32 results on '"Karthik, Chandran"'
Search Results
2. Analysis of mechanical properties in self‐compacting concrete enhanced with steel fibres
- Author
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Mukilan Karuppasamy, Baranitharan Balakrishnan, Karthik Chandran, Mehdi Gheisari, Payam Porkar Rezaeiye, and Boris Andrievsky
- Subjects
carbon fibres ,impact (mechanical) ,Chemical technology ,TP1-1185 ,Materials of engineering and construction. Mechanics of materials ,TA401-492 - Abstract
Abstract This study explores the effect of incorporating steel fibres and fly ash into self‐compacting concrete (SCC) in various combinations on its mechanical properties. The study begins with thoroughly investigating the fresh properties to ensure compliance with SCC standards when adding steel fibres. Subsequently, mixes that meet SCC standards are evaluated for their mechanical properties. The study aims to enhance the mechanical properties of SCC while maintaining its flowability, filling ability, and passing ability. The research findings provide valuable insights into the optimal combination of steel fibres and fly ash for improving the mechanical properties of SCC. The addition of hooked end type steel fibres increases the compressive strength. When compared to crimped type the mechanical properties increased to 14.4%; however, the strength decreases beyond 1% of steel fibres. Satisfactory results are obtained for fresh properties test.
- Published
- 2024
- Full Text
- View/download PDF
3. Context-Aware Augmented Reality Using Human-Computer Interaction Models.
- Author
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Ying Sun, Qiongqiong Guo, Shumei Zhao, Karthik Chandran, and G. Fathima
- Published
- 2024
- Full Text
- View/download PDF
4. Tikhonov Regularization and Perturbation-Level Tuning for the CNM in Pharmacokinetics.
- Author
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Luong Thi Theu, Quang-Huy Tran, Duc-Tan Tran 0001, Bhisham Sharma, Subrata Chowdhury, Karthik Chandran, and Saravanakumar Gurusamy
- Published
- 2023
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- View/download PDF
5. Frequency-hopping along with Resolution-turning for Fast and Enhanced Reconstruction in Ultrasound Tomography
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Quang-Huy, Tran, primary, Sharma, Bhisham, additional, Theu, Luong Thi, additional, Tran, Duc-Tan, additional, Chowdhury, Subrata, additional, Karthik, Chandran, additional, and Gurusamy, Saravanakumar, additional
- Published
- 2024
- Full Text
- View/download PDF
6. Accurate Magnetic Resonance Image Super-Resolution Using Deep Networks and Gaussian Filtering in the Stationary Wavelet Domain.
- Author
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Gunnam Suryanarayana, Karthik Chandran, Osamah Ibrahim Khalaf, Youseef Alotaibi, Abdulmajeed Alsufyani, and Saleh Ahmed Alghamdi
- Published
- 2021
- Full Text
- View/download PDF
7. Task Modelling of Sports Events for Personalized Video Streaming Data in Augmentative and Alternative Communication.
- Author
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Lei Zheng, Zhiqiang Jia, Hui Guan, Liang Ma, Karthik Chandran, and K. Deepa Thilak
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- 2021
- Full Text
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8. Institutionalizing Open Science in Africa: Limitations and Prospects
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Izuchukwu Azuka Okafor, Smart Ikechukwu Mbagwu, Terkuma Chia, Zuwati Hasim, Echezona Ejike Udokanma, and Karthik Chandran
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open science ,Africa ,advocacy ,institutions ,engagement ,Bibliography. Library science. Information resources - Abstract
The advancement of scientific research and raising the next-generation scientists in Africa depend largely on science access. The COVID-19 pandemic has caused discussions around open science (OS) to reemerge globally, especially in resource-poor settings like Africa, where the practice of OS is low. The authors highlighted the elements, benefits, and existing initiatives of OS in Africa. More importantly, the article critically appraised the challenges, opportunities, and future considerations of OS in Africa. Addressing challenges of funding and leadership at different levels of educational, research, and government parastatals may be pivotal in charting a new course for OS in Africa. This review serves as an advocacy strategy and an informative guide to policymaking and institutionalization of OS in Africa.
