Effective View of Swimming Pool Using Autodesk 3ds Max: 3D Modelling and Rendering
3D modelling; Autodesk; Rendering; UVW map
As well as setting up the sources, working with editable poly, information in the interior of the swimming pool, using turbo-smooth and symmetry modifier, this procedure of making a 3D swimming pool model is clarified. The lighting the scene and setting up the rendering, the method in which substances are added to the replica is defined. The methods and techniques of rendering are defined, too. The final rendering is the result of multiple images being drawn. The aim of our research work is to create a swimming pool design with enhancing models with materials affect. The shapes used for that are cylinder, sphere, box, plane and splines. The modifiers are editable poly, editable spline and UVW map. Finally, we used a material editor and target lights for enhancing the model. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Lecture Notes in Electrical Engineering, Vol-825, pp. 47-53.
Springer Science and Business Media Deutschland GmbH
Kumar G., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Samanta D., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India
Grading of Red Chilli, Cardamom and Coriander Using Image Processing
Cardamom; Chilli; Coriander; Discrete cosine transform; Fast Fourier transform; Image processing; Multilayer perceptron; Nae Bayes; Random forest
Indian cuisine is known for its wide range of spices. Spices are known as the heart and soul of Indian food. Traditionally, categories are identified based on certain chemical technology or with the help of senses gifted to mankind. In this paper, an image processing technique used to extract multiple features is presented to determine the various categories of spices consumed. This proposed work uses different varieties of common Indian spices such as Capsicum annuum (dry red chilli), Elettaria cardamomum (cardamom) and Coriandrum Sativum (coriander). While creating the image dataset, different categories of all spices were taken from southern region of India. Features are extracted from the manually created image dataset, which forms the base for classification. The result obtained using Multilayer Perceptron (MLP), Naive Bayes and Random Forest classifier is found to be optimal. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Lecture Notes in Networks and Systems, Vol-356, pp. 425-433.
Renupriya P., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Anita H.B., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Sunil S.R., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bengaluru, India
A Comparative Study of Collaborative Movie Recommendation System
Clustering; Collaborative Filtering; Content-based Filtering; Machine Learning; Movie Recommendation; User ratings
The number of movies available has expanded, making it challenging to select a film that uses current technology to meet users' needs. Following the widespread use of internet services, recommendation systems have become commonplace. The objective for all recommendation systems now is to employ filtering and clustering algorithms to recommend content users are interested in. Suggestions for a media commodity like movies are offered to consumers by locating user profiles of people with comparable likes which makes users' preferences initially determined to allow them to rate movies of their choosing. After a period of use, the recommender system understands the user and offers films that are more likely to receive higher ratings. A comparison study on the existing models helps to understand future scope and improvements for more personalized models for movie recommendation. In comparison to previous models, the MovieLens dataset gives a dependable model that is exact and delivers more customized movie suggestions. In this paper, an approach to do a detailed study and review the user preferences based on item and content of movies has been made to understand the filtering techniques of the collaborative recommendation system to increase accuracy and give highly rated movies as recommendations to the user is carried and based on the results the recommendation system is built with a content-based filtering technique. 2022 IEEE.
Proceedings of the International Conference on Electronics and Renewable Systems, ICEARS 2022, pp. 1579-1583.
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICEARS53579.2022.9752015 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128953748&doi=10.1109%2fICEARS53579.2022.9752015&partnerID=40&md5=afcfc95e9093b587e9cff824c75e3b31
Joseph A.A., Christ (Deemed to Be University), Department of Data Science, India; Nair A.M., Christ (Deemed to Be University), Department of Data Science, India
A Review on Synchronization and Localization of Devices in WSN
Energy consumption; Localization; Military applications; Radio communications; Synchronization; Wireless sensor networks
Wireless sensor networks are communication networks that deal with sensor devices that are wirelessly interconnected in order to collect and forward data between different environments. Network scaling of small sensor devices with all its limitations has a foolproof scope for future applications. The advantage of minimal infrastructural cost and applicability within challenging environments make it an attractive choice. Statistics have been shown to prove the demand for research for synchronization and localization as a research problem. WSNs are capable of dynamically building virtual infrastructure and getting synchronized with the rhythm of communication setup. Limitations in the amount of energy that can be utilized make it a necessity for the networks to be more optimal in terms of energy consumption. These challenges necessitate the need to study and analyze the recent advancements implemented in approaching synchronization and localization problems. This paper reviews recent research proposals and methodologies to identify related attributes and their relation to the system. A detailed comparative study is conducted to identify relevant patterns that influence the performance of the networks in terms of energy consumption. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Varun Somanna M.N.; Sandeep J.; Thomas L.
