Eggshells biowaste for hydroxyapatite green synthesis using extract piper betel leaf - Evaluation of antibacterial and antibiofilm activity
Antibacterial property; Antibiofilm activity; HAp composites; Hydroxyapatite; Piper betel leaf
The present research work reports the biosynthesis of hydroxyapatite (HAp) from eggshells and green synthesis of HAp from eggshells with incorporation of Piper betel leaf extract (PBL-HAp) using microwave conversion method. Although there are several works on synthesis of HAp from eggshells and other calcium and phosphorus rich substrates, the incorporation of herbal extract with HAp to promote antimicrobial and antibiofilm activity is less explored and reported. This research work highlights a simple and cost-effective method for development of antimicrobial biomaterials by combining the concepts of waste management, biomaterial science, and herbal medicine. In the present study, characterization of synthesized HAp was applied by X-ray Diffraction (XRD), Fourier Transform Infrared (FTIR) spectroscopy, Proton Nuclear Magnetic Resonance (1H NMR) spectroscopy, and morphological analysis using Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). The characterization results indicated that the prepared HAp and PBL-HAp were pure b-type carbonated HAp. The PBL-HAp was checked for its antibacterial activity using the well diffusion method and biofilm inhibitory activity by crystal violet assay against some common pathogens. The antibacterial activities against Staphylococcus aureus and biofilm inhibitory activities against Escherichia coli, Vibrio harveyi, Pseudomonas aeruginosa, and Staphylococcus aureus of Piper betel leaf extract coated HAp (PBL-HAp) were showed to be significant and offered a promising role for the development of potent dental biomaterials. 2021 Elsevier Inc.
Umesh M.; Choudhury D.D.; Shanmugam S.; Ganesan S.; Alsehli M.; Elfasakhany A.; Pugazhendhi A.
ISSN: 139351; PubMed ID: 34129868; CODEN: ENVRA
https://doi.org/10.1016/j.envres.2021.111493 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107980241&doi=10.1016%2fj.envres.2021.111493&partnerID=40&md5=04efa0256aacc537bc5a4ecf6b4d45f5
Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, Karnataka, India; Choudhury D.D., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, Karnataka, India; Shanmugam S., Bioprocess Laboratory, Department of Microbial Biotechnology, Bharathiar University, Coimbatore, 641046, India; Ganesan S., Department of Safety, Health and Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City, 807, Taiwan; Alsehli M., Mechanical Engineering Department, College of Engineering, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia; Elfasakhany A., Mechanical Engineering Department, College of Engineering, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia; Pugazhendhi A., School of Renewable Energy, Maejo University, Chiang Mai, 50290, Thailand, College of Medical and Health Science, Asia University, Taichung, Taiwan
Microbial Fuel Cells: The Microbial Route for Bioelectricity
Bioelectricity; Electrodes; Energy; Membranes; Microbial fuel cells
The quest for sustainable energy sources serves as the essential pillar for development of humans since the dawn of civilization. The alarming increase in demand of energy, especially electricity propelled the need to screen for alternative sources of energy over the conventional fossil based non-renewable counterparts. Electricity generation through microbial route functions by the fundamental phenomena of electron transport chain and the microbes operate as the source of energy production utilizing the substrate. Since its initiation, microbial fuel cell has gained a lot of research focus from all over the world. The integration of waste treatment with power generation was highlighted as the most productive and sustainable part of microbial fuel cells. Over the past few decades, a lot of research and development was done on improving the design of fuel cells, searching for cost-effective electrodes and membranes for commercialization. Despite tremendous research done on this domain, its commercialization still faces a lot of hurdles especially once it comes to the overall maintenance and production cost. This chapter summarizes the basic architecture of different microbial fuel cells and the challenges that need to be addressed for making microbial fuel cells a sustainable route for the bioelectricity generation from microorganisms. Springer Nature Singapore Pte Ltd. 2020.
Bioelectrochemical Systems: Vol.2 Current and Emerging Applications, Vol-2, pp. 375-398.
Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Hamza H.M.C., Department of Environmental Sciences, Bharathiar University, Tamil Nadu, Coimbatore, India
Fish waste valorisation through production of biodiesel and biopolymers for sustainable development: A mini review
Biofuel; Biopolymer; Remediation; Renewable sources; Sustainability; Sustainable development
Fish processing waste accounts for one of the major classes of food waste generated worldwide in terms of the high volume of waste generated. The presence of high amounts of organic compounds (proteins: 1530 %, lipids: 520 %) in fish waste makes them highly susceptible to autolysis which when not managed properly pose adverse effects on the environment like production of offensive odor, generation of hydrogen sulfide, higher biological oxygen demand (1000 mg/L to 12,000 mg/L or even higher) (BOD), and multiplication of pathogenic bacteria. Fish waste is rich in lipids and polysaccharides that can be channelized for biodiesel and biopolymer production respectively. Biodiesel refers to the biofuel produced from transesterification of plant and animal fats. Extraction of oils from fish waste followed by transesterification reactions can yield biodiesel through a biorefinery approach. Biorefinery concept emphasizes the conversion of biomass into commercially important byproducts. Biopolymers refers to the natural polymers that can be extracted from the natural sources or produced through microbial fermentation process. Furthermore, commercially important biopolymers like chitosan and polyhydroxyalkanoates (PHAs) can be used as biorefineries. This review work presents the sequential strategies for conversion of fish waste to biodiesel, PHA and chitosan through various physicochemical and biological methods. The review also presents the existing challenges and the future in the fish waste biorefinery concept. The scope of this review is to present a broader concept of integrating fish waste biorefinery for production of multiple value added products like biodiesel and biopolymers. 2025 Elsevier Ltd
Umesh M.; Kumar V.; Priyanka K.; Kathirvel P.; Suresh S.; Santhosh A.S.
