A Review on Deep Learning Algorithms in the Detection of Autism Spectrum Disorder
ASD; CNN; CRNN algorithms; Deep learning; LSTM; RNN
Autism spectrum disorder (ASD) is a neurodisorder that has an impact on how people interact and communicate with each other for the rest of their lives. Most autistic symptoms appear throughout the first two years of a child's life. This is why autism is called a behavioral disease. If you have a child with ASD, the problem starts in childhood and keeps going through adolescence and adulthood. Deep learning techniques are becoming more common in research on medical diagnosis. In this paper, there is an effort to see if convolutional neural network (CNN), recurrent neural network (RNN), long short-term memory network (LSTM), and a fusion technique known as convolutional recurrent neural network (CRNN) can be used to detect ASD problems in a child, adolescents, and adults. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Lecture Notes in Networks and Systems, Vol-865, pp. 283-297.
Springer Science and Business Media Deutschland GmbH
Lamani M.R., CHRIST (Deemed to Be University), Kanmanike, Kumbalgudu, Mysor Road, Karnataka, Bangalore, 560074, India; Julian Benadit P., CHRIST (Deemed to Be University), Kanmanike, Kumbalgudu, Mysor Road, Karnataka, Bangalore, 560074, India
A Review on Development and Properties of Ultra-High-Performance Concrete
Microstructural analysis; Particle packing density; Ultra-high-performance concrete
This study presents a review of literature on ultra-high-performance concrete that brings in information regarding the preparation of UHPC, mix design of UHPC on the basis of various particle packing density models, microstructural analysis, durability studies, and strength characteristics. A data base is collected to study the performance, mechanical strength and durability of UHPC from various research works. UHPC can found to be a long-term solution for present day challenges that is faced in construction industry when conventional concrete is used and makes this concrete a novel concept in concrete technology. The advantages of UHPC are: less porosity, high abrasion resistance, greater mechanical properties, high packing density, and improvement in fatigue behavior though the cost of UHPC is high. The non-availability of a standard code for mix design of UHPC makes it difficult to arrive at consistent and comparable mix. The cost of UHPC can be controlled with the use of naturally available materials and utilizing agricultural and industrial waste materials in UHPC. From the data collected, it is observed that the binder content can be optimized and cement which is residual in UHPC can be replaced by industrial residue like fly ash, GGBS, glass powder, etc. and thereby brings down the cost without compromising on the strength and performance. The information shared in this paper will help the contractors, consultants, engineers, industry stakeholders and researchers to alleviate the confusions regarding the use of UHPC in construction industry and to encourage research to make this concrete construction-industry friendly. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
Lecture Notes in Civil Engineering;Volume;666 LNCE;pp.95-114
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.1007/978-981-96-7971-3_8 https://www.scopus.com/pages/publications/105021000803?origin=resultslist
D B.M., Christ University, Bengaluru, India; Unnikrishnan S., Christ University, Bengaluru, India
A Review on EMG-based Pattern Identification Methods for Effective Controlling of Hand Prostheses
Classification Algorithms; Deep Learning; Electromyography; Hand Prosthesis; Recognition Accuracy
The ability of amputees to do daily duties is significantly restricted by upper limb amputation. The myoelectric prosthesis uses impulses from the surviving muscles in the stump to gradually restore function to such severed limbs. Such myosignals are unfortunately tedious and challenging to gather and employ. The process of transforming it into a user control signal after it has been acquired often consumes a significant amount of processing resources. By modifying machine learning strategies for pattern recognition, the factors that influence the traditional electromyography (EMG)-pattern identification approaches may be significantly minimized. Although more recent developments in intelligent pattern recognition algorithms could discern between a variety of degrees of freedom with high levels of accuracy, their usefulness in practical (amputee) applications was less obvious. This review paper examined how well various pattern recognition algorithms for hand prostheses performed. Finally, we discussed the current difficulties and offered some suggestions for future research in our paper's conclusion. 2023 IEEE.
Ramkumar S.; Rema D.; Devi T.A.; Elavarasi K.; Selvaganapathi T.; Gokila S.
3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023 - Proceedings, pp. 517-523.
Institute of Electrical and Electronics Engineers Inc.
