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A New Method for Diagnosis of Leukemia Utilizing a Hybrid DL-ML Approach for Binary and Multi-Class Classification on a Limited-Sized Database

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 593-631页

作者： Nilkanth Mukund Deshpande Shilpa Gite Biswajeet Pradhan Abdullah Alamri Chang-Wook Lee Department of Electronics&Telecommunication LavaleSymbiosis Institute of TechnologySymbiosis International(Deemed University)PuneMaharashtra412115India Electronics&Telecommunication Dr.Vithalrao Vikhe Patil College of EngineeringAhmednagarMaharashtra414111India Artificial Intelligence and Machine Learning Department Symbiosis Institute of TechnologySymbiosis International(Deemed)UniversityPune412115India symbiosis Centre of Applied AI(SCAAI) Symbiosis International(Deemed)UniversityPune412115India Centre for AdvancedModelling and geospatial Information Systems(CAMGIS) School of Civil and Environmental EngineeringFaculty of Engineering&ITUniversity of Technology SydneySydneyAustralia Earth Observation Centre Institute of Climate ChangeUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia Department of geology&geophysics College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia Department of Science Education Kangwon National UniversityChuncheon-si24341Korea

Infection of leukemia in humans causes many complications in its later *** impairs bone marrow’s ability to produce *** diagnosis of human blood cells is a well-known and well-proven technique for diagnosis in this *** binary classification is employed to distinguish between normal and leukemiainfected *** addition,various subtypes of leukemia require different *** sub-classes must also be detected to obtain an accurate diagnosis of the type of *** entails using multi-class classification to determine the leukemia *** is usually done using a microscopic examination of these blood *** to the requirement of a trained pathologist,the decision process is critical,which leads to the development of an automated software framework for *** utilized state-of-the-art machine learning approaches,such as Support Vector Machine(SVM),Random Forest(RF),Na飗e Bayes,K-Nearest Neighbor(KNN),and others,to provide limited accuracies of *** advanced deep-learning methods are also *** to constrained dataset sizes,these approaches result in over-fitting,reducing their outstanding *** study introduces a deep learning-machine learning combined approach for leukemia *** uses deep transfer learning frameworks to extract and classify features using state-of-the-artmachine learning *** transfer learning frameworks such as VGGNet,Xception,InceptionResV2,Densenet,and ResNet are employed as feature *** extracted features are given to RF and XGBoost classifiers for the binary and multi-class classification of leukemia *** the experimentation,a very popular ALL-IDB dataset is used,approaching a maximum accuracy of 100%.A private real images dataset with three subclasses of leukemia images,including Acute Myloid Leukemia(AML),Chronic Lymphocytic Leukemia(CLL),and Chronic Myloid Leukemia(CML),is also employed to generalize the *** d

关键词： Leukemia diagnosis deep learning machine learning random forest XGBoost

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Evolution of tectonic landscapes and deformation in the southeast Kumaun and western Nepal Himalaya

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Journal of Mountain Science 2024年第8期21卷 2592-2617页

作者： Khayingshing LUIREI Girish Ch.KOTHYARI Param K GAUTAM Ambar SOLANKI Atul Kumar PATIDAR Sentisenla JAMIR Anirudh DATTA Tanupriya CHOUDHURY Wadia institute of Himalayan geology Dehradun 248001India Department of Petroleum Engineering and Earth Sciences University of Petroleum and Energy StudiesDehradun248007India Department of geology Nagaland UniversityKohima 797004India Academy of Scientific and Innovative Research Ghaziabad 201002India CSE Department Graphic Era deemed to be UniversityDehradun 248002India CSE Department Symbiosis Institute of TechnologySymbiosis International(Deemed University)Pune 412114India

The area of the present investigation’s expanse constitutes the southernmost extent of the southeast Kumaun Himalaya and western Nepal *** approaches have been employed to understand the landforms associated with tectonic deformation,through detailed field investigation supplemented by the geodetic,chronological,and morphometric *** morphogenic expressions of the Main Boundary Thrust(MBT)are reflected in the form of~25 km long E-W trending north dipping fault *** deformation along the strike length of the Himalayan Frontal Thrust(HFT)is noticed in the form of uplifted and incised fill terraces,and strath *** deformation within the fluvial sequences in the study area can be visualized in the form of sheared boulders and pebbles,tilted and faulted terrace ***,the chronological data of fluvial landforms in the study area suggests two major phases of tectonic deformations that have occurred around 58.7±10.8 ka and 3.88±0.4 *** chronology of late-Quaternary landforms advocates that the initial stage of aggradations in the Himalayan foothills commenced around 75.1±0.58 *** aggradational landforms resulted from the diverse depositional regime as evident from the nature of the sediment sequences from clasts dominated to thick mud *** rate of deformation in the southeastern Kumaun and western Nepal Himalaya is±7 mm/yr,as per the data obtained from the Persistent Scatterer Interferometric Synthetic Aperture Radar(PSInSAR).The landform deformation pattern,phase of incision and aggradation,frequent occurrence of landslides,and recent past earthquake activity within the wide zone of the HFT,the MBT,and Ramgarh Thrust suggests that the southernmost front of the Kumaun Himalaya is active and has potential for future *** foothill zone of Himalayan towns are actively growing in terms of population and infrastructural ***,such intradisciplinary studies for tectonically active r

