Volume-8 Issue-2S, December 2018 – International Journal of Innovative Technology and Exploring Engineering (IJITEE)

BS2732128218

IJITEE Journal — Sat, 25 Nov 2023 12:54:32 +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. Challenges of Industry and their Solutions, Communications #Advanced Manufacturing Technologies #Artificial Intelligence #Autonomous Robots #Augmented Reality #Big Data Analytics and Business Intelligence #Cyber Physical Systems (CPS) #Digital Clone or Simulation #Industrial Internet of Things (IIoT) #Manufacturing IoT #Plant Cyber Security #Smart Solutions – Wearable Sensors and Smart Glasses #System Integration #Small Batch Manufacturing #Visual Analytics #Virtual Reality #3D Printing # Internet of Things (IoT) #Internet of Things (IoT) & IoE & Edge Computing #Distributed Mobile Applications Utilizing IoT #Security, Privacy and Trust in IoT & IoE #Standards for IoT Applications #Ubiquitous Computing #Block Chain-enabled IoT Device and Data Security and Privacy #Application of WSN in IoT #Cloud Resources Utilization in IoT #Wireless Access Technologies for IoT #Mobile Applications and Services for IoT #Machine/ Deep Learning with IoT & IoE #Smart Sensors and Internet of Things for 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A Study on Mechanical Properties of Concrete Reinforced with Hybrid Fibers at a Low Fiber Volume Fractions
Srikanth Koniki¹, D Ravi Prasad²

¹Srikanth Koniki, Research Scholar, Department of Civil Engineering, National Institutes of Technology, Warangal, Telangana, India.

²D. Ravi Prasad, Assistant Professor, Department of Civil Engineering, National Institutes of Technology, Warangal, Telangana, India.

Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© 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 study is aimed to investigate the effect of fiber hybridization on basic mechanical properties of 30 MPa concrete. Fibers used in the study are Hooked-end steel, polyester and polypropylene. Hybridization was done in two stages, the first stage of the investigation was to develop and study the effect of polyester-polypropylene (Non–metallic) HFRC at a total fiber volume fraction of 0.15%. Further, the investigation was carried out to develop a hybrid fiber reinforced concrete made with metallic (hooked-end Steel) and non-metallic fibers at a total fiber volume fraction of 0.5%. Mechanical properties, namely compressive strength, direct tensile strength and flexural strength were investigated. The results obtained were compared with mono-fiber reinforced concrete and conventional concrete. Significant improvement in direct tensile strength and flexural strength observed with the with the fiber hybridization compared to mono-fiber reinforced concrete and control mix. This may be due to synergic response of different fibers at different scales of cracking at different stress levels in concrete. Superior results were observed at metallic – non-metallic hybridization due to exhibition of synergetic response of fibers by inhibition of crack growth and propagation, at different scales of cracking at different stress levels in concrete.

Keywords: Fiber hybridization, concrete. Fibers, compressive strength
Scope of the Article: Computational Techniques in Civil Engineering

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BS2731128218

IJITEE Journal — Sat, 25 Nov 2023 12:50:39 +0000

Ground Level Ozone Prediction for Delhi using LSTM-RNN
S. Geetha¹, L. Prasika²

¹S. Geetha, Assistant Professor, Mepco Schlenk Engineering College, Sivakasi (Tamil Nadu), India.

²L. Prasika, Assistant Professor, Mepco Schlenk Engineering College, Sivakasi (Tamil Nadu), India.

Abstract: Outdoor air pollutants are bringing adverse effects on the living being health. Air quality is deteriorating due to multi-pollutants such as sulfur dioxide (SO2 ), Nitrogen dioxide (NO2 ), Nitrogen oxide (NOx ), Ozone (O3 ), Carbon Monoxide (CO), Particulate Matter 2.5 (PM2.5), Particulate Matter 10 (PM10), etc. Out of these multi-pollutants, ground level Ozone is creating major health issues in lungs, heart, etc. Ground level Ozone is formed due to reactions between Nitrogen, vehicle emissions, Industrial emissions, and gasoline with the presence of sunlight. Recently, Deep Learning Techniques are applied in all prediction problems. Here, we proposed the Recurrent Neural Network based LSTM prediction model to predict the ground level ozone. The model is created with the historical data collected from various stations in and around Delhi. The model is providing more accuracy to predict the ground level ozone than the stare-of-art techniques. The model is evaluated with normalized mean square error and mean absolute error.

