Volume-11 Issue-1, May 2022 – International Journal of Recent Technology and Engineering (IJRTE)

A69810511122

IJRTE Journal — Sat, 07 May 2022 09:30:59 +0000

Early Prediction of Cardiac Disease using Expert Systems
Ajaay Krishna P¹, Akhilesh R², Aravind C J³, Rama Abirami K⁴
¹Ajaay Krishna P, Student, Department of Computer Science, Krishna College of Engineering and Technology, Kuniyamuthur (Tamil Nadu), India.
²Akhilesh R*, Student, Department of Computer Science, Krishna College of Engineering and Technology, Kuniyamuthur (Tamil Nadu), India.
³Aravind C J, Student, Department of Computer Science, Krishna College of Engineering and Technology, Kuniyamuthur (Tamil Nadu), India.
⁴Dr. K Rama Abirami, Ph.D, Associate Professor, Department of Computer Science, Krishna College of Engineering and Technology, Kuniyamuthur (Tamil Nadu), India.
Manuscript received on 28 April 2022. | Revised Manuscript received on 04 May 2022. | Manuscript published on 30 May 2022. | PP: 140-145 | Volume-11 Issue-1, May 2022. | Retrieval Number: 100.1/ijrte.A69810511122 | DOI: 10.35940/ijrte.A6981.0511122
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Machine learning is effective in helping and making selections from the high volumes of data created by the healthcare business. In this work, completely different classification algorithms are applied with their own advantage on separate databases of malady accessible for disease prediction. The results of the study strengthen by using Artificial Intelligence in the early detection of diseases and this will increase the survival rate of patients considerably. The motivation of this paper is to develop efficacious treatment of data processing techniques that will facilitate remedial things. Data processing classification algorithms are used to diagnose heart diseases.
Keywords: Machine Learning, Artificial Intelligence, Prediction model, Classification Technique, Deep Learning.
Scope of the Article: Machine Learning

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A69630511122

IJRTE Journal — Fri, 06 May 2022 11:56:27 +0000

Detection of Android Malware using Machine Learning and Deep Learning Review
Kiran K. Joshi
Kiran K. Joshi*, Ph.D. Student, Department of Computer Engineering & IT, VJTI, Mumbai (Maharashtra), India.

Manuscript received on 23 April 2022. | Revised Manuscript received on 30 April 2022. | Manuscript published on 30 May 2022. | PP: 134-139 | Volume-11 Issue-1, May 2022. | Retrieval Number: 100.1/ijrte.A69630511122 | DOI: 10.35940/ijrte.A6963.0511122
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Android apps are fast evolving throughout the mobile ecosystem, yet Android malware is always appearing. Various researchers have looked at the issue related with detection of Android malware and proposed hypothesis and approaches from various angles. According to existing studies, machine learning and deep learning seems to be an effective and promising method for detecting Android malware. Despite this, machine learning is used to detect Android malware from various angles. By evaluating a broader variety of facets of the issue, the review work complements prior evaluations. The review process undertakes a systematic literature review to discuss a number of machine learning and deep learning technology that might be used to detect and prevent Android malware from infecting mobile devices. This is a strategy to cope with the rising threat of malware in the Android apps.
Keywords: Android, Malware, Machine Learning, Deep Learning
Scope of the Article: Machine Learning

