bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Claims Statements from Viral Videos for Instrument Development to Assess Argumentation Thinking Skills
Authors: Suyono  , Nasrudin H , Yonata B , Sabtiawan W B 
Published: May 2021

Abstract
The final goal of the research that is being carried out by researchers is to produce empirical data in the form of a profile of the argumentation ability of chemistry education study program students in assessing the phenomena of daily life that are exposed to viral on social networks/media. To achieve that goal, it requires the identification stage and the formulation of a claim statement that is written in the video. Thus, the goal to be achieved at this stage is to obtain a list of claim statements that will be used as a stem in the preparation of questions to assess the ability of the argument or counterargument of the test objectives. The method used is content analysis. There were 11 claim statements have been successfully formulated and the uses in the preparation of argumentation questions. The formulated claim statements are grouped into two statuses, namely true claim statements and false claims statements from a scientific perspective. The two groups of claim statements can then be taken into consideration by researchers for two designations. The first designation is to determine the types of questions to be developed, namely questions of argumentation and/or questions of counter argumentation. The second designation is the preparation of a rubric in scoring students’ argumentative abilities.
Design Seamless Learning Environment in Higher Education with Mobile Device
Authors: Dakir  , El Iq Bali Muhammad Mushfi , Zulfajri  , Muali Chusnul , Baharun Hasan , Ferdianto Dani , Al-Farisi Muhammad Salman 
Published: May 2021

AbstractMobile learning functions to facilitate student learning because it has characteristics that are practical to carry anywhere, so mobile learning has its interests. With mobile learning, learning is more flexible and effective. The consideration of the effectiveness of mobile learning-based learning demands the importance of research on the development of cutting-edge learning models to help students and educators to make learning easier and provide learning motivation for students in higher education. This research is descriptive quantitative research with data collection techniques using a questionnaire. This research was conducted from April to June 2020 in the PGMI Nurul Jadid University. The research population is students of the PGMI who are still active in the 2019/2020 academic year. Mobile learning based on mobile devices is in the useful category with a frequency of 28 and a percentage of 75.67, the rest is in the fairly good category, a frequency of 3 is obtained with a percentage of 8.10%, in the very good category a frequency of 4 is obtained with a percentage of 10.82%, and less, obtained a frequency of 2 with a percentage of 5.40%.
Performance of CH-DVR during Phase Angle Jump and Fault Riding
Authors: Palleswari Y T R , Siva Asapu , Kadali KalyanSagar , bhukya Ramu 
Published: May 2021

Abstract
In this paper, a seven-level cascaded H-Bridge dynamic voltage restorer (CHDVR) is proposed to mitigate power quality issues in the power system that are causing severe problems both in industrial and commercial sectors which may sometimes lead to interruption of power. To improve the voltage quality, many series compensators are been using in which DVR is one best solution wherein in many cases phase angle jump is not considered during the initial stage of compensation which influences the power quality. In this paper voltage Phase Angle Jump (PAJ) is taken into consideration to improve voltage quality using DVR. Moreover, Fault riding capability (FRC) is also considered along with phase jump to progress overall execution of the power system. The control strategy adopted is worked out for several sag cases and the analysis is validated using results acquired from MATLAB/SIMULINK 2019 platform.
Texture based Clustering Technique for Fetal Ultrasound Image Segmentation
Authors: Sree S Jayanthi , Kiruthika V , Vasanthanayaki C 
Published: May 2021

Abstract
Segmentation of fetal ultrasound image is an important and necessary task in the automation of fetal biometric measurement. Fetal ultrasound image segmentation is tedious because of the fuzzy nature and textured appearance of fetal structures. Hence, texture based Clustering is proposed for segmenting fetal ultrasound images. Clustering is performed using texture properties of the images which are used for segmenting ultrasound images of fetus. Texture based clustering technique can be used for segmenting all fetal anatomies specifically abdomen, the boundaries of which are very vague and difficult to delineate. Synthetic, simulated ultrasound images and 120 ultrasound fetal images were used for validating the method achieving an accuracy of 90%.
Efficient Clustering of Unlabeled Brain DICOM Images based on similarity
Authors: Murugan Suriya , Sumithra M G , Murugappan M 
Published: May 2021