https://doi.org/10.1016/j.biteb.2025.102045 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215840797&doi=10.1016%2fj.biteb.2025.102045&partnerID=40&md5=d67e056a26a1dc512b0842592323a572
Umesh M., Department of Life Sciences, Christ University, Karnataka, Bangalore, India; Kumar V., Biomaterials & Tissue Engineering (BITE) Laboratory, Department of Community Medicine, Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences (SIMATS), Thandalam, Chennai, 602105, India; Priyanka K., Department of Microbial Biotechnology, Bharathiar University, Tamil Nadu, Coimbatore, India; Kathirvel P., Department of Microbial Biotechnology, Bharathiar University, Tamil Nadu, Coimbatore, India; Suresh S., Department of Life Sciences, Christ University, Karnataka, Bangalore, India; Santhosh A.S., Department of Life Sciences, Christ University, Karnataka, Bangalore, India
Fruit Waste as Sustainable Resources for Polyhydroxyalkanoate (PHA) Production
Biodegradability; Biopolymers; Downstream processing; Fruit waste; Polyhydroxyalkanoates
Production of polyhydroxyalkanoate (PHA) using commercially available carbon sources like glucose or sucrose makes the bioprocess economically nonviable, thereby hindering its commercialization. As an alternative to this issue, inexpensive and easily available agro-industrial wastes are now being exploited as feedstock for PHA production. Fruit wastes are generally discarded as they are considered to be the non-product leftovers which do not have any economic value when compared with the cost of their collection and recovery steps for reuse. But through the use of appropriate technological applications, these wastes can be converted to valuable by-products, which can increase the value of the products much higher than the cost associated with recovery steps. By recycling and reprocessing the fruit wastes, they can be channeled into many applications, and thereby the amount of fruit wastes discharged into the environment can be completely reduced along with their detrimental effects. Large amounts of fruit wastes are produced by fruit-based industries. The waste products can be both solids and liquids, and these wastes are of high nutritional and biomass values for microorganism; thus their addition to waterbodies can make them highly polluted (high BOD or COD). These fruit-based wastes still have a promising potential for bioconversion into products of commercial importance or can be successfully exploited as cheap raw materials for industrial production of commercially important metabolites. This chapter deals with the strategies for production of PHA from fruit waste substrates, extraction and characterization of PHA, and their applications in diverse sectors. The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2021.
Bioplastics for Sustainable Development, pp. 205-229.
Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Sankar S.A., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Thazeem B., Vellalar Institutions (Maruthi Nagar Campus), Tamilnadu, Erode, India
Extraction, characterization, and fabrication of cellulose biopolymer sheets from Pistia stratiotes as a biodegradative coating material: an unique strategy for the conversion of invasive weeds into value-added products
Alkali treatment; Biodegradation; Biopolymer coating; Cellulose; Water lettuce
This study explores the possibility of using Water lettuce (Pistia stratiotes) as a cost-effective substrate for the commercial extraction of cellulose biopolymer using a wide variety of physicochemical treatment methods to compare their efficiency in cellulose extraction. The extraction of cellulose from water lettuce, although promising due to their high cellulose content, was less explored as per the available literature. In this study, functional properties like bulk density-packed density, hydrated density, water retention capacity, oil retention capacity, emulsifying activity and setting volume of the extracted cellulose were studied. The cellulose content from water lettuce was found to be 38.94 0.10% by anthrone method. Preliminary confirmation of cellulose biopolymer was done using the study of functional groups using Fourier Transform Infrared (FT-IR) analysis. Further characterization studies like Scanning Electron Microscopy (SEM), X- Ray Diffraction (XRD), Differential Scanning Calorimetry (DSC) and thermogravimetric analysis (TGA) were conducted to understand the molecular architecture and purity of the cellulose extracted. Fabrication of cellulose sheets was carried out using starch as the plasticizer. Biodegradation studies were conducted in garden soil for four weeks and a high degradation rate of 78.22 0.71% was observed in the fourth week of soil burial. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Umesh M.; Santhosh A.S.; Shanmugam S.; Thazeem B.; Alharbi S.A.; Almoallim H.S.; Chi N.T.L.; Pugazhendhi A.