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- 2022
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- View/download PDF
9. Nonlinear system parameter estimation of drying process using modified state transition algorithm in cloud environment.
- Author
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Karthik Chandran, Manikandan Ramasamy, Sathian Dananjayan, Ankur Dumka, and Loganathan Jayakumar
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- 2020
- Full Text
- View/download PDF
10. Modified Cascade Controller Design for Unstable Processes With Large Dead Time.
- Author
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Karthik Chandran, Rajalakshmi Murugesan, Saravanakumar Gurusamy, K. Asan Mohideen, Sanjeevi Pandiyan, Anand Nayyar, Mohamed Abouhawwash, and Yunyoung Nam
- Published
- 2020
- Full Text
- View/download PDF
11. Computer-Aided Controller Design for a Nonlinear Process Using a Lagrangian-Based State Transition Algorithm.
- Author
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Rajalakshmi Murugesan, Jeyadevi Solaimalai, and Karthik Chandran
- Published
- 2020
- Full Text
- View/download PDF
12. Chest CT Image based Lung Disease Classification – A Review
- Author
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Kondamuri, Shri Ramtej, primary, Thadikemalla, Venkata Sainath Gupta, additional, Suryanarayana, Gunnam, additional, Karthik, Chandran, additional, Reddy, Vanga Siva, additional, Sahithi, V. Bhuvana, additional, Anitha, Y., additional, Yogitha, V., additional, and Valli, P. Reshma, additional
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- 2023
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13. Innovative and efficient method of robotics for helping the Parkinson's disease patient using IoT in big data analytics.
- Author
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C. B. Sivaparthipan 0001, Bala Anand Muthu, Gunasekaran Manogaran, Balajee Maram, Revathi Sundarasekar, Sujatha Krishnamoorthy, Ching-Hsien Hsu, and Karthik Chandran
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- 2020
- Full Text
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14. Notice of Retraction: Adaptive Decentralized Tracking Control for Nonlinear Large-Scale Systems.
- Author
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Karthik Chandran, Weidong Zhang 0004, Rajalakshmi Murugesan, S. Prasanna, A. Baseera, and Sanjeevi Pandiyan
- Published
- 2021
- Full Text
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15. A study on agricultural engineering equipment in South Tamilnadu using linear regression
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Chandrakumar Thangavel, Ramya Thangavel, Karthik Chandran, Gunnam Suryanarayana, Subrata Chowdhury, Nguyen Duc Uyen, Thi-Thu Nguyen, and Duc-Tan Tran
- Subjects
Control and Optimization ,Computer Networks and Communications ,Hardware and Architecture ,Control and Systems Engineering ,Agricultural engineering equipment ,Computer Science (miscellaneous) ,Mechanization strategy ,Electrical and Electronic Engineering ,Agricultural implements ,Instrumentation ,Mechanization ,Information Systems - Abstract
Economic growth in India purely depends on the Indian agricultural sector. In developing countries, the mechanization of agriculture plays a vital role in productivity. The research focuses on identifying which farmers in South Tamilnadu mostly use agricultural machinery. In this paper, we have taken farmer names and mobile numbers, choice of implement requirement into consideration by collecting the real data through DBT portal (https://agrimachinery.nic.in). This research work deals with five southern districts in Tamilnadu, namely Dindigul, Madurai, Theni, Ramnad, and Virudhunagar, in which we have predicted which machinery is suitable for that area. The linear regression model was used in this research by testing and training the dataset in all five data frames to get efficient results. Prediction of each data frame reveals the efficient working of the particular machinery for that specific area due to the different geographical features.
