Search results for: Swathi Gosh Acharyya

Authors: K. Sruthi, Sai Snehitha Yadavalli, Swathi Gosh Acharyya

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Water is the most crucial element for sustaining life on earth. Increasing water pollution directly or indirectly leads to harmful effects on human life. Most of the heavy metal ions are harmful in their cationic form. These heavy metal ions are released by various activities like disposing of batteries, industrial wastes, automobile emissions, and soil contamination. Ions like (Pb, Co, Cd) are carcinogenic and show many harmful effects when consumed more than certain limits proposed by WHO. The simultaneous detection of the heavy metal ions (Pb, Co, Cd), which are highly toxic, is reported in this study. There are many analytical methods for quantifying, but electrochemical techniques are given high priority because of their sensitivity and ability to detect and recognize lower concentrations. Square wave voltammetry was preferred in electrochemical methods due to the absence of background currents which is interference. Square wave voltammetry was performed on GCE for the quantitative detection of ions. Three electrode system consisting of a glassy carbon electrode as the working electrode (3 mm diameter), Ag/Agcl electrode as the reference electrode, and a platinum wire as the counter electrode was chosen for experimentation. The mechanism of detection was done by optimizing the experimental parameters, namely pH, scan rate, and temperature. Under the optimized conditions, square wave voltammetry was performed for simultaneous detection. Scan rates were varied from 5 mV/s to 100 mV/s and found that at 25 mV/s all the three ions were detected simultaneously with proper peaks at particular stripping potential. The variation of pH from 3 to 8 was done where the optimized pH was taken as pH 5 which holds good for three ions. There was a decreasing trend at starting because of hydrogen gas evolution, and after pH 5 again there was a decreasing trend that is because of hydroxide formation on the surface of the working electrode (GCE). The temperature variation from 25˚C to 45˚C was done where the optimum temperature concerning three ions was taken as 35˚C. Deposition and stripping potentials were given as +1.5 V and -1.5 V, and the resting time of 150 seconds was given. Three ions were detected at stripping potentials of Cd²⁺ at -0.84 V, Pb²⁺ at -0.54 V, and Co²⁺ at -0.44 V. The parameters of detection were optimized on a glassy carbon electrode for simultaneous detection of the ions at lower concentrations by square wave voltammetry.

Keywords: cadmium, cobalt, lead, glassy carbon electrode, square wave anodic stripping voltammetry

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Authors: Swathi Sampath, V. Kalaichelvi

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The assessment of the risk posed by a borrower to a lender is one of the common problems that financial institutions have to deal with. Consumers vying for a mortgage are generally compared to each other by the use of a number called the Credit Score, which is generated by applying a mathematical algorithm to information in the applicant’s credit report. The higher the credit score, the lower the risk posed by the candidate, and the better he is to be taken on by the lender. The objective of the present work is to use fuzzy logic and linguistic rules to create a model that generates Credit Scores.

Keywords: credit scoring, fuzzy logic, mortgage, risk assessment

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Authors: Mohamad Shurair, Fares Almomani, Simon Judd, Rahul Bhosale, Anand Kumar, Ujjal Gosh

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This study evaluated the use of mixed indigenous microalgae (MIMA) as a treatment process for wastewaters and CO2 capturing technology at different temperatures. The study follows the growth rate of MIMA, removals of organic matter, removal of nutrients from synthetic wastewater and its effectiveness as CO2 capturing technology from flue gas. A noticeable difference between the growth patterns of MIMA was observed at different CO2 and different operational temperatures. MIMA showed the highest growth grate when injected with CO2 dosage of 10% and limited growth was observed for the systems injected with 5% and 15 % of CO2 at 30 ◦C. Ammonia and phosphorus removals for Spirulina were 69%, 75%, and 83%, and 20%, 45%, and 75% for the media injected with 0, 5 and 10% CO2. The results of this study show that simple and cost-effective microalgae-based wastewater treatment systems can be successfully employed at different temperatures as a successful CO2 capturing technology even with the small probability of inhibition at high temperatures