Ramkumar S., Christ (Deemed to Be University), Department of Computer Science, Bangalore, India; Rema D., Karpagam Academy of Higher Education, Department of Food Technology, Coimbatore, India; Devi T.A., Karpagam Academy of Higher Education, Department of Food Technology, Coimbatore, India; Elavarasi K., Karpagam Academy of Higher Education, Department of Electrical and Electronics Engineering, Coimbatore, India; Selvaganapathi T., Karpagam Academy of Higher Education, Department of Electrical and Electronics Engineering, Coimbatore, India; Gokila S., Karpagam Institute of Technology, Department of CSE, Coimbatore, India
A review on ensembles-based approach to overcome class imbalance problem
Bagging; Boosting; Class imbalance; Classification; Ensemble; Ensemble approach for class imbalance; Sampling
Predictive analytics incorporate various statistical techniques from predictive modelling, machine learning and data mining to analyse large database for future prediction. Data mining is a powerful technology to help organization to concentrate on most important data by extracting useful information from large database. With the improvement in technology day by day large amount of data are collected in raw form and as a result necessity of using data mining techniques in various domains are increasing. Class imbalance is an open challenge problem in data mining and machine learning. It occurs due to imbalanced data set. A data set is considered as imbalanced when a data set contains number of instance in one class vastly outnumber the number of instances in other class. When traditional data mining algorithms trained with imbalanced data sets, it gives suboptimal classification model. Recently class imbalance problem have gain significance attention from data mining and machine learning researcher community due to its presence in many real world problem such as remote-sensing, pollution detection, risk management, fraud detection and medical diagnosis. Several methods have been proposed to overcome the problem of class imbalance problem. In this paper, our goal is to review various methods which are proposed to overcome the effect of imbalance data on classification learning algorithms. Springer Nature Singapore Pte Ltd 2019.
Advances in Intelligent Systems and Computing, Vol-906, pp. 155-172.
Kumar S., Department of CSE, Christ(Deemed to BeUniversity), Bengaluru, 560029, India; Madhuri J.N., Department of CSE, Christ(Deemed to BeUniversity), Bengaluru, 560029, India; Goswami M., Department of CSE, Christ(Deemed to BeUniversity), Bengaluru, 560029, India
A review on ethanol tolerance mechanisms in yeast: Current knowledge in biotechnological applications and future directions
Biofuels; Ethanol production; Ethanol tolerance; Fermentation; Saccharomyces cerevisiae; Sustainability; Yeast stress
Saccharomyces cerevisiae is one of the prominent strains in the brewing and bioethanol industries and has been used for many industrial purposes for ages. Though the organism is an outstanding ethanol producer, the major limiting factor is the stress the organism undergoes during fermentation. One of the significant stresses is the ethanol stress, created by ethanol accumulation in the medium. The ethanol starts to interact with the yeast cell membrane; further, as ethanol concentration increases, it affects a lot of cell organelles. Thereby, cellular activities get disrupted, causing cell death and hence reducing ethanol production. The organism has developed many strategies to overcome this stress by activating the stress response pathway, which regulates many genes involved in modifying the cell membrane cell wall, renaturation of proteins, and altering the metabolism. However, with higher ethanol concentrations, the yeast cells will be unable to tolerate, leading to cell death. Hence, to minimize cell death at higher ethanol concentrations, there is a need to understand the effect of ethanol and its response by the organism; this helps improve the ethanol tolerance of the organism and, thereby, ethanol production. Although many research works are carried out to understand the vital aspect of the tolerance and are reported, very few review papers cover all these points. Hence, this review is designed to include information on all the elements of ethanol tolerance, i.e., ethanol tolerance of different strains of S. cerevisiae, the effect of ethanol on the yeast cells, the mechanism used to tolerate the ethanol, and various techniques developed to improve the ethanol tolerance of the yeast cells. 2024 Elsevier Ltd
Sahana G.R.; Balasubramanian B.; Joseph K.S.; Pappuswamy M.; Liu W.-C.; Meyyazhagan A.; Kamyab H.; Chelliapan S.; Joseph B.V.