Lecture Notes in Electrical Engineering, Vol-840, pp. 585-602.
Varun Somanna M.N., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Sandeep J., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Thomas L., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India
Cloud Computing Application: Research Challenges and Opportunity
Cloud Computing; Cloud Security; Cloud Service Provider; Data Security; E-Learning; Government Sector
In a world with intensive computational services and require optimal solutions, cloud security is a critical concern. As a known fact, the cloud is a diverse field in which data is crucial, and as a result, it invites the dark world to enter and create a virtual menace to businesses, governments, and technology that is facilitated by the cloud. This article addresses the fundamentals of cloud computing, as well as security and threats in various applications. This research study will explore how security is remaining as a potential risk for cloud users across the globe by listing some of the cloud applications. Some viable solutions and security measures that could help us in analyzing cloud security threats are reviewed. The analyzed solutions include profound analytical thinking on how to render the solutions more impactful in each scenario. Several cloud security solutions are available to assist businesses in reducing costs and enhancing security. This study discover that if the risks are taken into consideration without any delay then the matter of solutions gets divided into four pillars, which will assist us in obtaining a more comprehensive knowledge. Visibility, compute-based security, network protection, and lastly identity security are referred as four pillars. 2022 IEEE.
Karmakar A.; Raghuthaman A.; Kote O.S.; Jayapandian N.
International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2022 - Proceedings, pp. 1284-1289.
https://doi.org/10.1109/ICSCDS53736.2022.9760887 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130098116&doi=10.1109%2fICSCDS53736.2022.9760887&partnerID=40&md5=d2017e2d7460df675ab7588e8c3fcb86
Karmakar A., Christ University, Department of Cse, Bangalore, India; Raghuthaman A., Christ University, Department of Cse, Bangalore, India; Kote O.S., Christ University, Department of Cse, Bangalore, India; Jayapandian N., Christ University, Department of Cse, Bangalore, India
Role of Blockchain in the Healthcare Sector: Challenges, Opportunities and Its Uses in Covid-19 Pandemic
Blockchain; Covid-19; Healthcare; Hospital; Medical; Pandemic; Security; Technology
As the world grapples with the Covid-19 pandemic and major populations are getting vaccinated, increasing realisation processes healthcare industry needs to be augmented. It includes managing supply chains, healthcare records, and patient care. With a scarcity of time and resources, adaptation of blockchain technology will help mitigate the pressures on existing infrastructure. A blockchain distributed ledger helps to exchange health information securely without complex intermediation of trust with secure access. The organisations and persons in the blockchain network can verify and authorise the data, thus protecting patient identity, privacy, medical information system, and reducing transaction costs. The paper examines managing and protecting electronic medical records and personal health records data using blockchain. It also analyses issues in healthcare, blockchain implementation, and its uses in the Covid-19 pandemic. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Lecture Notes in Networks and Systems, Vol-420 LNNS, pp. 657-666.
Arumugam S.K., Department of Professional Studies, Christ University, Bangalore, India; Sharma A.M., Department of Professional Studies, Christ University, Bangalore, India
Dynamic job sequencing of converging-diverging conveyor system for manufacturing optimization
Converging conveyor system; Diverging conveyor system; Production optimization & dynamic sequencing
Some sectors, such as dairy, automobile, pharmaceutical, computer and electronics, require a range of manufacturing steps to produce a component. The goods in these industries are produced in varieties and the output volume varies from low to high. Typically, these types of businesses use a conveyor system that could have a combination of a diverging and converging conveyor system due to a variety of processing phases involved in the development of the commodity. A conceptual model of the of conveyor system is described, which works manually and to illustrate the importance of the sequence using buffer the buffer layout is modeled and compared to the manual layout. The genetic algorithm is used to find the optimal buffer storage. It can be observed that by adapting various sequencing methods there will be reduction in manufacturing time and setup cost. 2022 Elsevier Ltd. All rights reserved.