Keywords: Sulfur Dioxide (SO2 ), Nitrogen Dioxide (NO2 ), Nitrogen oxide (NOx ), Ozone (O3 ), Carbon Monoxide (CO), Particulate Matter 2.5 (PM2.5).
Scope of the Article: Building and Environmental Acoustics

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BS2644128218

IJITEE Journal — Sat, 25 Nov 2023 12:47:09 +0000

Handling Complete-Verbs of Telugu in Machine Translation
T. Kameswara Rao¹, M. Rajyalakshmi², T. V. Prasad³, V. Koteswara Rao⁴

¹Dr. T. Kameswara Rao, Department of Computer Science and Engineering, Vasireddy Venkatadri Institute of Technology, Namburu, Guntur Andhra Pradesh, India.

²M. Rajyalakshmi, Associate Professor, Department of Information Technology, Vasireddy Venkatadri Institute of Technology, Namburu, Guntur Andhra Pradesh, India.

³Dr. T. V. Prasad, Principal, Godavari Institute of Engineering and Technology, Rajahmundry Andhra Pradesh, India.

⁴V. Koteswara Rao, Assistant Professor, Department of Computer Science And Engineering, Vasireddy Venkatadri Institute of Technology, Namburu, Guntur Andhra Pradesh, India.

Abstract: Verbs can be divided into two types, transitive and intransitive. A verb can be derived into many forms like complete, incomplete, reflexive, causative, interrogative, passive, negative, etc. in Telugu. Transitive verbs need an object to perform action on it, while intransitive verbs do not need. Between the complete and incomplete verbs, only complete verbs can convey fulfilled or complete meaning of the sentence, while incomplete verbs cannot. Reflexive verbs convey that the action performed is for self. Causative verbs convey that the action is made done. Interrogative verbs are used for inquiry. Passive verbs are object oriented, which emphasize action rather than actor. A verb can be derived into its negative and positive forms. Verbs can again be grouped into regular and irregular type based on the way how they form. Various types of complete-verb derivatives of regular and irregular verbs, based on tense/ mood, number, and gender are discussed in detail in this paper. Only complete verbs of Telugu were considered for handling their conjugations in Machine Translation (MT) in this paper.

Keywords: Telugu Conjugations, Conjugation Handling, Machine Translation, Morphological Analysis.
Scope of the Article: Computer Science and Its Applications

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BS2725128218

IJITEE Journal — Sat, 25 Nov 2023 12:43:04 +0000

Embedded System Based Home Security Surveillance using Raspberry PI
S.Kaliappan¹, A.Ezhilarasi², S.Abhianaya Priya³, N.J.Nivetha⁴

¹S.Kaliappan, Assistant Professor, Department of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore (TamilNadu), India.

²A.Ezhilarasi, Assistant Professor, Department of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore (TamilNadu), India.

³S.Abhianaya Priya, PG Scholar, Kumaraguru College of Technology, Coimbatore (TamilNadu), India.

⁴N.J.Nivetha, PG Scholar, Kumaraguru College of Technology, Coimbatore (TamilNadu), India.

Abstract: This paper is based on home based security system. In modern world people are instructed on home automation, but don’t care about home security. Security is much more important than automation of home because it can save life and commodity of the people. This paper proposes two main important aspects. One of the processes is automatic sending of message to home owner with help of GSM when door is open by unauthorized user using PIC microcontroller and next one is surveillance camera usage for home security by raspberrypi-3Raspberrypiis used for image processing, image processing can be done only if user can enter wrong password it will indicate to raspberry pi for image processing for finding out the unauthorized person.

Keywords: Home Automation, Camera, GSM, PIC-Microcontroller
Scope of the Article: Computer Architecture and VLSI

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BS2724128218

IJITEE Journal — Sat, 25 Nov 2023 12:36:28 +0000

A Novel Improved Resonant LLC Converter with Minimal Components
Tamilarasu Viswanathan¹, P Maithili²

¹Tamilarasu Viswanathan, Assistant Professor, Department of Electrical and Electronics Engineering, Kumaraguru College of Technology Coimbatore (TamilNadu), India.

²P Maithili, Assistant Professor, Department of Electrical and Electronics Engineering, Kumaraguru College of Technology Coimbatore (TamilNadu), India.

Abstract: This paper presented a novel improved resonant LLC converter with minimal components compared with existing design. Conventional Full H-Bridge in converter replace with differential boost for improving the overall gain of the circuit and also able to operated buck, boost and buck-boost. As a result, the component size is significantly reduced and enhance the size and cost of the converter. Different modes of operations presented for understanding the new converter in terms of switching frequency and gain. An Experimental and simulation result confirms the effectiveness of the proposed inverter.