- Published
- 2022
16. Dynamic Wireless Charging for Inductive Power Transfer Systems in Electric Vehicles
- Author
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Ponmani Raja M, Karthik Chandran, Jeyakkannan N, John Paul, and Jibin Jaison
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Hardware_GENERAL - Abstract
The charging plate creates magnetic fluxing. The charging plate and the adjacent coil can induce current without any contact. By the new trends, wireless charging got more social attention to the outside world as an alternative method for primitive wired charging. Even though wireless charging was implemented to various electronics industries, it is still proven that wired charging is faster than the wireless. But can make the gadget hot, which may not be good for the battery efficiency. The wireless charging does not degrade the battery. A vehicle that is powered by an electric motor rather than a typical petrol or diesel engine is referred to as an electric vehicle. The electric motor is powered by rechargeable batteries. In this article, the dynamic wireless charging of electric vehicles introduces a new methodology of charging even when the vehicle is in motion. The dynamic wireless charging is proposed to allow power transfer to the electric vehicles when they are in motion. Multiple inductive pads should be buried under the roadways. The inductive pads should be energized by a power supply. The track which is dedicated for the wireless charging should have enough distance so that the vehicles can charge up to a stable value until they leave the charging track. This proposed methodology reduces unnecessary time wastage for charging of vehicles. Hardware results obtained the primary pads mounted on road and power supply for primary roads. Besides, it will flow the efficient inductive power transfer and time saving opportunity.
- Published
- 2022
17. Context-Aware Augmented Reality Using Human–Computer Interaction Models
- Author
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Ying Sun, Qiongqiong Guo, Shumei Zhao, Karthik Chandran, and G. Fathima
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Human-Computer Interaction ,Control and Optimization ,Artificial Intelligence ,Computer Networks and Communications ,Control and Systems Engineering ,Signal Processing ,Information Systems - Published
- 2022
18. Psychological behavior signal analysis for sports person during their activity session
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Guochun Liu, Karthik Chandran, Beenu Mago, Lin Jiang, and Jian Zheng
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Statistics and Probability ,03 medical and health sciences ,Signal processing ,0302 clinical medicine ,Artificial Intelligence ,Applied psychology ,0202 electrical engineering, electronic engineering, information engineering ,General Engineering ,020201 artificial intelligence & image processing ,030229 sport sciences ,02 engineering and technology ,Psychology ,Activity Session - Abstract
The signal analysis helps us derive useful knowledge from biological processes to analyze, describe, and understand their origin mechanisms. However, biomedical signals are not immune and have time-consuming statistics. The major challenges of signal analysis of sportsperson are reliability and accuracy. Sports psychology uses psychological skills to discuss the optimum success and well-being of sports athletes, the developmental and social dimensions of the sport and sports facilities, and structural problems. The signal detection tool is used to detect the best combination of long-term practice predictors for active, sedentary adults’ signal. This paper proposed the wearable assisted signal detection method (WASDM) to find the sportspersons’ behavior signal analysis. This method performs an IoT based heart rate monitoring using a wearable device named intelligent bracelet mounted on the sportsperson to track the variations in his/her human heart rate. The wearable signal detector method analysis the heart rate abnormality and predicts health status, followed by an alarm to the physician and the respective personnel while performing activity session. In this research, various machine learning algorithms have been tried to perform signal analysis and prediction and compared their results to suggest the best in this application scenario. Finally, the experimental analysis shows better outcomes for the sportspersons’ psychological behavior signal analysis than the conventional methods.
- Published
- 2021
19. Adaptive Decentralized Tracking Control for Nonlinear Large-Scale Systems
- Author
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Sanjeevi Pandiyan, Rajalakshmi Murugesan, Karthik Chandran, S. Prasanna, A. Baseera, and Weidong Zhang
- Subjects
Nonlinear system ,Adaptive control ,Scale (ratio) ,Artificial Intelligence ,Control and Systems Engineering ,Control theory ,Computer science ,Control (management) ,Block triangular form ,Tracking (particle physics) ,Software ,Information Systems - Abstract
Decentralized Model Reference Adaptive Control problems are investigated for a class of linear time-invariant two time-scale model, having fast and slow dynamics and unmatched interconnections. Design of full state feedback controller is a critical task to the system having interrelated dynamics and nonlinear interconnections of time varying lags, however, can be addressed by singular perturbation procedures and time scale modeling. In this research, full order observer-based state feedback control is designed to two-time scale system to ensure the stability of the closed loop system. Then, decentralized model reference adaptive controller with the novel reference model is designed to individual subsystems. It is found that the proposed design enforces the system states to track the reference state asymptotically. To investigate the proposed design, an example of drying process is considered. Simulation results are analyzed to confirm the efficacy of the proposed control scheme.