Process Biochemistry, Vol-138, pp. 1-13.
https://doi.org/10.1016/j.procbio.2023.12.024 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183024475&doi=10.1016%2fj.procbio.2023.12.024&partnerID=40&md5=80974ce4f3b4bd62688f58bb9587ccbf
Sahana G.R., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, 560 029, India; Balasubramanian B., Department of Food Science and Biotechnology, College of Life Science, Sejong University, Seoul, South Korea; Joseph K.S., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, 560 029, India; Pappuswamy M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, 560 029, India; Liu W.-C., Department of Animal Science, College of Coastal Agricultural Sciences, Guangdong Ocean University, Zhanjiang, 524088, China; Meyyazhagan A., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, 560 029, India; Kamyab H., Faculty of Architecture and Urbanism, UTE University, Calle Rumipamba S/N and Bourgeois, Quito, Ecuador, Department of Biomaterials, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences, Chennai, 600 077, India, Process Systems Engineering Centre, Department of Chemical and Energy Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor, Skudai, Malaysia; Chelliapan S., Engineering Department, Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia, Kuala Lumpur, Jln Sultan Yahya Petra, 54100, Malaysia; Joseph B.V., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, 560 029, India
A review on extraction and separation of cellulose fibers from agro wastes
Over the past few decades, there was significant increase in research concerning resources that have certain desirable characteristics like renewability, ease of availability, economic value, excellent mechanicalthermal properties, biocompatibility and biodegradability. Cellulose is one such resource that possesses these characteristics and yet various sources that constitute ample quantities of lignocellulose are discarded, as their peculiarities and applications were not widely known to the population. Agro wastes, which are generated every year at a tremendous rate, are viewed as a promising substrate for the commercial extraction of cellulose. Hence in this review, an appropriate utilization of these agricultural by-products, with respect to extraction of cellulose is discussed, so as to ameliorate their applications in an aim to diminish the disposal rate of essential commodities. 2021 World Research Association. All rights reserved.
Research Journal of Chemistry and Environment, Vol-25, No. 10, pp. 158-171.
Kariyadan S., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India
A review on feature selection algorithms
Classification; Feature selection; Genetic algorithm; Wrapper method
A large number of data are increasing in multiple fields such as social media, bioinformatics and health care. These data contain redundant, irrelevant or noisy data which causes high dimensionality. Feature selection is generally used in data mining to define the tools and techniques available for reducing inputs to a controllable size for processing and analysis. Feature selection is also used for dimension reduction, machine learning and other data mining applications. A survey of different feature selection methods are presented in this paper for obtaining relevant features. It also introduces feature selection algorithm called genetic algorithm for detection and diagnosis of biological problems. Genetic algorithm is mainly focused in the field of medicines which can be beneficial for physicians to solve complex problems. Finally, this paper concludes with various challenges and applications in feature selection. Springer Nature Singapore Pte Ltd 2019.
Colaco S.; Kumar S.; Tamang A.; Biju V.G.
Advances in Intelligent Systems and Computing, Vol-906, pp. 133-153.
Colaco S., Department of CSE, Christ(Deemed to Be University), Bangalore, 560029, India; Kumar S., Department of CSE, Christ(Deemed to Be University), Bangalore, 560029, India; Tamang A., Department of CSE, Christ(Deemed to Be University), Bangalore, 560029, India; Biju V.G., Department of CSE, Christ(Deemed to Be University), Bangalore, 560029, India
A Review on Fish Skin-Derived Gelatin: Elucidating the Gelatin PeptidesPreparation, Bioactivity, Mechanistic Insights, and Strategies for Stability Improvement
applications; bio-functionality; characteristics; fish skin; gelatin; gelatin peptides; limitations; stability
Fish skin-derived gelatin has garnered significant attention recently due to its abundant availability and promising bioactive properties. This comprehensive review elucidates various intricacies concerning fish skin-derived gelatin peptides, including their preparation techniques, bioactive profiles, underlying mechanisms, and methods for stability enhancement. The review investigates diverse extraction methods and processing approaches for acquiring gelatin peptides from fish skin, emphasizing their impact on the peptide composition and functional characteristics. Furthermore, the review examines the manifold bioactivities demonstrated by fish skin-derived gelatin peptides, encompassing antioxidant, antimicrobial, anti-inflammatory, and anticancer properties, elucidating their potential roles in functional food products, pharmaceuticals, and nutraceuticals. Further, mechanistic insights into the functioning of gelatin peptides are explored, shedding light on their interactions with biological targets and pathways. Additionally, strategies aimed at improving the stability of gelatin peptides, such as encapsulation, modification, and integration into delivery systems, are discussed to extend the shelf life and preserve the bioactivity. Overall, this comprehensive review offers valuable insights into using fish skin-derived gelatin peptides as functional ingredients, providing perspectives for future research endeavors and industrial applications within food science, health, and biotechnology. 2024 by the authors.
Joy J.M.; Padmaprakashan A.; Pradeep A.; Paul P.T.; Mannuthy R.J.; Mathew S.