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A69760511122

IJRTE Journal — Fri, 06 May 2022 11:51:06 +0000

A Comprehensive Study on Impacts of Air Pollution on Environment and Human Health
Garima Singh¹, Rakshit Jakhar², Ravi Raj³, Preeti Sachar⁴
¹Garima Singh*, Department of Geography, University of Mumbai, Mumbai (Maharashtra), India.
²Rakhshit Jakhar*, Department of Geography, University of Mumbai, Mumbai (Maharashtra), India.
³Ravi Raj, Faculty of Computer Science, Electronics, and Telecommunications, AGH University of Science and Technology, Krakow, Poland.
⁴Dr. Preeti Sachar, Department of Geography, University of Delhi, Delhi, India.
Manuscript received on 27 April 2022. | Revised Manuscript received on 02 May 2022. | Manuscript published on 30 May 2022. | PP: 129-133 | Volume-11 Issue-1, May 2022. | Retrieval Number: 100.1/ijrte.A69760511122 | DOI: 10.35940/ijrte.A6976.0511122
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: One of the biggest challenges for our society is air pollution because it is not only impacting our climate, but it affects the environment as well as human health badly. There are various pollutants present in the air nowadays that are the main reasons for disease in human beings. One of the major pollutants is Particulate Matter (PM), which is particles of very small diameter and variable, impale the respiratory system through breath, causing cardiovascular and respiratory diseases, dysfunction of the central and reproductive nervous system, and cancer. Although the ozone layer in the troposphere plays an important and protective role against irradiation of ultraviolet, it is dangerous when in extreme concentrations near the level of the ground, also impacting the cardiovascular and respiratory systems. Lastly, changes in climate resulting from environmental pollution impact the distribution of various infectious diseases, like natural disasters. The best way to overcome these issues is through awareness in public integrated with an approach multidisciplinary by scientific experts; organizations of international and national levels must study the emergence of this problem and provide sustainable solutions. This paper presents a comprehensive study on the impacts of air pollution on human health and the environment. Also, we are discussing the role of artificial intelligence to overcome these problems.
Keywords: Air Pollution, Artificial Intelligence (Ai), Diseases, Environment, Greenhouse Gases (Ghg), Policy.
Scope of the Article: Artificial Intelligence

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A69570511122

IJRTE Journal — Sat, 30 Apr 2022 11:13:04 +0000

Image Fusion by a Hybrid Multiobjective Genetic Algorithm Technique
Jyoti S. Kulkarni
Dr. Jyoti S. Kulkarni*, Assistant Professor, Department of Data Struc-tures and Algorithms, Pimpri Chinchwad College of Engineering, Pune (Maharashtra), India.

Manuscript received on 21 April 2022. | Revised Manuscript received on 29 April 2022. | Manuscript published on 30 May 2022 | PP: 123-128 | Volume-11 Issue-1, May 2022. | Retrieval Number: 100.1/ijrte.A69570511122 | DOI: 10.35940/ijrte.A6957.0511122
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Sensors used in image acquisition. This sensor technology is going on upgrading as per user need or as per need of an application. Multiple sensors collect the information of their respective wavelength band. But one sensor is not sufficient to acquire the complete information of one scene. To gain the overall data of one part, it becomes essential to cartel the images from multiple sources. This is achieved through merging. It is the method of merging the data from dissimilar input sources to create a more informative image compared with an image from a single input source. These are multisensor photos e.g. panchromatic and multispectral images. The first image offers spatial records whereas the lateral image offers spectral data. Through visible inspections, the panchromatic photo is clearer than a multispectral photo however the grey shade image is. Articles are greater clear however now not recognized whereas multispectral picture displays one of a kind shades however performing distortion. So comparing the characteristics of these two images, the resultant image is greater explanatory than these enter images. Fusion is done using different transform methods as well as the genetic algorithm. Comparing the results obtained by these methods, the output image by the genetic algorithm is clearer. The feature of the resultant image is verified through parameters such as root mean square error, peak signal to noise ratio, mutual information, and spatial frequency. In the subjective analysis, some transform techniques also giving exact fused images. The hybrid approach combines the transform technique and a genetic algorithm is used for image fusion. This is again compared with genetic algorithm results. The same performance parameters are used. And it is observed that the hybrid genetic algorithm is superior to the genetic algorithm. Here the only root means square error parameter is considered under the fitness function of the genetic algorithm so only this parameter is far better than the remaining parameters. If we consider all parameters in the fitness function of the genetic algorithm then all parameters using a hybrid genetic algorithm will give better performance. This method is called a hybrid multiobjective genetic algorithm.
Keywords: Genetic Algorithm, Hybrid Multiobjec Tive Genetic Algorithm, Image Fusion
Scope of the Article: Sequential, Parallel and Distributed Algorithms and Data Structures

