bluuebunny/crossref_metadata_2025 huggingface dataset:
Automated Tongue Diagnosis: A Deep Autoencoder Neural Network and Clustering-Based Image Segmentation Approach
Authors: L Abisha , K. Sindhu
Published: September 2023

Automatic tongue image segmentation and tongue image classification are two crucial tongue characterization tasks in traditional Chinese medicine (TCM). Due to the complexity of tongue segmentation and fine-grained traits of tongue image classification, both tasks are challenging. Fortunately, from the perspective of computer vision, these two Tasks are highly interrelated, making them compatible with the idea of Multi-Task Joint learning (MTL).By sharing the underlying parameters and adding two different task loss functions, an MTL method for segmenting and classifying tongue images is proposed in this paper. Moreover, two state-of-the-art deep neural network variants (UNET and Discriminative Filter Learning (DFL)) are foused into the MTL to perform these two tasks. To the best of our knowledge, our method is the first attempt to manage both tasks simultaneously with MTL. We conducted extensive experiments with the proposed method. The experimental results show that our joint method out performs the existing tongue characterization methods. The process of tongue diagnosis by extracting meaningful features from tongue images and segmenting the relevant regions for analysis. The deep auto encoder neural network is employed to learn a compact representation of tongue images by encoding and decoding the input data.
IoT Network Traffic Classification Using Machine Learning Algorithms: An Experimental Analysis
Authors: E Evelyn Lisa , T. L. Ajeesha
Published: September 2023

In this project, classification of IoT network traffic using random forest classifier is proposed. More-dataset is utilized to separate the IoT traffic classification. Data preprocessing is the concept of changing the raw data into a clean data set. The dataset is preprocessed in order to check missing values, noisy data, and other inconsistencies before executing it to the algorithm. Extraction takes place using Chi-square based feature extraction. To improve classification, the extraction regions are processed using the Chi- Square technique to extract several features and select the necessary features. This project uses the effective Chi-square technique to find feature extraction and feature selection. Finally, the selected features are fed into an extra tree and random forest classifier for accurate classification. This project is implemented using Python software.
Mechanical Characterization of Bamboo Fiber over Glass and Carbon Fiber Reinforced Polymer Composites
Authors: N. Shalom , J Edwin Raja Dhas
Published: September 2023

Composite materials have different effective material properties with different combinations of material components. Recently, composites are growing in mechanical, automotive and other usages owing to many of their benefits. Natural are receiving considerable attention as a substitute for many conventional materials, such as plastics, in industrial applications. Especially in countries like India, the rich supply of bamboo makes it a sustainable source of natural fiber to be used for composite manufacturing. Conventional material alone is not enough to meet the diverse requirements of design engineers. The fiber-matrix-filler interfacial adhesion of composites with fiber and filler reinforcement greatly enhances their mechanical performance. Composite structures’ stiffness is frequently decreased by dynamic loads in various environments. To enhance the mechanical characteristics of such structures, nano particles such as carbon nanotubes and grapheme have been incorporated into composites. The composite material can be fabricated by stir casting technique, compression molding, hand lay-up process etc. Mechanical, metallurgical and thermal properties of the fabricated materials can be done. The recent literature revealed the different combinations and different process in the fabrication of composites. The addition of bamboo fiber reinforced polymer composite with natural coconut shell carbon nano filler as additive proves to be very novel and has a possibility to explore in many upcoming mechanical and automotive applications.
A Study on Financial Performance Analysis with Reference to the Leela Palace, Chennai
Authors: J. V Blesslin Shermi , A. Robert Raja Singh , C. R Manju
Published: September 2023

In this project we are looking at the Financial Performance Analysis in a core sector industry. Balance sheet review of the last five years along with the changes in the component wise analysis of Current Asset and Current Liabilities to identify the causes of changes, with trend analysis and comparative Balance sheet for a term of five years covering a case study on financial performance analysis with reference to The Leela Palace is largely a study of relationship among the various financial factors in a business as disclosed by a single set of statements and a study of the trends of these factors as shown in a series of statements.” The purpose of financial Performance analysis is to diagnose the information content in financial statements so as to judge the profitability and financial soundness of the firm. In this project we will perform the financial analysis of The Leela Palace we will go through the financial statements of the company to diagnose financial soundness.
Strength Analysis of Layered Sandwich Beam
Authors: K S Dins
Published: September 2023