Keywords: greenhouse, climate change, CO2 capturing, green algae

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Authors: Sonali Banrjee, Swarup Kumar Mitra, Aritra Acharyya

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A piano note recognition method has been proposed by the authors in this paper. The authors have used a comprehensive method for onset detection of each note present in a piano piece followed by segmented short-time Fourier transform (STFT) for the identification of piano notes. The performance evaluation of the proposed method has been carried out in different harsh noisy environments by adding different levels of additive white Gaussian noise (AWGN) having different signal-to-noise ratio (SNR) in the original signal and evaluating the note detection error rate (NDER) of different piano pieces consisting of different number of notes at different SNR levels. The NDER is found to be remained within 15% for all piano pieces under consideration when the SNR is kept above 8 dB.

Keywords: AWGN, onset detection, piano note, STFT

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Authors: Fares Almomani, Majeda Khraisheh, Rahul Bhosale, Anand Kumar, Ujjal Gosh

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Septic tanks (STs) are very commonly used wastewater collection systems in the world especially in rural areas. In this study, the use of moving bed biological reactors (MBBR) for the treatment of septic tanks effluents (STE) was studied. The study was included treating septic tank effluent from one house hold using MBBRs. Significant ammonia removal rate was observed in all the reactors throughout the 180 days of operation suggesting that the MBBRs were successful in reducing the concentration of ammonia from septic tank effluent. The average ammonia removal rate at 25◦C for the reactor operated at hydraulic retention time of 5.7 hr (R1) was 0.540 kg-N/m3and for the reactor operated at hydraulic retention time of 13.3hr (R2) was 0.279 kg-N/m3. Ammonia removal rates were decreased to 0.3208 kg-N/m3 for R1 and 0.212 kg-N/m3 for R3 as the temperature of reactor was decreased to 8 ◦C. A strong correlation exists between theta model and the rates of ammonia removal for the reactors operated in continuous flow. The average ϴ values for the continuous flow reactors during the temperature change from 8°C to 20 °C were found to be 1.053±0.051. MBBR technology can be successfully used as a polishing treatment for septic tank effluent.

Keywords: septic tanks, wastewater treatment, morphology, moving biological reactors, nitrification

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Authors: Dechrit Maneetham

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Pick and place task is one among the most important tasks in industrial field handled by 'Selective Compliance Assembly Robot Arm' (SCARA). Repeatability with high-speed movement in a horizontal plane is a remarkable feature of this type of manipulator. The challenge of design SCARA is the difficulty of achieving stability of high-speed movement with the long length of links. Shorter links arm can move more stable. This condition made the links should be considered restrict then followed by restriction of operation area (workspace). In this research, authors demonstrated on expanding SCARA robot’s workspace in horizontal area via linear sliding actuator that embedded to base link of the robot arm. With one additional prismatic joint, the previous robot manipulator with 3 degree of freedom (3-DOF), 2 revolute joints and 1 prismatic joint becomes 4-DOF PRRP manipulator. This designation increased workspace of robot from 0.5698m² performed by the previous arm (without linear actuator) to 1.1281m² by the proposed arm (with linear actuator). The increasing rate was about 97.97% of workspace with the same links' lengths. The result of experimentation also indicated that the operation time spent to reach object position was also reduced.