Sharath Chandra H.S.; Hebbale A.; Hemanth T.S.; Naveen J.; Niranjana S.J.
Materials Today: Proceedings, Vol-52, pp. 1901-1908.
https://doi.org/10.1016/j.matpr.2021.11.523 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127403560&doi=10.1016%2fj.matpr.2021.11.523&partnerID=40&md5=bab398f8d1f23989965cbd92760dcb6a
Sharath Chandra H.S., Department of Mechanical Engineering, NMAM Institute of Technology, Nitte, 574110, India; Hebbale A., Department of Mechanical Engineering, NMAM Institute of Technology, Nitte, 574110, India; Hemanth T.S., Industrial and Production Engineering Department, Malnad College of Engineering, Hassan, 573201, India; Naveen J., Electrical and Electronics Engineering, NMAM Institute of Technology, Nitte, 574110, India; Niranjana S.J., Department of Mechanical and Automobile Engineering, CHRIST University, Bangalore, 560029, India
Improved Computer Vision-based Framework for Electronic Toll Collection
Automatic Toll Ticketing; License Plate Recognition; Siamese Network Architecture; Toll Plaza; Vehicle Fingerprinting; Vehicle Re-identification
The world is moving towards artificial intelligence and automation because time is the most crucial asset in today's scenario. This paper proposes an automatic vehicle fingerprinting system that avoids long waiting times in toll plazas with the help of computer vision. The number plate recognition and vehicle re-identification focus on this research. Day/night IR cameras are used to get the images of the vehicle and its number plate. The VeRi776 datum, which contains real-world vehicle images, is used to facilitate the research of vehicle re-identification. The proposed framework employs Siamese model architecture to identify the attributes such as color, model, and type of vehicle. The Car License Plate Detection datum is used to evaluate the efficiency of the proposed license plate recognition system. An ensemble of image localization techniques using CNNs and application of the OCR model on the localized snapshot is used to recognize the vehicle's license plate. A combination of license plate recognition and vehicle re-identification techniques is used in the proposed framework to improve the efficiency of identifying vehicles in toll plazas 2022 IEEE.
Mathews M.S.; Prabu M.; Pitchai A.; Roberts D.B.; Rahul G.
Proceedings of the Confluence 2022 - 12th International Conference on Cloud Computing, Data Science and Engineering, pp. 213-216.
https://doi.org/10.1109/Confluence52989.2022.9734219 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127600404&doi=10.1109%2fConfluence52989.2022.9734219&partnerID=40&md5=b73a76452c80a09509718a851ddfe9f2
Mathews M.S., CHRIST(Deemed To Be University), Department Of Computer Science, Bangalore, 560029, India; Prabu M., CHRIST(Deemed To Be University), Department Of Computer Science, Bangalore, 560029, India; Pitchai A., CHRIST(Deemed To Be University), Department Of Computer Science, Bangalore, 560029, India; Roberts D.B., CHRIST(Deemed To Be University), Department Of Computer Science, Bangalore, 560029, India; Rahul G., CHRIST(Deemed To Be University), Department Of Computer Science, Bangalore, 560029, India
Factors Affecting Data-Privacy Protection and Promotion of Safe Digital Usage
Anxiety; Data breach; Data-security; Online Apps
India is facing the problem of the digital divide. Being developing countries and with low literacy rates, digital knowledge among the public is weak. Those who know a bit about digital operations on smartphones and computers are not having complete knowledge of data security and its peculiarities. Therefore, this study aimed to find determinants of data-privacy anxiety among Indians and to understand their stress and anxiety during the use of digital applications in their daily routines, especially amid the COVID-19 scenario. The current study adopted an inductive qualitative exploratory approach to delve into the above issues. This study employed a reflexive thematic analysis method to analyse interview data of 10 participants across young-adult to middle-adult age groups of male and female gender. Participants belonged to middle socio-economic status having urban background. The study found 6 themes and 26 subordinate themes as determinants of data-privacy anxiety. Emerging themes from the data indicated at the systemic determinants of data-security anxiety, the paradox of learned helplessness and convenience preference among participants. This paper employed the Foucauldian lens of bio-power to discuss the circumscribing function of ill-structured knowledge dissemination approaches. This paper argues in favor of a critical pedagogy approach in educating people about digital security, dealing with data-privacy anxiety, and promoting safe digital usage among all generations of Indians. It also suggests measures of modifications in policies and documentation processes of major online platforms and apps to curb uncertainty and sense of insecurity among users. 2022 Copyright for this paper by its authors.