Multidisciplinary Digital Publishing Institute (MDPI)
https://doi.org/10.3390/foods13172793 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203655048&doi=10.3390%2ffoods13172793&partnerID=40&md5=e94564c423f3a2e64b8006357c0255e9
Joy J.M., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India, Faculty of Marine Sciences, Cochin University of Science and Technology, Kerala, Cochin, 682022, India, Department of Zoology, St. Teresas College (Autonomous), Kerala, Ernakulam, 682011, India; Padmaprakashan A., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India, Faculty of Marine Sciences, Cochin University of Science and Technology, Kerala, Cochin, 682022, India, Department of Life Sciences, Christ University, Hosur Main Road, Bhavani Nagar, Karnataka, Bangalore, 560029, India; Pradeep A., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India, Faculty of Marine Sciences, Cochin University of Science and Technology, Kerala, Cochin, 682022, India; Paul P.T., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India, Faculty of Marine Sciences, Cochin University of Science and Technology, Kerala, Cochin, 682022, India; Mannuthy R.J., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India, Faculty of Marine Sciences, Cochin University of Science and Technology, Kerala, Cochin, 682022, India; Mathew S., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India
A Review on Flood Prediction Algorithms and A Deep Neural Network Model for Estimation of Flood Occurrence
Gated Recurrent Units (GRU); Long Short-Term Memory (LSTM)network; Multilayer Perception Layer (MLP) architecture; Precipitation; Recurrent Neural Network (RNN)
Flood occurs as often as possible happens due to many environmental changes in our planet in the present years. The occurrence and damages caused by flood is very high. Major cause of flood is due to heavy rainfall which in turn increases the water level of the rivers and other water bodies. The various factors that play a major role in the occurrence of rainfall are rise in temperature, humidity level, dew point, pressure in and around the area of concern, wind speed, etc. In order to reduce the number of victims due to flood it is necessary to have a system to predict flood occurrence. In this paper, we classify and analyzed the various prediction algorithms which show usage of Deep Neural Network produces better results. In addition, a design model has been proposed to predict the flood by training the Deep Neural Network with the above-mentioned factors. 2020, Asian Research Association. All rights reserved.
Ullah T.F.; Gnana Prakasi O.S.; Kanmani P.
International Research Journal of Multidisciplinary Technovation, Vol-2, No. 5, pp. 8-14.
https://doi.org/10.34256/irjmt2052 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130881065&doi=10.34256%2firjmt2052&partnerID=40&md5=a7e437201302286858f3e007e63e7c80
Ullah T.F., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Gnana Prakasi O.S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Kanmani P., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India
A Review On Geospatial Intelligence For Investigative Journalism
Geospatial Intelligence; Investigative Journalism; Satellite Imagery; Suez Canal; Uttarakhand Landslide
Throughout the ongoing Russian invasion of Ukraine, satellite images like the vast convoy of Russian military vehicles approaching the beleaguered Ukrainian city of Kyiv, Russian aircraft deployed at Zyabrovka, Belarus and many more such visuals have been in circulation and are being used as a tool to facilitate investigative journalistic studies. Such satellite-based images are one of the latest means of accessing vital data that can help in expanding the scope and impact of investigative journalism. Geospatial intelligence uses varied graphical content to convey information about the activities that occur on the surface of the earth. It includes colour and panchromatic (black and white) aerial photographs, multispectral or hyperspectral digital imagery, and products such as shaded relief maps or three-dimensional images produced from digital elevation models. The improving technology in geospatial spectra has broadened the scope of its usage to investigative journalism which lies at the core of this review paper. Some of the path-breaking journalistic stories that have come up in the past decade - imaging of the Uttarakhand landslide in 2021 using satellite images, coverage of the Fukushima nuclear plant since 2011, and 2021 tracking of Asia's border disputes emerging due to climate change and the satellite journalism built around the blockage of Suez canal in 2021 - showcase the potential that geospatial intelligence has in the domain of journalism. All four identified stories point out how we can practice satellite-based investigative studies, especially, for scrutinizing and comparing historical records regarding cross-border issues as well as the disappearance of pastures and forests in vast open lands. However, the arena of using geospatial intelligence, enabled by satellite images, remains underutilized and limited to specific journalistic organizations, based in a few countries. This exploratory review of the four mentioned journalistic accounts identifies the contexts where such efforts are feasible, methods that are required, sources that could be tapped, associated skill sets needed for its usage, the dynamics of such investigative approaches, and their scope and limitations. This review and the conclusions drawn from the above-mentioned cases provides a direction for journalists from small organizations and low income countries to explore the potential of satellite-based images in furthering their investigative reporting with a technological edge that persists to be sovereign in the geopolitical powerplay. Copyright 2022 by the International Astronautical Federation (IAF). All rights reserved.
