Search results for: Mohan Mathew

Authors: B. Parchem, M. Watanabe, D. Modrakovic, L. Mathew, A. Franklin, M. Cao, R. E. Broudy

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Objective: Executive functioning (EF) deficits underlie several mental health diagnoses including ADHD, anxiety, and depression. Community mental health clinics face extensive waitlists for services with many referrals involving EF deficits. A pilot trial of a four-week group therapy was developed using key components from Cognitive-Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), and mindfulness with an aim to improve EF skills and offer low-fee services. Method: Eight adults (M = 34.5) waiting for services at a community clinic were enrolled in a four-week group therapy at an in-house training clinic for doctoral trainees. Baseline EF, pre-/post-intervention ADHD and distress symptoms, group satisfaction, and curriculum helpfulness were assessed. Results: Downward trends in ADHD and distress symptoms pre/post-intervention were not significant. Favorable responses on group satisfaction and helpfulness suggest clinical utility. Conclusion: Preliminary pilot data from a brief group therapy to improve EF may be an efficacious, acceptable, and feasible intervention for adults waiting for services at community mental health and training clinics where there are high demands and limits to services and staffs.

Keywords: executive functioning, cognitive-behavioral therapy, dialectical behavior therapy, mindfulness, adult group therapy

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Authors: Jiji Jose, R. Narayanacharyulu, Molly Mathew, Jisha Prems

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Introduction: Lercanidipine hydrochloride (LD), an effective calcium channel blocker, widely used for the treatment of chronic stable angina and hypertension seems to be potential transdermal therapeutic system candidate, mainly due to its low oral bio availability, short half life and high first-pass metabolism. Objective: To develop transdermal therapeutic systems for LD and to evaluate its in vivo performance in rabbits. Methodology: Transdermal patches of LD were formulated using the polymer blend of eudragit RL100 (ERL) and polyvinyl pyrolidone (PVP) by casting method Propylene glycol (PG) and tween 80 were used as plasticizer and permeation enhancer respectively. The pharmaco kinetic parameters of LD after the administration of transdermal patches was compared with that of oral administration. The study was carried out in a two way crossover design in male New Zealand albino rabbits. Results: The formulation with ERL: PVP ratio 1:4 with 15% w/w PG as plasticizer and 4% w/w tween 80 as permeation enhancer showed the best drug release results. The pharmacokinetic parameters such as Cmax, tmax, mean residence time (MRT) and area under the curve (AUC 0-∞) were significantly different following transdermal administration compared to oral administration. The terminal half life of transdermally administered LD was found to similar that of oral administration. A sustained drug release over a period of 24 hrs was observed after transdermal administration. Conclusion: The fabricated transdermal delivery system have the potential to provide controlled and extended drug release, better bio availability and thus, this may improve the patient compliance.

Keywords: transdermal therapeutic system, lercanidipine hydrochloride, eudragit, skinpermeation

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Authors: Virender Singh, Mathew Rees, Simon Hampton, Sivaram Annadurai

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Plant identification is a challenging task that aims to identify the family, genus, and species according to plant morphological features. Automated deep learning-based computer vision algorithms are widely used for identifying plants and can help users narrow down the possibilities. However, numerous morphological similarities between and within species render correct classification difficult. In this paper, we tested custom convolution neural network (CNN) and vision transformer (ViT) based models using the PyTorch framework to classify plants. We used a large dataset of 88,000 provided by the Royal Horticultural Society (RHS) and a smaller dataset of 16,000 images from the PlantClef 2015 dataset for classifying plants at genus and species levels, respectively. Our results show that for classifying plants at the genus level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420 and other state-of-the-art CNN-based models suggested in previous studies on a similar dataset. ViT model achieved top accuracy of 83.3% for classifying plants at the genus level. For classifying plants at the species level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420, with a top accuracy of 92.5%. We show that the correct set of augmentation techniques plays an important role in classification success. In conclusion, these results could help end users, professionals and the general public alike in identifying plants quicker and with improved accuracy.