Chakraborty R.; Prakasha G.S.; Sripavithra C.K.
CEUR Workshop Proceedings, Vol-3094, pp. 49-58.
Chakraborty R., Christ University, Central Campus, Bangalore, 560029, India; Prakasha G.S., Christ University, Central Campus, Bangalore, 560029, India; Sripavithra C.K., Christ University, Central Campus, Bangalore, 560029, India, Maharanis Science College for Women, Mysore, 570005, India
Fake News Detection: An Effective Content-Based Approach Using Machine Learning Techniques
Fake News; Machine Learning; Natural Language Processing; Passive-Aggressive Classifier; Support Vector Classifier; Voting Classifier
Fake news is any information fabricated to mislead readers to spread an idea for certain gains (usually political or financial). In today's world, accessing and sharing information is very fast and almost free. Internet users are growing significantly than ever before. Therefore, online platforms are perfect grounds to spread information to a broader section of society. What could circulate between a relative few can now circulate globally overnight. This advantage also marked the increase in the number of fake news attacks by its users, which is unsuitable for a healthy society. Therefore, there is a need for good algorithms to identify and take down fake information as soon as they appear. This paper aims at solving the problem by automating the process of identifying fake news using its content. Evaluation metrics like the accuracy of correct classification, precision, recall and f1-score assess the performance of the approach. The machine learning approach achieved its best performance with 96.7 percentage accuracy, 96.2 percentage precision, 97.5 percentage recall and 96.9 percentage f1 score on the ISOT dataset. 2022 IEEE.
2022 International Conference on Computer Communication and Informatics, ICCCI 2022
Mathews E.Z., Christ University, Data Science Department, Pune, India; Preethi N., Christ University, Data Science Department, Pune, India
An Efficient Fuzzy Logic Cluster Formation Protocol for Data Aggregation and Data Reporting in Cluster-Based Mobile Crowdsourcing
Cluster cranium; Data aggregation; Data reporting; Mobile crowdsourcing; Query optimization; Security
Crowdsourcing is a procedure of outsourcing the data to an abundant range of individual workers rather than considering an exclusive entity or a company. It has made various types of chances for some difficult issues by utilizing human knowledge. To acquire a worldwide optimal task assignment scheme, the platform usually needs to collect location information of all workers. During this procedure, there is a major security concern; i.e., the platform may not be trustworthy, and so, it brings about a threat to workers location privacy. Recently, many distinguished research papers are published to address the security and privacy issues in mobile crowdsourcing. According to our knowledge, the security issues that occur in terms of data reporting were not addressed. Secure and efficient data aggregation and data reporting are the critical issue in Mobile Crowdsourcing (MCS). Cluster-based mobile crowdsourcing (CMCS) is the efficient way for data aggregation and data reporting. In this paper, we propose a novel procedure, the efficient fuzzy logic cluster formation protocol (EFLCFP) for cluster formation, and use cluster cranium (CC) for data aggregation and data reporting. We recommend a couple of secure and efficient data transmission (SET) protocols for CMCS, (i) SET-IBE uses additively homomorphic identity-based encryption system and (ii) SET-IBOOS uses the identity-based online/offline digital signature system, respectively. Then, we have widen the features of cluster cranium by increasing the propensity to achieve aggregation and reporting on the data yielded by the requesters without scarifying their privacy. Also, considering query optimization using cost and latency. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Renukadevi M.; Mary Anita E.A.; Mohana Geetha D.