- Published
- 2020
20. Modified Cascade Controller Design for Unstable Processes With Large Dead Time
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Mohamed Abouhawwash, Anand Nayyar, Sanjeevi Pandiyan, Rajalakshmi Murugesan, Karthik Chandran, K. Asan Mohideen, Yunyoung Nam, and Saravanakumar Gurusamy
- Subjects
fractional-order PI/PD ,General Computer Science ,Series (mathematics) ,Computer science ,020208 electrical & electronic engineering ,General Engineering ,02 engineering and technology ,Dead time ,Series cascade control ,Stability (probability) ,convex stability region ,Cascade control system ,Cascade controller ,Simple (abstract algebra) ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,General Materials Science ,internal model control ,lcsh:Electrical engineering. Electronics. Nuclear engineering ,unstable time-delay process ,lcsh:TK1-9971 ,Inner loop - Abstract
In this article, a simple controller design with the fractional order calculations applies to unstable cascade processes with a significant time delay. Series cascade control system consists of two loops in which the inner loop is designed using the IMC principle based on the synthesis method. The primary controller is designed with the FOPI-FOPD controller to ensure stable and satisfactory closed-loop performances for the unstable processes. For the primary controller, five tuning parameters are involved, which tuned using the centroid of the convex stability region method. Different examples are given to illustrate the superiority of the proposed design over some existing designs. Results obtained from simulation reveals that with the proposed control design, enhanced closed-loop control performances are obtained for nominal and perturbed conditions.
- Published
- 2020
21. Computer-Aided Controller Design for a Nonlinear Process Using a Lagrangian-Based State Transition Algorithm
- Author
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Jeyadevi Solaimalai, Karthik Chandran, and Rajalakshmi Murugesan
- Subjects
0209 industrial biotechnology ,Computer science ,Applied Mathematics ,Evolutionary algorithm ,Process (computing) ,02 engineering and technology ,Nonlinear system ,020901 industrial engineering & automation ,Control theory ,Signal Processing ,Convergence (routing) ,Computer-aided ,Transient (oscillation) ,State (computer science) ,Algorithm - Abstract
Model parameter estimation and controller tuning of the nonlinear clarification process are primary issues in the sugar industry. This paper proposes a Lagrangian-based state transition algorithm (LSTA) for controlling the clarification process and identifying the model parameters. First, the standard system identification procedure is used to estimate the model parameters for the clarifier. Then, the LSTA is used to enhance the accuracy of the identified system parameters. Once a suitable model is obtained, the proposed LSTA is used to fine-tune the optimal controller parameters off-line. We choose two types of evolutionary algorithms for comparison to show the efficacy of the proposed design. The results of the simulations indicate that the proposed controller achieves optimum transient and tracking performance in all cases. For fast convergence and the ability to provide the global optimum when estimating the modeling and controller parameters, the LSTA performance was found to be superior to that of the other algorithms.
- Published
- 2019
22. Machine Learning for Healthcare Systems : Foundations and Applications
- Author
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C. Karthik Chandran, M. Rajalakshmi, Sachi Nandan Mohanty, Subrata Chowdhury, C. Karthik Chandran, M. Rajalakshmi, Sachi Nandan Mohanty, and Subrata Chowdhury
- Subjects
- Artificial intelligence--Medical applications, Machine learning, Medical informatics
- Abstract
The introduction of digital technology in the healthcare industry is marked by ongoing difficulties with implementation and use. Slow progress has been made in unifying different healthcare systems, and much of the world still lacks a fully integrated healthcare system. The intrinsic complexity and development of human biology, as well as the differences across patients, have repeatedly demonstrated the significance of the human element in the diagnosis and treatment of illnesses. But as digital technology develops, healthcare providers will undoubtedly need to use it more and more to give patients the best treatment possible. The extensive use of machine learning in numerous industries, including healthcare, has been made possible by advancements in data technologies, including storage capacity, processing capability, and data transit speeds. The need for a personalized medicine or'precision medicine'approach to healthcare has been highlighted by current trends in medicine due to the complexity of providing effective healthcare to each individual. Personalized medicine aims to identify, forecast, and analyze diagnostic decisions using vast volumes of healthcare data so that doctors may then apply them to each unique patient. These data may include, but are not limited to, information on a person's genes or family history, medical imaging data, drug combinations, patient health outcomes at the community level, and natural language processing of pre-existing medical documentation.This book provides various insights into machine learning techniques in healthcare system data and its analysis. Recent technological advancements in the healthcare system represent cutting-edge innovations and global research successes in performance modelling, analysis, and applications.