Abstract
Clustering has proven to be an effective method in the medical field for finding patterns in labelled and unlabelled datasets. This work is implemented over whole body CT scans (∼1TB) of 3500 patients in form of unlabelled DICOM images. The whole-body CT images have been anonymized for 30 attributes based on DICOM regulations and the Brain images alone are segmented using the DICOM tag element called ‘Protocol stack’. The segmented Brain images are efficiently grouped based on visual similarity using K-means clustering after performing feature extraction and dimensionality reduction. The results of the clustering can be furtherutilized by radiologists to perform labelling or find patterns in Brain CT scans of patients that are difficult where each scan consists of a varying number of slices during detection of Internal Bleeding. The efficiency of K-means is analyzed by performing computation over a different number of clusters (K) by applying silhouette scores to find optimal cluster.
An Effectual Smart Waste Assortment using Metallic sensors
Authors: Keerthana S , Kiruthika B , Lokeshvaran R , Midhun Chakkaravarthi B , Dhivyasri G 
Published: May 2021

Abstract
Quick expansion in populace has prompted inappropriate waste administration in metro urban communities and metropolitan regions. It makes unhygienic conditions for the residents in the environmental factors, prompting spread of infections and disease. To stay away from this issue, IoT based waste assortment and removal, is the best arrangement. This framework identifies the appearance of garbage utilizing an IR sensor and checks the substance of metal by utilizing metallic sensor. Moreover, the waste is grouped into dry and wet waste build-up with the assistance of capacitive finder. It comprises of ultrasonic sensors which quantifies the degree of trash, and shows the level in LCD screen just as message to clean in the event that it is full.. It is normal that this framework brings about establishing greener climate by observing and arranging the assortment of waste shrewdly through IoT.
Object Recognition in Images with Low-Resolution using Convolutional Neural Network
Authors: Raghunathan T , Sharmili G , Shreejaa T H , Saru S 
Published: May 2021

Abstract
Object recognition is a technology in computer vision that finds objects in an image or video series and identifies them. Phenomenal results have been recorded in object recognition studies using deep neural networks. But it has generally been deduced that sufficient image resolution and object size are obtainable, which cannot be assured in practical uses. Recognition of objects in lower resolution images is difficult. To overcome the stated problem, a Convolutional Neural Network (CNN) model for identifying objects in lower resolution images is proposed in this paper. In object recognition datasets, this approach outperforms the high recognition accuracy. In convolutional neural network models, both convolution and max-pooling layers are typically stacked. In the proposed approach, the pooling layer was substituted with a convolutional layer with an expanded phase without loss of precision in image recognition. The All Convolutional Neural Network with trained weights for recognizing lower resolution images is deployed. Through the obtained results, it is verified that the proposed model has high efficiency and accuracy.
Movie Recommender System Using Machine Learning Algorithms
Authors: Kumar Piyush , Kibriya Shaik Golam , Ajay Yuva , Ilampiray  
Published: May 2021

Abstract
These days, a recommendation of a movie from a server-based system has made finding a piece of cinema easier. Film recommendation helps us to find films that we need to watch, instead of searching extensively online and help cinephiles and movie buffs by suggesting top tier films to watch without looking into huge databases which is very time consuming. As an approach to this dilemma, we Introduce a model based on collaborative and content-based approach which will use a variety of Python based Machine Learning algorithms from huge datasets and immensely produce a movie suggestion based on their taste and past watch history or genre. This compared to other recommendation systems is different and is based on a content-based approach.
Design of an integrated system of wireless power transfer, battery health monitoring system and automated power factor correction in electric vehicles
Authors: Senthil Kumar R , Saravanan S , Sivaram M K Raj , Kishore Aravindh S , Manoj Kiran K , Kavin Kumar M 
Published: May 2021