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A69620511122

IJRTE Journal — Sat, 30 Apr 2022 11:07:50 +0000

Student Centric Approach of the Content Based Instruction and Instructional Scaffolding
V. J. Vinita¹, M. Ilankumaran²
¹V. J. Vinita*, Research Scholar, Department of English, Noorul Islam Centre for Higher Education, Kumaracoil, Thuckalay (Tamil Nadu), India.
²Dr. M. Ilankumaran, Principal, Geetha Jeevan Arts and Science College, Thoothukudi, Affiliated to Manonmaniam Sundaranar University, Tirunelveli (Tamil Nadu), India.
Manuscript received on 22 April 2022. | Revised Manuscript received on 28 April 2022. | Manuscript published on 30 May 2022. | PP: 116-122 | Volume-11 Issue-1, May 2022. | Retrieval Number: 100.1/ijrte.A69620511122 | DOI: 10.35940/ijrte.A6962.0511122
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Teaching English as a second language expedites the probability of teaching English language in the utmost trying situations. The process of language instruction of English, as a second language. is a highly demanding skill. A number of challenges arise during the process as second language learners have fewer linguistic resources in the language of instruction. Content-Based Instruction lays a stress-free interactive platform for English language learners. Scaffolding students’ learning is a possible way to overcome certain tasks that learners come across. Content-Based Instruction oriented teachers hold key responsibility for the implementation of language learning in a classroom condition. The English language is used as an instructional language not only to teach English language lessons in classrooms but also functional in delivering other subjects. The article deals with the English language learning principle through Content-Based Instruction along with the collaboration of scaffolding. The goal of the study mainly rests on the factors responsible for the successful implementation, the strategies, the prospect, and the advantages of language learning through the approach. Content-Based Instructors function as scaffolds offering support to the students to create more specific learning activities. Using scaffolding, Content-Based Instruction can approach the English language learners to promote themselves from what they are capable of doing at present to what they will be able to do later. Scaffolding is a promising teaching technique. It is an interaction promoting tool that promises to enhance speaking skills in second language learning English students. This paper intends to prove the usability features of scaffolding teaching technique in Content-Based Instruction promoting English language teaching, the characteristics and critical features of scaffolded Instruction, methods of instructional scaffolding, and the challenges and benefits of instructional scaffolding. The article ponders upon the importance of time and the preparation of the course of study undertaken by this technique and throws light on how the language facilitators face the challenges like the choice of the topic till the content reaches the language learner and is expected to go an extra mile in imparting the English language learners.
Keywords: Content-Based Instruction, Instructional Scaffolding, Second Language Learners, Interaction, Speaking skills
Scope of the Article: Enhancement of the English Language in current scenario

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A69490511122

IJRTE Journal — Sat, 30 Apr 2022 11:01:02 +0000

Comparative Analysis of Routing Algorithms to Enhance the Quality of Service in MANET
K. Vimala¹, D. Maruthanayagam²
¹K. Vimala*, Research Scholar, Sri Vijay Vidyalaya College of Arts & Science, Dharmapuri (Tamil Nadu), India.
²Dr. D. Maruthanayagam, Professor & Head, PG and Research, Department of Computer Science, Sri Vijay Vidyalaya College of Arts & Science, Dharmapuri (Tamil Nadu), India.
Manuscript received on 18 April 2022. | Revised Manuscript received on 28 April 2022. | Manuscript published on 30 May 2022. | PP: 108-115 | Volume-11 Issue-1, May 2022. | Retrieval Number: 100.1/ijrte.A69490511122 | DOI: 10.35940/ijrte.A6949.0511122
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Mobile Ad hoc Network is a self-organizing, infrastructure-free, distributed wireless networks made up of various mobile devices. Quality-of-Service routing is most difficult task in MANET due to inherent characteristics–for example frequent dynamic topology, node mobility, resource scarcity, absence of centralized control, etc as well. The QoS variables of any MANET routing algorithms determine its performance. QoS routing is process of routing packets from source (S) to destination (D) based on QoS resource constraints such as bandwidth, delay, packet loss rate, cost, security, link stability, and so on. Swarm intelligence, which mimics the collective behaviour of biological organisms to handle routing problems and improve QoS in the network, has been one of most popular studies for network routing in recent years. Particle Swarm Optimization algorithm (PSO), Genetic Algorithm (GA) and Ant Colony Optimization algorithm (ACO) have all been shown to be effective for developing routing algorithms by improving QoS metrics in ad hoc networks using Swarm Intelligence (SI). The primary objective of this comparative study paper is to improve QoS parameters by applying swarm intelligence to MANET routing algorithms. Swarm intelligence-based routing algorithms will be more promising for the specific nature of adhoc networks, outperforming in real scenarios/constraints/environmental conditions and will be tuned and simulated to obtain an efficient and effective MANET routing protocol. This paper investigates four potential pre-existing approaches proposed for MANET routing problems. These routing algorithms are evaluated using various performance metrics such as packet delivery ratio, routing overhead, link failure prevention, energy consumption, accuracy, and throughput, among others.
Keywords: MANET, Routing, Link failure, Security, Swarm Intelligence and Quality of Services.
Scope of the Article: Swarm Intelligence