Journal of Polymers and the Environment, Vol-30, No. 12, pp. 5057-5068.
Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Santhosh A.S., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Shanmugam S., Biosystems Engineering, Institute of Forestry and Engineering, Estonian University of Life Sciences, Kreutzwaldi 56, Tartu, 51006, Estonia; Thazeem B., Integrated Rural Technology Centre (IRTC), Kerala, Palakkad, India; Alharbi S.A., Department of Botany and Microbiology, College of Science, King Saud University, PO Box - 2455, Riyadh, 11451, Saudi Arabia; Almoallim H.S., Department of Oral and Maxillofacial Surgery, College of Dentistry, King Saud University, PO Box-60169, Riyadh, 11545, Saudi Arabia; Chi N.T.L., School of Engineering and Technology, Van Lang University, Ho Chi Minh City, Viet Nam; Pugazhendhi A., Emerging Materials for Energy and Environmental Applications Research Group, School of Engineering and Technology, Van Lang University, Ho Chi Minh City, Viet Nam
Sustainable Biodegradable and Bio-based Materials
The quest for sustainable biodegradable and bio-based materials is ever increasing due to their versatile properties and also their ability to serve as potential alternatives to their synthetic counterparts. The major types of bio-based materials of commercial importance can be derived majorly from plant, animal, and microbial sources through physical, chemical, or biological extraction methods. Despite their potential applications, biocompatibility, and biodegradability, these bio-based polymers still face hurdles in competing with conventional plastics. The major factors contributing to this involve the production and extraction cost. In recent years, the integration of waste valorization with biopolymer production and the development of eco-friendly green extraction protocols with minimum usage of chemicals were visualized as efficient strategies for the sustainable production of biopolymers. This study summarizes the important biodegradable and bio-based materials of commercial importance along with their production methods and application in diverse sectors. 2023 selection and editorial matter, Ajay, Parveen, Sharif Ahmad, Jyotsna Sharma, Victor Gambhir.
Umesh M.; Sarojini S.; Basheer T.; Suresh S.; Santhosh A.S.; Stanly L.M.; Grigary S.; James N.
Handbook of Sustainable Materials: Modelling, Characterization, and Optimization, pp. 71-92.
Umesh M., Department of Life Sciences, CHRIST, Karnataka, Bangalore, India; Sarojini S., Department of Life Sciences, CHRIST, Karnataka, Bangalore, India; Basheer T., Waste Management Division, Integrated Rural Technology Centre, Kerala, Palakkad, India; Suresh S., Department of Life Sciences, CHRIST, Karnataka, Bangalore, India; Santhosh A.S., Department of Life Sciences, CHRIST, Karnataka, Bangalore, India; Stanly L.M., Department of Life Sciences, CHRIST, Karnataka, Bangalore, India; Grigary S., Department of Life Sciences, CHRIST, Karnataka, Bangalore, India; James N., Department of Life Sciences, CHRIST, Karnataka, Bangalore, India
Progress in bio-based biodegradable polymer as the effective replacement for the engineering applicators
Biocomposites; Biomass; Biopolymers; Cellulose; Polyhyroxyalkanoates
The development of biopolymers has significantly touched each and every sphere of human life due to their eco friendliness and biodegradability. In recent decades, the production of biopolymers gained profound attention due to the serious environmental concerns and threat to the non-renewable resources. The increased use of synthetic plastic in biomedical and engineering applications stays as a major threat to environment when these xenobiotics enter the food chain and soil upon their careless discharge after use. The significant material properties of plastic has made it as an inevitable part in our day to day life, but the concern over the environment directs the research focus on searching and developing biopolymers and bio composites as sustainable alternatives for their synthetic counterparts. Biopolymers of commercial interest can be majorly produced intracellularly by microbes or can be extracted through chemical or biological methods from plant and animal based substrates. The potential candidates with high market value with specific reference to biomedical engineering and tissue engineering include as polyhydroxyalkanoates, cellulose, chitosan and chitin, hydroxyapatite, and pectin. Despite of having high degree of biocompatibility, the major hurdle that retracts their widespread use commercially is attributed to the cost of production. This can be tackled out by exploiting cheap raw materials like agro waste as substrate and by employing green approaches over solvent based conventional extraction methods. The reduction in the material properties of purified biopolymers restricts their widespread application especially in the fabrication of thermoplastic blends. This can be resolved by production of bio composites with improved properties than their parent biopolymers. The current review focuses on the recent developments in biopolymer science especially with regard to its application in engineering majorly biomedical and tissue engineering. This study throws light on the biosynthetic pathways, extraction methods and applications of commercially important biopolymers. Furthermore, the challenges, limitations, and future prospects in the production and commercialization of biopolymers is briefly discussed in this review. 2022 Elsevier Ltd
Umesh M.; Shanmugam S.; Kikas T.; Lan Chi N.T.; Pugazhendhi A.
