Nagalakshmi Malempati

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence, Computer Engineering, Information Systems

Scopus Publications

AI DRIVEN GAME THEORY OPTIMIZED GENERATIVE CNN-LSTMMETHOD FOR FAKE CURRENCY DETECTION




Smart Contracts for Real Estate Sales-A New Era of Efficiency and Transparency
G. Sowmya, K. Alankruthi, Jami Harika, T. Nagini, M. Nagalakshmi, and J. Pradeep Kumar
IEEE
The technology of smart contracts will change the real estate sector forever through a greater efficiency and openness. The research investigates smart contracts as a possibility for dealing with real estate transactions, their elimination of the middleman, improved security and transparency of transactions. Besides the possibility of traditional procedures, smart contracts (self-executed agreements having the terms in the code of the contract) yield several benefits such as increased fraud prevention, automated execution of contracts, and immutable records. Through vivid examples of practical uses, this article points to legal and regulatory challenges to be addressed. It also underlines the working benefits of smart contracts in real estate. The paper’s conclusion consists of the investigation of the present boundaries and the descriptions of the further inquiries, emphasizing the possibility of smart contracts to be a game-changer in the real estate sector.


Revolutionizing Magnetic Resonance Imaging Image Reconstruction: A Unified Approach Integrating Deep Residual Networks and Generative Adversarial Networks
M Nagalakshmi, M. Balamurugan, B. Hemantha Kumar, Lakshmana Phaneendra Maguluri, Abdul Rahman Mohammed ALAnsari, and Yousef A.Baker El-Ebiary
The Science and Information Organization
— Advancements in data capture techniques in the field of Magnetic Resonance Imaging (MRI) offer faster retrieval of critical medical imagery. Even with these advances, reconstruction techniques are generally slow and visually poor, making it difficult to include compression sensors. To address these issues, this work proposes a novel hybrid GAN-DRN architecture-based method for MRI reconstruction. This approach greatly improves texture, boundary characteristics, and picture fidelity over previous methods by combining Generative Adversarial Networks (GANs) with Deep Residual Networks (DRNs). One important innovation is the GAN's all-encompassing learning mechanism, which modifies the generator's behaviour to protect the network against corrupted input. In addition, the discriminator assesses forecast validity thoroughly at the same time. With this special technique, intrinsic features in the original photo are skillfully extracted and managed, producing excellent results that adhere to predetermined quality criteria. The


Forest fire management using machine learning techniques
Harishchander Anandaram, Nagalakshmi M, Ricardo Fernando Cosio Borda, Kiruthika K, and Yogadinesh S
Elsevier BV



A Robust Deep Neural Network Framework for the Detection of Dementia
K. Sweety and M. Nagalakshmi
IEEE
The basic goal of this Deep Learning (DL) framework is to identify early pathological signals that people could miss in order to improve physicians' effectiveness in disease identification. The most common degenerative condition that causes dementia, is the Alzheimer's disease (AD), it offers serious health hazards to middle aged and older people. Different people can experience dementia in different ways and it will create individual signs dependent on the fragment of their brain which is affected. However, it is more essential to treat this disease because, the person with this disease may suffer to communicate with others, to eat and chew their own food etc. Several state-of-art methods are utilized for the detection of dementia earlier. In this study, the detection of dementia is done by DL based Convolutional Neural Network (CNN). The Grey Level Co-occurrence Matrix (GLCM) is recycled for the feature extraction process. The Spider Monkey Optimization (SMO) is used in this study for feature selection process. Subsequently, CNN is a deep learning (DL) network architecture that it will learn directly from the data. This will be utilized for identifying objects and the category of the image pattern. Moreover, this can also be used for signaling the data, time-series and categorizing signal. Therefore, the investigational outcome reveals that the future algorithm has the ability to identify and treat dementia. The effectiveness of the proposed work can be proved by comparing the CNN with other existing models. The comparison outcome gives the proposed system has better accuracy than other existing methods.


