Volume-7 Issue-5, February 2018 – International Journal of Innovative Technology and Exploring Engineering (IJITEE)

E2489027518

IJITEE Journal — Sat, 17 Dec 2022 07:37:36 +0000

The International Journal of Innovative Technology and Exploring Engineering (IJITEE) has ISSN: 2278-3075 (online), an open-access, peer-reviewed, periodical monthly international journal. This journal is published by Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) in January, February, March, April, May, June, July, August, September, October, November and December.The journal aims to publish high–quality peer–reviewed original articles in the area of Engineering and Technology that covers Computer Science and Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering and all interdisciplinary streams of Engineering and Technology. #Smart Computing and Information Processing #Signal and Speech Processing #Image Processing and Pattern Recognition #WSN#Artificial Intelligence and machine learning #Data mining and warehousing #Data Analytics #Deep learning #Bioinformatics #High Performance computing #Advanced Computer Networking #Cloud Computing #IoT #Parallel Computing on GPU #Human Computer Interactions #Recent Trends in Microelectronics and VLSI Design #Process & Device Technologies #Low-Power Design #Nanometer-Scale Integrated Circuits #Application specific ICs (ASICs) #FPGAs #Nanotechnology #Nano Electronics and Quantum Computing #3. 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Effect of Indian Gooseberry Doping on Potassium Dihydrogen Phosphate Crystals (KDP)
Usha Rani Pisipaty¹, S. Balaji²
¹Usha Rani Pisipaty, Department of Chemistry, SCSVMV, Kanchipuram (Tamil Nadu), India.
²S. Balaji, Department of Chemistry, SCSVMV, Kanchipuram (Tamil Nadu), India.
Manuscript received on 8 February 2018 | Revised Manuscript received on 15 February 2018 | Manuscript Published on 28 February 2018 | PP: 41-45 | Volume-7 Issue-5, February 2018 | Retrieval Number: E2489027518/18©BEIESP
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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: Potassium dihydrogen phosphate (KDP) crystal is an interesting non linear optical inorganic material. In this present work, KDP crystal and Indian Gooseberry extract doped KDP crystal has been grown by slow evaporation aqueous solution growth technique. The grown crystals have been investigated through various techniques viz. Fourier Transform Infrared Spectroscopy has been used for spectral analysis of grown crystals. The grown crystal have been subjected to X-ray diffraction for structural analysis. Using Energy Dispersive X-ray Spectroscopy, presence of element with weight percentage has been calculated. Nonlinear optic measurement has been used to find the SHG efficiency. Increase in KDP crystal thermal stability by an organic additive of Indian Gooseberry extract has been determined by Thermo-Gravimetric Analysis (TGA) and Differential Thermal Analysis (DTA). Using Vicker’s micro hardness test the mechanical property of KDP crystal and Indian Gooseberry extract doped KDP has been studied.
Keywords: KDP-Potassium Dihydrogen Phosphate, slow evaporation technique, organic impurity, NLO.
Scope of the Article: Bio-Science and Bio-Technology

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E2497027518

IJITEE Journal — Sat, 17 Dec 2022 07:29:40 +0000

An Efficient Face Detection and Recognition
Thanh Tan Nguyen Thi¹, Khanh Nguyen Trong²
">¹Dr. Thanh Tan Nguyen Thi, Department of Computer Science and Information Systems, Information Technology, Electric Power University, Hanoi, Vietnam.
²Dr. Khanh Nguyen Trong, Department of Software Engineering, Posts Tele Communications Institute of Technology, Hanoi, Vietnam.
Manuscript received on 8 February 2018 | Revised Manuscript received on 15 February 2018 | Manuscript Published on 28 February 2018 | PP: 35-39 | Volume-7 Issue-5, February 2018 | Retrieval Number: E2497027518/18©BEIESP
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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 this article, we propose a new method to effectively recognize faces from connected devices like real-time camera or webcam. The method contains two phases: Detecting and recognizing faces from the webcam frame. The face detection phase uses HOG features and SVM linear classifier. The second phase bases on FaceNet neural network model to automatically extract facial features and SVM classifiers. The experiments with UOF, FEI, JAFFE and LZW dataset is presented to show the efficiency of the proposed method. Experimental results show that the proposed method achieves high accuracy and stability on the test data sets collected from the actual environment.
Keywords: Face Recognition, Real-Time Recognition, Frame based Recognigition, Recognition Deep Neural Network.
Scope of the Article: Pattern Recognition