Keywords: plant identification, CNN, image processing, vision transformer, classification

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Authors: Joseph C. Chen, Venkata Mohan Kudapa

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Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.

Keywords: surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations

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Authors: Ivy Rose Mathew

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The purpose of this study is to outline the efficacy of technology and the opportunities it can bring to implement a successful delivery model in Distance Learning. Distance Learning has proliferated over the past few years across the world. Some of the current challenges faced by current students of distance education include lack of motivation, a sense of isolation and a need for greater and improved communication. Hence the author proposes a creative technology supported model for distance learning exactly mirrored on the traditional face to face learning that can be adopted by distance learning providers. This model suggests the usage of a range of technologies and social networking facilities, with the aim of creating a more engaging and sustaining learning environment to help overcome the isolation often noted by distance learners. While discussing the possibilities, the author also highlights the complexity and practical challenges of implementing such a model. Design/methodology/approach: Theoretical issues from previous research related to successful models for distance learning providers will be considered. And also the analysis of a case study from one of the largest private tertiary institution in Botswana, Botho University will be included. This case study illustrates important aspects of the distance learning delivery model and provides insights on how curriculum development is planned, quality assurance is done, and learner support is assured for successful distance learning experience. Research limitations/implications: While some of the aspects of this study may not be applicable to other contexts, a number of new providers of distance learning can adapt the key principles of this delivery model.

Keywords: distance learning, efficacy, learning experience, technology supported model

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Authors: Rohini Hariharan, Yazhini R., Blessy Maria Mathew

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The task of detecting email spam is a very important one in the era of digital technology that needs effective ways of curbing unwanted messages. This paper presents an approach aimed at making email spam categorization algorithms transparent, reliable and more trustworthy by incorporating Local Interpretable Model-agnostic Explanations (LIME). Our technique assists in providing interpretable explanations for specific classifications of emails to help users understand the decision-making process by the model. In this study, we developed a complete pipeline that incorporates LIME into the spam classification framework and allows creating simplified, interpretable models tailored to individual emails. LIME identifies influential terms, pointing out key elements that drive classification results, thus reducing opacity inherent in conventional machine learning models. Additionally, we suggest a visualization scheme for displaying keywords that will improve understanding of categorization decisions by users. We test our method on a diverse email dataset and compare its performance with various baseline models, such as Gaussian Naive Bayes, Multinomial Naive Bayes, Bernoulli Naive Bayes, Support Vector Classifier, K-Nearest Neighbors, Decision Tree, and Logistic Regression. Our testing results show that our model surpasses all other models, achieving an accuracy of 96.59% and a precision of 99.12%.

Keywords: text classification, LIME (local interpretable model-agnostic explanations), stemming, tokenization, logistic regression.

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Authors: Dinesh Kumar Maurya, Sapan Mohan Saini

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A theoretical formalism to calculate the structural, electronic and optical properties of orthorhombic crystals from first principle calculations is described. This is applied first time to new YNi4Si-type DyNi4Si compound. Calculations are performed using full-potential augmented plane wave (FPLAPW) method in the framework of density functional theory (DFT). The Coulomb corrected local-spin density approximation (LSDA+U) in the self-interaction correction (SIC) has been used for exchange-correlation potential. Our optimized results of lattice parameters show good agreement to the previously reported experimental study. Analysis of the calculated band structure of DyNi4Si compound demonstrates their metallic character. We found Ni-3d states mainly contribute to density of states from -5.0 eV to the Fermi level while the Dy-f states peak stands tall in comparison to the small contributions made by the Ni-d and R-d states above Fermi level, which is consistent with experiment, in DNi4Si compound. Our calculated optical conductivity compares well with the experimental data and the results are analyzed in the light of band-to-band transitions. We also report the frequency-dependent refractive index n(ω) and the extinction coefficient k(ω) of the compound.