关键词： MBT HFT Fault trace Quaternary deposits sheared boulders

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Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data

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Computers, Materials & Continua 2024年第8期80卷 2301-2330页

作者： Uddagiri Sirisha Parvathaneni Naga Srinivasu Panguluri Padmavathi Seongki Kim Aruna Pavate Jana Shafi Muhammad Fazal Ijaz Department of Computer Science and Engineering Prasad V Potluri Siddhartha Institute of TechnologyVijayawada520007India Amrita School of Computing Amrita Vishwa VidyapeethamAmaravatiAndhra Pradesh522503India Department of Tele informatics Engineering Federal University of CearáFortaleza60455-970Brazil Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramGunturAndhra Pradesh522302India Department of Computer Engineering Chosun UniversityGwangju61452Republic of Korea School of CSIT Symbiosis Skills and Professional UniversityPune412101India Department of Computer Engineering and Information College of Engineering inWadi AlddawasirPrince Sattam bin Abdulaziz UniversityWadi Alddawasir11991Saudi Arabia School of IT and Engineering Melbourne Institute of TechnologyMelbourne3000Australia

Fetal health care is vital in ensuring the health of pregnant women and the *** check-ups need to be taken by the mother to determine the status of the fetus’growth and identify any potential *** know the status of the fetus,doctors monitor blood reports,Ultrasounds,cardiotocography(CTG)data,***,in this research,we have considered CTG data,which provides information on heart rate and uterine contractions during *** researchers have proposed various methods for classifying the status of fetus *** processing of CTG data is time-consuming and ***,automated tools should be used to classify fetal *** study proposes a novel neural network-based architecture,the Dynamic Multi-Layer Perceptron model,evaluated from a single layer to several layers to classify fetal *** strategies were applied,including pre-processing data using techniques like Balancing,Scaling,Normalization hyperparameter tuning,batch normalization,early stopping,etc.,to enhance the model’s performance.A comparative analysis of the proposed method is done against the traditional machine learning models to showcase its accuracy(97%).An ablation study without any pre-processing techniques is also *** study easily provides valuable interpretations for healthcare professionals in the decision-making process.

关键词： Fetal health cardiotocography data deep learning dynamic multi-layer perceptron feature engineering

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LSTM Based Neural Network Model for Anomaly Event Detection in Care-Independent Smart Homes

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2689-2706页

作者： Brij B.Gupta Akshat Gaurav Razaz Waheeb Attar Varsha Arya Ahmed Alhomoud Kwok Tai Chui Department of Computer Science and Information Engineering Asia UniversityTaichung413TaiwanChina symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India Computer Engineering Ronin InstituteMontclairNJ 07043USA Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Business Administration Asia UniversityTaichung413TaiwanChina Department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia School of Science and Technology Hong Kong Metropolitan University(HKMU)Hong KongChina

This study introduces a long-short-term memory(LSTM)-based neural network model developed for detecting anomaly events in care-independent smart homes,focusing on the critical application of elderly fall *** balances the dataset using the Synthetic Minority Over-sampling Technique(SMOTE),effectively neutralizing bias to address the challenge of unbalanced datasets prevalent in time-series classification *** proposed LSTM model is trained on the enriched dataset,capturing the temporal dependencies essential for anomaly *** model demonstrated a significant improvement in anomaly detection,with an accuracy of 84%.The results,detailed in the comprehensive classification and confusion matrices,showed the model’s proficiency in distinguishing between normal activities and *** study contributes to the advancement of smart home safety,presenting a robust framework for real-time anomaly monitoring.