Lecture Notes in Networks and Systems, Vol-351, pp. 427-446.
Renukadevi M., Department of CSE, S.A. Engineering College, Chennai, India; Mary Anita E.A., Department of CSE, School of Engineering and Technology, CHIRST University, Bengaluru, India; Mohana Geetha D., Department of CSE, Sri Krishna College of Engineering and Technology, Coimbatore, India
Influence of nano ?-Al2O3 as sintering aid on the microstructure of spray dried and sintered ?-Al2O3 ceramics
Liquid phase sintering; Micron alumina; Microstructure; Nano alumina; Sintering aid
Alpha Alumina (?-Al2O3) has traditionally been sintered to near theoretical density by employing variations in raw material properties, particle sizes, grinding methods, compaction pressures, sintering aids or minor quantities of additives and sintering temperatures. All these parameters directly influence the grain growth morphology and microstructure of the sintered alumina ceramic characteristics. Growth of large grained microstructure facilitated by fine grinding of raw material and coalescence of the grains enhanced by dopant additions are well researched. The maximum sintered density and strength of the fired body could be attained through large grained microstructure which include near spheroidal grains. Most of the final sintering is accomplished via additions of suitable aids which also may be promoted by liquid-phase sintering which is considered highly advantageous compared to solid-state sintering for products in many defense applications. In this paper the influence of nano ?-Al2O3 (<100 nm particle size) as sintering aid to obtain the desired microstructure in sintered micron sized (1 to 5 m) ?-Al2O3 is being reported. 1.0 and 1.5 wt% nano ?- Al2O3 powder were spray dried with 99.0 and 98.5% ?-Al2O3 powder respectively, with polyvinyl alcohol binder, compacted into 10 mm dia and 5 mm thick pellets and sintered at 1450 C with 3 h soak time. In addition to the two different sintering aid additive percentages, other variables included are spray dried powders removed from (i) chamber and (ii) cyclone. The sintered ceramics were characterized for bulk density and fracture surface microstructure via SEM analysis. Nano alumina as sintering aid exhibited significant influence that included generation of microstructure with porosity, precipitation or liquid phase sintering. The study was limited to establishing the definitive role played by nano alumina to influence the sintering of micron alumina. 2022
Ramaswamy P.; Gowtham Sanjai S.; Ramawarrier R.
Materials Today: Proceedings, Vol-62, pp. 902-907.
https://doi.org/10.1016/j.matpr.2022.04.063 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129000224&doi=10.1016%2fj.matpr.2022.04.063&partnerID=40&md5=6edde41a3d889d3408318544ce7ed2b2
Ramaswamy P., Department of Mechanical and Automobile Engineering, School of Engineering and Technology, Kengeri Campus, Christ University, Kanminike, Bangalore, India; Gowtham Sanjai S., Department of Mechanical and Automobile Engineering, School of Engineering and Technology, Kengeri Campus, Christ University, Kanminike, Bangalore, India; Ramawarrier R., Department of Mechanical and Automobile Engineering, School of Engineering and Technology, Kengeri Campus, Christ University, Kanminike, Bangalore, India
The Future Warfare with Multidomain Applications of Artificial Intelligence: Research Perspective
Artificial ?ntelligence; Artificial neural networks; Cyber security; Machine learning; Navy application; Robots; Unmanned air vehicle
We live in a period when historical fiction has become current reality. With our future being automated, using AI on a daily basis will only get more convenient. Making military weapons to detect, monitor, and engage a human being with attacks may all be done in the privacy of one's own garden. There is a plethora of AI software out there that can be readily integrated into combat weapons. The automobile industry is already incorporating AI into vehicles to assess driving circumstances and give augmented reality to drivers via heads-up displays in order to assist avert accidents. Similarly, artificial intelligence will be utilized to study the battlefield and give soldiers with augmented reality information via heads-up displays and weapon control systems. Since AI is not a single technology, it has been argued that it might be used by the military in a variety of ways. Intelligence, surveillance, and reconnaissance (ISR) activities, as well as processing and interpreting sensor data and geographic imaging analysis, are all examples of AI. Artificial intelligence has the potential to reduce human involvement in conflict, whether it is employed for combat robots or data analysis. AI has the potential to profoundly alter the nature of war. The article mainly focussed on warfare technologies and applications. The main aim of this review is to understand the current applications being used in armed forces and proposed technologies of artificial intelligence. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Nikitha M.A.; Sai Swetha B.S.; Mantripragada K.H.; Jayapandian N.