Sandwich beams are composite systems that have properties such as high rigidity, high strength and low weight. The sandwich system include glass fiber reinforced polymer (GFRP) skins and phenolic cores, and several layers of sandwich panels are bonded with an epoxy polymer matrix to manufacture the packages. In sandwich beam (LSB) layers, four horizontally oriented layers and the other four vertically oriented layers were tested. To understand the basic behavior of a multilayer sandwich beam, a 3D finite element model was developed using ANSYS. To explore the suitability of this new concept for structural applications, the flexural behavior of the layered sandwich beam is validated using data available in the literature, and the numerical model can be improved by incorporating shear and fatigue behavior which increases confidence in using this novel concept of beam in the civil construction sector.
Enhancing Fruit Disease Recognition Using Deep Learning Model
Authors: S Jasmin , R Benschwartz
Published: September 2023

Fruit and vegetable identification and classification system is always necessary and advantageous for the agriculture business, the food processing sector, as well as the convenience shops and hypermarkets where these products are sold. Therefore, it is necessary to build an effective automated tool to meet the needs of the market by boosting the outcome, in order to improve economic efficiency. In this paper, a two-stage model is proposed to recognize fruits using camera images. Fruit disease recognition plays a crucial role in ensuring the quality and yield of fruits in agriculture. The framework for fruit disease recognition using a combination of VGG16 feature extraction, APGWO and CNN classification.VGG16 is a deep convolutional neural network known for its excellent feature extraction capabilities. APGWO adaptively adjusts the parameters to enhance the search efficiency and accuracy of feature selection. In this study, Adaptive particle – Grey Wolf Optimization (APGWO) has been applied for choosing the most pertinent features.
Experimental Investigations on Modifie Fibre Reinforced Concrete
Authors: S. Nithiya Shoba
Published: September 2023

In reviewing technology advances through the centuries, it is evident that material development plays a key role. Considerable efforts are still being made in every part of the world to develop new construction materials. In the construction industry, concrete technology is heading towards entirely new era by way of using polymers and fibres along with Super plasticizer in concrete. Increasing interest is being shown in the area of new materials in the past decade. This is quite understandable because, it is slowly, but increasingly being recognized that economic progress in construction depends more on an intelligent use of the materials and constant improvement of available materials than on extreme refinements of structural analysis. Concrete is probably the most widely used material in the world in view of its strength, structural stability, durability, economic considerations and low level maintenance and Portland cement, probably the most important constituent of concrete, is a versatile and relatively low cost material. With the extensive use of cement for widely varying conditions, technologists catered to the needs of the construction industries for specific purposes. Some of the admixtures presently being used include pozzolanas, retarders, accelerators etc. Concrete is usually characterized by its compressive strength. It has been observed that microstructure is very important for the macro performance. The versatility of concrete as a building material pushed the research into improving rather old material, the demand for taller reinforced concrete structures which increase the quest for higher concrete strength.
Experimental Investigation on Corrosion Prevention in RCC by Enhancing the Durability Properties using Organic and Inorganic Additives
Authors: R Jereesh , S. Shijilin Prem Shirold
Published: September 2023

Corrosion of reinforcing steel and other embedded metals is the leading cause of deterioration in concrete. When steel corrodes, the resulting rust occupies a greater volume than the steel. This expansion creates tensile stresses in the concrete, which can eventually cause cracking, delamination, and spalling. General corrosion occurs when most or all of the atoms on the same metal surface are oxidized, damaging the entire surface. There has been increasing search for organic and inorganic corrosion inhibitors, due to the toxic behavior of some inhibitors. Green inhibitors are the compounds containing one or more polar groups such as O, N, P, S atoms and π electrons which prevent corrosion on the metal surface. In this experimental project, the inhibitors are added as three proportions of inhibitors while giving coating to the steel bar. Neem powder, Zinc powder, fine aggregate, coarse aggregate, water were the materials used for this investigation. Considering the mechanical and durability properties, it was found that increase of organic inhibitors gave better strength to the concrete than inorganic inhibitor and reduces the corrosion compared to the conventional concrete. An organic inhibitor coating given to the steel bar increased the bond strength and well behaved in durability testing.
Life Strength Prediction of GFRP Pressure Vessels Using Acoustic Emission Technique
Authors: D. F Jingle Jabha , R Joselin , R. S Sarath Gokul , S Japdrew
Published: September 2023