Abstract
Since gasoline prices have risen, electric vehicles (EVs) are becoming more common. As a result of these conditions, many vehicle manufacturers are searching for alternative energy sources to petrol. Electrical energy sources could be better for the environment because they produce fewer emissions. Furthermore, electric cars have major benefits in terms of energy efficiency and environmental safety. This project aims in providing a complete solution of wireless power transfer, battery health alert system and automated power factor correction of the electrical system of electrical vehicles, thereby providing a complete integrated solution of wireless charging of rechargeable battery present in electric vehicles as well as proper utilization of the active power to the maximum in AC Electric vehicles, therefore increasing the efficiency of the power utilization. This project also discusses the battery health alert system. This project aims in providing an automated solution of reactive power compensation of electrical system in EVs to reduce the wastage of power effectively.
Deep learning based Food Recognition using Tensorflow
Authors: Abirami K Rama , ManojKumar M , Insaf Mohammed , Sakthivel Naveen 
Published: May 2021

Abstract
Cutting edge profound learning models for food acknowledgment don’t permit information steady taking in and frequently experience the ill effects of cataclysmic impedance issues during the class gradual learning. This is a significant issue in food acknowledgment since certifiable food datasets are open-finished and dynamic, including a persistent expansion in food tests and food classes. Model retraining is frequently done to adapt to the powerful idea of the information, yet this requests very good quality computational assets and critical time. This paper proposes another open-finished ceaseless learning system by utilizing move learning on profound models for include extraction, Relief F for highlight determination, and a novel versatile decreased class steady portion extraordinary learning machine (ARCIKELM) for characterization. Move learning is gainful because of the great speculation capacity of profound learning highlights. Alleviation F lessens computational intricacy by positioning and choosing the extricated highlights. The tale ARCIKELM classifier progressively changes network design to decrease calamitous neglect. It tends to space variation issues when new examples of the current class show up. To direct complete analyses, we thought about the model in contrast to four standard food benchmarks and an as of late gathered Pakistani food dataset. Test results show that the proposed structure learns new classes steadily with less calamitous induction and adjusts space changes while having serious characterization execution.
Efficient Method for Storing Health Record in Cloud Using Integrity Auditing and Data Sharing
Authors: Abirami K Rama , Ajaye K P , Amrrish Roshan B L , Arun Nishanthan A 
Published: May 2021

Abstract
Identity based cloud storage authorization is proposed in this paper to provide protection of cloud data. Many sensitive information is stored in the cloud, and it must be kept safe from unauthorized access. By hiding the sensitive information’s, privacy for an individual or organization is provided. The data in the cloud are secured by hiding the sensitive information. In the proposed system when the user and data analyzer sign-in they will receive the verification mail to assure as a valid user or data analyzer. The verification key for the user and the data analyzer is generated by the Private Key Generator (PKG). The user and the data analyzer enter the cloud using the verification key to upload and retrieve data from the cloud. Until uploading data to the cloud, the user encrypts the data, concealing confidential details. The Third Party Auditor is in charge of the cloud auditing process (TPA). This scheme allows data files stored in the cloud to be shared and used by data analyzers under the condition that confidential information is hidden, allowing the auditing system to operate more efficiently.
A Review on Development of Rare Earth Based Contrast Agents for Dual Modal Imaging of Cancer Cells
Authors: Gayathri T 
Published: May 2021