Lecture Notes in Networks and Systems, Vol-351, pp. 329-341.
Nikitha M.A., Department of Computer Science and Engineering, CHRIST (Deemed To Be University), Kengeri Campus, Bangalore, India; Sai Swetha B.S., Department of Computer Science and Engineering, CHRIST (Deemed To Be University), Kengeri Campus, Bangalore, India; Mantripragada K.H., Department of Computer Science and Engineering, CHRIST (Deemed To Be University), Kengeri Campus, Bangalore, India; Jayapandian N., Department of Computer Science and Engineering, CHRIST (Deemed To Be University), Kengeri Campus, Bangalore, India
Sulfamic acid catalyzed grinding: A facile one-pot approach for the synthesis of polysubstituted pyrazoles under green conditions
Four-component; One-pot; Pyrazole; Solvent-free; Sulfamic acid
A competent, rapid and simple grinding procedure for the synthesis of pharmacologically relevant polysubstituted pyrazoles catalyzed by sulfamic acid is reported via multicomponent reaction of substituted arylaldehydes, 4-nitrophenylacetonitrile, hydrazine hydrate, ethyl acetoacetate under solvent-free reaction conditions. In our reported protocol, four different reactants featuring diverse functional groups are assembled in one pot, enabling the synthesis of more diverse molecular structures in a facile manner. 2022
Govindaraju S.; Daniel N.K.; Tabassum S.
Materials Today: Proceedings, Vol-62, pp. 5336-5340.
https://doi.org/10.1016/j.matpr.2022.03.416 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128337920&doi=10.1016%2fj.matpr.2022.03.416&partnerID=40&md5=48c1e7c470c7568adfb3ea3972c473ce
Govindaraju S., Department of Sciences and Humanities, School of Engineering and Technology, CHRIST (Deemed to be University), Kumbalagodu, Mysore Road, Bengaluru, 560074, India; Daniel N.K., Department of Sciences and Humanities, School of Engineering and Technology, CHRIST (Deemed to be University), Kumbalagodu, Mysore Road, Bengaluru, 560074, India; Tabassum S., Department of Chemistry, Surana College, South End Road, Basavanagudi, Bengaluru, 560004, India
A Survey on Arrhythmia Disease Detection Using Deep Learning Methods
Artificial neural network; Decision tree; Heart disease; K nearest neighbor; Multilayer perceptron; Support vector machine
The Cardiovascular conditions are now one of the foremost common impacts on human health. Report from WHO, says that in India 45% of deaths are caused due to heart diseases. So, heart disease detection has more importance. Manual auscultation was used to diagnose cardiovascular problems just a few years ago. Nowadays computer-assisted technologies are used to identify diseases. Accurate detection of the disease can make recovery simpler, more effective, and less expensive. In this proposed work, 11years of research works on arrhythmia detection using deep learning are integrated. Moreover, here presents a comprehensive evaluation of recent deep learning-based approaches for detecting heart disease. There are a number of review papers accessible that focus on traditional methods for detecting cardiac disease. This article addresses some essential approaches for categorizing ECG signal images into desired classes, such as pre-processing, feature extraction, feature selection, and classification. However, the reviewed literatures consolidated details have been summarized. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Lecture Notes in Networks and Systems, Vol-419 LNNS, pp. 55-64.
