildings, multiple elevators are usually installed to meet the commuting needs of a large number of workers. How to dispatch multiple elevators efficiently is particularly important. As a widely used controller in industry, PLC has the characteristics of high reliability, fast calculation speed, and easy programming and installation. The PLC is used to make real-time comprehensive judgments of elevator car position, running direction, load situation and call signals situation. Then the optimal elevator is selected to reduce the waiting and boarding time of passengers.
Reliability Evaluation Method of Torpedo in Service Based on Conditional Reliability
Authors: Wang Xinpeng , Meng Bo , Xu Dong , Yang Tao 
Published: March 2021

Abstract
In order to effectively evaluate the reliability index of in-service torpedo, combined with the actual use of torpedo, the reliability evaluation method of in-service torpedo based on conditional reliability is proposed. On the basis of determining the failure distribution under the single state of components, the variation of the reliability distribution of the components after several states are studied. Based on the fault tree structure function, the reliability simulation model of torpedo is established, and the Monte Carlo method is used to establish the simulation solution process, so as to obtain the reliability parameters of torpedo. This method is simple and easy to implement, and has important guiding significance for evaluating the reliability of in-service torpedoes.
Application of Electronic Information Technology in Electrical Automation
Authors: Zhou Zihang , Geng Yuyin , You Shikun , Ziteng Chen , Nong Yuan 
Published: March 2021

Abstract
With the further development of the industrial revolution, various regions in the world have entered the era of industrial economy one after another. And modern science and technology go deep into all walks of life at the same time in the industrial field has made great changes. This makes the domestic electrical automation technology tend to change to the level of intelligence, automation and information. In order to better strengthen the integration of electronic technology in the industry, an effective application strategy is put forward for the specific application of electronic information technology in electrical automation.
EEG signal classification method based on improved empirical mode decomposition and SVM
Authors: Zhang Zihao , Li Zhiyi , Ma Ting , Zhao Jiayu 
Published: March 2021

Abstract
Epilepsy is a common phenomenon formed by abnormal discharges between brain neurons. The seizures of epilepsy are sudden and irregular. As a non-stationary signal, EEG signals can express its characteristics to a certain extent, and makes a significant difference in the monitoring and treatment of epilepsy diseases. This study employs empirical mode decomposition (EMD) to decompose the interictal and epileptic EEG signals into multiple eigenmode functions (IMF), and combines the correlation coefficient to screen the main IMF and extract its variance, fluctuation coefficient and Coefficient of variation and other features, combined with support vector machines for classification. Compared with the traditional empirical mode decomposition, this method has higher accuracy in the identification and classification of epileptic signals. The combination of this method not only provides a theoretical method for disease diagnosis and treatment, but also verifies the research and application value of EEG signals to a certain extent.
Learning of Zero-Velocity Detection for Inertial Pedestrian Navigation
Authors: Chen Ze , Pan Xianfei 
Published: March 2021

Abstract
The detection of zero-velocity states is the vital prerequisite for zero-velocity update in the foot-mounted inertial pedestrian navigation system. The previous zero-velocity detector determines zero-velocity states by comparing measured inertial data with a calibrated threshold. The calibration of the threshold is inconvenient for this kind of the zero-velocity detector because the threshold is variable corresponding to different people and locomotion. The best threshold needs to be tuned corresponding to different situations. In essence, the detection of zero-velocity states is a binary classification problem. As the success of deep learning in in image classification and speech recognition, it is possible to design an adaptive zero-velocity detector based on it. A Siamese network is designed to learn the metric of distinguish zero-velocity states. This method can adaptively get the most likely correct results without threshold tuning. Experiments are conducted and results show that the matching degree is about 96.31% and the navigation accuracy can reach within 4m in 20min.
Simulation research on miniature planar induction heater with cavity
Authors: Liu Bendong , Ma Chenxu , Dong Shijie , Tan Jingkai 
Published: March 2021

Abstract
This paper studies a new type of miniature planar induction heater through simulation. The miniature plane induction heater consists of a metal heating plate, a glass slide and a plane coil. The metal micro heating plate is designed with a cavity of a specific size. Since the cavity contains residual gas, when the micro heating plate is heated, hot bubbles will be generated in the cavity better and faster. Through the analysis of the energy density, eddy current density, and temperature distribution of the metal micro heating plate, it is found that the cavities play a very good role in the concentration of eddy current and the increase of energy. This kind of micro planar induction heater can be used for various hot bubbles to drive micro execution devices, such as micro ejectors, micro mixers and micro pumps.
On the Design of Open Source Programming Language in Noise Pollution Interaction Installations
Authors: Xinyun Fang 
Published: March 2021

Abstract
With the progress of time and the development of science and technology, interactive installation art, as an important and novel part of the new media art, is becoming more prominent on the stage of major international exhibitions. Artists create a new experience in a variety of perceptions using the unique language of interactive installation art to stimulate people’s inspirations through their interaction with the works, and to trigger in-depth thinking. This new art form shortens the distance between art and the public and gives people novel experiences in the interaction. Taking the work “Uncomfortable” as a case study, this paper shows the harm of noise pollution to human bodies with the help of Processing and Arduino, studies the practical value of program design in interactive installation art, discusses the influence of open source programming language on the future development of interactive installation art, and provides new ideas for further integration of future art and technology.
Analysis and comparison of Gaussian noise denoising algorithms
Authors: Jia Mingchen , Dong Mingming 
Published: March 2021

Abstract
Collecting and processing various images has become an irreversible trend. It is meaningful to conduct more in-depth research on image denoising algorithms. We proposed mean filtering, median filtering, wiener filtering and wavelet filtering to denoise the image with Gaussian noise separately. And the objective image quality assessments are used to evaluate the quality of the images after denoising. Among them, wavelet filtering and Wiener filtering have a better effect on weaken Gaussian noise. Mean filtering and median filtering can also weaken Gaussian noise to some extent but the effect is limited. At the same time, it is equally important to select the appropriate denoising block for the diverse mean and variance of Gaussian noise. In wavelet filtering, the number of layers to be decomposed and the choice of threshold will also affect the effect of image denoising.