Keywords: kinematics, linear sliding actuator, manipulator, control system

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Authors: Swathi M. Vanniarajan

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Reading research suggests that online contextual vocabulary comprehension while reading is an interactive and integrative process. One’s success in it depends on a variety of factors including the amount and the nature of available linguistic and nonlinguistic cues, his/her analytical and integrative skills, schema memory (content familiarity), and processing speed characterized along the continuum of controlled to automatic processing. The experiment reported here, conducted with 30 native speakers as one group and 30 nonnative speakers as another group (all graduate students), hypothesized that while working on (24) tasks which required them to comprehend an unfamiliar word in real time without backtracking, due to the differences in the nature of their respective reading processes, the nonnative subjects would be less able to construct the meanings of the unknown words by integrating the multiple but sufficient contextual cues provided in the text but the native subjects would be able to. The results indicated that there were significant inter-group as well as intra-group differences in terms of the quality of definitions given. However, when given additional time, while the nonnative speakers could significantly improve the quality of their definitions, the native speakers in general would not, suggesting that all things being equal, time is a significant factor for success in nonnative vocabulary and reading comprehension processes and that accuracy precedes automaticity in the development of nonnative reading processes also.

Keywords: reading, second language processing, vocabulary comprehension

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Authors: S. S. Sravanthi, Swati Ghosh Acharyya

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Automotive light weighting is of major prominence in the current times due to its contribution in improved fuel economy and reduced environmental pollution. Various arc welding technologies are being employed in the production of automobile components with reduced weight. The present study is of practical importance since it involves preferential substitution of Zinc coated mild steel with a light weight alloy such as 6061 Aluminium by means of Gas Metal Arc Welding (GMAW) – Brazing technique at different processing parameters. However, the fabricated joints have shown the generation of Al – Fe layer at the interfacial regions which was confirmed by the Scanning Electron Microscope and Energy Dispersion Spectroscopy. These Al-Fe compounds not only affect the mechanical strength, but also predominantly deteriorate the corrosion resistance of the joints. Hence, it is essential to understand the phases formed in this layer and their crystal structure. Micro area X - ray diffraction technique has been exclusively used for this study. Moreover, the crevice corrosion analysis at the joint interfaces was done by exposing the joints to 5 wt.% FeCl₃ solution at regular time intervals as per ASTM G 48-03. The joints have shown a decreased crevice corrosion resistance with increased heat intensity. Inner surfaces of welds have shown severe oxide cracking and a remarkable weight loss when exposed to concentrated FeCl₃. The weight loss was enhanced with decreased filler wire feed rate and increased heat intensity. 

Keywords: automobiles, welding, corrosion, lap joints, Micro XRD

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Authors: B. S. Chandrashekar, M. K. Prasannakumar, P. Buela Parivallal, Sahana N. Banakar, Swathi S. Patil, H. B. Mahesh, D. Pramesh

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Bacterial soft rot is one of the most often seen diseases in many plant species globally, resulting in considerable yield loss. Radish roots with dark water-soaked lesions, maceration of tissue, and a foul odour were collected in the Kolar region, India. Two isolates were obtained from rotted samples that demonstrated morphologically unpigmented, white mucoid convex colonies on nutrient agar medium. The isolated bacteria (RDH1 and RDH3) were gram-negative, rod-shaped bacteria with biochemically distinct characteristics similar to the type culture of Enterobacter cloacae ATCC13047 and Bergy's handbook of determinative bacteriology. The 16s rRNA gene was used to identify Enterobacter species. On carrot, potato, tomato, chilli, bell pepper, knolkhol, cauliflower, cabbage, and cucumber slices, the Koch′s postulates were fulfilled, and the pathogen was also pathogenic on radish, cauliflower, and cabbage seedlings were grown in a glasshouse. After 36 hours, both isolates exhibited a hypersensitive sensitivity to Nicotianatabacum. Semi-quantitative analysis revealed that cell wall degrading enzymes (CWDEs) such as pectin lyase, polygalacturonase, and cellulase (p=1.4e09) contributed to pathogenicity, whereas isolates produced biofilms (p=4.3e-11) that help in host adhesion. This is the first report in India of radish soft rot caused by E. cloacae.