Acoustic Emission (AE) has the unique potential for the real time integrity evaluation of pressurized systems. The technique has found greater importance in its application towards fibre reinforced plastic (FRP) pressure vessels in aerospace use. There is no method till date spelt out in open literature for burst pressure prediction of composite pressure vessels. This paper brings out a methodology for the burst pressure prediction of Glass Fibre Reinforced Plastic (GFRP) pressure vessels using a lucid empirical relation. Acoustic Emission monitoring was carried out during hydrostatic loading of five identical GFRP pressure vessels, about 6- litre capacity. An empirical relation was generated on the basis of the governing AE parameters viz., count rate, duration rate, amplitude rate and felicity ratio exhibited when the h/w was subjected to cyclic proof pressure cum burst test. AE data is acquired up to 50% of the theoretical burst pressure, and then the vessels were pressurized upto failure. The authors have framed an empirical relation to predict the burst performance, solving the typical equations with MAT LAB program for the four identical GFRP vessels. An attempt is made on the fifth hardware to predict its burst pressure. This innovative methodology illustrates the behaviour of GFRP pressure vessels in terms of AE parameters and its derivatives. This can possibly predict in real time the burst pressure of similar hardware if extended to other material systems. The failure is significant even at 50 to 60% of Maximum Expected Operating Pressure (MEOP) with an acceptable error margin.
Hybrid Deep Transfer Learning Framework for Stroke Risk Prediction
Authors: S. V Reshma , R Gini
Published: September 2023

Stroke has become a leading cause of death and long-term disability in the world with no effective treatment. Deep learning-based approaches have the potential to outperform existing stroke risk prediction models. Due to the strict privacy protection policy in health-care systems, stroke data is usually distributed among different hospitals in small pieces. Transfer learning can solve small data issue by exploiting the knowledge of a correlated domain, especially when multiple source of data are available. In this work, we propose a novel Hybrid Deep Transfer Learning-based Stroke Risk Prediction scheme.
Hospital services Management system using Internet of Things (IoT) Techniques
Authors: S. Tamilmani , J Reena Benjamin , A S Shiji
Published: September 2023

A hospital patient tracking system using RFID technology is a web application developed for medical personnel (doctors and nurses) to monitor the movement of hospitalized patients. A RFID reader placed in each room will detect a patient wearing a registered tag when entering and leaving the room. It is designed to address the problems of long queues, overcrowding, delayed treatments and insufficient beds for patients. The tracking process is used to track all registered patients. At the same time, the duration of the patient process in each room will be recorded and calculated to obtain the range processing times in each room. It can be used to refer to and address the bottlenecks they face at the hospital. All medical personnel must register and be approved by the system administrator before access the system.
An Experimental Study of Mechanical and Durability Properties of Concrete Incorporating Glass Powder and GGBS as Supplementary Cementitious Materials
Authors: V Ashbin Jini , S Belfin Raj
Published: September 2023

Ground granulated blast furnace slag (GGBS) was used in this study to replace Portland cement and also investigate the effect of glass powder (GP) on the behaviour of mechanical and durability properties of concrete as a partial replacement in cement. Cement can be used as a mortar to bind large stones or bricks. When sand and stones are added to cement, the aggregate is called concrete. The mechanical properties were examined by the tests of compressive strength, flexural strength, bond strength and split tensile strength. Durability behaviour was carried out by water absorption and sorptivity. 3/8 Replacement of cement by glass powder was from 5% to 45% in step of 5% and the GGBS with range of replacement from 45% to 5% in step of 5% respectively.
Planning Analysis and Design of Multi Storied Building by Staad.Pro.v8i
Authors: S Sunil
Published: September 2023

The aim of the project is to design a multi storied building of G+5 floors, at Avanavan cherry about 2 km from Attingal. He design is done by taking in to account the requirements and standards recommended by IS code, Kerala building rules and national building rules. Planning is done using the 3D modeling software Revit 2018with the help of Auto CAD 2017. The structure analysis and design is done using STAAD.PRO.V8i and a cross check is done for selected members using limit state method of design as per IS 456-2000. STAAD. Pro uses a command language based input format, which can be created through an editor called the editor file, the powerful STAAD. Pro graphics input generator or through CAD based input generators like AutoCAD. Output generated by staad.pro consists of detailed numerical results for analysis and design.
Study of Earthquake Loading On the Analysis of Cable Bridge Structure Using Staad Pro
Authors: T. Shibin
Published: September 2023

To overcome the obstacles like crossing of river, Dam, Heavy Traffic flow in the way of journey Bridges were the part of our day-today life. Construction of such kinds of Bridges were being much challenging. Construction of bridge works are making the life complicated. Much efficient and quick construction of bridges are very important. Cable stayed bridges are visualized for their less construction time, Higher Efficiency. In the construction aspect cable stayed bridges have less supporting points to the ground when compared with traditional Bridges. By thus it is having higher sensitivity to natural calamities like Seismic activity like Earthquakes. Because of supporting long length by pylons the response of these kind of structures should be analyzed for safe construction and better serviceability. The complicated analysis procedure makes the structure safer. The complicated analysis can be simplified by the software’s like Staad Pro. In the software we can create earthquakes in various intensities and the real-time response can be found out. This paper describes more about the cable bridges and their response for the Seismic activity. The analysis procedure is done in Staad Pro and the response of a model cable stayed bridge is figured out for gaining the safety standards for safer construction of Cable Stayed Bridge.
Kinship Measurement on Face Images by Structured Similarity Fusion
Authors: R Akash , S. T Sukanya
Published: September 2023