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E2496027518

IJITEE Journal — Sat, 17 Dec 2022 07:17:56 +0000

Climate Change Impact on Water Resources in Baram Basin Malaysia
Nasser Rostam Afshar¹, Nurainin Mirhassan²
">¹Nasser Rostam Afshar, Associate Professor, Abbaspour School of Engineering, Shahid Beheshti University, Tehran, Iran.
²Er. Nurainin Mirhassan, Quick Fortune Sdn. Bhd, Kuching, Sarawak, Malaysia.
Manuscript received on 8 February 2018 | Revised Manuscript received on 15 February 2018 | Manuscript Published on 28 February 2018 | PP: 30-34 | Volume-7 Issue-5, February 2018 | Retrieval Number: E2496027518/18©BEIESP
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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: Climate change is undeniably has become a worldwide issue for the past few decades for its significant impact on water resources. Continuous growing water demand has pushed the natural water resource to the brink whereby the rivers in Sarawak are not spared. For the case of Baram basin, the long term impact of climate change on that regional scale is unapparent. Therefore, a detail study is needed for future back up plan and mitigation. This paper aims at presenting the findings on the rainfall pattern of Baram basin in conformity to the climate regime. By using Classical Multiplicative time-series modeling, data for the year 2005-2014 forecasted and the trend between hydrological parameters(temperature, evaporation and rainfall ) and meteorological Parameters (evaporation, temperature, relative humidity, wind speed and cloud cover) is then discussed. From the historical time series trend of hydrological and meteorological data, it was observed that the rainfall trend has decreased within 10 years’ time period (2005-2014) due to the change in climate regime. The forecast has predicted decrease in the rainfall trend throughout the future 30 years (2015-2044) and it gives a direct effect on the water resources in terms of its quantity and quality.
Keywords: Climate Change, Rainfall Pattern, Water Resources, Forecast, Baram basin.
Scope of the Article: Water Supply and Drainage

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E2495027518

IJITEE Journal — Sat, 17 Dec 2022 07:08:48 +0000

Environment and Urban Sustainability
Bahieh Rostam Afshar¹, Nune Petrosyan²
">¹Bahieh Rostam Afshar, Department of Architecture, National University of Architecture and Construction of Armenia, Yerevan, Armenia.
²Dr. Nune Petrosyan, Associate Professor, Department of Architecture, National University of Architecture and Construction of Armenia, Yerevan, Armenia.
Manuscript received on 8 February 2018 | Revised Manuscript received on 15 February 2018 | Manuscript Published on 28 February 2018 | PP: 27-29 | Volume-7 Issue-5, February 2018 | Retrieval Number: E2495027518/18©BEIESP
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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: Urbanization is an increase in population of cities over time.This very rapid population growth, proved harmful effect to the city’s survival. In this research, a new approach is introduced for evaluating urban sustainability by relating urbanization and urban planning in Tehran. This is based on the assumption that urban planning is a dynamic profession that works to improve the welfare of people and attractive places for present and future generations. Using this definition, Sustainability Index (SI), can be calculated as [1 – (Vu)], where Vu is Urbanization velocity. When SI is equal to 1, the urban development process is considered to be sustainable. Evaluation of the results indicate that Sustainability Index (SI) presents a more rational basis for evaluation of urban sustainability. Hence, the proposed model is an effective tool to help policy makers to understand whether the urban development process is sustainable or need to be corrected.
Keywords: Urban Sustainability, Urbanization, Urban Planning, Sustainability Index, Urbanization Velocity.
Scope of the Article: Environmental Engineering