https://doi.org/10.1016/j.jclepro.2022.132267 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131037628&doi=10.1016%2fj.jclepro.2022.132267&partnerID=40&md5=2924590f9761f7bc0eb5d61882d14cc2
Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Shanmugam S., Chair of Biosystems Engineering, Institute of Forestry and Engineering, Estonian University of Life Sciences, Kreutzwaldi 56/1, Tartu, 51006, Estonia; Kikas T., Chair of Biosystems Engineering, Institute of Forestry and Engineering, Estonian University of Life Sciences, Kreutzwaldi 56/1, Tartu, 51006, Estonia; Lan Chi N.T., School of Engineering and Technology, Van Lang University, Ho Chi Minh City, Viet Nam; Pugazhendhi A., Emerging Materials for Energy and Environmental Applications Research Group, School of Engineering and Technology, Van Lang University, Ho Chi Minh City, Viet Nam
Valorization of pineapple peel waste for fungal pigment production using Talaromyces albobiverticillius: Insights into antibacterial, antioxidant and textile dyeing properties
Antioxidant; Fungal pigment; Pineapple peel; Talaromyces sp.; Textile dye
The present study explores natural pigments as sustainable alternatives to synthetic textile dyes. Due to their therapeutic applications and easy production, fungal pigments have gained attention. However, data on pigment production using solid-state fermentation and optimization is limited. Milk whey was used to grow Talaromyces sp., followed by an evaluation of pigment production in solid and liquid media. Pineapple peels were used as a cost-effective substrate for pigment production, and a one-factor-at-a-time approach was used to enhance pigment production. Pineapple peel-based media produced 0.523 0.231 mg/g of pigment after eight days of incubation. The crude pigment had promising antibacterial and significant antioxidant properties. The extraction fungal pigment's possible use as an eco-friendly textile dye was assessed through fabric dyeing experiments with different mordants. This work contributes to the valorization of agricultural waste and provides insight into using fungal pigments as sustainable alternatives to synthetic textile dyes. 2023 Elsevier Inc.
Umesh M.; Suresh S.; Santosh A.S.; Prasad S.; Chinnathambi A.; Al Obaid S.; Jhanani G.K.; Shanmugam S.
https://doi.org/10.1016/j.envres.2023.115973 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153367865&doi=10.1016%2fj.envres.2023.115973&partnerID=40&md5=2a9510aa534d195745cccf275d68d195
Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Suresh S., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Santosh A.S., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Prasad S., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Chinnathambi A., Department of Botany and Microbiology, College of Science, King Saud University, PO Box -2455, Riyadh, 11451, Saudi Arabia; Al Obaid S., Department of Botany and Microbiology, College of Science, King Saud University, PO Box -2455, Riyadh, 11451, Saudi Arabia; Jhanani G.K., University Centre for Research & Development, Chandigarh University, Mohali, 140103, India; Shanmugam S., Chair of Biosystems Engineering, Institute of Forestry and Engineering, Estonian University of Life Sciences, Tartu, 51010, Estonia
A sustainable approach for fish waste valorization through polyhydroxyalkanoate production by Bacillus megaterium NCDC0679 and its optimization studies
Bacillus megaterium; BoxBehnken design; Fish scale hydrolysate; PHA; PlackettBurman design; Response surface methodology
Polyhydroxyalkanoates (PHAs) are considered as the only class of truly biodegradable and biocompatible polymers. Although extensive research has been carried out in producing them from a wide variety of organisms, their commercialization still faces hurdles majorly associated with the cost of production media. This research work exploits the use of discarded fish scale waste as a major media component for biopolymer production. The major novelty of the research work is the utilization of a Bacillus megaterium NCDC0679 for PHA production using fish scale waste that is not reported previously. Furthermore, a sequential and systematic statistical optimization strategy employing response surface methodology was used to trace out the level of the most significant variables and their interaction effects on PHA production add to the significant novelty of this work. The significance of the model developed was determined from the p values of ANOVA. Under optimized levels of glucose (50g/L), NaCl (0.125g/L), and fish scale hydrolysate concentration (62.5% v/v), maximum PHA yield of 6.33g/L was achieved in the shake flask culture system. This was found to be 5.50-fold higher than the unoptimized medium. The ANOVA results established the significance of the model (p < 0.05). The extracted polymer was characterized through Fourier-transform infrared (FTIR), nuclear magnetic resonance (NMR), X-ray diffraction (XRD), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). Thus, the present investigation suggests an innovative method for valorization of fish scale waste for commercial production of PHA. 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Umesh M.; Suresh S.; Sarojini S.; Santosh A.S.