Keywords: Resonant tank, DC-DC Converter, buck, Boost, Buck-Boost, Switching Frequency, Inverter, Overall gain.
Scope of the Article: Computer Architecture and VLSI

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BS2723128218

IJITEE Journal — Sat, 25 Nov 2023 12:33:22 +0000

Texture Classification Based On Fuzzy Similarity Texton Co-Occurrence Matrix
J.Srinivas¹, Ahmed Abdul Moiz Qyser², B. Eswara Reddy³

¹J.Srinivas, Research Scholar, Muffakham Jah College of Engineering and Technology, Hyderabad, Telangana, India.

²Dr. Ahmed Abdul Moiz Qyser, Department of Computer Science and Engineering, Muffakham Jah College of Engineering and Technology, Hyderabad, Telangana, India.

³Dr. B. Eswara Reddy, Principal, JNTUA College of Engineering, Kalikiri Chittoor, Andhra Pradesh, India.

Abstract: In the existing texton based methods a texton is derived in a grid by a collection of pixels exhibiting exactly the similar grey level values/color/attributes. The disadvantage of this approach is they fail in recognizing textons, whenever a small random noise changes the pixels intensity values slightly. This paper addresses this by deriving a fuzzy similarity ‘S’ in identification of texton patterns. The proposed Fuzzy similarity Texton Co-occurrence Matrix (FSTCM) framework considers the pixels whose gray level value falls within the fuzzy similarity index value as texton pattern. The FSTCM divides initially the texture image into micro regions of size 2×2, identifies the textons and transforms the texture image into a fuzzy texton image. This paper derives gray level co-occurrence matrix (GLCM) features on FSTCM and the proposed method is tested on five popular texture image databases. The experimental investigation reveals the high performance of the proposed method over the state of art local based and texton based methods.

Keywords: Texton, Similarity; Micro Region; GLCM Features; Random Noise.
Scope of the Article: Classification

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BS2722128218

IJITEE Journal — Sat, 25 Nov 2023 12:27:50 +0000

Age Classification Based On Appearance Model Using Local Ternary Direction Pattern Approach
Nara Sreekanth¹, Munaga HM Krishna Prasad²

¹Nara Sreekanth, Research Scholar, Department of Computer Science and Engineering, BVRIT Hyderabad College of Engineering for Women, Bachupally, Telengana, India.

²Munaga HM Krishna Prasad, Professor, Department of Computer Science and Engineering, University College of Engineering Kakinada, JNTUK, Pithapuram Road, Nagamallithota, Kakinada, Andhra Pradesh, India.

Abstract: The appearance model play a vital role in many applications related to facial images. This paper derives a new approach of appearance model using local ternary derivative patterns on human facial images for effective age groups classification. In the literature direction patterns are derived with respect to central pixel of the neighborhood. This paper derives ternary direction patters (TDP) between sampling points of the neighborhood with a strong assumption that the relationship between adjacent pixels derive rich information. This paper divides the neighborhood into vertical and horizontal units and derives the TDP and based on the relative frequencies of horizontal and vertical TDP, this paper derives horizontal vertical direction unit matrix (HVDUM). The gray level co-occurrence matrix (GLCM) features are derived on HVDUM for age classification and the experimental results are compared with the existing methods and the results indicate the efficiency of the proposed method over the existing methods.

Keywords: Neighborhood; Vertical-Horizontal Units; GLCM Features; Sampling Points
Scope of the Article: Classification

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BS2721128218

IJITEE Journal — Sat, 25 Nov 2023 12:23:44 +0000

Local Texton Centre Symmetric Pattern Matrix (Ltcspm) On Wavelet Domain for Texture Classification
B. Kishore¹, V. Vijaya Kumar²

¹B. Kishore, Research Scholar, Sri Chandrasekharan Saraswathi Viswa Mahavidyalaya University, Kanchipuram, Tamil Nadu, India.

²V. Vijaya Kumar, Professor, Department of Computer Science and Engineering, Manipal Institute of Technology, MAHE, Manipal, India.