Kinship verification, which is a challenging problem in computer vision and pattern discovery. It has several applications, such as organizing photo albums, recognizing resemblances among humans, and finding missing children. A system for facial kinship verification based on several kinds of texture descriptors (local binary patterns, local ternary patterns, local directional patterns, local phase quantization, and binarized statistical image features) with pyramid multilevel (PML) face representation for feature extraction along with our proposed paired feature representation and our proposed robust feature selection to reduce the number of features. The proposed approach consists of the following three main stages: (1) face pre-processing, (2) feature extraction and selection, and (3) kinship verification. Extensive experiments are conducted on five publicly available databases (Cornell, UB KinFace, Family 101, KinFace W-I, and KinFace W-II). Additionally, a wide experiment for each stage to find the best and most suitable settings. Many comparisons with state-of-the-art methods and through these comparisons, it appears that our experiments show stable and good results.
Highly Accurate Deep Learning PNN Classifier Based Skin Cancer and Depth Analysis
Authors: M Janani , J. k Gershom King Rose
Published: September 2023

Melanoma cancer is a type of skin cancer and is the most dangerous one because it causes the most of skin cancer deaths. Melanoma comes from melanocyte cells, melanin producing cells, so that melanomas are generally brown or black colored. Melanomas are mostly caused by exposure to ultraviolet radiation that damages the DNA of skin cells. The diagnoses of melanoma cancer are often performed manually by using visuals of the skilled doctors, analyzing the result of Dermoscopy examination and match it with medical sciences. Manual detection weakness is highly influenced by human subjectivity that makes it inconsistent in certain conditions. Therefore, a computer assisted technology is needed to help classifying the results of Dermoscopy examination and to deduce the results more accurately with a relatively faster time. The making of this application starts with problem analysis, design, implementation, and testing. This application uses deep learning technology with Probabilistic Neural Network method and LeNet-5 architecture for classifying image data.
Optimized Multi Support Vector Machine Based Approach for Fake News Detection
Authors: M Ganga , R Gini
Published: September 2023

Fake News creates erroneous suspense information that can be identified. This spreads dishonesty about a country’s status or overstates the expense of special functions for a government, destroying democracy in certain countries. The project proposes an Multi Support Vector Machine (MSVM) -based approach for detecting fake news. The proposed model will be used to classify or detect the news as fake or real. Principal Component Analysis (PCA) is used for Feature Extraction. Principal Component Analysis (PCA) reduces the dimension of the data set comprising many related variables and recalls the maximum change in actual data. The proposed work will select the essential features with a Firefly-Optimized Algorithm (FA). The Firefly Optimized Algorithm (FA) is one of the various Evolutionary Algorithms (EAs) with various purposes. For the classification of fake news, an Multi Support Vector Machine (MSVM) classifier algorithm is implemented.
Surveillance Video Summarization based on Target Object Detection
Authors: D. Minola Davids , C. Seldev Christopher
Published: September 2023

The recent trend increases the use of surveillance cameras in many of the private and public premises, which causes the number of surveillance videos to grow exponentially. The information gained from these surveillance videos not only helps the owner of the property, but also helps in crime investigations for police and security officials. Though there are several applications of such videos, yet their storage, management and retrieval processes are still challenging. Hence, it is important to develop an efficient technique to describe a long video into a shorter video with semantic information by eliminating the redundant and unimportant frames. This technique makes the larger video to shrink in length for efficient storage and also helps the users to attain a complete knowledge of the video by only watching the shorter video, without spending more time in watching the original longer video. To achieve this objective, this paper proposes a video summarization technique for summarizing the surveillance videos by extracting the target object using YOLO then discarding the remaining frames and finally combining the extracted key frames into a single video. This method first detects the target object related in the original video frames and then eliminates the remaining frames that are irrelevant without prominent objects, resulting in video with only the key frames which are into the interest of the user, finally those frames are combined to form a summarized video.
Flexural Behaviour of RC Beam with Welded Mesh as Transverse Reinforcement
Authors: S. S Gokul
Published: September 2023