Springer Science and Business Media Deutschland GmbH
Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Suresh S., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Sarojini S., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Santosh A.S., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India
Biodegradation studies of polyhydroxyalkanoates extracted from Bacillus subtilis NCDC 0671
Biodegradation; Biopolymers; Phytotoxicity; Polyhydroxyalkanoates; Synthetic plastics
The major characteristic feature that distinguishes polyhydroxyalkanoates (PHAs) from its synthetic counterparts is its biodegradability. PHAs are the only class of biopolymers reported to be 100% degradable under both aerobic and anaerobic conditions without production of any toxic residues. The biodegradability of PHAs is influenced by several factors like moisture, temperature, pH, surface area and molecular weight of the polymer. The rate of biodegradation varies greatly depending on the environment. Biodegradation studies were carried out using plating method and direct inoculation method using selected Bacillus strains. Fungal degradation of PHA sheets was assessed using Penicillium chrysogenum. Biodegradation of PHA sheets in different soil types like river valley, agricultural land and garden soil was investigated. The degree of PHA degradation in aqueous environment was studied by incubating the sheets in distilled water, sea water, fish tank water and pond water. The highest degradation rate was observed with agriculture land soil (35.47 0.13%) and fish tank soil (36.93 0.13%). The non-toxic nature of the soil incubated with PHA sheets was ensured using plant growth test. 2019, World Research Association. All rights reserved.
Research Journal of Chemistry and Environment, Vol-23, No. 6, pp. 107-114.
Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, Karnataka, India; Thazeem B., Department of Microbial Biotechnology, Bharathiar University, Coimbatore, 641046, Tamil Nadu, India
Valorization of pineapple peels through single cell protein production using saccharomyces cerevisiae NCDC 364
Amino acid profiling; Pineapple peels; Saccharomyces cerevisiae; Single cell protein
Background and objective: Pineapple peels contain significant quantities of carbohydrates, which can be used as cheap raw materials for production of commercially important products through fermentation. The aim of this study was to use this feed stock for the cultivation of Saccharomyces cerevisiae NCDC 364 and its use as single cell protein. Material and methods: The single cell protein was produced using discarded pineapple peels and Saccharomyces cerevisiae NCDC 364. Optimization of bioprocess variables (temperature, pH, incubation period, carbon source and nitrogen source) affecting single cell protein production was carried out using classical "one factor at a time" approach. The harvested cells from optimized media were screened for amino acid content using high-performance thin-layer chromatography. Results and conclusion: The Saccharomyces cerevisiae NCDC 364 produced maximum single cell protein in pineapple peel based media, compared to non-optimized media. The "one factor at a time" approach showed that the maximum biomass production was achieved at optimized levels of temperature of 25C, pH of 5, incubation period of 120 h, carbon source of 1% sucrose and nitrogen source of 0.5% beef extract. The amino acid profiling of the harvested biomass using high-performance thin-layer chromatography analysis revealed that tryptophan included a comparatively higher concentration of 6.52%, followed by threonine (3.25%). Results of this study suggest that easily available raw materials such as fruit peels offer cost-effective substrates for production of commercially important microbial proteins for alarming global issues linked to protein malnutrition. Conflict of interest: The authors declare no conflict of interest. 2019 National Nutrition and Food Technology Research Institute.
Applied Food Biotechnology, Vol-6, No. 4, pp. 255-263.
National Nutrition and Food Technology Research Institute
Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Bengaluru, Karnataka, 560029, India; Thazeem B., Department of Microbial Biotechnology, Bharathiar University, Coimbatore, Tamil Nadu, 641046, India; Preethi K., Department of Microbial Biotechnology, Bharathiar University, Coimbatore, Tamil Nadu, 641046, India
Universal Electrical Motor Acoustic Noise Reduction based on Rotor Surface Modification
Acoustic noise; Decibels; Electromagnetic flux; Electromagnetic noise; Flux density; Torque
Electromagnetic noise is referred to the audible sound which is produced by materials vibrating due to electromagnetic force. In the present day circumstances, a greater attention is being given to the electromagnetic acoustic noise produced by electrical machines. It is found to annoy human beings and other living organisms due to its tonal sound. The current work aims at designing a rotor for a universal motor with the objective to decrease the acoustic noise by minimization of forced density harmonics. The design consists of some irregularities in the rotor surface to decrease the acoustic noise by internally modifying the air gap permeance. Simulation shall be carried out based on FEM. A lot of research is being carried out on the methods of reducing the noise from electrical machines. The results of the current work significantly help in reducing a lot of noise pollution. The change in the rotor surface will reduce the electromagnetic acoustic noise from the electrical machine. It will also affect the torque parameters positively as studied from earlier research work. 2019 IEEE.
Umesh V.; Mishra S.; Simon S.; Singh A.K.; Moses P.