- Published
- 2023
23. Innovative and efficient method of robotics for helping the Parkinson's disease patient using IoT in big data analytics
- Author
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C. B. Sivaparthipan, Balajee Maram, Revathi Sundarasekar, Sujatha Krishnamoorthy, Gunasekaran Manogaran, Ching-Hsien Hsu, Karthik Chandran, and BalaAnand Muthu
- Subjects
Parkinson's disease ,Computer science ,business.industry ,Big data ,medicine ,Robotics ,Artificial intelligence ,Electrical and Electronic Engineering ,Internet of Things ,business ,medicine.disease ,Data science - Published
- 2019
24. Notice of Retraction: Adaptive Decentralized Tracking Control for Nonlinear Large-Scale Systems
- Author
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S. Prasanna, A. Baseera, Karthik Chandran, Rajalakshmi Murugesan, Sanjeevi Pandiyan, and Weidong Zhang
- Subjects
Nonlinear system ,Adaptive control ,Scale (ratio) ,Notice ,Artificial Intelligence ,Control and Systems Engineering ,Computer science ,Control theory ,Control (management) ,Tracking (particle physics) ,Software ,Information Systems - Abstract
This article has been retracted at the request of the first and corresponding author, Dr. Karthik Chandran. The author has alerted the Editor-in-Chief of IJUFKS the reasons for the retraction: The proposed system was modelled with the incorrect data set. The system response has become incorrect because of this incorrect data set. Two percent of the information (mathematical assumptions) was taken from one paper without proper citation of the source.
- Published
- 2021
25. Optimized hybridized mathematical model for wastewater treatment and energy generation using microbial fuel cells
- Author
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R. Premalatha, Youwei Lin, Karthik Chandran, Gongdi Xu, Ruina Liu, and Yong Feng Li
- Subjects
Battery (electricity) ,Microbial fuel cell ,Renewable Energy, Sustainability and the Environment ,business.industry ,Energy Engineering and Power Technology ,Context (language use) ,Energy consumption ,Biodegradable waste ,Renewable energy ,Electricity generation ,Environmental science ,Sewage treatment ,Process engineering ,business - Abstract
In the current era of urbanization and industrialization, water pollution and energy generation are the main concerns in the climate change context. Microbial Fuel Cells (MFCs) utilize biodegradable carbon compounds in organic waste to produce an electric current.MFC technology provides sustainable solutions for renewable power systems and energy-efficient wastewater treatment for distributed electricity systems. However, in wastewater treatment, generating usable energy from the MFC remains a significant challenge for the system scale and implementation. Hence, in this paper, the Optimized Hybridized Mathematical Model (OHMM) has been proposed for wastewater treatment and energy generation using microbial fuel batteries. Furthermore, statistical analysis has a role in synthesizing knowledge of fuel cells, defining and limiting factors in electricity production. The findings show that the proposed OHMM method, Sensitivity Analysis, Uncertainty Analysis, and Accuracy reduces energy consumption and cost function compared to other existing methods. With more miniature steam, it reduces the amount of harmful smoke that power plants emit, preserves the natural resources of a planet, and protects habitats against destruction. They will lead to a healthier and happier world by taking action to reduce the battery.
