Volume-8 Issue-6, March 2020 – International Journal of Recent Technology and Engineering (IJRTE) https://www.ijrte.org Exploring Innovation | ISSN:2277-3878(Online) | A Periodical Journal | Reg. No.: C/819981 | Published By BEIESP Wed, 13 Apr 2022 04:22:17 +0000 en-US hourly 1 https://www.ijrte.org/wp-content/uploads/2021/02/cropped-IJRTE-Logo-WS-32x32.png Volume-8 Issue-6, March 2020 – International Journal of Recent Technology and Engineering (IJRTE) https://www.ijrte.org 32 32 C6141098319 https://www.ijrte.org/portfolio-item/c6141098319/ https://www.ijrte.org/portfolio-item/c6141098319/#respond Wed, 13 Apr 2022 04:22:17 +0000 https://www.ijrte.org/?post_type=portfolio&p=14516 The post C6141098319 appeared first on International Journal of Recent Technology and Engineering (IJRTE).

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De-noising of MRI Images in Wavelet Domain
Munazza Farha Arshi1, Vandana V. Hanchate2, K. R. Joshi3
1Munazza Farha Arshi*, Student, Department of E&TC, Pune University, India.
2Vandana V. Hanchate, Faculty, Department of E&TC, Pune University, India.
3Dr. K. R. Joshi, Faculty, Department of E&TC, Pune University, India.
Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 1947-1949 | Volume-8 Issue-4, November 2019. | Retrieval Number: C6141098319/2019©BEIESP | DOI: 10.35940/ijrte.C6141.118419
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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: Magnetic resonance imaging (MRI) is a diagnostic medical procedure that utilizes solid attractive fields and radio waves to deliver definite pictures of within the body. Extensive research has been completed into whether the attractive fields and radio waves utilized during MRI sweeps could represent a hazard to the human body. No proof has been found to propose there’s a hazard, which means MRI outputs are one of the most secure restorative methodology accessible. MRI has several advantages which make it ideal in numerous situations, in particular, it can identify small changes of structures inside the body. The disadvantage is the noise that degrades the quality of the image. A threestep processing algorithm is proposed to reduce this noise. Here, first it includes soft thresholding in wavelet domain where the original image is divided into blocks that do not overlap. Then it includes restoration of the object boundaries and texture which are lost as a result of the first step and finally enhancing the image using CLAHE (Contrast Limiting Adaptive Histogram Equalization). It is then analyzed using the error parameters like peak signal to noise ratio and mean square error.
Keywords: MRI, Medical Image Denoising, Rician Noise, Soft Thresholding, CLAHE
Scope of the Article: Image Security.

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Prediction of Sugarcane Yields from Field Records using Regression Modeling
Shivani S. Kale1, Preeti S. Patil2
1Shivani S. Kale, Research Scholar, Department of Computer Science and Engineering, VTU Belgaum, India.
2Dr. Preeti S. Patil, Head and Professor, Department of Information Technology, D.Y. Patil College of Engineering Akurdi, Pune, India.
Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 1603-1606 | Volume-8 Issue-4, November 2019. | Retrieval Number: C4174098319/2019©BEIESP | DOI: 10.35940/ijrte.C4174.118419
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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: Prediction Of Sugarcane Crop Yield Benefits The Farmer To Get Best Possible Decision Regarding Sugarcane Crop Cultivation. The Purpose Of This Work Is To Identify Possible Relationship Between N, P, K Fertilizer, Water Resource And Planting Densities. The Algorithm Used Is Multiple Regression. The Paper Focuses On The Generation Of Multiple Regression Models For The Dataset Of Sugarcane Crop For Season Adasali, Suru And Preseasonal Method. The Intercept And Slope For Variables Are Calculated And Equation For Each Model Is Generated. Sample Of N,P,K And Other Are Considered For A Period Of 7 Years From 2012 To 2018. Data Of Experimentation Is Collected For Arid Region I.E. Pandharpur, Maharashtra State.
Keywords: Prediction, Crop Yield, Regression Analysis.
Scope of the Article: Regression and Prediction.