Keywords: band structure, density of states, optical properties, LSDA+U approximation, YNi4Si- type DyNi4Si compound

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Authors: Noor Shafifiyaz Mohd Yazid, Najihah Mohd Hashim, Hapipah Mohd Ali, Syam Mohan, Rosea Go

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Artocarpus kemando is a plant species from Moraceae family. This plant is used as household utensil by the local and the fruits are edible. The plants’ bark was used for the extraction process and yielded the chloroform crude extract which was used to screen for anticancer potential. The cytotoxic effect of the extract on CAOV-3 and WRL 68 cell lines were determined using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide or MTT assays. Qualitative AO/PI assay was performed to confirm the apoptosis and necrosis process. Meanwhile, the measurement of cell loss, nuclear morphology, DNA content, cell membrane permeability, mitochondrial membrane potential changes and cytochrome c release from mitochondria were detected through cytotoxicity 3 assay. In MTT assay, A. kemando inhibited 50% growth of CAOV-3 cells at 27.9 ± 0:03, 20.1± 0:03, 18.21± 0:04 µg/mL after 24, 48 and 72 hour, respectively. The morphology changes can be seen on CAOV-3 with a production of cell membrane blebbing, cromatin condensation and apoptotic bodies. Evaluation of cytotoxicity 3 on CAOV-3 cells after treated with extract resulting loss of mitochondrial membrane potential and release of cytochrome c from mitochondria. The results demonstrated A. kemando has potentially anticancer agent, particularly on human ovarian cancer.

Keywords: anticancer, Artocarpus kemando, ovarian cancer, cytotoxicity

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Authors: Ankur P. Sati, Manju Mohan

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The hazardous combination of smoke and pollutant gases, smog, is harmful for health. There are strong evidences that the Agricultural waste burning (AWB) in the Northern India leads to adverse air quality in Delhi and its surrounding regions. A severe smog episode was observed over Delhi, India during November 2012 which resulted in very low visibility and various respiratory problems. Very high values of pollutants (PM10 as high as 989 µg m-3, PM2.5 as high as 585 µg m-3 an NO2 as high as 540 µg m-3) were measured all over Delhi during the smog episode. Ultra Violet Aerosol Index (UVAI) from Aura satellite and Aerosol Optical Depth (AOD) are used in the present study along with the output trajectories from HYSPLIT model and the in-situ data. Satellite data also reveal that AOD, UVAI are always at its highest during the farmfires duration in Punjab region of India and the extent of these farmfires may be increasing. It is observed that during the smog episode all the AOD, UVAI, PM2.5 and PM10 values surpassed those of the Diwali period (one of the most polluted events in the city) by a considerable amount at all stations across Delhi. The parameters used from the remote sensing data and the ground based observations at various stations across Delhi are very well in agreement about the intensity of Smog episode. The analysis clearly shows that regional pollution can have greater contributions in deteriorating the air quality than the local under adverse meteorological conditions.

Keywords: smog, farmfires, AOD, remote sensing

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Authors: Lavanya Mohan, Suneha Sethi

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This paper seeks to study the concept of existential anguish and its relation to personal growth. Generally, existential anguish is taken to be an all-pervading negative feeling arising from an individual’s knowledge of their absolute freedom. However, this paper investigates the possible positive impact of this sense of anguish, such as its role in commencing an individual’s journey towards authentic living, characterized by an internal locus of will, and acceptance of absolute freedom. This journey towards authentic living is what is referred to as personal growth, in this paper, in the context of existential philosophy. The work of four prominent existentialists has been used to elucidate existential anguish. A human’s scope for personal growth in the existential framework has been compared to that in the teleological framework of religion. In the latter, individuals must abide by the moral code of an external authority and work towards a pre-ordained purpose of life. This is illustrated by the examination of Hinduism, Christianity, and Islam. To test people’s levels of existential anguish, religiosity, and personal growth, a survey using an originally constructed questionnaire has been undertaken. Simple and partial correlation analyses have been used to ascertain the relationships between these three variables. Contrary to the hypothesis, the results indicate that existential anguish has a detrimental effect on personal growth, while religiosity does not affect it at all. Through their responses, it was also evident that the respondents do not adhere to teleological concepts of morality, despite a belief in God. This study has further scope in determining how variations in sample demography may influence the relationship of existential anguish with personal growth.

