Dr. D P Gaikwad | Computer Engineering | Best Innovation Award

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Dr. D P Gaikwad | Computer Engineering | Best Innovation Award

👩‍⚕️Dr. D P Gaikwad | AISSMS College of Engineering, Pune  | India

Dr. D P Gaikwad Arzideh distinguished academic and researcher in the field of renewable energy, holds a PhD in Biosystems Engineering from Kangwon National University, South Korea. His academic journey has been marked by a profound dedication to advancing solar energy technologies, specifically in solar thermal harvesting and its integration into agricultural and architectural applications.

Professional Profiles

Scopus profile

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🎓 Academic Record:

Ph.D. 

Passing Year: 2017 Board/University: Swami Ramanand Teerth Marathwada University, Nanded Main Subject: Computer Science and Engineering. Class, % Marks, No. of Attempts: NA

M. Tech.

Passing Year: 2006 Board/University: College of Engineering, Pune, SPPU, Pune Main Subject: Computer Science and Engineering. Class, % Marks, No. of Attempts: 7.03 CGPA First Class

B.E

Passing Year: 1996 Board/University: SGGS College of Engineering, Nanded Main Subject: Computer Science and Engineering. Class, % Marks, No. of Attempts: 60.80%, First Class

HSC

Passing Year: 1990 Board/University: Science College, Nanded Main Subject: General Science Class, % Marks, No. of Attempts: 69.33%, First Class

SSC

Passing Year: 1988 Board/University: Shri Sharada Bhavan High School, Nanded Main Subject: General Class, % Marks, No. of Attempts: 73.42%, First Class

📚 Teaching Experience:

Courses Taught: Microprocessor and Microcontrollers (UG) Network security (UG) Advanced Computer Networks (UG) Design of Algorithms (UG) Distributed Operating System (UG) Principles of Compiler Design (UG) Object Oriented Programming (UG) Neural Networks (UG) Theory of Computation (UG) Soft Computing Optimization Algorithm (PG) Machine Learning (PG) Advanced Computer Architecture (PG) Research Methodology (PG) Bio-inspired Optimization Algorithm (PG)

🏢 Administration Responsibilities Held:

Faculty Development Programme coordinator Head, Department of Computer Engineering In charge of Research and Development NBA Co-ordinator of Computer Department Subject Chairman of Computer and Network security Practical Chairman of Microprocessor and Interfacing techniques Chairman of Machine Learning Subject of ME (Computer)

🏆 International Awards Received:

Best Researcher Award – VDGOOD Technology Factory ICONIC Educationalist Award – The Glorious Organization for Accelerated in Literacy(GOAL) Shiksha Vibhuti Award – The Glorious Organization for Accelerated in Literacy(GOAL)  Best Researcher Award – Knowledge Research Academy, Coimbatore Best Faculty Award – Knowledge Research Academy, Coimbatore

📘 Chapter in International Book Publisher:

Machine Learning Algorithms for Prediction of Chemical Toxicity – CRC Press, 2023 Ensemble of Soft Computing Techniques for Inline Intrusion Detection System – Theory and Applications of Mathematical Science.

📊 Citation Metrics (Google Scholar):

Citations by: All – 502, Since 2018 – 370

h-index: All – 6, Since 2018 – 8

i10 index: All – 8, Since 2018 – 7

📖 Publications  Top Note :

Intrusion detection system using bagging ensemble method of machine learning  paper publication in

Intrusion detection system using bagging with partial decision treebase classifier    paper publication in  September 2015 cite by 85

Real time hybrid intrusion detection system using signature matching algorithm and fuzzy-GA   paper publication in 2016 cite by 39

Automated irrigation and crop security system in agriculture using Internet of Things  paper publication in  2020 cite by 10

Anomaly based intrusion detection system using artificial neural network and fuzzy clustering  paper publication in 2012 cite by 28

Hiding the Text and Image Message of Variable Size Using Encryption and Compression Algorithms in Video Steganography  paper publication in 2014 cite by 24

DAREnsemble: Decision tree and rule learner based ensemble for network intrusion detection system   paper publication in 2016 cite by 23

Color Image Restoration for an Effective Steganography    paper publication in 2010 cite by 16

Normalization using improvised K-means applied in diagnosing thyroid disease with ANN      paper publication in 2017 cite by 9

Sign-Talk: Hand gesture recognition system       paper publication in 2017 cite by 9

 

 

Dr. Seyyed Mohammad Arzideh | Response Surface Methodology | Engineering Data Analytics Leadership Award

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Dr. Seyyed Mohammad Arzideh | Response Surface Methodology | Engineering Data Analytics Leadership Award

👩‍⚕️Dr. Seyyed Mohammad Arzideh | Babol Noshirvani University of Technology  | Iran

Dr. Seyyed Mohammad Arzideh distinguished academic and researcher in the field of renewable energy, holds a PhD in Biosystems Engineering from Kangwon National University, South Korea. His academic journey has been marked by a profound dedication to advancing solar energy technologies, specifically in solar thermal harvesting and its integration into agricultural and architectural applications.