- Published
- 2021
26. Deterministic oscillatory search: a new meta-heuristic optimization algorithm
- Author
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R. Vidhyapriya, N. Archana, Antony Manoj Fh Benedict, and Karthik Chandran
- Subjects
Mathematical optimization ,021103 operations research ,Multidisciplinary ,Meta-optimization ,Optimization problem ,Computer science ,0211 other engineering and technologies ,02 engineering and technology ,Multi-objective optimization ,Derivative-free optimization ,0202 electrical engineering, electronic engineering, information engineering ,Test functions for optimization ,020201 artificial intelligence & image processing ,Standard algorithms ,Algorithm ,Metaheuristic ,Global optimization - Abstract
The paper proposes a new optimization algorithm that is extremely robust in solving mathematical and engineering problems. The algorithm combines the deterministic nature of classical methods of optimization and global converging characteristics of meta-heuristic algorithms. Common traits of nature-inspired algorithms like randomness and tuning parameters (other than population size) are eliminated. The proposed algorithm is tested with mathematical benchmark functions and compared to other popular optimization algorithms. The results show that the proposed algorithm is superior in terms of robustness and problem solving capabilities to other algorithms. The paradigm is also applied to an engineering problem to prove its practicality. It is applied to find the optimal location of multi-type FACTS devices in a power system and tested in the IEEE 39 bus system and UPSEB 75 bus system. Results show better performance over other standard algorithms in terms of voltage stability, real power loss and sizing and cost of FACTS devices.
- Published
- 2017
27. An Empirical Analysis of Green Technology Innovation and Ecological Efficiency Based on a Greenhouse Evolutionary Ventilation Algorithm Fuzzy-Model
- Author
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Xiumei Xu, Yu Sun, Karthik Chandran, and Sujatha Krishnamoorthy
- Subjects
Computer science ,020209 energy ,lcsh:TJ807-830 ,Geography, Planning and Development ,lcsh:Renewable energy sources ,Evolutionary algorithm ,Greenhouse ,02 engineering and technology ,Management, Monitoring, Policy and Law ,law.invention ,green technology ,law ,fuzzy-model-based solar quantum greenhouse evolutionary ventilation algorithm ,Genetic algorithm ,0202 electrical engineering, electronic engineering, information engineering ,Penalty method ,ecological efficiency ,Greenhouse effect ,lcsh:Environmental sciences ,Physics::Atmospheric and Oceanic Physics ,lcsh:GE1-350 ,Fitness function ,Renewable Energy, Sustainability and the Environment ,lcsh:Environmental effects of industries and plants ,Natural ventilation ,Function (mathematics) ,lcsh:TD194-195 ,Ventilation (architecture) ,020201 artificial intelligence & image processing ,Astrophysics::Earth and Planetary Astrophysics ,Algorithm ,Membership function - Abstract
The combination and convergence of energy-intensive industries developed by ecological factors based on energy clusters is discussed in this paper. Here, a few models for the prediction of greenhouse effects are used as a single type of modeling. In this model, the solar panel system is included as a measure of the greenhouse effect, Commitment Unit (CU) formulations are changed with flouted logic because solar integrations and other unknown variables are intermittent. In general, the greenhouse model with natural ventilation temperature prediction is incomplete, in which the resulting fluid logical CU problem can be solved with an evolutionary algorithm based on the definition and the theory of quantum calculation. This paper proposes a Fuzzy Model-Based Quantum Greenhouse Evolutionary Ventilation Algorithm (FM-BSQGEVA) which helps to minimize the CU problem. The QGEVA is updated to include a hierarchy-group-oriented scheme to tackle the non-linear nature of the issue and its multifaceted nature. The QGEVA is further developed to support a new binary differential operator and several genetic algorithm operators with a redefined rotational angle look-up. The chances that such operators are used on separate solutions are affected by stating the membership function based on their related fitness. The fitness function is calculated through a combination of the penalty function, objective function and the added fluid function. The models built can be used to regulate and control natural ventilation in greenhouse effects. This finding shows that an energy-intensive industrial cluster's environmental chain of the industry has improved eco-efficiency.