Design and development of global industrial process monitoring through IoT using Raspberry Pi
T Rajesh Kumar, Mohammad Jabirullah, G. R. Anantha Raman, and M. Nagalakshmi
AIP Publishing



Artificial Intelligence-based cloud computing for Industry 5.0
Neeraj Kumar Singh, Sunil Kr Pandey, M Nagalakshmi, A Arun Kumar, Mohit Tiwari, and Sarvesh Kumar
IEEE
The cloud computing, characterized as the conveyance of figuring administrations, consisting of servers, stockpiling, records set, organizing, programming, investigation, and insight, making use of the net presents faster advancement, adaptability, readiness, and versatility upholds AI like no different stage and ensures higher matters for the improvement of organizations. The standing of Artificial Intelligence (AI) has accordingly harmonized with the growth of distributed computing. Involving AI in the cloud can improve cloud general execution and viability while riding advanced change in undertakings. Simulated intelligence abilities in the distributed computing environmental factors are crucial for making business undertaking activities more prominent productive, key, and knowledge-driven while also granting additional adaptability, deftness, and expense reserve funds. In Industry 5.0, client aspirations will force the market pursuits towards hyper customization. Each man or woman product will be special to its supposed consumer and manufactured accordingly. To cater to the fashion of "batch measurement one," producers will have large, robotized shrewd factories placed round the globe to manufacture the fundamental graph of the product in bulk.


A microservices-based IoT applications in Edge computing environments
Sunil Kumar Agarwal, S M Ramesh, A Arun Kumar, Sachin Yadav, M Nagalakshmi, and Prabhishek Singh
IEEE
With the improvement of Internet of Things, the scope of local area devices is expanding, and the cloud data center burden builds; some deferral delicate contributions can’t be answered to opportune, which outcomes in a brought down good of transporter (QoS). Edge computing (EC) supports the utilization of its contributions with low idleness, place perception and versatility help to compensate for the risks of distributed computing, and has gotten a colossal energy as of late. Notwithstanding, the powerfully modifying fine of transporter (QoS) may also outcome in screw ups of QoS-mindful guidance and organization of EC administrations, which strikingly debases clients’ pride and nullifies the gifts of MEC. To handle this issue, with the guide of pondering client related and administration related context-oriented components and an assortment of EC contributions booking situations, we suggest two setting mindful QoS expectation plans for EC administrations. The main plan is intended for the circumstances when EC contributions are planned for continuous, which conveys two setting mindful constant QoS assessment strategies. One strategy can assess the ongoing multi-QoS of EC contributions and the different procedure can appraise the continuous outfitted QoS of EC administrations. The 2d plan is intended for the circumstances when EC contributions are planned for what is in store. This plan comprises of two setting mindful QoS expectation strategies. One method can anticipate the multi-QoS of EC contributions and the different procedure can foresee the furnished QoS of EC administrations. At long last, versatile QoS expectation strategies are created in the gentle of qualities of the proposed QoS forecast techniques. As indicated by these systems, the most stunning QoS forecast approach can be planned. Broad investigations are completed to approve our proposed strategies and to display their exhibition.


Hadoop Map Reduce Techniques: Simplified Data Processing on Large Clusters with Data Mining
S. Suresh, T Rajesh Kumar, M Nagalakshmi, J. Bennilo Fernandes, and S. Kavitha
IEEE
Data mining applications have become outdated and outmoded in recent years. The use of incremental processing to refresh mining results is a promising method. It makes use of previously saved states to save time and energy on re-computation. In this research, we offer a novel increment processing addition to the Map Reduce, the most extensively used methodology for mining the big data by using the Naive Bayes, the J48, and the Random Forest algorithms. Map reduction is a programming model for simultaneous processing and generation of massive amounts of data. We examine Map Reduce employing Naive Bayes, J48, and Random Forest algorithms with a variety of processing features for efficient mining that also saves energy. The Naive Bayes algorithm generates more energy and fewer maps. Priority-based scheduling is a task that allocates schedules based on the jobs’ requirements and utilization. As a result of decreasing the maps, the system’s workload is reduced, and energy efficiency is improved. The experimental comparison of the several algorithm techniques (Naive Bayes, J48, and Random Forest) have applied in this article and found that the Random forest is performed better than remaining two algorithms i.e. 92%.