The use of welded mesh as transverse reinforcement in reinforced concrete beams has gained increasing interest due to its potential advantages over traditional stirrups. This study investigates the strength behaviour of RC beams with welded mesh as transverse reinforcement through experimental approaches. Usage of welded wire mesh results in stress-free and quicker assembly, and better budget and superiority control. One Control beam with conventional reinforcement with five other beams with vary welded mesh were cast and tested under two point loading. The results were used to study the flexural behaviour. It is obtained that the beam with continuous weld mesh and longitudinal bar given the maximum load carrying capacity. The test results are analysed to determine the load-carrying capacity, deflection characteristics, and failure modes of the specimens. The study aims to provide valuable insights into the applicability and effectiveness of welded mesh as transverse reinforcement in RC beams, offering potential benefits such as cost-efficiency, ease of construction, and improved structural performance. The findings will contribute to enhancing the understanding of welded mesh behaviour in RC structures and aid in the development of optimized and sustainable construction practices for reinforced concrete beams.
Experimental Investigation of Flexural Performance of Sandwiched Engineered Cementitious Composite Concrete Slab and Analysis using ANSYS Software
Authors: S Hima , P. M. Eso Kumary Paul
Published: September 2023

Engineered cementitious composite (ECC) is an ultra-ductile cement based material reinforced with fibers. It is also called as Bendable concrete. ECC has many capabilities due to its superior properties characterized by high ductility, low permeability and high tensile strength. In this paper, the conventional concrete and engineered cementitious composite concrete are prepared of M30 grade incorporated with polypropylene fiber and sandwiched using steel mesh and the results are being compared and studied. The flexural behaviour of a sandwiched engineered cementitious composite (ECC) is studied and compared with that observed in a conventional concrete. Results of the sandwiched ECC concrete slab test indicate that brittle failures as shear failure and bond splitting failure observed in the conventional concrete slab can be prevented by using PP-ECC in place of the concrete. As a result, the sandwiched PP-ECC concrete slab indicate excellent ductile manner.
Enhancing Data Security in Cloud Computing using Block chain
Authors: S Divya , R Gini
Published: September 2023

Block chain (BC) and Software Defined Networking (SDN) are some of the most prominent emerging technologies in recent research. These technologies provide security, integrity, as well as confidentiality in their respective applications. Cloud computing has also been a popular comprehensive technology for several years. Confidential information is often shared with the cloud infrastructure to give customers access to remote resources, such as computation and storage operations. However, cloud computing also presents substantial security threats, issues, and challenges. Therefore, to overcome these difficulties, we propose integrating Block chain and SDN in the cloud computing platform. In this research, we introduce the “DistB-SD Cloud” architecture to better secure clouds. Moreover, we leverage a distributed Block chain approach to convey security, confidentiality, privacy, integrity, adaptability, and scalability in the proposed architecture. BC provides a distributed or decentralized and efficient environment for users. Also, we present an SDN approach to improving the reliability, stability, and load balancing capabilities of the cloud infrastructure. Finally, we provide an experimental evaluation of the performance of our SDN and BCbased implementation using different parameters, also monitoring some attacks in the system and proving its efficacy.
Food Classification Using Deep Learning Method: A Review
Authors: S Vaishnavi , R Sujitha
Published: September 2023

Image classification has become less complicated with deep learning and availability of larger datasets and computational assets. The Convolution neural network is the most popular and extensively used image classification technique in the latest days. Image classification is performed on diverse food dataset using various transfer learning techniques. The food plays a vital role in human’s life as it provides us different nutrients and consequently it is necessary for every individual to maintain a watch on their eating habits. Therefore, food classification is a quintessential thing for a healthier lifestyle. Unlike the traditional methods of building a model from the scratch, pre trained models are used in this project which saves the computation time and cost and also has given better results. The food dataset of many classes with many images in each class is used for training and validating. Using these pre-trained models, the given food will be recognized, and the nutrient content will be predicted based on the colour in the image.
Skin Disease Detection Using Convolutional Neural Network and Support Vector Machine Classification
Authors: S Vignesh Kumar , S. T Sukanya
Published: September 2023

Dermatological issues are one of the most preventable diseases in the world. Diagnosing skin problems early is essential for effective therapy. The method for identifying and treating skin injury is based on the specialist’s level of competence and experience. Skin disease diagnosis has benefited from the application of AI calculations and the utilization of the large quantity of information available in hospitals and clinics. Existing the specialists employed numerous frameworks, instruments, and calculations. A small number of frameworks have been developed that are capable of correctly identifying skin diseases with varying degrees of suggestive precision. In this proposed convolutional neural networks and Support Vector Machine are used this approach is simple, fast and does not require expensive equipment other than a camera and a computer. The process makes use of machine learning technology to train itself with the various skin images. The main objective of this process is to increase the accuracy of skin disease detection and the three important features in image classification are texture, color and shape.
A Study on Cockle Seashell and Silicafume in Concrete
Authors: M. S Arya
Published: September 2023