Harshitha V.; Nainani M.; Padmakumar M.M.; Kumar R.
Proceedings of the International Astronautical Congress, IAC, Vol-2022-September
International Astronautical Federation, IAF
Harshitha V., Department of Media and Communication Studies, Christ Deemed to be University, Hosur Road, Bhavani Nagar, S G Palya, Karnataka, Bengaluru, 560054, India; Nainani M., Department of Media and Communication Studies, Christ Deemed to be University, Hosur Road, Bhavani Nagar, S G Palya, Karnataka, Bengaluru, 560054, India; Padmakumar M.M., Department of Media and Communication Studies, Christ Deemed to be University, Hosur Road, Bhavani Nagar, S G Palya, Karnataka, Bengaluru, 560054, India; Kumar R., Grahaa Space, Lomonosov Moscow State University (MSU), Karnataka, Bengaluru, India
A Review on Influence of Cutting Fluid on Improving the Machinability of Inconel 718
Ceramic inserts; CNC milling machine; Flank surface; Inconel 718; Rake surface
Nickel-based superalloys are widely used in the production and manufacturing sectors that require processes or applications that endure or operate at very high superheating temperatures. With the properties of high tensile strength, high melting point, and lightweight structural arrangement of molecules within the alloy material composition makes it more suitable for industrial utilization in aerospace industries and marine applications. This review paper discusses the use of various coolant lubricants that improves the machinability of Inconel 718 based on parameters such as surface roughness and tool wear under the influence of cutting speed, feed rate, and depth of cut. The machine used for analysis is CNC milling machine which will be used for experimentation using ceramic inserts as end milling tool. Various cooling techniques such as hybrid cooling, flood emulsion cooling, minimum quantity lubrication, and cryogenic cooling are being summarized in this paper from various experimentations and conclusions of other authors. On the basis of review, the hybrid cooling technique is found to be better than other cooling techniques because of its ability to obtain long tool life and smoother surface finish on the workpiece. With the use of these reviewed data, further research for finding a more compatible and effective cooling lubricant has to be done by experimentation in order to obtain an improved machining process for Inconel 718 material. 2020, Springer Nature Singapore Pte Ltd.
Sivadasan P.; Sharma G.S.; Rout I.S.; Pal Pandian P.
Springer Proceedings in Materials, Vol-8, pp. 497-504.
Sivadasan P., CHRIST (Deemed to be University), Bangalore, India; Sharma G.S., CHRIST (Deemed to be University), Bangalore, India; Rout I.S., CHRIST (Deemed to be University), Bangalore, India; Pal Pandian P., CHRIST (Deemed to be University), Bangalore, India
A review on metal nanoparticles from medicinal plants: Synthesis, characterization and applications
Anti-cancerous; Anti-diabetic; Anti-larval; Anti-microbial; Dye degradation; Food preservation; Green nanotechnology; Medicinal plants; Plant growth enhancement
Plant extracts contain secondary metabolites which have the potential to act as reducing and stabilizing agents contributing to a greener and more efficient method to synthesize nanoparticles. Rapid growth of Nanotechnology has led to an increased demand in various fields. This review summarizes the use of potent medicinal plant extracts to synthesize metal nanoparticles, methods employed to characterize the properties of the nanoparticles and its application. Characterization of the nanoparticle based on its shape, size, chemical bonds, surface properties, hydrodynamic diameter and crystalline structure using techniques such as UV-Visible Spectroscopy, XRD (X-ray Diffraction), TEM (Transmission Electron Microscopy), SEM (Scanning Electron Microscopy), EDS (X-ray energy dispersive spectroscopy), DLS (Dynamic Light Scattering), Zeta Potential and FTIR (Fourier Transform-Infrared Spectroscopy) are elaborated. The synthesized metal nanoparticles have wide ranges of applications such as antimicrobial activity, antioxidative capability, anticancer effect, antidiabetic properties, plant growth enhancement, dye degradation effects and anti-larval properties. Recent advances in nanotechnology with special emphasis on plant metabolites provide an insight into their usage as plant-derived edible nanoparticles (PDNPs). Applications, limitations and future prospects of this technology have also been briefly discussed. 2021 Bentham Science Publishers.