Blockchain Confidence Protection and Cloud Chain Management Support
M Nagalakshmi, K Saravanan, Mohammad Jabirullah, and T Rajesh Kumar
IOP Publishing
Abstract Verification and completeness are main challenges for today’s ever more diverse supply chains. Even with the ability to counter blockchain technologies by offering a trail of manipulation-resistant audit It does not address the confidence issue associated with the source chain activities also information related to a produce life cycle Information itself. Reputation mechanisms are a promising solution for this faith problem. Yet existing structures of credibility are Not ideal for supply chain applications based on blockchain as centred on restricted findings, lack of granularity and their overhead was not discussed and automation. We recommend the system as a three-layer faith in this job. Management platform is using a blockchain consortium tracking relationships between actors in the supply chain and Assign trust and prestige dynamically dependent on these interactions. Its novelty is based on a Model for credibility assessing product quality and the trust of individuals based on many observations funding for credibility qualities in supply chain incidents separating the member in the supply chain from the goods, enables brand credibility to be reserved for smart contracts for straightforward use by the same participant, Effective, secure, and automatic credibility scoring measurement, and the latency and throughput minimum overhead as compared to a straightforward supply chain model based on blockchain.


Power Route Selection for Spatial Modulation and Multi-Hop Wireless Networks with Minimal Energy Supplies
Mohammad Jabirullah, M Nagalakshmi, K Saravanan, and G R Anantha Raman
IOP Publishing
Abstract Concurrent w ireless and data transmission information and power transmits cellular nodes information and power with almost the same radio transmitter. The lifespan of the energy-reducing mobile networks can be increased. The focus on a single and double hop cellular network is currently being focused on. This essay simultaneously discusses and routing selection in order to check the efficiency of the energy-controlled wireless network in multi-hop operators, in which the energy received through the recipient node can be used to counteract energy transfer. We initial articulate the dataalso energy distribution problem in a possible through the development which depends on the following node; also overcome it through an iterative aspect algorithm, in order to reduce demand for energy. The power usage of the links distributed with or without a current routing metric evaluates. The energy conscious routing algorithm assigns knowledge and energy to the access control mechanism during the step of trajectory finding. This is the first approach to our understanding that takes care of the routing process. Our efficiency studies indicate that our existing methodology can efficiently harness node capital whose energy is inadequate and reduce energy consumption considerably.


Flexible Language-Agnostic Framework To Emit Informative Compile-Time Error Messages
Malathy Nagalakshmi, Tanya Sharma, and N. S. Kumar
Springer Nature Singapore



Design and research of ADHOC based wireless network system
and Dr M Nagalakshmi*
Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Fiasco watching is a champion the diverse maximum hard software in some distance flung uncommonly delegated frameworks as putting in established order based totally frameworks are neither feasible nor suitable in that conditions. In the direction of disaster, setbacks commonly take secures in packs in some nearby sheltered zones (as an instance, some university systems, and quick tents in a few terrific us of a regions, and so forth.). Thusly, the post catastrophe help assignments and route of benefits are regularly guard pushed. Thusly, dynamic after and engrossing sanctuary data (concerning open useful useful resource, required beneficial useful resource, reputation of setbacks and volunteers at the sheltered residence, and so on.) at a manage station is essential for great need examination from the piecewise positive points of view at every safe haven. Anyhow, in a regular fiasco circumstance, correspondence shape gets irritated snappy and the cell accessibility may be pitifully open in multiple areas of the catastrophe struck locale. As such, control correspondence of safe haven information to control station is restrained. The objective of this assignment is to have a examine using reducing aspect cellular cellular phone based keen framework for following and acclimatizing cozy houses' information and supporting the correspondence with manage station. In this splendid situation, the power of mitigation government/salvage car/police van with phones assume a easy element to make the specified ground- breaking correspondence established order. This text is an overview on the drift reputation and heading of studies on impromptu networking. We type the on-going exploration and diagram the actual challenges which want to be tackled before throughout the board association of the technology is practicable. The perspectives exhibited by way of manner of Perkins in [1] are applied as a motive, that is then supplemented with communicate and references to the latest publications. distinctive methodologies and conventions had been proposed to deal with in particular appointed structures management problems, and several institutionalization efforts are underneath route in the internet Engineering task pressure, just as scholarly and mechanical studies of difference projects.