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Type-2 Neuro Fuzzy Current Controlled Inverter Fed Induction Motor Drive
R. Ramanjan Prasad1, G. Durga Sukumar2
1R.Ramanjan Prasad, VFSTR University, Vadlamudi, Guntur,
2G.Durga Sukumar, VITS, Deshmukhi, Nalgonda
Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 93-100 | Volume-8 Issue-4, November 2019. | Retrieval Number: C6197098319/2019©BEIESP | DOI: 10.35940/ijrte.C6197.118419
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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: As the conventional PI controller’s operation is not satisfactory due to the operating point oscillations in a closed loop system, intelligent based controllers are employed. This paper presents Neuro Type 2 fuzzy controlled (NT2FC) based speed controller in the IVC of induction motor. The advantage of T2NFC is the area of point of intersection of membership functions is less so the value obtained by the centroid method is more accurate compared to NT1FC system. This paper presents performance comparison of IVC of IMD with conventional PI, NT1FC and NT2FC. The tuning of type 2 fuzzy membership functions is done using neural network by applying LSE in forward pass and BP algorithm in backward pass. The experimental validation is also carried out using Dspace 1104 micro controller. The date of at this experimental validation has been taken from the simulation. It is carried out considering 2HP Induction motor and it is observed that the NT2FC gives better performance of IMD.
Keywords: Neuro Type-2 fuzzy controller (NT2FC), Neuro Type-1 Fuzzy Controller (NT1FC), Space vector modulation (SVM), Induction motor drive (IMD), Proportional and integral controller (PI) and Indirect Vector Control (IVC).
Scope of the Article: Fuzzy Logics.

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Load Frequency Control of Two Area Hydro-Thermal System considering GRCs and GDB Non Linearity’s with Intelligent Controller
J.Srilekha1, Ch.Naga sai Kalyan2, G.Stanley3, K.Suneetha4, Md.M.Thakreem5
1J.Srilekha, EEE department, vasireddy venkatadri institute of technology, Guntur, India.
2Ch.Naga sai kalyan*, EEE department, vasireddy venkatadri institute of technology, Guntur, India.
3G.Stanley, EEE department, vasireddy venkatadri institute of technology, Guntur, India.
4K.Suneetha, EEE department, vasireddy venkatadri institute of technology, Guntur, India.
5Md.M.Thakreem, EEE department, vasireddy venkatadri institute of technology, Guntur, India. 
Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 4697-4705 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6959018520/2020©BEIESP | DOI: 10.35940/ijrte.E6959.018520
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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 focuses on design and development of intelligent based optimal secondary controller which could sustain with system dynamic conditions to maintain frequency and tie-line power exchange with in specified limits. For analysis purpose, a two area interconnected system comprising of thermal and hydro units in each area with system non linearity’s like generation rate constraints (GRC) and governor dead band theory (GDB) are considered to get more practical approach. System frequency and tie-line variations are observed in MATLAB/ SIMULINK platform for 1% step load perturbation (SLP) in area-1. Proportional- integral (PI), proportional-integral-derivative (PID) and Fuzzy-PID controllers are employed as secondary controllers one at a time, whose gains are optimized with Grey wolf optimization (GWO) algorithm. Later, the system dynamic responses are investigated by incorporating superconducting magnetic energy storage devices (SMES) in both areas and static synchronous series compensator (SSSC) placed in series with the tie-line. Investigation reveals the superiority of fuzzy controller with coordinated performance of SMES and SSSC in mitigating frequency deviations and tie-line power variations. Finally, sensitivity analysis is carried out to test robustness of proposed coordinated control scheme.
Keywords: Fuzzy-PID Controller, Grey Wolf Optimization (GWO), Load Frequency Control (LFC), Non Linearity’s, Static Synchronous Series Compensator (SSSC), Superconducting Magnetic Energy Storage (SMES).
Scope of the Article: Waveform Optimization for Wireless Power Transfer.