关键词： LSTM neural networks anomaly detection smart home health-care elderly fall prevention

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Frilled Lizard Optimization: A Novel Bio-Inspired Optimizer for Solving Engineering Applications

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Computers, Materials & Continua 2024年第6期79卷 3631-3678页

作者： Ibraheem Abu Falahah Osama Al-Baik Saleh Alomari Gulnara Bektemyssova Saikat Gochhait Irina Leonova OmParkash Malik Frank Werner Mohammad Dehghani Department of Mathematics Faculty of ScienceThe Hashemite UniversityP.O.Box 330127Zarqa13133Jordan Department of Software Engineering Al-Ahliyya Amman UniversityAmman19328Jordan Faculty of Science and Information Technology Software EngineeringJadara UniversityIrbid21110Jordan Department of Computer Engineering International Information Technology UniversityAlmaty050000Kazakhstan symbiosis institute of Digital and Telecom Management Constituent of Symbiosis International Deemed UniversityPune412115India Neuroscience Research institute Samara State Medical UniversitySamara443001Russia Faculty of Social Sciences Lobachevsky UniversityNizhny Novgorod603950Russia Department of Electrical and Software Engineering University of CalgaryCalgaryAB T2N 1N4Canada Faculty of Mathematics Otto-von-Guericke UniversityP.O.Box 4120Magdeburg39016Germany Department of Electrical and Electronics Engineering Shiraz University of TechnologyShiraz***Iran

This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural *** draws its inspiration from the sit-and-wait hunting strategy of these *** algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases:(i)an exploration phase,which mimics the lizard’s sudden attack on its prey,and(ii)an exploitation phase,which simulates the lizard’s retreat to the treetops after *** assess FLO’s efficacy in addressing optimization problems,its performance is rigorously tested on fifty-two standard benchmark *** functions include unimodal,high-dimensional multimodal,and fixed-dimensional multimodal functions,as well as the challenging CEC 2017 test ***’s performance is benchmarked against twelve established metaheuristic algorithms,providing a comprehensive comparative *** simulation results demonstrate that FLO excels in both exploration and exploitation,effectively balancing these two critical aspects throughout the search *** balanced approach enables FLO to outperform several competing algorithms in numerous test ***,FLO is applied to twenty-two constrained optimization problems from the CEC 2011 test suite and four complex engineering design problems,further validating its robustness and versatility in solving real-world optimization ***,the study highlights FLO’s superior performance and its potential as a powerful tool for tackling a wide range of optimization problems.

关键词： Optimization engineering bio-inspired metaheuristic frilled lizard exploration exploitation

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Adsorption in combination with ozonation for the treatment of textile waste water： a critical review

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Frontiers of Environmental Science & Engineering 2017年第1期11卷 17-34页

作者： Shraddha Khamparia Dipika Kaur Jaspal symbiosis Centre for Research and Innovation Symbiosis International University Lavale. Pune-412115 India symbiosis institute of Technology A Constituent of Symbiosis International University Lavale Pune-412115 India

Intrusion of synthetic textile dyes in the ecosystem has been recognized as a serious issue worldwide. The effluents generated from textiles contain large amount of recalcitrant unfixed dyes which are regarded as emerging contaminants in the field of waste water study. Removal of various toxic dyes often includes diverse and complex set of physico-chemical, biological and advanced oxidation processes adopted for treatment. Adsorption in itself is a well-known technique utilized for treatment of textile effluents using a variety of adsorbents. In addition, ozonation deals with effective removal of dyes using high oxidising power of ozone. The review summarizes dye removal study by a combination of ozonation and adsorption methods. Also, to acquire an effective interpretation of this combined approach of treating wastewater, a thorough study has been made which is deliberated here. Results assert that, with the combined ability of ozone and a catalyst/adsorbent, there is high possibility of total elimination of dyes from waste water. Several synthetically prepared materials have been used along with few natural materials during the combined treatment. However, considering practical applicability, some areas were identified during the study where work needs to be done for effective implementation of the combined treatment.

关键词： Adsorption Ozonation Catalytic Ozonation Textile dyes Mineralization

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Implications of future climate change on crop and irrigation water requirements in a semi-arid river basin using CMIP6 GCMs

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Journal of Arid Land 2022年第11期14卷 1234-1257页

作者： Kunal KARAN Dharmaveer SINGH Pushpendra K SINGH Birendra BHARATI Tarun P SINGH Ronny BERNDTSSON Department of Water Engineering and Management Central University of JharkhandBrambeRanchi 835205India symbiosis institute of geo-informatics Symbiosis International(Deemed University)Pune 411016India Water Resources Systems Division National Institute of HydrologyRoorkee 247667India Division of Water Resources Engineering&Centre for Advanced Middle Eastern Studies Lund UniversityLund Box 11722100Sweden