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A69550511122

IJRTE Journal — Sat, 30 Apr 2022 10:54:40 +0000

A Practical Research Methodology for Implementation of the Ems in Iraqi Enterprises
Emad Al-Mahdawi
Dr. Emad Al-Mahdawi, Department of Electrical Engineering, Mid Kent College – Chatham – England.

Manuscript received on 20 April 2022. | Revised Manuscript received on 25 April 2022. | Manuscript published on 30 May 2022. | PP: 103-107 | Volume-11 Issue-1, May 2022. | Retrieval Number: 100.1/ijrte.A69550511122 | DOI: 10.35940/ijrte.A6955.0511122
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In practice, energy management encompasses several activities that give objective data on the principal users of fuel and energy, the energy efficiency of various developments and certain types of products, and energy conservation reserves. This research investigates the benefits and stages of EMS that must be adopted in Iraq. The work considers the significance of using EMS technology at Baghdad International Airport. Airport infrastructure necessitates much energy due to its vast size and particular design. Annually, the airport consumes nearly 9.2M KWh, costing 1.2 billion Iraqi Dinars/KWh. As Iraq’s current energy crisis is massive, the energy audit will show an accurate picture of the energy consumption. EMS aims to increase the organisation’s stability (including financial) and improve its competitive position by reducing costs and increasing management efficiency. The work has accomplished that Iraqi companies need a modern management strategy-energy consumption management. Traditional heads of departments must be updated to be active in fixing the organisation’s energy issues. The EMS technology can identify conflicts and re-document structures. The technique also enables addressing any safety issues in the design phase. Therefore, this paper contributes to enhancing and developing the traditional Energy Management System in Iraq.
Keywords: Energy Management System, Smart Energy System, Planning, Sustainable Development.
Scope of the Article: Sustainable Structures

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A69520511122

IJRTE Journal — Sat, 23 Apr 2022 12:34:52 +0000

A Geo-Spatial Approaches for Integrated Watershed Management (IWM): Case Study of Boni Mukundaraju Cheruvu, Andhra Pradesh, India
Ummaneni Ajay Kumar¹, Venu Gopal Rao V², Rajesh M³, Krishna Naik V⁴, Uma Maheswara Rao G⁵
¹Ummaneni Ajay Kumar*, Research Scholar, Department of Environmental Sciences, Andhra University, Visakhapatnam (Andhra Pradesh), India.
²Venu Gopal Rao V, Research Scholar, Department of Environmental Sciences, Andhra University, Visakhapatnam (Andhra Pradesh), India.
³Rajesh M, Research Scholar, Department of Environmental Sciences, Andhra University, Visakhapatnam (Andhra Pradesh), India.
⁴Krishna Naik V, Research Scholar, Department of Environmental Sciences, Acharya Nagarjuna University, Guntur (Andhra Pradesh), India.
⁵Uma Maheswara Rao G, Research Scholar, Department of Environmental Sciences, Andhra University, Visakhapatnam (Andhra Pradesh), India.
Manuscript received on April 19, 2022. | Revised Manuscript received on 23 April 2022. | Manuscript published on 30 May, 2022. | PP: 96-102 | Volume-11 Issue-1, May 2022. | Retrieval Number: 100.1/ijrte.A69520511122 | DOI: 10.35940/ijrte.A6952.0511122
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Sustainable management of available water resources and judicious allocation to user needs within the ecosystem threshold can be achieved through Remote Sensing. To estimate the surface features with the help of change analysis which improves better resource management and decision-making in watershed hydrology assessment, interactions and relationships between human activities and natural phenomena are important. The present study on Geo-spatial approaches for Watershed management of Boni Mukundaraju cheruvu in Visakhapatnam district, Andhra Pradesh, India. From the study, we fixed it that the LULC of study area was classified into 5 major classes and 13 sub classes. During the study period from 2010-11 to 2020-21, it was observed that the wastelands in the catchment area were converted into water bodies seasonal and agricultural lands. It is also observed that the forest area was increased and majorly built up area was decreased from 2010-11 to 2020-21. The present study brings out the potential of geospatial techniques in LULC changes from 2010-11 to 2020-21, drainage patterns, Hydrological soil types (4types) and rainfall-runoffs from 1991-2021 (30 years) were described in detail.
Keywords: Watershed Management, LULC, SCS-SN Method, Geo-spatial Techniques, HSG.
Scope of the Article: Environmental Engineering