Efforts are made to incorporate by-products and their wastes from different industries as alternatives in concrete to reduce the need of virgin materials for construction purpose. Cement production is highly intensive and production cause tons of carbon dioxide (CO2) emission every year. To overcome this crisis, pozzolanic material such as silicafume is deployed. Also, the exploitation of nature by over consumption of aggregate is increasing day by day. Fishery waste such as cockle seashell which is usually dumped or landfilled without any re-use value can be used as a partial solution for ecological, economical and environmental problems. Experimental investigations have been carried out on the use of cockle seashell as aggregate replacement materials in concrete. Seashells were utilised as partial coarse aggregates in concrete with different percentages as 10%, 15%, 20% and 25% and silicafume with different percentages as 10%, 12%, 14% and 15% of cement. This study aims to evaluate the strength properties, durability and quality of concrete using Ultrasonic Pulse Velocity (UPV) test of normal and modified mix. Strength properties such as compressive strength, split tensile strength and flexural strength were conducted for normal and modified mix. However, proper treatment such as heating at a high temperature is desirable for a better quality seashell. This presents an overview of behaviour of the cockle seashells and silicafume in concrete. It shows a higher mechanical strength and better durability compared to conventional concrete.
Review on Spray Coating Techniques
Authors: K. R. Harish , M. Edwin Sahayaraj , B. Stanly Jones Retnam
Published: September 2023

A vast array of plating processes, the substances through which different plating can be applied with the natural intention of saving the component, shape and the outer layer that are left unprotected to any kind of physical, chemical and also mechanical adversities. Thus, Spray pyrolysis is very efficient, cost effective, and utilizes simple equipment. Spray pyrolysis is an important technique in which a thin film is deposited on the dielectric matrix by spraying a precursor solution on a heated surface. Spray pyrolysis has been applied to deposit a wide variety of thin films. These films were used in various devices such as solar cells, carbon solar cells, sensors, and solid oxide fuel cells, etc. It is observed that often the properties of deposited thin films depend on the preparation conditions. An extensive investigation of the effects of spray parameters on film quality is given to demonstrate the importance of the process of optimization. However, spray pyrolysis seems not useful due to poor quality of thin film, thermal decomposition, and vapor convection. The vapors are generated due to temperature difference, which restricts the source from binding with the substrate. In this paper, briefly study the spray pyrolysis techniques and using the same for metal coating done over polymers. Also, this study highlighted many research obstacles and presented future direction for research in developing new methodology using the inadequacies of the existing approaches.
Charging Slot Prediction and Automation System for Electric Vehicle Charging Station
Authors: Y. Abi Tirshan , S. Ajaikrishnan , S. Suresh
Published: September 2023

With ever-increasing pollution levels and its impact on the environment, governments are looking for alternate energy options for transportation services. Rapidly depleting global oil reserves and rising oil import bills of governments are also driving the need for alternate energy sources for the transport vehicles. Transportation as a whole is undoing a transformational change worldwide and Electric vehicle are the best solution to address both pollution and oil import bills. Electric vehicles are becoming more and more common these days. With the growing demand for Electric vehicles, the charging infrastructure is critical for sustaining the E-Mobility services. As EVs become more commercial, there will be a need to create an efficient slot booking system as the charging process can be time consuming and the need for more stations will be demanding. Developed the Framework and Architecture of the Next- Generation Communication based Online EV’s Charging Slot Booking at Charging Station. We built the stochastic queuing model for EVs in the charging station. We formulated the objective function of EV’s charging at charging points in charging stations to determine the optimal charging time, minimal charging cost, least distance, minimal queuing delay and optimal duration for particular charging slots. The proposed model of the booking system is designed to create a cost effective and efficient system. Our Cloud based Charging Station Management platform is developed to network and manage multiple charging stations. The proposed server-based real-time forecast charging infrastructure avoids waiting times and its scheduling management efficiently prevents the EV from halting on the road due to battery drain out.
Shear Behaviour of RCC Beams Retrofitted with Ultra High Performance Concrete
Authors: V Abhirami
Published: September 2023

The main contributing factors are change in their use new design standards, deterioration due to corrosion in the steel caused by exposure to an aggressive environment and accident events such as earthquakes. In such circumstances there are only two possible solutions: replacement or retrofitting. Full structure replacement might have determinate disadvantages such as high costs for material and labour, a stronger environmental impact and inconvenience due to interruption of the function of the structure. Whenever possible, it is often better to repair or upgrade the structure by retrofitting or strengthening. In this study, shear behaviour of reinforced concrete beams retrofitted with Ultra High Performance Fibre Reinforced Concrete (UHPFRC) with two types of fibres (crimped and micro steel fibre) and a plain UHPC were compared with control beams. A normal M20 mix was designed for the study. Two point loading system was adopted for the test. And deflection were noted for each load increment. Behaviour of retrofitted beams and control beams were studied by comparing the properties such as first crack load, ultimate load and load deflection plot. The result showed that shear performance was improved by 88% for UHPFRC-C, 78% for UHPFRC-M and 36% for UHPC, showing the effect of fibres which improved the shear performance of UHPFRC retrofitted beams.
Development of Emotion Detector Using Biometric
Authors: S. V. Shabin , J Reena Benjamin , D. B Juliet Rose
Published: September 2023