- Published
- 2020
28. Cytosolic LPS sensing triggers the release of a lectin DAMP that promotes inflammation
- Author
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Ashley Jean Russo, Swathy Vasudevan, Antoine Menoret, Shivalee Duduskar, Margaret Fettis, Chuan Li, Santiago Mendez Huergo, Puja Kumari, Karthik Chandran, Sivapriya Kailasan Vanaja, Michael Bauer, Christoph Sponholz, Gabriel Rabinovich, Gregory Hudalla, Anthony Vella, Sachin Deshmukh, Beiyan Zhou, and Vijay Rathinam
- Subjects
Immunology ,Immunology and Allergy - Abstract
Activation of inflammatory caspases, such as caspase-11 and caspase-4, by lipopolysaccharide (LPS) from Gram-negative bacteria, is a key mechanism of innate immune defense against infections. This cytosolic LPS sensing pathway results in activation of a pore-forming protein, gasdermin D, which mediates an inflammatory form of cell death called pyroptosis. In addition, caspase-11-mediated cytosolic LPS sensing leads to the activation of caspase-1 and the maturation of IL-1b and IL-18. Importantly, cytosolic LPS-induced pyroptosis is associated with the release of intracellular proteins that act as alarmins or damage-associated molecular patterns (DAMPs) to modulate the inflammatory response and play an important role during infectious diseases and sepsis. However, the identity and function of DAMPs released downstream of caspase-11 activation are poorly characterized. Using a proteomic approach involving ProteomeLab’s PF2D fractionation system followed by mass spectrometry, we have discovered that galectin-1, a b-galactoside-binding lectin, is released as a consequence of cytosolic LPS sensing. By utilizing various mutant cell lines and primary cells we show that galectin-1 secretion is dependent on caspase-11 and gasdermin D, but not NLRP3 or caspase-1. Importantly, in vivo studies using galectin-1-deficient mice showed that galectin-1 acts as a DAMP to promote systemic inflammation and plays a detrimental role during septic shock. Additionally, human septic patients were found to have increased levels of galectin-1 in their serum. Taken together, we have characterized the secretion and function of a novel lectin DAMP released upon lytic cell death and provide new insights into outcomes of inflammasome activation.
- Published
- 2020
29. Nonlinear system parameter estimation of drying process using modified state transition algorithm in cloud environment
- Author
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Ankur Dumka, Karthik Chandran, Sathian Dananjayan, Loganathan Jayakumar, and Manikandan Ramasamy
- Subjects
020203 distributed computing ,Estimation theory ,business.industry ,Computer science ,Computer Networks and Communications ,Computation ,System identification ,Process (computing) ,Cloud computing ,02 engineering and technology ,Nonlinear system ,symbols.namesake ,Lagrange multiplier ,Convergence (routing) ,0202 electrical engineering, electronic engineering, information engineering ,symbols ,020201 artificial intelligence & image processing ,business ,Algorithm - Abstract
The parameter estimation optimisation with constraints for the nonlinear complex system requires a serious of computation. This paper introduced a novel constrained optimisation method named Lagrangian-based state transition algorithm (LSTA) to solve problems in distributed cloud computing environment. LSTA with the physical constraints involved in solving the problems which occurs while the conventional techniques are used. In LSTA, the updating of the result to an optimisation problem with constraints known as, a state transition. The Lagrangian multiplier is used as a constraint for state transition process to estimate the drying process system effectively. The experiments are conducted in the cloud computing environment and simulated results validated the proposed LSTA methodology for parameter estimation. This method is a promising way for system identification due to its searching competency, enduring performance considering physical limitations and quick convergence.