Agriculture faces risks due to increasing stress from climate change,particularly in semi-arid *** of understanding of crop water requirement(CWR)and irrigation water requirement(IWR)in a changing climate may result in crop failure and socioeconomic problems that can become detrimental to agriculture-based economies in emerging nations *** research in CWR and IWR has largely focused on large river basins and scenarios from the Coupled Model Intercomparison Project Phase 3(CMIP3)and Coupled Model Intercomparison Project Phase 5(CMIP5)to account for the impacts of climate change on *** basins,however,are more susceptible to regional climate change,with more significant impacts on *** study estimates CWRs and IWRs for five crops(sugarcane,wheat,cotton,sorghum,and soybean)in the Pravara River Basin(area of 6537 km^(2))of India using outputs from the most recent Coupled Model Intercomparison Project Phase 6(CMIP6)General Circulation Models(GCMs)under Shared Socio-economic Pathway(SSP)245 and SSP585 *** increase in mean annual rainfall is projected under both scenarios in the 2050s and 2080s using ten selected CMIP6 *** for all crops may decline in almost all of the CMIP6 GCMs in the 2050s and 2080s(with the exceptions of ACCESS-CM-2 and ACCESS-ESM-1.5)under SSP245 and SSP585 *** availability of increasing soil moisture in the root zone due to increasing rainfall and a decrease in the projected maximum temperature may be responsible for this decline in ***,except for soybean and cotton,the projected IWRs for all other three crops under SSP245 and SSP585 scenarios show a decrease or a small increase in the 2050s and 2080s in most CMIP6 *** findings are important for agricultural researchers and water resource managers to implement long-term crop planning techniques and to reduce the negative impacts of climate change and associated rainfall variability to avert crop failure and agricultural

关键词： climate change crop water requirement irrigation water requirement CMIP6 GCMs emission scenario Pravara River Basin

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Effects of viscous dissipation and Joule heating on the Couette and Poiseuille flows of a Jeffrey fluid with slip boundary conditions

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Propulsion and Power Research 2018年第4期7卷 329-341页

作者： K.Ramesh Department of Mathematics Symbiosis Institute of TechnologySymbiosis International UniversityPune 412115India

In this article,we have presented the exact solutions of the Couette,Poiseuille and generalized Couette flows of an incompressible magnetohydrodynamic Jeffrey fluid between parallel plates through homogeneous porous *** effects of slip boundary conditions and heat transfer are *** dissipation,radiation and Joule heating are also considered in the energy *** governing equations of the Jeffrey fluid flow are modeled in Cartesian coordinate *** solutions for the velocity and temperature the velocity and temperature profiles are studied and the results are presented through *** Temperature behaves as a decreasing function due to the impact of Hartmann number,non-Newtonian parameter and slip parameter in all noted problems.

关键词： Jeffrey fluid Heat transfer Joule heating Radiation Viscous dissipation Slip boundary conditions

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Design of a fractional PI~λD~μ controller using the cohort intelligence method

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Frontiers of Information Technology & Electronic Engineering 2018年第3期19卷 437-445页

作者： Pritesh SHAH Sudhir AGASHE Anand J.KULKARNI symbiosis institute of Technology Symbiosis International University Department of Instrumentation and Control Engineering College of EngineeringPune Odette School of Business University of Windsor

The cohort intelligence （CI） method has recently evolved as an optimization method based on artificial intelligence. We use the CI method for the first time to optimize the parameters of the fractional proportional- integral-derivative （PID） controller. The performance of the CI method in designing the fractional PID controller was validated and compared with those of some other popular algorithms such as particle swarm optimization, the genetic algorithm, and the improved electromagnetic algorithm. The CI method yielded improved solutions in terms of the cost function, computing time, and function evaluations in comparison with the other three algorithms. In addition, the standard deviations of the CI method demonstrated the robustness of the proposed algorithm in solving control problems.

关键词： Cohort intelligence Fractional calculus Fractional PID controller Tuning

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Plant trait estimation and classification studies in plant phenotyping using machine vision - A review

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Information Processing in Agriculture 2023年第1期10卷 114-135页

作者： Shrikrishna Kolhar Jayant Jagtap symbiosis International(Deemed University)(SIU) LavalePuneIndia VPKBIET BaramatiMaharashtraIndia symbiosis institute of Technology(SIT) Symbiosis International(Deemed University)(SIU)LavalePuneMaharashtraIndia

Today there is a rapid development taking place in phenotyping of plants using non-destructive image based machine vision *** vision based plant phenotyping ranges from single plant trait estimation to broad assessment of crop canopy for thousands of plants in the *** phenotyping systems either use single imaging method or integrative approach signifying simultaneous use of some of the imaging techniques like visible red,green and blue(RGB)imaging,thermal imaging,chlorophyll fluorescence imaging(CFIM),hyperspectral imaging,3-dimensional(3-D)imaging or high resolution volumetric *** paper provides an overview of imaging techniques and their applications in the field of plant *** paper presents a comprehensive survey on recent machine vision methods for plant trait estimation and *** this paper,information about publicly available datasets is provided for uniform comparison among the state-of-the-art phenotyping *** paper also presents future research directions related to the use of deep learning based machine vision algorithms for structural(2-D and 3-D),physiological and temporal trait estimation,and classification studies in plants.

关键词： Plant phenotyping Machine vision Plant trait estimation Imaging techniques Leaf segmentation and counting Plant classification studies

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