Keywords: soft rot, enterobacter cloacae, 16S rRNA, nicotiana tabacum, and pathogenicity

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Authors: Basavaraj Kabade, K. T. Nagaraja, Swathi Ramanathan, A. Veeraragavan, P. S. Reashma

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Deteriorating quality of the pedestrian environment and the increasing risk of pedestrian crashes are major concerns for most of the cities in India. The recent shift in the priority to motorized transport and the abating condition of existing pedestrian facilities can be considered as prime reasons for the increasing pedestrian related crashes in India. Bengaluru City – the IT capital hub of the nation is not much different from this. The increase in number of pedestrian crashes in Bengaluru reflects the same. To resolve this issue and to ensure safe, sustainable and pedestrian friendly sidewalks, Govt. of Karnataka, India has implemented newfangled pedestrian sidewalks popularized programme named Tender S.U.R.E. (Specifications for Urban Road Execution) projects. Tender SURE adopts unique urban street design guidelines where the pedestrians are given prime preference. The present study presents an assessment of the quality and performance of the pedestrian side walk and the walkability index of the newly built pedestrian friendly sidewalks. Various physical and environmental factors affecting pedestrian safety are identified and studied in detail. The pedestrian mobility is quantified through Pedestrian Level of Service (PLoS) and the pedestrian walking comfort is measured by calculating the Walkability Index (WI). It is observed that the new initiatives taken in reference to improving pedestrian safety have succeeded in Bengaluru by attaining a level of Service of ‘A’ and with a good WI score.

Keywords: pedestrian safety, pedestrian level of service (PLoS), Right of Way (RoW), Tender S.U.R.E (Specifications for Urban Road Execution), walkability index (WI), walkway facilities

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Authors: Swathi Gopakumar, Sruthi Krishna, Shivasubramani Krishnamoorthy

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Contactless, painless and radiation-free thermal imaging technology is one of the preferred screening modalities for detection of breast cancer. However, poor signal to noise ratio and the inexorable need to preserve edges defining cancer cells and normal cells, make the segmentation process difficult and hence unsuitable for computer-aided diagnosis of breast cancer. This paper presents key findings from a research conducted on the appraisal of two promising techniques, for the detection of breast cancer: (I) marker-controlled, Level-set segmentation of anisotropic diffusion filtered preprocessed image versus (II) Segmentation using marker-controlled level-set on a Gaussian-filtered image. Gaussian-filtering processes the image uniformly, whereas anisotropic filtering processes only in specific areas of a thermographic image. The pre-processed (Gaussian-filtered and anisotropic-filtered) images of breast samples were then applied for segmentation. The segmentation of breast starts with initial level-set function. In this study, marker refers to the position of the image to which initial level-set function is applied. The markers are generally placed on the left and right side of the breast, which may vary with the breast size. The proposed method was carried out on images from an online database with samples collected from women of varying breast characteristics. It was observed that the breast was able to be segmented out from the background by adjustment of the markers. From the results, it was observed that as a pre-processing technique, anisotropic filtering with level-set segmentation, preserved the edges more effectively than Gaussian filtering. Segmented image, by application of anisotropic filtering was found to be more suitable for feature extraction, enabling automated computer-aided diagnosis of breast cancer.

Keywords: anisotropic diffusion, breast, Gaussian, level-set, thermograms

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Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

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Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis

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Authors: V. Sai Geethika, Sai Snehitha Yadavalli, Swati Ghosh Acharyya