2019 International Conference on Data Science and Communication, IconDSC 2019
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/IconDSC.2019.8817005 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072765159&doi=10.1109%2fIconDSC.2019.8817005&partnerID=40&md5=9593063a48e7fc8ec54da283160eb648
Umesh V., Mechanical Engineering, Faculty of Engineering, CHRIST, Deemed to be University, Bengaluru, Karnataka, 560074, India; Mishra S., Mechanical Engineering, Faculty of Engineering, CHRIST, Deemed to be University, Bengaluru, Karnataka, 560074, India; Simon S., Mechanical Engineering, Faculty of Engineering, CHRIST, Deemed to be University, Bengaluru, Karnataka, 560074, India; Singh A.K., Mechanical Engineering, Faculty of Engineering, CHRIST, Deemed to be University, Bengaluru, Karnataka, 560074, India; Moses P., Mechanical Engineering, Faculty of Engineering, CHRIST, Deemed to be University, Bengaluru, Karnataka, 560074, India
Active Learning from an Imbalanced Dataset: A Study Conducted on the Depression, Anxiety, and Stress Dataset
The proposed chapter deals with psychological data related to depression, anxiety, and stress to study how the classification and analysis is carried out on imbalanced data. The proposed study not only contributes on providing practical information about the balancing techniques such as synthetic minority oversampling technique but also reveals the strategy for dealing with the working of many existing classification algorithms such as the support vector machine, random forest, XGBoost, etc. on the imbalanced dataset. The present use of evaluation metrics that are solely implied for the imbalanced data classification is also illustrated. It was observed that the ordinary model assessment techniques do not precisely quantify model execution when gone up against imbalanced datasets and that the common techniques such as the logistic regression and decision tree have a predisposition toward classes that have many observations. The attributes of the minority class are treated low and are routinely overlooked. Henceforth, there is a high likelihood of misclassification of the minority class when compared to the majority class. A confusion matrix which contains data about the real and predicted class is used as an assessment standard to check the exhibition of grouping calculation. Rather than going for accuracy, F-score and the area under the curve are considered as the measures to evaluate the classification model. 2022 selection and editorial matter, Vishal Jain, Sapna Juneja, Abhinav Juneja, and Ramani Kannan.
Handbook of Machine Learning for Computational Optimization: Applications and Case Studies, pp. 251-266.
https://doi.org/10.1201/9781003138020-14 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132463979&doi=10.1201%2f9781003138020-14&partnerID=40&md5=d18c38d6e87f0ca6f9fd2cc34fdfff90
Umme Salma M., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Amala Ann K.A., Data Science Department, CHRIST (Deemed to be University), Bangalore, India
An Empirical Study ofSignal Transformation Techniques onEpileptic Seizures Using EEG Data
Brain disorder; EEG; Epileptic seizures; Feature selection; Signal transformation techniques
Signal processing may be a mathematical approach to manipulate the signals for varied applications. A mathematical relation that changes the signal from one kind to a different is named a transformation technique in the signal process. Digital processing of electroencephalography (EEG) signals plays a significant role in a highly multiple application, e.g., seizure detection, prediction, and classification. In these applications, the transformation techniques play an essential role. Signal transformation techniques are acquainted with improved transmission, storage potency, and subjective quality and collectively emphasize or discover components of interest in an extremely measured EEG signal.The transformed signals result in better classification. This article provides a study on some of the important techniques used for transformation of EEG data. During this work, we have studied six signal transformation techniques like linear regression, logistic regression, discrete wavelet transform, wavelet transform, fast Fourier transform, and principal component analysis with Eigen vector to envision their impact on the classification of epileptic seizures. Linear regression, logistic regression, and discrete wavelet transform provides high accuracy of 100%, and wavelet transform produced an accuracy of 96.35%. The proposed work is an empirical study whose main aim is to discuss some typical EEG signal transformation methods, examine their performances for epileptic seizure prediction, and eventually recommend the foremost acceptable technique for signal transformation supported by the performance. This work also highlights the advantages and disadvantages of all seven transformation techniques providing a precise comparative analysis in conjunction with the accuracy. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Lecture Notes on Data Engineering and Communications Technologies, Vol-111, pp. 797-806.
Umme Salma M., Assistant Professor Department of Computer Science, Christ (Deemed to be University), Hosur Road, Bangalore, India; Najmusseher, Research Scholar Department of Computer Science, Christ (Deemed to be University), Hosur Road, Bangalore, India
Classification Algorithms Used in the Study of EEG-Based Epileptic Seizure Detection
Classification; Decision Tree Classifier; EEG; Epileptic Seizures; KNN; Linear Discriminant Analysis; SVM; XGBOOST
Epilepsy is a neurological illness that has become more frequent around the world. Nearly 80% of epileptic seizure sufferers live in low- and middle-income nations. In persons with encephalopathy, the risk of dying prematurely is three times higher than in the general population. Three-quarters of people with brain illnesses in low-income countries do not receive the treatment they require. Recurrent seizures are a symptom of epilepsy, characterized by strange bursts of excess energy in mind. Experts agree that most people diagnosed with epilepsy may be managed successfully, provided the episodes are discovered early on. As a result, machine learning plays an essential role in seizure detection and diagnosis. Support Vector Machine(SVM), Extreme Gradient Boosting(Xgboost), Decision Tree Classifier, Linear Discriminant Analysis(LDA), Perceptron, Naive Bayes Classifier, k-Nearest Neighbor(k-NN), and Logistic Regression are eight of the most widely used machine learning classification algorithms used to classify EEG based mostly Epileptic Seizures. Almost all classifiers, according to the study, give an efficient process. Despite this, the results show that SVM is the most effective method for detecting epileptic seizures, with a 96.84% accuracy rate. For diagnosing Epileptic Seizures using EEG signals, the perceptron model has a lower accuracy of 76.21% percent. 2021 IEEE.