Professional Profiles

Scopus profile

google scholar

orcid profile

👩‍🎓 Profile

Highly self-motivated Ph.D. in Chemical EngineeringResearch expertise: Separation Processes, Chemical Thermodynamics, Polymeric Solutions CharacterizationsExperimental techniques: Ionic Liquid Based Bioseparation System, Polymeric Biphasic Systems, Supercritical Fluid Extraction (SFE)Computerized simulation: MATLAB, Aspen HYSYS, ANSYS FluentLaboratory skills: Gas and Liquid Chromatography (GC/LC), Atomic Absorption Spectroscopy (AAS), UV-Vis. Spectroscopy

🎓 Education:

🏫 Ph.D. in Chemical Engineering from Babol Noshirvani University of Technology, Iran (GPA: 3.9/4.0, 2021).📝 Thesis Title: “An Activity Coefficient Model for Fluid Phase Multicomponent Mixtures Based on Binary and Ternary Collision in Liquid-liquid Equilibrium along with Experimental Study of Aqueous Two Phase Equilibria of Ionic Liquids.”🏫 M.Sc. in Chemical Engineering from Sharif University of Technology, Tehran, Iran (GPA: 3.7/4.0, 2010).📝 Thesis Title: “Extraction of Organic Component by Supercritical Fluid.”🏫 B.Sc. in Chemical Engineering from General Directorate of Girls Colleges, Girls College of Education-Scientific Section, Jeddah, Saudi Arabia (GPA: Excellent with Honor, 1997).

🔍 Research Interest:

🧪 Innovative separation techniques for biomolecules and organic substances.🧪 Design of separation processes using novel solvents like ILs, DES, and SCF.📊 Thermodynamic model development for separation processes.⚗️ Ion-solvation analysis in complex electrolyte mixtures.

👩‍🔬Research Experience:

🧫 Developed the HIS-UNIQUAC activity coefficient model for fluid phase multicomponent mixtures during Ph.D. thesis.🌡️ Investigated the biomolecule partition in an adjuvant quaternary biphasic system.🧪 Explored IL solvation in HIS-UNIQUAC model, analyzing ion-association behavior in mixed-solvent solutions.

💡Research Contributions:

📈 HIS-UNIQUAC model efficiently describes both single-solvent and mixed-solvent electrolyte systems.🌐 Proposed a quaternary biphasic system for biomolecule partitioning, considering IL selectivity.⚡ Studied ion-association and solvation behavior of IL in mixed-solvent solutions, enhancing biomolecule affinity.

🔬 Laboratory Skills:

🧪 Gas and Liquid Chromatography (GC/LC).🌈 Atomic Absorption Spectroscopy (AAS).🌞 UV-Vis. Spectroscopy.🔥 Thermal Gravimetric Analysis (TGA).📏 Karl-Fischer Titration.

📚  Research Publications

📄 Published articles in reputable journals covering topics such as HIS-UNIQUAC model, biomolecule partitioning, and IL solvation.

🛠️ Software And Programming Skills:

🖥️ MATLAB, Aspen HYSYS, ANSYS Fluent for computerized simulation.📊 Statistical analysis using tools like SPSS.💻 Programming skills in QBasic, Fortran, C++, and Mathematica.

🏆 Awards And Honor:

🏅 Recognized for the Ph.D. thesis on “An Activity Coefficient Model for Fluid Phase Multicomponent Mixtures.”

🌍 Internationl Conllaborations:

🌐 Collaborated with researchers from diverse backgrounds in conferences and workshops.

📖 Teaching Experience:

👩‍🏫 Shared expertise in chemical engineering and separation processes through teaching.

🔍 Extracurricular Activities:

🌐 Actively engaged in peer review activities for renowned journals.

📈 Mentorship:

🤝 Provided guidance and mentorship to students in research projects.

🏆 Certificates And RSanking:

🏆 Received certificates of recognition for outstanding contributions.📊 Ranked among the top students in academic evaluations.

📑 Conclusion: .

Dr. [Name] is a highly self-motivated and accomplished Ph.D. graduate with a strong background in chemical engineering and a focus on separation processes. Her research contributions, laboratory skills, and proficiency in various software make her a valuable asset in the field. The innovative approaches and international collaborations reflect her commitment to advancing scientific knowledge. 🌟

📊 Citation Metrics (Google Scholar):

Citations by: All – 82, Since 2018 – 82

h-index: All – 6, Since 2018 – 6

i10 index: All – 4, Since 2018 – 4

📖 Publications  Top Note :

Influence of the temperature, type of salt, and alcohol on phase diagrams of 2-propanol+ inorganic salt aqueous two-phase systems: experimental determination and correlation   paper publication in

Phase equilibria of aqueous two-phase systems of PEG with sulfate salt: effects of pH, temperature, type of cation, and polymer molecular weight  paper publication in  September 2021 cite by 13

Ion-solvent interaction of 1-decyl-3-methylimidazolium chloride and isopropanol in a quaternary aqueous two phase system for the efficient partitioning of vanillin and L-tryptophan   paper publication in 2021 cite by 12