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E2490027518

IJITEE Journal — Sat, 17 Dec 2022 06:59:04 +0000

Flood Frequency Analysis for Greater-Zab River
Salah AL- Dubai
">Salah AL- Dubai, Department of Engineering, Near East University, Near East Boulevard, Nicosia, North Cyprus.
Manuscript received on 8 February 2018 | Revised Manuscript received on 15 February 2018 | Manuscript Published on 28 February 2018 | PP: 23-26 | Volume-7 Issue-5, February 2018 | Retrieval Number: E2490027518/18©BEIESP
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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 this study, Flood Frequency Analysis at Greater-Zab was carried out using different distribution models such as Log-Normal type 3(LN3), Log-Pearson type 3(LP3) and Generalize Extreme value(GEV). The annual peak flow series of Zab River was used for this purpose. Using Kolmogorov and Anderson Darling tests, the fitness of the models was evaluated. Log-Normal Type 3 was found as the best model for estimation of floods (magnitude and return period for Greater-Zab River.
Keywords: Frequency Data Analysis, Greater-Zab, Annual flood series, Anderson Darling Test.
Scope of the Article: Frequency Selective Surface

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E2492027518

IJITEE Journal — Sat, 17 Dec 2022 06:49:26 +0000

Hybrid two Phase Page Ranking Algorithm for Ordering the Web Pages Based on Content and Usage Mining
M. Usha¹, N.Nagadeepa²
">¹M. Usha, Research Scholar, Bharathiar University, Coimbatore (Tamil Nadu), India.
²Dr. N. Nagadeepa, Principal, Karur Velalar College of Arts and Science for Women, Karur (Tamil Nadu), India.
Manuscript received on 8 February 2018 | Revised Manuscript received on 15 February 2018 | Manuscript Published on 28 February 2018 | PP: 17-22 | Volume-7 Issue-5, February 2018 | Retrieval Number: E2492027518/18©BEIESP
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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: Many existing page ranking algorithms are used in web mining to display the result in search engine result page. But these existing algorithms are either based on the inlinks and outlinks of the page or content of the page. It never consider the user interest on the page to calculate the page rank of that particular page. This leads to a need of web page ranking algorithm concerning content and usage of the pages. Proposed algorithm focuses on title, Meta, H1 and paragraph tags to find the similarity of the page.Tag Analyzer Algorithm is used to analyze these tags’ content. Besides, it considers how long the user stays in that page to compute user interest score. TPPR technique computes the score in two phases. Based on the output of TPPR algorithm, the URLs are sequenced and displayed to the user. Event Explore technique detects whether the user is idle or active on the page. The proposed algorithm produced better performance and displays the most relevant web pages in the top of the result. From the results, “Two Phase Page Ranking” (TPPR) algorithm is better than PR algorithm of taken data set. TPPR algorithm can be used in web mining to improve the ranking system of search engine.
Keywords: Content Mining, Page Rank, TPPR, Usage Mining.
Scope of the Article: Algorithm Engineering

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E2491027518

IJITEE Journal — Sat, 17 Dec 2022 06:31:38 +0000

A Graph Based Multilingual Word Sense Disambiguation
J. H. Patil¹, S. N. Patankar²
">¹Jyotsna Harshal Patil, Department of Computer Engineering, Datta Meghe College of Engineering, Airoli Thane (Maharashtra), India.
²Prof. S. N. Patankar, Associate Professor, Department of Computer Engineering, Datta Meghe College of Engineering, Airoli Thane (Maharashtra), India.
Manuscript received on 8 February 2018 | Revised Manuscript received on 15 February 2018 | Manuscript Published on 28 February 2018 | PP: 11-16 | Volume-7 Issue-5, February 2018 | Retrieval Number: E2491027518/18©BEIESP
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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: Nowadays, the need of advanced free text filtering is increasing. Therefore, when searching for specific keywords, it is desirable to eliminate occurrences where the word or words are used in an inappropriate sense. This task could be exploited in internet browsers, and resource discovery systems, relational databases containing free text fields, electronic document management systems, data warehouse and data mining systems, etc. In order to resolve this problem in this work, we present joint approach to Word Sense Disambiguation (WSD). Our method exploits IndoWordNet, is a linked lexical knowledge base of word nets of 18 scheduled languages of India, a very large knowledge base, to perform graph based WSD across different languages in India, and brings together empirical evidence from these languages using ensemble methods. Therefore the results show that, by complementing the wide-coverage lexical knowledge with robust graph-based algorithms and combination methods, we can achieve the state of the art in WSD settings. However, it does not require any sort of training process, no hand-coding of lexical entries, nor the hand-tagging of texts.
Keywords: Word Sense Disambiguation, Indoword Net, Graph Based Approach, Multilingual Information.
Scope of the Article: Graph Algorithms and Graph Drawing