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This study involves a single element and simultaneous electrochemical detection of heavy metal ions through square wave anodic stripping voltammetry. A glassy carbon electrode was used to detect and quantify heavy metals such as As(III), Hg(II), Cr(VI) ions in water. Under optimized conditions, peak separation was obtained by varying concentrations, scan rates, and temperatures. As (III), Hg (II), Cr (III) were simultaneously detected with GCE. Several analytical methods, such as inductively coupled plasma mass spectroscopy (ICP-MS), atomic absorption spectroscopy (AAS), were used previously to detect heavy metal ions, which are authentic but are not good enough for online monitoring due to the bulkiness of the equipment. The study provides a good alternative that is simple, more efficient, and low-cost, involving a portable potentiostat. Heavy metals having different oxidation states can be detected by anodic stripping voltammetry. This method can be easily integrated with electronics. Square wave Anodic stripping voltammetry is used with a potential range of -2.5 V – 2.5 V for single ion detection by a three-electrode cell consisting of silver/silver chloride(Ag/AgCl) as reference and platinum (Pt) counter and glassy carbon (GCE) working electrodes. All three ions are optimized by varying the parameters like concentration, scan rate, pH, temperature, and all these optimized parameters were used for studying the effects of simultaneous detection. The procedure involves preparing an electrolyte using deionized water, cleaning the surface of GCE, depositing the ions by applying the redox potentials obtained from cyclic voltammetry (CV), and then detecting by applying oxidizing potential, i.e., stripping voltage. So this includes ASV techniques such as open-circuit voltage (OCV), chronoamperometry (CA), and square wave voltammetry (SWV). Firstly, the concentration of the ions varied from 50 ppb to 5000 ppb, and an optimum concentration was determined where the three ions were detected. A concentration of 400 ppb was used while varying the temperatures in the range of 25°C – 45°C. Optimum peak intensity was obtained at a temperature of 30°C with a low scan rate of 0.005 V-s⁻¹. All the parameters were optimized, and several effects have been noticed while three ions As(II), Cr(III), Hg(II) were detected alone and simultaneously.

Keywords: Arsenic(III), Chromium(III), glassy carbon electrode, Mercury (II), square wave anodic stripping voltammetry

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Authors: Sai Snehitha Yadavalli, K. Sruthi, Swati Ghosh Acharyya

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Heavy metal ions are toxic to humans and all living species when exposed in large quantities or for long durations. Though Fe acts as a nutrient, when intake is in large quantities, it becomes toxic. These toxic heavy metal ions, when consumed through water, will cause many disorders and are harmful to all flora and fauna through biomagnification. Specifically, humans are prone to innumerable diseases ranging from skin to gastrointestinal, neurological, etc. In higher quantities, they even cause cancer in humans. Detection of these toxic heavy metal ions in water is thus important. Traditionally, the detection of heavy metal ions in water has been done by techniques like Inductively Coupled Plasma Mass Spectroscopy (ICPMS) and Atomic Absorption Spectroscopy (AAS). Though these methods offer accurate quantitative analysis, they require expensive equipment and cannot be used for on-site measurements. Anodic Stripping Voltammetry is a good alternative as the equipment is affordable, and measurements can be made at the river basins or lakes. In the current study, Square Wave Anodic Stripping Voltammetry (SWASV) was used to detect the heavy metal ions in water. Literature reports various electrodes on which deposition of heavy metal ions was carried out like Bismuth, Polymers, etc. The working electrode used in this study is a polyvinyl chloride (PVC) modified glassy carbon electrode (GCE). Ag/AgCl reference electrode and Platinum counter electrode were used. Biologic Potentiostat SP 300 was used for conducting the experiments. Through this work of simultaneous detection, four heavy metal ions were successfully detected at a time. The influence of modifying GCE with PVC was studied in comparison with unmodified GCE. The simultaneous detection of Cd⁺², Fe⁺², Co⁺², Pb⁺² heavy metal ions was done using PVC modified GCE by drop casting 1 wt.% of PVC dissolved in Tetra Hydro Furan (THF) solvent onto GCE. The concentration of all heavy metal ions was 0.2 mg/L, as shown in the figure. The scan rate was 0.1 V/s. Detection parameters like pH, scan rate, temperature, time of deposition, etc., were optimized. It was clearly understood that PVC helped in increasing the sensitivity and selectivity of detection as the current values are higher for PVC-modified GCE compared to unmodified GCE. The peaks were well defined when PVC-modified GCE was used.

Keywords: cadmium, cobalt, electrochemical sensing, glassy carbon electrodes, heavy metal Ions, Iron, lead, polyvinyl chloride, potentiostat, square wave anodic stripping voltammetry

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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