Proceedings - 2nd International Conference on Smart Electronics and Communication, ICOSEC 2021, pp. 1518-1521.
Umme Salma M., CHRIST (Deemed To Be University), Department of Computer Science, Bangalore, India; Najmusseher, CHRIST (Deemed To Be University), Department of Computer Science, Bangalore, India
A meta-heuristic based hybrid predictive model for sensor network data
Many prediction algorithms and techniques are used in data mining to predict the outcome of the response variable with respect to the values of input variables. However from literature, it is confirmed that a hybrid approach is always better in performance than a single algorithm. This is because the hybridization leads to combine all the advantages of the individual approaches, leading to the production of more effective and much improved results. Thus, making the model a productive one, which is far better than model proposed using individual techniques or algorithms. The purpose behind this chapter is to provide information to the users on how to build and investigate a hybrid Feed-forward Neural Network (FNN) using nature inspired meta heuristic algorithms such as the Gravitational Search Algorithm (GSA), Binary Bat Algorithm (BBAT), and hybrid BBATGSA algorithm for the prediction of sensor network data. Here, FNN is trained using a hybrid BBATGSA algorithm for predicting temperature data in sensor network. The data is collected using 54 sensors in a controlled environment of Intel Berkeley Research lab. The developed predictive model is evaluated by comparing it with existing two meta heuristic models such as FNNGSA and FNNBBAT. Each model is tested with three different V-shaped transfer functions. The experimental results and comparative study reveal that the developed FNNBBATGSA shows best performance in terms of accuracy. The FNNBBATGSA under three different V-shaped transfer functions produced an accuracy of 91.1, 98.5, and 91.2%. 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
Umme Salma M.; Narasegouda S.; Patil A.N.
Studies in Computational Intelligence, Vol-776, pp. 167-186.
Umme Salma M., Computer Science Department, Christ (Deemed to be University), Bengaluru-29, Bangalore, 560029, India; Narasegouda S., Freelance Researcher, Bangalore, India; Patil A.N., Department of Mathematics, Government First Grade College and PG study center, Gadag, India
Clustering Faculty Members fortheBetterment ofResearch Outcomes: A Fuzzy Multi-criteria Decision-Making Approach inTeam Formation
From a talent-pool of people, choosing an efficient team is tough. Faculty members of a higher education institution constitute the talent-pool. Teams have to be formed from them so that research output of each team is maximum. Amongst numerous research skills, thirteen are identified as most desirable skills. The level of these thirteen skills, viz., concept articulation, formatting according to templates/style sheets, identifying the relevant literature, initiative, logical reasoning, patience, problem formulation/problem finding, proof reading skills/identifying mistakes in written communication, searching/browsing skills/quick search techniques, sense of positive criticism, statistical knowledge, the ability to stay calm, and written communication skills, varies from person to person. Historical ranking of these skills and self-evaluation of the level of acquisition of these skills is used along with the years of experience, educational qualification, gender, marital status, etc., to rank individual faculty members. The fuzzy ranking of the faculty members thus obtained is used to cluster them into teams that are efficient in complementary skills. Each team thus formed is involved in collaborative research leading to research publication. The model is successfully implemented in a university department with 40 faculty members. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Umme Salma M.; Narayanamoorthy S.; Kureethara J.V.
Studies in Fuzziness and Soft Computing, Vol-420, pp. 605-618.