Emotions play a vital role in people’s everyday life. It is a mental state that does not arise through free will and is often accompanied by physiological changes. Therefore monitoring these changes is important as they are perceptions of emotional changes and can help in identifying matters of concern at an early stage before they become serious. Emotion recognition has become an important subject when it comes to human-machine interaction. Various methods have been used in the past to detect and evaluate human emotions. The most commonly used techniques include the use of textual information, facial expressions, speech, body gestures and physiological signals. In this project we have developed an emotion recognition system based on information provided by the physiological signals. These signals are obtained from a skin temperature sensor, a heart rate sensor, and a blood pressure sensor. The amplified and filtered signals from the sensors are input into the microcontroller where all the processing takes place. The microcontroller wirelessly transmits data to a computer where it is stored for data analyses and feature extraction for emotion recognition. The three basic emotions observed in this project are happy (excited), stressed and neutral (relaxed).
Noise Adaptive Fuzzy Switching Median Filters for Removing Gaussian Noise
Authors: M Jeba Jenitha , D Kani Jesintha , P Mahalakshmi
Published: September 2023

Recently, in all image processing systems, image restoration plays a major role and it forms the major part of image processing systems. Medical images such as brain Magnetic Resonance Imaging (MRI), ultrasound images of liver and kidney, retinal images and images of uterus images are often affected by various types of noises such as Gaussian noise and salt and pepper noise. All image restoration techniques attempts to remove various types of noises. This paper deals with various filters namely Mean Filter, Averaging Filter, Median Filter, Adaptive Median Filter, Adaptive Weighted Median Filter, Gabor Filter and Noise Adaptive Fuzzy Switching Median Filter (NAFSM) for removing salt and pepper noise. Among all the filters, NAFSM removes the Gaussian noise better than the other filters and the performance of all the filters are compared using metrics such as PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error), NAE (Normalized Absolute Error), Normalized Cross Correlation (NK), Average Difference (AD), Maximum Difference (MD), SC (Structural Content) and time elapsed to produce the denoised image.
Flextural Behaviour of Ferro Cement Slab by Using GGBS and Nano Silica by Using ANSYS Software
Authors: N. R Aarthi , P. M Eso Kumary Paul
Published: September 2023

The use non – corrodible reinforcements in Ferro cement slabs may prevent its failure corrosion of welded mesh. Ferro cement slab of 700 x 150 x 20 mm & 700 x 150 x 30mm. The ratio of cement and fine aggregate is 1: 2 with the addition of geo polymer such as GGBS and Fly ash. The GGBS are added as 20%, 40%, 60%, 80% by weight of cement directly into the mortar while mixing. GGBS Fly ash, Fine aggregate, water, Nano Silica is the material used for this investigation. The grade of cement is OPC 53 and grade of Fly ash is class F. The material testing of fine aggregate, fly ash, GGBS were conducted and observed result within the limits. Also, the literature survey was done related to the experimental work with GGBS, Fly ash. The tests are conducted to determine various properties of Ferro cement such as corrosion, failure pattern, tension and punching load. It is eco – friendly and cost – effective. Geo polymer mortar achieved considerable strength with the addition of GGBS with fly ash based geo polymer Slab by using ansys Software.
A Study on Increase in Productivity of Foams Bed Products in Foams India Bed Product, Chennai
Authors: S. M Sarjin Lal , A. Robert Raja Singh , S. R Haritha
Published: September 2023

The title of the project report is A Study On increase in productivity of foams bed products. The project work has been carried out at foams India bed product, thirumazhisai Chennai for the potential fulfillment of the MBA program under Anna University, Chennai. The objective of the study is to assess about the Increase in productivity, in Foams India bed product, To Standard Costing market demand by considering last 6 months demand and supply for in Foams India bed product, to analyze the variance analysis. Associated with the production, to analyse the current productivity of bed products in Foams India bed product, to determine the measure of System effectiveness in Foams India bed product. The research design used in this study is Analytical research design. The primary data was collected as conversation with the core team members as well as operational line manager. Secondary data was collected through flow diagrams, company profile. The collected data has been edited, classified and tabulated. The statistical tool used in the study is Standard costing, Variance Analysis.
Dense Net Model Based Traffic Sign Board Recognition and Voice Alert System
Authors: P Anuja , S. B Anuja
Published: September 2023