Abstract: This paper proposes a novel local descriptor, local texton center symmetric texture matrix (LTCSTM) for texture classification on wavelet domain. The proposed LTCSTM extracts i) structural features from texton representation ii) Local texton center symmetric pattern (LTCSP) code iii) integrates the above two features with gray level co-occurrence matrix (GLCM) features. The texture classification is performed using machine learning classifiers. Initially the raw image is transformed in to wavelet based image. The LL-1 image is sub divided in to local regions of size 2 x 2 and each region is replaced with texton index. The LTCSP is derived on texton index image. The LTCSP code replaces the center pixel of the 3×3 window. The derivation of co-occurrence matrix on this LTCSP coded image derives the proposed LTCSTM. The GLCM features on LTCSTM are used for texture classification. The proposed LTCSTM is compared with state-of-art of texton based methods and local descriptors of LBP on five popular databases. The experimental evidence clearly indicates the efficiency of the proposed method over the rest of the state-of-art methods.

Keywords: Local Binary Pattern, GLCM Features, Classifiers, Integrated Features, Wavelet Domain.
Scope of the Article: Classification

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BS2720128218

IJITEE Journal — Sat, 25 Nov 2023 12:19:37 +0000

Use of Steel Slag as Coarse and Fine Aggregate in Porous Concrete Pavements
Vishwanath B J¹, Rex²

¹Vishwanath B J, Department of Civil Engineering, Malla Reddy Engineering College, Hyderabad, India.

²Dr. Rex, Department of Civil Engineering, Malla Reddy Engineering College, Hyderabad, India.

Abstract: Due to increasing demand of raw materials for construction of roads, the environmental eco system is getting imbalanced. Hence there is a need to preserve natural resources by using eco friendly alternative materials. Steel slag is one such alternative material, which is an industrial by product that can be used as an alternative to aggregates in partial replacement in road construction. Slag may be used as both coarse and fine aggregates in cement concrete. Hence in the present study mix design for conventional porous concrete was carried out for different proportion of fine and coarse aggregate (0:100, 10:90, 15:85, 20:80, and 30:70). The optimum dosage of FA:CA for the conventional porous concrete mix, giving high strength with acceptable permeability was fixed i.e 20:80 Then the mix design for porous concrete was carried out for partial replacement coarse and fine aggregates with steel slag in 20:80 mix. i.e Replacing only the coarse aggregate in FA:CA (20:80) mix with the air cooled LD slag in three different proportions such as 10%, 30% and 50% .i.e keeping FA-20% constant and replacing coarse aggregate by slag in 80% of CA and Replacing only the fine aggregate in FA:CA (20:80) with the granulated LD slag in three different proportions such as 30%, 60% and 90% .i.e keeping CA 80% constant and replacing fine aggregate by slag in 20% FA. Finally the mix design properties in terms of strength and permeability are evaluated for the porous concrete prepared with coarse and fine slag.

Keywords: Porous Concrete; Air Cooled LD slag; Granulated LD slag; Coarse Aggregate
Scope of the Article: Computational Techniques in Civil Engineering

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BS2719128218

IJITEE Journal — Sat, 25 Nov 2023 12:16:32 +0000

RSM based Empirical Model for the Performance and Emission Characteristics of ROME Biodiesel
T. Ramachandran¹, S Murugapoopathi², D. Vasudevan³

¹T.Ramachandran, Department of Mechanical Engineering, Malla Reddy Engineering College, Secundrabad, Telgana, India.

²S.Murugapoopathi, Department of Mechanical Engineering, PSNA College of Engineering & Technology, Dindigul, Tamilnadu, India.

³D.Vasudevan, Department of Mechanical Engineering, PSNA College of Engineering & Technology, Dindigul, Tamilnadu, India.

Abstract: In the current scenario, the production of biodiesel for IC engine plays important role due to the undesirable pollution and cost hike of the conventional fuels. In India, milk from the rubber tree (HeveaBrasiliensis) is used for the production of elastic materials which are most widely used in engineering applications. But the seed from the rubber tree is kept wasted without any further usage and hence in this research the oil produced from the rubber seed is suggested for effective biodiesel production. The rubber seed oil (RSO) is converted in to usable rubber seed oil methyl ester (ROME) biodiesel using trans-esterification and tested for the characteristics of performance and emission through variable compression ratio (VCR) engine. The detailed set of experiments are conducted in the VCR engine with different biodiesel-diesel ratios to evaluate the BTE, SFC, CO, CO2 and NOx levels of the blends. A mathematical model also developed using Response Surface Method (RSM) for these parameters such that the compression ratio, fuel blend, engine load, and injection pressure are the design variables, The experimental results are used in the RSM to create the mathematical models and the models are checked for the ANOVA and p-test. Finally the models are tested with the new sets of experimental results.

Keywords: ROME, VCR Engine, RSM, Emission, Biodiesel
Scope of the Article: Mechanical Maintenance

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