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Predicting Autism Spectrum Disorder using Machine Learning Technique
Jaber Alwidian1, Ammar Elhassan2, Rawan Ghnemat3
1Jaber Alwidian, King Hussein School of Computing Sciences Princess Sumaya University for Technology (PSUT), Jordan.
2Ammar Elhassan, King Hussein School of Computing Sciences Princess Sumaya University for Technology (PSUT), Jordan.
3Rawan Ghnemat, King Hussein School of Computing Sciences Princess Sumaya University for Technology (PSUT), Jordan.
Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 4139-4145 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6016018520/2020©BEIESP | DOI: 10.35940/ijrte.E6016.018520
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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: Autism Spectrum Disorder (ASD) is a psychiatric disorder that puts constraints on the ability to use of cognitive, linguistic, communicative, and social skills. Recently, many data mining techniques employed to serve this domain by determining the main features of the condition and the correlation between them. In this article, we investigate the Association Classification (AC) technique as a data mining technique in predicting whether an individual has autism or not. Accordingly, seven well-known algorithms are selected to conduct analysis and evaluation of the performance of the AC technique in term of identifying correlations between the features to help decide early on whether an individual has autism; this is particularly significant for children. The evaluation for the behavior and the performance in the prediction tasks for the AC algorithms was conducted for the common metrics of including Precision, Accuracy F-Measure as well as Recall. Finally, a comparative performance analysis among the algorithms was used as final result for the study. The results show better performance for the WCBA algorithm in most test scenarios with accuracy of 97 % although, the majority of algorithms exhibited excellent accuracy when applied in this domain.
Keywords: Association Classification, Autism Spectrum Disorder, Association Rules, Classification.
Scope of the Article: Classification.

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Modified Form of PSO and Its Variation in Channel Equalization
Sunita Panda1, Kamalanathan Chandran2, Anughna N3, Padma Charan Sahu4, Sekar Karthick5
1Sunita Panda, Assistant Professor,Elecrical Electronics and Communication Engineering, GITAM School of Technology, GITAM Deemed to be University, Bengaluru.
2Kamalanathan Chandran, Associate Professor, Elecrical Electronics and Communication Engineering, GITAM School of Technology,GITAM Deemed to be University, Bengaluru.
3Anughna N, Assistant Professor, Elecrical Electronics and Communication Engineering, GITAM School of Technology, GITAM Deemed to be University, Bengaluru
4Padma Charan Sahu, Assistant Professor, Electronics and Communication Engineering, GIET University, Gunupur
5Sekar Karthick, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andra Pradesh.  
Manuscript received on January 01, 2020. | Revised Manuscript received on January 20, 2020. | Manuscript published on January 30, 2020. | PP: 3534-3538 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6330018520/2020©BEIESP | DOI: 10.35940/ijrte.E6330.018520
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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: Novelty of PSO is the techniques of parameter improvement. Using many “strategy principles” for the PSO is important for its convergence performance and the optimisation job. In the proposed work, we applied PSO and its advanced form trained with our proposed algorithm for channel equalization. Since particle swarm optimization is matured in the literature ,we apply PSO in its optimized structure trained with radial basis function Artificial Neural Network (ANN). Therefore, this work introduces most favourable design of RBFNN equalizers using OPSO. We treat equalization problem as a classification problem. We assessed a set of fitness functions of modified form of PSO and analysed with it to the presentation of existing PSO.
Keywords: ANN,OPSO, Channel Equalization.
Scope of the Article: Microwave Link Design.