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E67410110522

IJRTE Journal — Sat, 23 Apr 2022 05:57:06 +0000

Image Captioning using Convolutional Neural Networks and Long Short Term Memory Cells
Hitoishi Das
Hitoishi Das*, Department of Computer Science and Engineering, ICFAI Foundation for Higher Education, Hyderabad (Telangana), India.

Manuscript received on 03 January 2022 | Revised Manuscript received on 18 April 2022 | Manuscript published on 30 May 2022 | PP: 91-95 | Volume-11 Issue-1, May 2022. | Retrieval Number: 100.1/ijrte.E67410110522 | DOI: 10.35940/ijrte.E6741.0511122
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This paper discusses an efficient approach to captioning a given image using a combination of Convolutional Neural Network (CNN) and Recurrent Neural Networks (RNN) with Long Short Term Memory Cells (LSTM). Image captioning is a realm of deep learning and computer vision which deals with generating relevant captions for a given input image. The research in this area includes the hyperparameter tuning of Convolutional Neural Networks and Recurrent Neural Networks to generate captions which are as accurate as possible. The basic outline of the process includes giving an image as input to the CNN which outputs a feature map. This feature map is passed as input to the RNN which outputs a sentence describing the image. The research in image captioning is relevant because this method demonstrates the true power of the encoder-decoder network made up of Convolutional Neural Network and Recurrent Neural Network and potentially will open many pathways for further interesting research on different types of neural networks.
Keywords: Captioning, Deep Learning, Encoders, Decoders, Convolutional Neural Networks, Recurrent Neural Networks, Computer Vision
Scope of the Article: Deep Learning

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A69150511122

IJRTE Journal — Sat, 16 Apr 2022 06:36:52 +0000

A Brief Overview of Utilizing Crumb Rubber as Asphalt Binder Modifier
Ali A. S. Bayagoob¹, Péter Füleki²
¹Ali A. S. Bayagoob*, Department of Transport Infrastructure and Water Resources Engineering, Széchenyi István University, 9026 Győr, Hungary.
²Péter Füleki, Associate Professor, Department of Transport Infrastructure and Water Resources Engineering, Széchenyi István University, 9026 Győr, Hungary.
Manuscript received on 11 April 2022. | Revised Manuscript received on 15 April 2022. | Manuscript published on 30 May 2022. | PP: 83-90 | Volume-11 Issue-1, May 2022. | Retrieval Number: 100.1/ijrte.A69150511122 | DOI: 10.35940/ijrte.A6915.0511122
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The discarding of scrap tires is a serious environmental hazard worldwide. Simultaneously, the asphalt mixture containing neat binders do not always perform as required. Therefore, various efforts have been taken in the past to enhance the performance properties of the neat asphalt cements by modifying them with crumb rubber powder. Consequently, this will decrease the environmental hazards of waste tires. According to prior and ongoing research, the modification of asphalt mixtures using crumb rubber have enhanced the asphalt mixtures properties such as low and high temperature performance as well as rutting deformation resistance, fatigue cracking resistance. This paper affords via an overview of the physical and rheological properties of the rubberized asphalt binders under different conditions. This review transacts through the impact of crumb rubber particles on the asphalt binder’s workability, rotational viscosity, the needle penetration, softening point, low- temperature and high-temperature performance. Furthermore, fatigue cracking resistance, rutting behavior and storage stability are in the focus.
Keywords: Crumb Rubber, Asphalt Modification, Physical Behavior, Rheological Behavior
Scope of the Article: Routing and Transport Protocols

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