AbstractThe risk of developing cancer is becoming higher due to the genetic and environmental factors. Diagnosing cancer at an early stage is a very big challenge to clinicians and researchers. Several imaging modalities are being used in hospitals for diagnostic purposes. But each imaging modality has some limitations to identify the cancer cells at their early stage. Magnetic resonance imaging can be combined with optical imaging for better diagnosis of cancer. This concept of combining two imaging modalities is termed as ‘dual modal imaging’. In dual modal imaging, the limitation of one technique becomes the advantage of other. This review article focuses on the dual modal imaging which is achieved by using rare earth doped gadolinium oxide nanoparticles. By doping the rare earth ions into the gadolinium oxide matrix, both the optical and magnetic properties of the material are shared.
Secure Data Access Privacy Preserving Using Cloud Services
Authors: Rajkumar M , Kanmani E , Bhuvanesh M , Haritha B , Kalaiyarasi B 
Published: May 2021

Abstract
Notwithstanding the huge computational advantages, re-appropriating information to the public internet, furthermore avoiding end-users, quick authority towards the systems which using their information, which inescapable gets up to the minute privacy tasks. Circulated registering allows different pros and unrivalled comfort for the cloud users to obtain the needed permission of cloud gave that the close by establishment limits need not be thought of. While getting to information, there may be a co-employable connection between various customers which assembles sharing and exchanging of data, a grim cycle. The viewpoint on present privacy courses of action is basically on confirmation to catch that the information of an independent can’t be moved nearer illegitimately, anyway there arose an insurance problem when a user interest for information splitting into various customers between cloud specialist. The customer security may be uncovered by tried induction appeal itself, if data permission approval for the users is gained or loosed. In the introduced structure, an assurance saving affirmation show is used to hinder the above security bothers. According to this Method, control of data through shared induction is cultivated by route toward convey baffling permission appeal that offers security to the cloud users. Permission authority relies upon credits so the cloud customers can simply get to their own endorsed data fields. Advanced encryption standard estimation is used to achieve data lack of clarity and data protection. The proposed system oversaw secure assurance saving data access authority is appealing for various customer in cloud consistent limit.
Construction Scheme of Regional Power Grid Dispatching Intelligent Error Prevention System Based on D5000
Authors: Wang Shenjie , Niu Haonan , Pan Na , Xu Zhicheng , Pan Qi 
Published: May 2021

Abstract
A construction scheme of regional power grid dispatching intelligent error prevention system based on D5000 system is proposed. The system architecture, system requirements, technical requirements and acceptance criteria of the system are described in detail. It provides reference for the construction of intelligent error prevention in the process of integration of regulation and control and intelligent layout in other power industry.
Analysis of Offshore Wind Power Integration
Authors: Niu Yukun , Wen Jun , Ma Limin , Wang Shujie 
Published: May 2021

Abstract
In recent years, global energy and environmental problems have become increasingly prominent, and wind power has entered a period of rapid development. At the same time, offshore wind power integration is also facing many challenges and problems. Based on the analysis and research of offshore wind power integration, this paper introduces the technologies of offshore wind power integration such as HVAC, LCC-HVDC and VSC-HVDC, and discusses the impact of large-scale offshore wind power on power grid, interaction with UHVDC, voltage ride through and harmonic vibration of offshore wind power, and the impact of large-scale wind power integration on power grid and power quality problems are studied. The research and breakthrough of these problems will greatly benefit the development of offshore wind power industry.
Research on Fidelity Simulation of Space Electromagnetic Environment Radiation Source
Authors: Wang Yuan , Tan Wei , Kong Rong , Ren Zhaorui 
Published: May 2021

Abstract
This paper proposes to model and simulate radiation sources in complex electromagnetic environments in space from three aspects of real-time, dynamic and parameter completeness, which solves the problem of fidelity simulation under the high dynamic conditions of multiple radiation sources in the space electromagnetic environment. This paper proposes the parameters covered by the real-time, dynamic and parameter completeness of the radiation source, and designs the basic model, which provides design ideas for the spacecraft’s adaptive simulation in the space electromagnetic environment, and provides for the design and development of the spacecraft’s anti-jamming capability Technical Reference.
A research on integrated district energy system planning considering hydrogen production
Authors: Zhang Wanqiu , Liu Li 
Published: May 2021