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Examination of Kernel Based Noise Classifier with Cross Resolution Dataset and with Untrained Class
Ishuita Sen Gupta1, Anil Kumar2, Rakesh Kumar Dwivedi3
1Ishuita SenGupta*, College of Computing Sciences and Information Technology, Teerthanker Mahaveer University, Moradabad, India.
2Anil Kumar, Indian Institute of Remote Sensing, ISRO, Dehradun, India.
3Rakesh Kumar Dwivedi, College of Computing Sciences and Information Technology, Teerthanker Mahaveer University, Moradabad, India.
Manuscript received on January 01, 2020. | Revised Manuscript received on January 20, 2020. | Manuscript published on January 30, 2020. | PP: 3389-3394 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6539018520/2020©BEIESP | DOI: 10.35940/ijrte.E6539.018520
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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: Determining the effect of untrained classes in the kernel based noise classifier is the prime object of the paper. It further includes, studying the effect of studied classifier over different datasets. Distinct nine Kernel functions has been associated with conventional supervised Noise Classifier. Landsat8 and Formosat2 along with Resourcesat-1 data have been opted for the performance evaluation. Decrease in classification accuracy has been found, in presence of untrained classes. A subtle consistency has been in classification accuracy in case of cross resolution data sets, thus, showing the robustness of the algorithm.
Keywords: Kernel functions, Noise Clustering Classifier, Cross Resolution, and Untrained Classes.
Scope of the Article: Clustering.

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Correlation Between Mentors’ Communication in E-Mentoring, Mentees’ Self-Efficacy and Mentees’ Academic Performance: Evidence from a Malaysian Public Research University
Azman Ismail1, Mohd Mursyid Arshad2, Asyakireen Samsudin3, Nur Izzaty Mohamad4, Najihah Omar5
1Azman Ismail*, Faculty of Economics & Management, Universiti Kebangsaan Malaysia, Selangor, Malaysia.
2Mohd Mursyid Arshad, Faculty of Educational Studies, Universiti Putra Malaysia, Selangor, Malaysia.
2Asyakireen Samsudin, Faculty of Economics & Management, Universiti Kebangsaan Malaysia, Selangor, Malaysia.
3Nur Izzaty Mohamad, Institute of Islam Hadhari, Universiti Kebangsaan Malaysia, Selangor, Malaysia.
4Najihah Omar, Faculty of Economics & Management, Universiti Kebangsaan Malaysia, Selangor, Malaysia.
Manuscript received on February 28, 2020. | Revised Manuscript received on March 22, 2020. | Manuscript published on March 30, 2020. | PP: 5864-5870 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7546038620/2020©BEIESP | DOI: 10.35940/ijrte.F7546.038620
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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: E-mentoring is often viewed as an informal teaching and learning method in excellent higher education institutions. Recent studies highlight that well-designed e-mentoring programs will not be able to support their objectives if mentors do not have capabilities to communicate effectively in the mentoring system. Even though this relationship has widely been examined, the role of mentors’ communication in e-mentoring as a significant determinant is not adequately discussed in the higher education institution literature. Thus, this study was done to assess the correlation between mentors’ communication in e-mentoring, mentees’ self-efficacy and mentees’ academic performance. A survey method was utilized to collect data from students at a public research university in Malaysia. The outcomes of the Statistical Package for Social Science displayed that the competency of mentors to openly deliver mentoring information through technology media had strongly invoked mentees’ self-efficacy. As a result, this situation could lead to an enhanced mentees’ academic performance in the examined higher education institution.
Keywords: E-Mentoring, Mentors’ Communication, Self-Efficacy, Academic Performance.
Scope of the Article: IoT Application and Communication Protocol.