Lufiya G.C., Department of Computer Science, CHRIST (Deemed To Be) University, Bangalore, India; Thomas J., Department of Computer Science, CHRIST (Deemed To Be) University, Bangalore, India; Aswathy S.U., Department of Computer Science, JYOTHI Engineering College Cheruthuruthy, Thrissur, India
Utilization of industrial and agricultural waste materials for the development of geopolymer concrete- A review
Corncob ash; Fly ash; Ground granulated blast furnace slag; Metakaolin; Red mud; Rice husk ash; Silica fume; Sugarcane bagasse ash
Concrete is a highly consumed construction material. Cement is the first and foremost ingredient in the manufacture of concrete. Manufacturing of cement results in emission of an equal amount of carbon dioxide. These greenhouse gases cause global warming. The utilization of environment-friendly construction materials has been identified to be most essential to overcome environmental issues. An ecofriendly concrete such as geopolymer concrete founds to be an alternative for cement concrete. Geopolymer concrete (GPC) is a sustainable construction material as it can reduce carbon dioxide emission by utilizing industrial and agricultural waste by-products. Hence in this context, to reduce global warming, usage of cement can be minimized by replacing it with other materials such as Fly ash, Silica fume, Red mud, Ground granulated blast furnace slag, Metakaolin, Rice husk ash, Corncob ash, Sugarcane bagasse ash etc. These materials have been utilized to prepare geopolymer concrete with good mechanical strength, durability and thermal resistivity. A lot of research has gone into the development of sustainable geopolymer concrete utilizing various industrial and agricultural waste. This review paper is on the research on the utilization of industrial and agricultural waste materials to produce sustainable geopolymer concrete. 2022
Materials Today: Proceedings, Vol-65, pp. 1290-1297.
https://doi.org/10.1016/j.matpr.2022.04.192 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129115259&doi=10.1016%2fj.matpr.2022.04.192&partnerID=40&md5=7d68e398fa23063bc35a1baaa72140f5
H.M. T., Research Scholar, Department of Civil Engineering, CHRIST (Deemed to be University), Bangalore, India; Unnikrishnan S., Associate Professor, Department of Civil Engineering, CHRIST (Deemed to be University), Bangalore, India
Pre and Post Operative Brain Tumor Segmentation and Classification for Prolonged Survival
BRATS; CNN; Dense net; EPISURG; Fig-Share; ResNET; TCIA; VGG
The aim of this research was to provide a detailed overview of the techniques in detecting and segmenting meningioma brain tumor in pre- and post-operative MRI images and classify for presence of meningioma thereby giving an early diagnosis to decrease the death rate. This study examines trending techniques for brain tumour segmentation and classification in Magnetic Resonance (MR) images of pre and post-surgery. For the segmentation and anomalies in the brain categorization, several approaches such as regular machine learning techniques (K-mean bunching, Fuzzy C mean grouping etc.), Deep Learning-based approaches (CNN, ResNET, Dense Net, VGG etc.), classical algorithms (Snake contour, watershed method etc.), and hybridization approaches were applied, according to the analysis. Information base, for example, BRATS, Fig-Share, EPISURG or TCIA can be taken to gather clinical pictures which principally contains of 2 classifications, pre and post pictures of Brain tumor. The multiple processes of brain tumour segmentation methodologies, such as preprocessing, feature extraction, segmentation, and classification, are also explained in this work. The task of segmenting residual and recurrent tumors differs greatly from that of segmenting tumors on baseline scans before surgery. This study shows that each approach has its own set of pros and limitations, as well as notable findings in terms of precision, sensitivity, and specificity, according to the comparison research. The use of segmentation approaches to determine success and reliability has been discovered. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Lecture Notes in Networks and Systems, Vol-417 LNNS, pp. 608-616.
Xavier P.S., Department of Computer Science, CHRIST (Deemed to be) University, Bangalore, India; Raju G., Department of Computer Science, CHRIST (Deemed to be) University, Bangalore, India; Asawthy S.U., Department of Computer Science, JYOTHI Engineering College Cheruthuruthy, Cheruthuruthy, India
A Novel Approach for Implementing Conventional LBIST by High Execution Microprocessors
conventional LBIS T; high execution microprocessor; power consumption and binning
The major VLS I circuits like sequential circuits, linear chips and op amps are very important elements to provide many logic functions. Today's competitive devices like cell phone, tabs and note pads are most prominent and those are used to get function the 5G related operations. In this work lower built-in self-test (LBIS T) mechanism is used to designing a microprocessor. The proposed methodology is giving performance measure like power efficiency 97.5%, improvement of delay is 2.5% and 32% development of area had been attained. This methodology attains more out performance and compete with present technology. The proposed equipment and execution for our approach requiring a constrained range overhead (lower than 3% power) over conventional LBIS T. 2022 IEEE
Shravani C.; Bollam H.L.; Krishna G.R.; Vatambeti R.; Saikumar K.