Equilibrium data and thermodynamic studies of L-tryptophan partition in alcohol/phosphate potassium salt-based aqueous two phase systems  paper publication in  2020 cite by 10

Phase equilibria of PEG/sulfate salt aqueous two-phase systems: Effects of PH and molecular weight of polymer  paper publication in 2021 cite by 7

Phase behavior for 1-butyl-3-methylimidazolium tetrafluoroborate with sodium oxalate/succinate/formate aqueous two-phase systems at 298.15 and 308.15 K   paper publication in 2020 cite by 7

Temperature, Polymer Molecular Weight, and Salt Effects on Phase Equilibria of PVP+ Formate Salts+ Water: Experimental Measurements, Correlations, and Thermodynamic Modeling    paper publication in 2021 cite by 6

Green extraction of Cu (II) in PEG-zinc sulfate aqueous two phase system using response surface methodology paper publication in 2022 cite by 5

Phase Equilibria of the Ternary System of Lithium Sulfate+ Polyethylene Glycol (PEG3000)+ Water at Different pH: Experiment Determination, Correlation, and Thermodynamic Modeling      paper publication in 2022 cite by 2

Measurements, correlations and thermodynamic modeling of aqueous two-phase systems of polyvinylpyrrolidone (PVP)+ sulfate/citrate salts  paper publication in 2023

 

 

Statistical Process Control (SPC)

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Statistical Process Control

Statistical Process Control (SPC) is a quality control and improvement methodology that uses statistical methods to monitor, control, and improve processes in various industries. SPC is particularly valuable in manufacturing and production settings but can be applied to virtually any process where data can be collected. Here are some key aspects and concepts related to SPC:

Process Variation

SPC is primarily concerned with understanding and managing two types of process variation: common cause variation (inherent to the process) and special cause variation (due to external factors or anomalies).

Control Charts

Control charts, also known as Shewhart charts or process-behavior charts, are a fundamental tool in SPC. They display process data over time, with upper and lower control limits to identify when a process is in or out of control.

Data Collection

SPC relies on the regular collection of data points or samples from a process. This data is then analyzed to assess process stability and identify any trends or deviations from expected performance.

Central Tendency and Variation

SPC often uses statistical measures of central tendency (e.g., mean or median) and measures of variation (e.g., range or standard deviation) to characterize a process and monitor its performance.

Process Capability Analysis

This involves assessing a process’s ability to produce products or services that meet customer specifications. Process capability indices like Cp, Cpk, Pp, and Ppk are used for this purpose.

Probability distributions

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Probability distributions

This conference serves as a platform for the exchange of cutting-edge ideas and methodologies for analyzing and interpreting data in the realm of engineering, with a particular focus on probability distributions and their applications.

Bayesian Methods for Engineering Data Analysis

This subtopic delves into the utilization of Bayesian statistical techniques for modeling and analyzing engineering data. It explores Bayesian inference, Markov Chain Monte Carlo (MCMC) methods, and their applications in engineering contexts.

Reliability Analysis and Probabilistic Design

This subtopic addresses the critical aspects of reliability analysis and how probability distributions play a vital role in assessing the reliability of engineering systems. It also covers probabilistic design methodologies to enhance system performance and safety.

Time Series Analysis in Engineering

Time series data are prevalent in engineering applications. This subtopic focuses on advanced statistical methods for modeling and forecasting time-dependent engineering data, addressing challenges like autocorrelation and seasonality.

Nonparametric Statistics for Engineering Data

Nonparametric statistical methods are vital when the underlying distribution of data is unknown or does not follow a specific parametric form. This subtopic explores techniques like kernel density estimation and rank-based tests in engineering contexts.

Statistical Quality Control and Process Optimization

Statistical methods for quality control and process optimization are critical in engineering industries. This subtopic examines the application of probability distributions in maintaining product quality and optimizing manufacturing processes.

Descriptive statistics

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Descriptive statistic

The International Research Awards on Statistical Methods for Analyzing Engineering Data serve as a prestigious platform recognizing and promoting groundbreaking research in the field of statistical analysis applied to engineering data.

Data Visualization Techniques

Effective visualization methods for engineering data, such as scatter plots, histograms, and box plots, to gain insights into data distributions and trends.

Summary Statistics for Engineering Parameters

Exploration of summary statistics like mean, median, variance, and skewness tailored to engineering variables, aiding in the characterization of data central tendencies and variability.

Time Series Analysis in Engineering

Application of descriptive statistical methods to analyze time-dependent engineering data, including autocorrelation, trend analysis, and seasonal decomposition.

Multivariate Data Analysis

Techniques for summarizing and visualizing multivariate engineering data, such as principal component analysis (PCA) and factor analysis, to identify latent patterns and relationships.

Reliability and Failure Analysis

Descriptive statistics specific to reliability engineering, including the calculation of failure rates, mean time to failure (MTTF), and Weibull analysis, to assess product and system performance.