Umme Salma M., Christ University, Bangalore, India; Narayanamoorthy S., Bharathiar University, Coimbatore, India; Kureethara J.V., Christ University, Bangalore, India
Constraint Governed Association Rule Mining for Identification of Strong SNPs to Classify Autism Data
Artificial Neural Network (ANN); Association Rule mining (ARM); Autism; Constraint Governed Association Rule Mining (CGARM); Dimensionality reduction; Machine Learning; SNP
Autism is a heterogeneous neuro developmental disorder found among all age groups. Nowadays more patients are detected with autism but very less awareness is prevailing in the society related to it. This paved a way for many researchers to carry out serious study on autism and its characteristics. Studying behavior and characteristics of Autistic patients is very important for diagnosing the level of autism. Classifying the association of different characteristic in autistic patients at gene level using machine learning techniques can give an important insight to the doctors and the care takers of the patients. Research is being carried out to identify the genes responsible for autism. The changes in gene sequence may lead to different characteristics in different people. Thus genotypic research is found to reveal well defined insight about various characteristics in autistic patients and their associations with genes. Single Nucleotide Polymorphism (SNP) being high in features indicate human genome variability and is associated with identification of traits for many human diseases including autism. The main aim of the proposed work is to identify SNP sequences which are responsible for carrying the autistic traits. This paper explore the application of Constraint Governed Association Rule Mining (CGARM) technique on SNP data for dimensionality reduction and thereby selecting the strong predominant SNP features which are relevant enough to accomplish classification with high accuracy. The research work incorporates the application of CGARM and is carried out in two stages. In the first stage CGARM was used to choose significant SNP features resulting in dimensionality reduction. In the second stage classification was carried out by subjecting the selected features to Artificial Neural Network (ANN) algorithm. The main advantage of the proposed work is its ability to reduce the dimensions without compromising the quality i.e. using CGARM strong SNPs were selected by applying various constraints like Syntactical constraints, Semantical constraints and Dimensionality Constraints resulting in higher accuracy. The CGARM technique is applied on Autism data collected from National Center for Biotechnology Information (NCBI) repository. The data is divided into a set of 118 features, out of 118 features CGARM contributed in identifying 22 predominant SNPs. Further by applying forward selection method top 17 features were selected and were given as input to ANN. The 10 fold cross validation resulted in 76.9% accuracy which was found to be 50% more than that of original features. The proposed work contributed in reducing the dimension by 85% and provided 76.9% accuracy with the help of only 15% features. 2020 IEEE.
Proceedings of the 2020 IEEE International Conference on Communication, Computing and Industry 4.0, C2I4 2020
Umme Salma M., Christ Deemed to be University, Department of Computer Science, Bangalore, India; Rajashekar P.K.M., Christ Deemed to be University, Department of Computer Science, Bangalore, India
A decade survey on internet of things in agriculture
Agriculture; Agronomics; Cloud computing; IoT; Livestock management; Precision agriculture; Smart irrigation
The Internet of Things (IoT) is a united system comprising of physical devices, mechanical and digital machines, and different hardware components like sensors, actuators, cameras etc., monitored and operated by the software. The combination of devices and systems connected over the internet opens the pathway for development of various applications beneficial in terms of economic growth of a nation. IoT has evolved as a potentially emerging computer technology solving various real-life problems and issues. IoT covers vast group of applications, from warfare to surveillance, from habitat monitoring to energy harnessing, predictive analytics and personalized health care, and so on. Among various fields, agriculture is one important field having maximum scope of implementation and investment. The main aim of this book chapter is to furnish all the details related to applications of IoT in the field of agriculture. This includes the details related to data collection, types of sensors used, deployment details, data access through cloud. It also covers details related to various communication technologies used in IoT such as Bluetooth, LoRaWAN, LTE, 6LowPAN, NFC, RFID etc. And above all, the chapter focuses on the significance of IoT on agronomics, agricultural engineering, crop production and livestock production. This chapter is a decade survey conducted to study the contribution of IoT in the field of agriculture. Around 40 research papers for the duration 2008-2018 are collected from peer reviewed journals and conferences. The collected articles are analyzed to provide relevant information required for the various end users. Springer Nature Switzerland AG 2020.
Ummesalma M.; Rachana Subbaiah M.; Narasegouda S.
Internet of Things (IoT): Concepts and Applications, pp. 351-370.
Ummesalma M., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, Karnataka, India; Rachana Subbaiah M., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, Karnataka, India; Narasegouda S., Department of Computer Science, Jyothi Nivas College (Autonomous), Bengaluru, Karnataka, India
COLPOUSIT: A Hybrid Model for Tourist Place Recommendation based on Machine Learning Algorithms
Collaborative filtering; Hybrid recommender system; Recommender system; Travel and tourism
Tourism is an important sector for a country's economic growth. The travel recommendations should be made focused on better growth and attract more travelers. There is a huge amount of travel information and ideas available on the web that allows the users to make poor travel decisions. This paper focuses on building a hybrid travel recommender system by implementing collaborative-based, popularity-based, and nearby place weighted recommender system. The proposed system recommends the travel spots to the users based upon their interests and other criteria specified. In order to implement these methods, we applied a comparative study on different machine learning algorithms for collaborative-based approach and have performed weighted hybridization. These methods provide a personalized and customized list of similar places with respect to places of interest to the users. Thus, a hybrid system built using these methods provides a better recommendation of places with the advantages of these methods. The obtained results confirm that the hybrid method better than other recommender approaches when used separately. 2021 IEEE.
Proceedings of the 5th International Conference on Trends in Electronics and Informatics, ICOEI 2021, pp. 1743-1750.
Ummesalma M., Christ (Deemed to Be University), Department of Computer Science, Bangalore, 560029, India; Yashiga C., Christ (Deemed to Be University), Department of Computer Science, Bangalore, 560029, India