An ADHOC based wireless network system
Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Fiasco watching is a champion the diverse maximum hard software in some distance flung uncommonly delegated frameworks as putting in established order based totally frameworks are neither feasible nor suitable in that conditions. In the direction of disaster, setbacks commonly take secures in packs in some nearby sheltered zones (as an instance, some university systems, and quick tents in a few terrific us of a regions, and so forth.). Thusly, the post catastrophe help assignments and route of benefits are regularly guard pushed. Thusly, dynamic after and engrossing sanctuary data (concerning open useful useful resource, required beneficial useful resource, reputation of setbacks and volunteers at the sheltered residence, and so on.) at a manage station is essential for great need examination from the piecewise positive points of view at every safe haven. Anyhow, in a regular fiasco circumstance, correspondence shape gets irritated snappy and the cell accessibility may be pitifully open in multiple areas of the catastrophe struck locale. As such, control correspondence of safe haven information to control station is restrained. The objective of this assignment is to have a examine using reducing aspect cellular cellular phone based keen framework for following and acclimatizing cozy houses' information and supporting the correspondence with manage station. In this splendid situation, the power of mitigation government/salvage car/police van with phones assume a easy element to make the specified ground-breaking correspondence established order.


Natural Language Interface to Linux Shell-Report
NS kumar, Malathy Nagalakshmi, Tanya Sharma, Sai Bhavana Ambati, and Vibha Satyanarayana
IEEE
Many a time, a user might not remember the exact Linux commands to apply while using the Linux shell. The programmer ends up searching for the correct solution. Having a natural language interface (like English) to a shell would help programmers’ in performing their desired tasks without having to think much about the particular command or option that needs to be used. We present a tool that can convert natural language into executable Linux commands. This paper covers the related work done in this field and our approach to solving this problem. Research in this field is fairly new and there are two tools in this domain, Tellina[1] and Betty. Tellina is a powerful tool which covers file operations with high complexity. Apart from file utilities, our tool also covers a wider scope of commands including awk and sed. A novel approach is used to find the structure of the command. This paper includes the comparisons between Neural Machine Translation (NMT), Statistical Machine Translation(SMT), similarity models and machine learning models.


Bigdata implementation of apriori algorithm for handling voluminous data-sets




A frame work of real time disaster management system (RDMS) using ADHOC wireless networks




Building secretkey based virtual machines in cloud computing to avoid vulnarabilities in hypervisors




Design of a secure digital signature for image authentication over wireless networks

RECENT SCHOLAR PUBLICATIONS

DFFMD A DEEPFAKE FACE MASK DATASET FOR INFECTIOUS DISEASE ERA WITH DEEPFAKE DETECTION ALGORITHMS
A Brahmareddy, AK Arigela, M Nagalakshmi
2024



Pest Detection and Classification in Peanut Crops Using CNN, MFO, and EViTA Techniques
M Nagalakshmi, AK Arigela, A Brahmareddy
2024



A Robust Deep Neural Network Framework for the Detection of Dementia
K Sweety, M Nagalakshmi
2023 3rd International Conference on Pervasive Computing and Social 2023



Forest fire management using machine learning techniques
H Anandaram, M Nagalakshmi, RFC Borda, K Kiruthika, S Yogadinesh
Measurement: Sensors 25, 100659 2023



A microservices-based IoT applications in Edge computing environments
SK Agarwal, SM Ramesh, AA Kumar, S Yadav, M Nagalakshmi, P Singh
2022 2nd International Conference on Innovative Sustainable Computational 2022



Artificial intelligence-based cloud computing for industry 5.0
NK Singh, SK Pandey, M Nagalakshmi, AA Kumar, M Tiwari, S Kumar
2022 2nd International Conference on Innovative Sustainable Computational 2022



Hadoop Map Reduce Techniques: Simplified Data Processing on Large Clusters with Data Mining
S Suresh, TR Kumar, M Nagalakshmi, JB Fernandes, S Kavitha
2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile 2022