- Published
- 2020
30. The Effect of Inorganic Carbon Limitation on the Performance of the CANON system
- Author
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Suneethi Sundar, Hongkeun Park, Karthik Chandran, Yiwei Ma, and Kara Koetje
- Subjects
Total inorganic carbon ,Chemistry ,Environmental chemistry ,General Engineering ,Canon - Published
- 2012
31. Effects of temperature on the electrical impedance of piezoelectric elements
- Author
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Krishnamurthy, Karthik Chandran, Mechanical Engineering, Rogers, Craig A., Inman, Daniel J., and Lalande, Frederic
- Subjects
mechanical impedance ,LD5655.V855 1996.K757 - Abstract
A structural health monitoring technique, developed at the Center for Intelligent Material Systems and Structures, employs piezoelectric (PZT) materials for tracking the structural impedance to qualitatively identify damage. The mechanical impedance of a structure is a function of the structure's mass, stiffness, damping, and structural boundary conditions. Changes in any of the above-mentioned properties lead to a change in the mechanical impedance of the structure and a change in the impedance pattern of the structure. The mechanical impedance of a structure can be measured by coupling the electrical and mechanical impedances via PZT patches. Therefore any change in the mechanical impedance leads to a change in the electrical impedance of the PZT bonded to the structure of interest. However, change of the electrical impedance can also occur due to changes in temperature. Piezoelectric materials have been known to have temperature dependency regarding their basic properties, such as the dielectric constant and the piezoelectric coefficient. In this thesis, this temperature dependency will be investigated. The motivation of this work is linked to the impedance-based nondestructive evaluation (NDE) technique which employs PZT sensors for tracking changes in the structural impedance, by measuring the electrical impedance, to qualitatively identify damage. However, for this NDE technique to be successful in all types of environments, it must be insensitive to temperature variations. As mentioned earlier, piezoelectric materials have strong temperature dependency and a temperature compensation procedure is necessary. Therefore, two software correction techniques were developed to eliminate the effects of temperature in the electrical impedance measurements of PZT sensors. (NDE) technique which employs PZT sensors for tracking changes in the structural impedance, by measuring the electrical impedance, to qualitatively identify damage. However, for this NDE technique to be successful in all types of environments, it must be insensitive to temperature variations. As mentioned earlier, piezoelectric materials have strong temperature dependency and a temperature compensation procedure is necessary. Therefore, two software correction techniques were developed to eliminate the effects of temperature in the electrical impedance measurements of PZT sensors. The second correction technique is based on the sensor output. Through experimental investigation, it was found that temperature will have the effect of shifting the electrical impedance magnitude of the piezoelectric sensor, while leaving the impedance phase unaffected. To characterize the temperature effects in PZT materials, a temperature coefficient which is independent of frequency has defined. Finally, based on the defined temperature coefficient, a simple temperature compensation technique has been implemented successfully, eliminating the effects of temperature on PZT sensors while not eliminating the effects of temperature on the structure. Master of Science
- Published
- 1996
32. Chest CT Image based Lung Disease Classification - A Review.
- Author
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Kondamuri SR, Thadikemalla VSG, Suryanarayana G, Karthik C, Reddy VS, Sahithi VB, Anitha Y, Yogitha V, and Valli PR
- Subjects
- Humans, Lung diagnostic imaging, Lung Neoplasms diagnosis, Machine Learning, Deep Learning, Tomography, X-Ray Computed methods, Lung Diseases classification, Lung Diseases diagnostic imaging
- Abstract
Computed tomography (CT) scans are widely used to diagnose lung conditions due to their ability to provide a detailed overview of the body's respiratory system. Despite its popularity, visual examination of CT scan images can lead to misinterpretations that impede a timely diagnosis. Utilizing technology to evaluate images for disease detection is also a challenge. As a result, there is a significant demand for more advanced systems that can accurately classify lung diseases from CT scan images. In this work, we provide an extensive analysis of different approaches and their performances that can help young researchers to build more advanced systems. First, we briefly introduce diagnosis and treatment procedures for various lung diseases. Then, a brief description of existing methods used for the classification of lung diseases is presented. Later, an overview of the general procedures for lung disease classification using machine learning (ML) is provided. Furthermore, an overview of recent progress in ML-based classification of lung diseases is provided. Finally, existing challenges in ML techniques are presented. It is concluded that deep learning techniques have revolutionized the early identification of lung disorders. We expect that this work will equip medical professionals with the awareness they require in order to recognize and classify certain medical disorders., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)
- Published
- 2024
- Full Text
- View/download PDF
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