Nanoscience and Nanotechnology - Asia, Vol-11, No. 5
George J.A., Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, India; Sundar S., Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, India; Paari K.A., Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, India
A review on power quality issues in electric vehicle interfaced distribution system and mitigation techniques
Distribution systems; Electric vehicles; Harmonic imbalance; Harmonics and voltage imbalance; Power quality issue mitigation
Electric vehicles (EV) penetration in the distribution systems is evident and intended to grow day by day. Power quality issues pop up in the distribution system with an increase in EV penetration. Distribution networks need to consider the power quality issues developed due to the penetration of EVs for planning and designing the system. The power quality issues, including voltage imbalance, total harmonic distortion, distribution transformer failure, and related issues, are anticipated due to EV penetration in distribution systems. Detailed review of power quality issues and mitigation techniques are detailed in this paper. Discussion on the effect of these power quality issues on the distribution systems and corresponding mitigation measures are detailed. Power quality impact mitigation techniques have been discussed recently, which exploits the bidirectional power flow of vehicle to grid vehicle to grid (V2G) and grid to vehicle grid-to-vehicle (G2V). Methods and methodologies that mitigate power quality problems in the EV penetrated distribution system is discussed. Bidirectional power flow during EV charging and discharging and power quality issues in this topology is detailed in this review paper. A discussion on future trends and different possible future research paradigms is discussed as the review's conclusion. 2022 Institute of Advanced Engineering and Science. All rights reserved.
Indonesian Journal of Electrical Engineering and Computer Science, Vol-25, No. 2, pp. 656-665.
Institute of Advanced Engineering and Science
All Open Access; Gold Open Access; Green Open Access
https://doi.org/10.11591/ijeecs.v25.i2.pp656-665 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124668280&doi=10.11591%2fijeecs.v25.i2.pp656-665&partnerID=40&md5=e7554f3ab349366522381fc663f5766a
Harish B.N., Department of Electrical and Electronics Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India; Surendra U., Department of Electrical and Electronics Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India
A review on prediction of cardiac arrest analysis in early stage
Cardiac Arrest; Early prediction; Electrocardiogram
Cardiac arrest occurs as the heart muscle fails to contract properly, resulting in a sudden loss of blood supply. The ECG signal is one of the techniques for detecting cardiac electrical activity and is used to investigate heart block. In this paper different standardized work for early detection of cardiac arrest is described. Stages of ECG signal pre-processing involves denoised using digital filtering algorithms and extracting different features from clean ECG predicting cardiac arrest in early stage. Several other body parameters were also considered for this purpose. In this work denoising validation parameters were compared for showing effectiveness of the filtering algorithm and several body parameters and its implication on cardiac arrest was described. 2022 Author(s).
Mukherjee C.; Selvi J.T.; Ramesh M.; Thomas L.; Anusuya M.; Lakwal V.R.
https://doi.org/10.1063/5.0074439 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131202895&doi=10.1063%2f5.0074439&partnerID=40&md5=2d3a74aaa5392eda9f3ea1098a160a92
Mukherjee C., Department ECE, Christ (Deemed to Be University), Bangalore, India; Selvi J.T., Department of ECE, SriSairam Engineering College, Tambaram west, Tamilnadu, Chennai, India; Ramesh M., Department of ECE, Saveetha School of Engineering, Thandalam, Chennai, India; Thomas L., Department of Social Work, Vimala College (Autonomous) Thrissur, Kerala, India; Anusuya M., IndraGanesan College of Engineering, Manikandam, Tamilnadu, Trichy, India; Lakwal V.R., Department of Zoology, Nanasaheb Yashwantrao Narayanrao, Chavan Arts, Science and Commerce College Chalisgaon Dist, MS, Jalgaon, India
A Review on Preprocessing Techniques for Noise Reduction in PET-CT Images for Lung Cancer
Computed tomography (CT); Discrete wavelet transform (DWT); Peak-to signal noise ratio (PSNR); Positron emission tomography (PET)
Cancer is one of the leading causes of death. According to World Health Organization, lung cancer is the most common cause of cancer deaths in 2020, with over 1.8 million deaths. Therefore, lung cancer mortality can be reduced with early detection and treatment. The components of early detection require screening and accurate detection of the tumor for staging and treatment planning. Due to the advances in medicine, nuclear medicine has become the forefront of precise lung cancer diagnosis. Currently, PET/CT is the most preferred diagnostic modality for lung cancer detection. However, variable results and noise in the imaging modalities and the lung's complexity as an organ have made it challenging to identify lung tumors from the clinical images. In addition, the factors such as respiration can cause blurry images and introduce other artifacts in the images. Although nuclear medicine is at the forefront of diagnosing, evaluating, and treating various diseases, it is highly dependent on image quality, which has led to many approaches, such as the fusion of modalities to evaluate the disease. In addition, the fusion of diagnostic modalities can be accurate when well-processed images are acquired, which is challenging due to different diagnostic machines and external and internal factors associated with lung cancer patients. The current works focus on single imaging modalities for lung cancer detection, and there are no specific techniques identified individually for PET and CT images, respectively, for attaining effective and noise-free hybrid imaging for lung cancer detection. Based on the survey, it has been identified that several image preprocessing filters are used for different noise types. However, for successful preprocessing, it is essential to identify the types of noise present in PET and CT images and the appropriate techniques that perform well for these modalities. Therefore, the primary aim of the review is to identify efficient preprocessing techniques for noise and artifact removal in the PET/CT images that can preserve the critical features of the tumor for accurate lung cancer diagnosis. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Lecture Notes on Data Engineering and Communications Technologies, Vol-111, pp. 455-475.