Design and development of global industrial process monitoring through IoT using Raspberry Pi
TR Kumar, M Jabirullah, GR Raman, M Nagalakshmi
AIP Conference Proceedings 2519 (1) 2022



Power route selection for spatial modulation and multi-hop wireless networks with minimal energy supplies
M Jabirullah, M Nagalakshmi, K Saravanan, GRA Raman
Journal of Physics: Conference Series 1964 (6), 062078 2021



Blockchain Confidence Protection and Cloud Chain Management Support
M Nagalakshmi, K Saravanan, M Jabirullah, TR Kumar
Journal of Physics: Conference Series 1964 (4), 042068 2021



AN ACCOMPLISHMENT OF RESEARCH STUDY ON IMPROVING CREATIVE WRITING SKILLS IN ENGLISH AT COLLEGE LEVEL STUDENTS WITH SPECIAL REFERENCE TO CHENNAI DISTRICT IN TAMIL NADU
AS Kumar, M Nagalakshmi
Journal of Electrical Engineering and Technology (IJEET) 12 (6), 67-75 2021



Experimental Study on Corrosion Resistivity of Low Calcium Fly Ash Based Geo Polymerconcrete
M NAGALAKSHMI, P RAJESH
2018



Active Power Decoupling for Single-Phase PWM Rectifiers without Extra Active Switches
SP KUMAR, M NAGALAKSHMI, L KISORE
2017



Distributed Concurrent & valid access to preserved Cloud Databases
PJ M Nagalakshmi
ISSN NO:2348-4845 2 (9) 2015



Authorized Data Retrieval for Anonymous disruption-Tolerant Military Networks
PJ M Nagalakshmi
ISSN NO:2348-4845 1 (11) 2014



Improvement of overall Network Security using routers
KVR M Nagalakshmi
ISSN NO:2348-4845 1 (7) 2014



Efficient Scheme for Recognition of Streaming Data outflow
DMAH M Nagalakshmi
ISSN:2319-8885 3 (49) 2014



Effective proposal for managing of Database services on Encrypted Information
DMAH M Nagalakshmi
ISSN NO:2320-3706 2 (9) 2013



Design and Implementation of Online Security using Graphical password systems using Captcha Technique
KVR M Nagalakshmi
ISSN NO:2320-3706 2 (12) 2013



A Dynamic Approach towards Confining Delay Tolerance of user on Auction Based Scheme
DMAH M Nagalakshmi
ISSN:2319-8885 2 (1) 2013

MOST CITED SCHOLAR PUBLICATIONS

Forest fire management using machine learning techniques
H Anandaram, M Nagalakshmi, RFC Borda, K Kiruthika, S Yogadinesh
Measurement: Sensors 25, 100659 2023
Citations: 9



Hadoop Map Reduce Techniques: Simplified Data Processing on Large Clusters with Data Mining
S Suresh, TR Kumar, M Nagalakshmi, JB Fernandes, S Kavitha
2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile 2022
Citations: 5



Vehicle routing problem with stochastic demand (VRPSD): optimisation by neighbourhood search embedded adaptive ant algorithm (ns-AAA)
MR Nagalakshmi, M Tripathi, N Shukla, MK Tiwari
International Journal of Computer Aided Engineering and Technology 1 (3 2009
Citations: 4



Artificial intelligence-based cloud computing for industry 5.0
NK Singh, SK Pandey, M Nagalakshmi, AA Kumar, M Tiwari, S Kumar
2022 2nd International Conference on Innovative Sustainable Computational 2022
Citations: 2



Power route selection for spatial modulation and multi-hop wireless networks with minimal energy supplies
M Jabirullah, M Nagalakshmi, K Saravanan, GRA Raman
Journal of Physics: Conference Series 1964 (6), 062078 2021
Citations: 1



Optimization of series-parallel system reliability: Adaptive memetic particle swarm optimization based approach
SK MANDAL, SK TYAGI, M TRIPATHI, MR NAGALAKSHMI, MK TIWARI
3rd International Conference on Reliability and Safety Engineering 2007
Citations: 1