Abstract
In this paper, the comprehensive energy system of wind power hydrogen production plant is considered. Firstly, wind power hydrogen production model, electrolysis hydrogen production model and comprehensive energy system model containing wind power hydrogen production are proposed, combining the operation model in the comprehensive energy system, electric heating load demand and the operation characteristics of the power system. Secondly, the objective function of the integrated energy system is to optimize for the lowest total operating cost, establish an optimization model, and restrict its overall power balance and the relevant constraints of each part. Finally, energyplan is adopted for simulation operation. The results show that the integrated energy system considering wind power for hydrogen production can better absorb wind energy, reduce the phenomenon of wind abandonment, and convert wind abandonment into hydrogen resources, which can improve economic benefits and make full use of energy.
Dynamic feedback H ∞ optimal control for singular systems
Authors: Zhao Lina , Qiu Zhanzhi 
Published: May 2021

Abstract
Time delay and packet loss often occur in the process of information transmission in descriptor systems, and H∞ optimal control is adopted to deal with this phenomenon. Firstly, the stability of singular systems is proved by using Lyapunov function, secondly, the existence of H∞ controller and-suboptimal control are proved, and finally, the necessary and sufficient condition of H ∞-optimal controller is proved. The validity and feasibility of the proposed method are verified by numerical simulation.
Analysis on the Circuit Design of Fire Alarm
Authors: Kang Shaoxuan 
Published: May 2021

Abstract
In the large airtight cinema and school, there are a lot of people in public places, thus the fire safety problems always attach great importance to everyone. The appearance of fire alarms can definitely help audience who are immersed in watching movies and students who are listening to the teachers carefully to remind them of a fire, so they can leave the scene in time and reduce property losses. This paper will take the fire alarm circuit as an example to realize the combined logic circuit by using various integrated circuits of different scales. This design is very flexible, effective and operable. In the actual process of use, the appropriate scheme can be selected according to the design requirements and the resource of the device. The object of study is a logic circuit, which is composed of an integration gate or a medium scale synthesizer. The experimental methods include practical ideas, application of Boolean logic principles, and sampling of data from others through the Internet, which are mentioned at the end of the paper. The conclusion is that abstract logic can be used step by step to design a practical and effective circuit diagram.
Flexible Load Scheduling Methods for Load Aggregators
Authors: Zhang Chenggang , Du Zeyu , Wu Pengtao , Sun Qianhao , Li Yunhao , Zhang Yao 
Published: May 2021

Abstract
Four typical flexible load resources in the customer side, i.e., industrial users, central air-conditioning load, electric vehicles, and energy storage stations, are first considered and modelled in this paper. Then, we present the combined dispatching model for load aggregators involving four flexible load resources mentioned above. Our results of numerical experiments demonstrate that on one hand, four typical flexible load resources on the user side can be dispatched to decrease peak-load as well as increase valley-load. On the other hand, scheduling the load resources with energy storage properties operates in accordance with pre-instructions. Compared with independent scheduling, the combined scheduling of various flexible loads can achieve significant advantages of various load characteristics and strengthen the dispatching ability of load aggregators. The methodology proposed in this paper can effectively promote renewable energy integrations, improve grid stability, and then reduce operating costs of load aggregators.
A New Microwave Heating Method Via the Combination of Rotation and Boundary Movement
Authors: Jiang Min , Tang Zhengming , Hong Tao , Hu Yusong 
Published: May 2021

Abstract
The local overheating may occur in microwave heating process, which results in poor heating uniformity. In order to improve the heating performance, in this paper, the boundary movement with periodical movement is added to the traditional rotating turntable model. The continuous algorithm based on moving mesh is adopted to simulate the heating process, and the results of calculation show that the proposed method can not only maintain the uniformity of the traditional rotating turntable method but also increase nearly 30% of the average temperature of the heated object.