Das K.P., Department of Computer Science, Christ (Deemed to be University), Hosur Road, Bangalore, 560029, India; Chandra J., Department of Computer Science, Christ (Deemed to be University), Hosur Road, Bangalore, 560029, India
A review on quantum utility for secure authentication protocol towards cryptographic standard in quantum dot cellular automata
ajority gate; Cipher; Clocking scheme; Mux and De-Mux; n value; Parity; PRBS; Quantum dot cellular automata (QCA); Quantum enhancement security level to optimized entanglement states; Schrodinger
QCA, which stands for Quantum Dot-Cellular Automata, is a nanotechnology model that offers an alternative solution to the widely used CMOS technology. Unlike CMOS, QCA is a semiconductor-less technology that transmits information based on the charge of electrons and the electrostatic repulsion between them. This technology provides several advantages over CMOS, including higher device density, faster switching speed, and lower power consumption. When it comes to cryptographic applications, QCA circuits can be extremely useful. Both encryption and decryption processes can be implemented using logic circuits based on QCA. The research paper describes a basic method for generating ciphertext in QCA, which is useful in secure nano communication based on QCA. The paper discusses how to achieve secure authentication in encrypted communication using QCA. To evaluate the performance and test the proposed method, the researchers used the QCA Designer-2.0.3 tool. This is a software tool specifically designed for designing and simulating QCA circuits. It enables researchers to model and analyze the behavior of QCA-based systems, allowing them to evaluate the effectiveness and feasibility of their proposed encryption technique. Overall, the research paper aims to present a secure encryption method using QCA and demonstrates its implementation and testing using the QCA Designer-2.0.3 tool. By leveraging the unique properties of QCA, such as high device density and low power consumption, the researchers aim to provide a novel approach for secure nano communication and cryptographic applications. Taru Publications.
Tapna S.; Chakrabarti K.; Mukhopadhyay D.
Journal of Discrete Mathematical Sciences and Cryptography, Vol-27, No. 4, pp. 1415-1423.
https://doi.org/10.47974/JDMSC-1995 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199253325&doi=10.47974%2fJDMSC-1995&partnerID=40&md5=6cdc888514e987cc6a359e5969e5982d
Tapna S., Department of Electronics & Communication Engineering, Brainware University, West Bengal, Barasat, 700125, India; Chakrabarti K., Department of Electronics & Communication Engineering, Haldia Institute of Technology, West Bengal, Haldia, 721657, India; Mukhopadhyay D., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India
A Review on Recent Scheduling Algorithms in the Cloud Environment
Cloud users and service providers are the leading players in the cloud computing environment. This environment comprises data centers, hosts, agents and virtual machines. The cloud users application of varied loads is leased on the providers resources. Scientific applications are large-scale complex workflow problems that demand more computing power. The cloud fulfills the workflow requirements of huge availability and increased computational power. One of the most crucial issues of cloud computing is scheduling tasks for the systems effective functioning. This paper reviews several existing task-scheduling techniques based on diverse metrics. This work will help the investigators to gain a better understanding of task scheduling techniques. In order to boost an algorithms performance, a few strategies are offered. 2023 American Institute of Physics Inc.. All rights reserved.