To ensure a smooth and secure flow of traffic, road signs are essential. A major cause of road accidents is negligence in viewing the Traffic signboards and interpreting them incorrectly. The proposed system helps in recognizing the Traffic sign and sending a voice alert through the speaker to the driver so that he/ she may take necessary decisions. The proposed system is trained using Convolutional Neural Network (CNN) which helps in traffic sign image recognition and classification. A set of classes are defined and trained on a particular dataset to make it more accurate. The German Traffic Sign Benchmarks Dataset was used, which contains approximately 43 categories and 51,900 images of traffic signs. The accuracy of the execution is about 98.52 percent. Following the detection of the sign by the system, a voice alert is sent through the speaker which notifies the driver. The proposed system also contains a section where the vehicle driver is alerted about the traffic signs in the near proximity which helps them to be aware of what rules to follow on the route. The aim of this system is to ensure the safety of the vehicle’s driver, passengers, and pedestrians.
Strength Characteristics of Concrete by Partially Replacing Cement with Silica Fumes and Tile Dust
Authors: S. K. Vidhya
Published: September 2023

The concrete is a cement-based material which has become most popular and widely used in construction field such as highways, flyovers, buildings, dams etc. Now a days the consumption of concrete increased exponentially and structure without concrete cannot be imagined. Durability of concrete mainly depends upon the climatic condition which may likely to damage the concrete structures. To enhance the life against such problems it is necessary to improve the mechanical properties of the concrete. The use of pozzolanic in concrete and mortar was started with a view to reduce the cost, overcome the adverse effects of OPC and utilize waste products and by products of industrial activities which were providing harmful to environment, natural resources etc. Also, the use of pozzolanas improves several properties of mortar and concrete viz. workability, strength, resistance to cracks permeability and durability. Further the use of pozzolanas has resulted in the production of high- performance concrete. Owing to globalization, privatization and liberalization, the construction of important infrastructure projects are increasing in developing countries like India. Such development activities require large quantities of natural resources. This leads to faster depletion of natural resources on one side and manifold increase in cost of construction of structures on the other side, which is a major problem in construction sector today. In view of this people have started searching for suitable alternate materials which can be used either as an additive or as a partial replacement to conventional ingredients of concrete. Use of tile dust as partial replacement for cement in concrete is one such economical method. In the laboratory tests were conducted by partially replacing cement in concrete by tile dust as 0%, 10%, 20%, 30%, 40% & 50%. The development of compressive strength, split tensile strength and flexural strength of concrete at the age of 7, 28, 56 days are investigated. These strengths are compared with conventional concrete of the same mix proportions.
Photochain: A Blockchain Based Secure Photo Sharing Framework for Cross-Social Network
Authors: W Wilfred Wessely , R Sujitha
Published: September 2023

Social Networks is one of the major technological phenomena on the Web 2.0. The evolution of social media has led to a trend of posting daily photos on online Social Network Platforms (SNPs). The privacy of online photos is often protected carefully by security mechanisms. However, these mechanisms will lose effectiveness when someone spreads the photos to other platforms. Photo Chain, a blockchain-based secure photo sharing framework that provides powerful dissemination control for cross-SNP photo sharing. In contrast to security mechanisms running separately in centralized servers that do not trust each other, our framework achieves consistent consensus on photo dissemination control through carefully designed smart contract-based protocols. These protocols to create platform-free dissemination trees for every image, providing users with complete sharing control and privacy protection. Considering the possible privacy conflicts between owners and subsequent re-posters in cross-SNP sharing, it design a dynamic privacy policy generation algorithm that maximizes the flexibility of re-posters without violating formers’ privacy. Moreover, Go-sharing also provides robust photo ownership identification mechanisms to avoid illegal reprinting. It introduces a random noise black box in a two-stage separable deep learning process to improve robustness against unpredictable manipulations. Through extensive real-world simulations, the results demonstrate the capability and effectiveness of the framework across a number of performance metrics.
A Supervised Framework for COVID-19 Classification Using FCNN
Authors: K. Abinaya
Published: September 2023

One or both of the lungs are affected by pneumonia, which is the enlargement of the lung tissue. Infection with organisms including bacteria, viruses, and fungi leads to its occurrence. Although its severity varies, its typical symptoms include coughing, breathing problems, fever, and chest pain. The respiratory illness COVID-19 is spreadable and is brought on by the SARS- CoV-2 virus. COVID-19 has similar symptoms to viral pneumonia and the patients of COVID-19 may also be subject to secondary bacterial infections. This study separates COVID-19 from other illnesses like mycoplasma, bacterial pneumonia, viral pneumonia, and other infections using a variety of deep learning techniques and computed tomography (CT) images. The results show that for all three cases, FCNN is one of the best performing architectures.