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E2488027518

IJITEE Journal — Sat, 17 Dec 2022 06:20:51 +0000

Face Recognition of Pedestrians from Live Video Stream using Apache Spark Streaming and Kafka
Abhinav Pandey¹, Harendra Singh²
">¹Abhinav Pandey, Department of Computer Science & Engineering, Lakshmi Narain College of Technology Excellence, Bhopal (M.P), India.
²Mr. Harendra Singh, Assistant Professor, Department of Computer Science & Engineering, Lakshmi Narain College of Technology Excellence, Bhopal (M.P), India.
Manuscript received on 8 February 2018 | Revised Manuscript received on 15 February 2018 | Manuscript Published on 28 February 2018 | PP: 4-10 | Volume-7 Issue-5, February 2018 | Retrieval Number: E2488027518/18©BEIESP
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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: Face recognition of pedestrians by analyzing live video streaming, aims to identify movements and faces by performing image matching with existing images using Apache Spark Streaming, Kafka and OpenCV, on distributed platform and derive decisions. Since video processing and analysis from multiple resources become slow when using Cloud or even any single highly configured machine, hence for making quick decisions and actions, Apache Spark Streaming and Kafka have been used as real time analysis frameworks, which deliver event based decisions making on Hadoop distributed environment. If continuous live events analysis is possible then the decision can make there-after or at the same time. And large amount videos in parallel processing are also not a bottleneck after getting the involvement of Hadoop because base of all real time analysis distributed tools is Hadoop. This event based analysis can be applied at any place where an immediate action is required like monitoring border areas of countries by cameras and drones, road traffic monitoring, life science domain, airlines, logo recognition and where-ever continuous monitoring and decision making involved in large scale data set.
Keywords: Distributed System, Hadoop, Spark, Spark Streaming, Kafka, Open CV.
Scope of the Article: Pattern Recognition and Analysis

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E2487027518

IJITEE Journal — Sat, 17 Dec 2022 06:12:44 +0000

A Survey on Live Video Stream using Distributed Technologies
Abhinav Pandey¹, Harendra Singh²
">¹Abhinav Pandey, Department of Computer Science & Engineering, Lakshmi Narain College of Technology Excellence, Bhopal (M.P), India.
²Mr. Harendra Singh, Assistant Professor, Department of Computer Science & Engineering, Lakshmi Narain College of Technology Excellence, Bhopal (M.P), India.
Manuscript received on 8 February 2018 | Revised Manuscript received on 15 February 2018 | Manuscript Published on 28 February 2018 | PP: 1-3 | Volume-7 Issue-5, February 2018 | Retrieval Number: E2487027518/18©BEIESP
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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 data is growing in multiple dimensions with lots of verities and gradually becoming humungous so there is high demand of frameworks for processing Big Data. There were frameworks available for processing structured and semi structured data but for processing un-structured data with real time analysis, very few options were availabe which can process only limited amount of data and high volume of data was a bottleneck for IT industries. It was not a big deal to work with ‘data in rest’ and only few frameworks available for analyzing data in motion like Apache Storm, got lots of motivation. Recently, for live streaming analysis and instant decision making Spark Streaming got introduced by Data Bricks and this is gaining lots of limelight due to its easy configuration and setup with loads of machine learning techniques and reliability at distributed platform. Using Storm prediction and face recognition were implemented. Through this study we will implement Real time video streaming analysis using Spark Streaming.
Keywords: Distributed System, Hadoop, Spark, Spark Streaming, Opne CV
Scope of the Article: Streaming Data

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