AIP Conference Proceedings, Vol-2909, No. 1
https://doi.org/10.1063/5.0183242 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179871371&doi=10.1063%2f5.0183242&partnerID=40&md5=7ccfc6fa3355bbd038f43d4edcbb4d7c
Sripavithra C.K., Dept. of Computer Science, Christ (Deemed to be University), Central Campus, Bangalore, India, Dept. of Computer Science, Maharanis Science College for Women (Autonomous), Mysore, India; Kirubanand V.B., Dept. of Computer Science, Christ (Deemed to be University), Central Campus, Bangalore, India
A Review on Recent Trends in Biological Applications of Non-conjugated Polymer Dots
Antibacterial; Bioimaging; Biosensing; Drug delivery; Fluorescence; Non-conjugated polymer dots
With the advancement of zero-dimensional carbon materials, carbon dots (CDs) have received immense attention owing to their exceptional optical properties, tailoring of size, and ease of functionalization. They have wide applications in fluorescent sensing, chemical sensing, bioimaging, photocatalysis, etc. Zero-dimensional polymer nanoparticles are called polymer dots (PDs) and are classified into conjugated and non-conjugated PDs based on their conjugated system. Non-conjugated polymer dots (NCPDs) do not have specific conjugated fluorophore groups, but they have superior chemical stability and water solubility than the conjugated PDs. The carbon core of NCPDs is surrounded by polymer chains containing ample functional groups such as C=O, N=O, and C=N, which are responsible for the luminescent PDs. NCPDs are less toxic, photostable, and biocompatible and are relevant in biological explorations in bioimaging, drug delivery, biosensing, etc. This mini-review provides a systematic overview of the inherent properties and the biological applications of NCPDs. It also emphasises the synergistic impacts on the optical performance of modified PDs and significant future research concerns. Graphical Abstract: [Figure not available: see fulltext.]. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Journal of Inorganic and Organometallic Polymers and Materials, Vol-33, No. 11, pp. 3340-3354.
Mathew A.A., Department of Physics and Electronics, Christ University, Karnataka, Bangalore, 560029, India; Balachandran M., Department of Physics and Electronics, Christ University, Karnataka, Bangalore, 560029, India
A Review on Rural Womens Entrepreneurship Using Machine Learning Models
Machine learning model; MSME; Rural entrepreneurship; Women
Rural womens entrepreneurship has contributed significantly to the countrys economy. Entrepreneurship rates have fluctuated in recent years, according to a variety of reasons including economic, social, and cultural influences. Therefore, machine learning models are used to assess the features to make better business decisions. In this research paper, papers from 2009 to 2022 were studied and found that machine learning models are being used to improve womens entrepreneurship. In this paper, nine machine learning models have been described in detail which include multiple regression, lasso regression, logistic regression, decision tree, Naive Bayes, clustering, classification, deep learning, artificial neural network, etc. In the study of all these models, it was found how accurately this model has been used in womens entrepreneurship work. It has been observed that by using different machine learning models with the data acquired from rural entrepreneurship, women entrepreneurs may use a new way of understanding the dynamics of rural entrepreneurship. Various machine learning models have been studied to improve rural development for women working in rural areas. Thus, we have proposed a comparative study of various machine learning models to predict entrepreneurship-based data. The findings of this study may be used to assess how rural women entrepreneurs may change the decisions made in several domains, such as making use of different economic policies and promoting the long-term viability of women entrepreneurs for the countrys economic growth. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
Pareek S.; Bhatnagar V.; Poonia R.C.; Sharma S.; Samanta D.
Lecture Notes in Networks and Systems, Vol-680 LNNS, pp. 375-395.
Pareek S., Department of Computer Applications, Manipal University Jaipur, Rajasthan, Jaipur, India; Bhatnagar V., Department of Computer Applications, Manipal University Jaipur, Rajasthan, Jaipur, India; Poonia R.C., Professor, Department of Computer Science, CHRIST (Deemed to be University), Delhi NCR, Uttar Pradesh, Ghaziabad, India; Sharma S., Department of Computer Applications, Manipal University Jaipur, Rajasthan, Jaipur, India; Samanta D., Department of Computing Information Technologies, RIT Kosovo (A.U.K), Rochester Institute of Technology RIT Global Campus n.n., Germia Campus, Pristina, Kosovo, 10000
A review on semiconductor nanoparticles in photovoltaic cells /
International Journal of Advanced Scientific Research And Management, Vol.4, Issue 4, pp.43-50, ISSN No: 2455-6378.
International Journal of Advanced Scientific Research And Management