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Vehicle Theft Recovery
S.Theepa Sri1, B.Sivasankari2, K.Subhikshaa3, M.Yasmin Fathima4, V.Sivakumar5
1B Sivasankari, Department of Computer Science and Engineering,National Engineering College, Kovilpatti, Tamil Nadu, India.
2K.Subhikshaa, Department of Computer Science and Engineering,National Engineering College, Kovilpatti, Tamil Nadu, India.
3S.Theepa Sri, Department of Computer Science and Engineering, National Engineering College, Kovilpatti, Tamil Nadu, India.
4M.Yasmin Fathima, Department of Computer Science and Engineering,National Engineering College, Kovilpatti, Tamil Nadu, India.
5Dr.V.Sivakumar*, Assistant Professor, Department of Computer Science amd Engineering, National Engineering College, Kovilpatti, Tamilnadu, India.
Manuscript received on February 28, 2020. | Revised Manuscript received on March 22, 2020. | Manuscript published on March 30, 2020. | PP: 5855-5858 | Volume-8 Issue-6, March 2020. | Retrieval Number: F8752038620/2020©BEIESP | DOI: 10.35940/ijrte.F8752.038620
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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: Presently a-days the whole world is confronting the instability which has gotten one of the major challenges. Each nation has their own unconventional security issues. The crime percentage in all aspects of our general public nowadays has become an undermining issue with the end goal that vehicles are currently utilized for carrying out crimes more than previously. The issue of vehicle robbery has expanded massively, for the most part at gunpoint or vehicle leaves. There is a requirement for reasonable records of taken, recognized and recuperated vehicles which are not promptly accessible in our general public and in that capacity significant. The improvement of a vehicle robbery caution and area distinguishing proof framework turns out to be increasingly essential for vehicle proprietors to guarantee burglary anticipation and an expedient recognizable proof over recuperation which incorporates missing of vehicles by an unapproved individual. Our model utilizes a GSM application created and introduced in a cell phone gadget that is installed in the vehicle to speak with the vehicle proprietor’s cell phone through SMS. The correspondences set up incorporate; (I). Sending an alarm message from introduced cell phone gadget to vehicle proprietor portable phone.(ii).Sending an admonition message from the vehicle proprietor’s cell phone to begin and stop the introduced cell phone. Decide the present area of a vehicle utilizing GPS.
Keywords: GSM,GPS, Arduino, Theft, Vehicle.
Scope of the Article: Image Processing and Pattern Recognition.

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Gis Application in Water Resourse Management in Uzbekistan
Ibraymov Ashiqmamut1, Bakiev Masharif2, Kodirov Odiljon3, Rahmatov Norqobul4, Ibragimova Saule5
1Ibraymov Ashiqmamut, researcher of hydrotechnical structures and engineering constructions, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, Tashkent, Uzbekistan.
2Bakiyev Masharif, professor, of hydrotechnical structures and engineering constructions, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, Tashkent, Uzbekistan.
3Kodirov Odiljon, PhD of hydrotechnical structures and engineering constructions, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, Tashkent, Uzbekistan.
4Rahmatov Norqobul, PhD of hydrotechnical structures and engineering constructions, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, Tashkent, Uzbekistan.
5Ibragimova Saule, assistant of hydrotechnical structures and engineering constructions, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, Tashkent, Uzbekistan.
Manuscript received on February 28, 2020. | Revised Manuscript received on March 22, 2020. | Manuscript published on March 30, 2020. | PP: 5850-5854 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7714038620/2020©BEIESP | DOI: 10.35940/ijrte.F7714.038620
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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 present time geoinformation systems are used to solve various problems in various spheres of economy. The difference of GIS from other information systems is that all GIS modeled objects have spatial link, that allows to analyze them in connection with other spatially determined objects. Besides, GIS cardinally differs from most other information systems with that all the information in them is visually presented as electronic maps, allowing users to acquire new knowledge. [3,4] The article presents recommendations on possibilities to create “mobile application” or model to design agricultural crop irrigation at field level with the use of GIS. [1,5] In order to realize the solution for this task they offer the use of existing data from previously conducted research in the republic. There is a certain experience in the republic in creating spatial and climatic database for operation of various scenario models in water management and development of irrigation maps for agricultural crops and irrigation rates with respect to time for chosen rates of irrigation. [1,5] GIS application is the new means in management of data distributed in time and space, and for development of imitation systems on the basis of obtained data. GIS supports various user applications, it is very flexible in searching, analyzing and using water resources.
Keywords: Soil Map and Irrigation Basin Map, Hydromodulus Region, Water Discharge, Irrigation Schedule, Water Saving.
Scope of the Article: Water Supply and Drainage.

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