Proceedings - 4th International Conference on Smart Systems and Inventive Technology, ICSSIT 2022, pp. 804-809.
https://doi.org/10.1109/ICSSIT53264.2022.9716411 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127367540&doi=10.1109%2fICSSIT53264.2022.9716411&partnerID=40&md5=d9aae90c454ff76a9e8a570f3b872d2c
Shravani C., Department of ECE, Vignan's Institute of Information Technology (A), Duvvada, Andhra Pradesh, India; Bollam H.L., Dept. of ECE, Nalla Malla Reddy Engineering College, Divyanagar, Narapally, India; Krishna G.R., CSE Department, Koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Andhra Pradesh, 522502, India; Vatambeti R., Dept. of CSE, CHRIST (Deemed to be University), Bangalore, India; Saikumar K., Dept. of CSE, Malla Reddy University, MRUH, Hyderabad, India
Clinical Text Classification of Medical Transcriptions Based on Different Diseases
Clinical text mining; Multiclass logistic regression; Natural language processing; scispaCy; Support vector classifier; TF-IDF vectorization; Transcriptions
Clinical text classification is the process of extracting the information from clinical narratives. Clinical narratives are the voice files, notes taken during a lecture, or other spoken material given by physicians. Because of the rapid rise in data in the healthcare sector, text mining and information extraction (IE) have acquired a few applications in the previous few years. This research attempts to use machine learning algorithms to diagnose diseases from the given medical transcriptions. Proposed clinical text classification models could decrease human efforts of labeled training data creation and feature engineering and for designing for applying machine learning models to clinical text classification by leveraging weak supervision. The main aim of this paper is to compare the multiclass logistic regression model and support vector classifier model which is implemented for performing clinical text classification on medical transcriptions. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Lecture Notes in Electrical Engineering, Vol-853, pp. 613-623.
Sreekumar Y., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Nizar Banu P.K., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India
Controlling Node Failure Localization in Data Networks Using Probing Mechanisms
CAP; Internal network; MANET; Message authenticate code; Probing mechanisms
In this paper, we prospect the potency of node failure localization in network communication from dual states (normal/fizzle) of the source to destination paths. To localize the failure nodes individually in the scheduled nodes, dissimilar path states must connect with various events of failure nodes. But, this situation is inapplicable or not easier to investigate or apply on enormous networks due to the obligation of any viable failure nodes. This objective is to deploy the set of adequate conditions for recognizing a set of failures in a set of arbitrary nodes which can be verified in a stipulated time. To avoid the above situation, probing mechanisms are assimilated additionally as a combination for network topology and locations of scrutinizes. Three probing mechanisms are considering which vary depending on measurement paths. Both the procedures can be transformed into single-node possessions by which they can be calculated effectively based on the given conditions. The exceeding measures are proposed for measuring the potency of failure localization which can be utilized for assessing the effect of different factors, which comprises topology, total monitors, and probing mechanisms. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Saritha K.; Devi B.M.; Kurni M.; Samanta D.; Joseph N.P.
Lecture Notes in Networks and Systems, Vol-373, pp. 331-338.
Saritha K., S. V. Degree & P. G. College, Andhra Pradesh, Anantapur, India; Devi B.M., Department of CSE, K.S. R. M College of Engineering, Andhra Pradesh, Kadapa, India; Kurni M., Department of Computer Science, SoS, GITAM (Deemed to be University), Telangana, Hyderabad, India; Samanta D., Department of Computer Science, CHRIST Deemed to be University, Bengaluru, India; Joseph N.P., Department of Computer Science, CHRIST Deemed to be University, Bengaluru, India