Keywords: existential anguish, existentialism, personal growth, religiosity, teleology

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Authors: Amrin Moger, Sagar Bhalerao, Martin Mathew

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Advertisements play a vital role in dissemination of information regarding products and services. Advertisements as Mass Media tool is not only a source of entertainment, but also a source of information, education and entertainment. It provides information about the outside world and exposes us to other ways of life and culture. Public service advertisements (PSA) are generally aimed at public well-being. Aim of PSA is not to make profit, but rather to change public opinion and raise awareness in the Society about a social issue.’ Start with the boys’ is one such PSA aims to create awareness about issue of ‘gender bias’ that is taught prevalent in the society. Persons with disabilities (PWDs) are also consumers of PSA in the society. The population of persons with disability in the society also faces gender bias and discrimination. It is a double discrimination. The advertisement selected for the study gives out a strong message on gender bias and therefore must be accessible to everyone including PWDs in the society. Accessibility of PSA in the digital format can be done with the help of Universal Design (UD) in digital media application. Features of UD inclusive in nature, and it focus on eliminating established barriers through initial designs. It considers the needs of diverse people, whether they are persons with or without disability. In this research two aspects of UD in digital media: captioning and Indian sign language (ISL) is used. Hence a short survey study was under taken to know the effects of a multimedia on gender bias, in accessible format on persons with and without disability. The result demonstrated a significant difference in the opinion, on the usage accessible and non-accessible format for persons with and without disability and their understanding of message in the PSA selected for the study.

Keywords: public service advertisements, gender, disability, accessibility

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Authors: Sanaz Mosadeghsedghi, Mathew Hudder, Mohammad Ali Baghbanzadeh, Charbel Atallah, Seyedeh Laleh Dashtban Kenari, Konstantin Volchek

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Lithium has recently been extensively used in lithium-ion batteries (LIBs) for electric vehicles and portable electronic devices. The conventional evaporative approach to recover and concentrate lithium is extremely slow and may take 10-24 months to concentrate lithium from dilute sources, such as geothermal brines. To response to the increasing industrial lithium demand, alternative extraction and concentration technologies should be developed to recover lithium from brines with low concentrations. In this study, a combination of electrocoagulation (EC) and electrodialysis (ED) was evaluated for the recovery of lithium from geothermal brines. The brine samples in this study, collected in Western Canada, had lithium concentrations of 50-75 mg/L on a background of much higher (over 10,000 times) concentrations of sodium. This very high sodium-to-lithium ratio poses challenges to the conventional direct-lithium extraction processes which employ lithium-selective adsorbents. EC was used to co-precipitate lithium using a sacrificial aluminium electrode. The precipitate was then dissolved, and the leachate was treated using ED to separate and concentrate lithium from other ions. The focus of this paper is on the study of ED, including a two-step ED process that included a mono-valent selective stage to separate lithium from multi-valent cations followed by a bipolar ED stage to convert lithium chloride (LiCl) to LiOH product. Eventually, the ED cell was reconfigured using mono-valent cation exchange with the bipolar membranes to combine the two ED steps in one. Using this process at optimum conditions, over 95% of the co-existing cations were removed and the purity of lithium increased to over 90% in the final product.

Keywords: electrochemical separation, electrocoagulation, electrodialysis, lithium extraction

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Authors: Nandini Mohan, Elayne Ahern

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Neurocognitive deficits, as well as psychosocial dysfunction, are typically observed in major depressive disorder (MDD). These deficits persist even after a significant reduction of symptoms and remission from MDD. These deficits have also been linked to greater relapse rates. The link between neurocognitive deficits, relapse, and psychosocial functioning in MDD, on the other hand, has received little attention. This review aimed to conduct an in-depth review of the literature on the association between neurocognitive deficits, relapse, and psychosocial functioning in MDD remission. We used search terms related to MDD, MDD remission, psychosocial functioning, neurocognitive impairments, and relapse to conduct a systematic review of English-language literature in PubMed, PsycArticles, PsycINFO, Medline, and Web of Science to identify relevant studies in the area from which 15 studies were identified for inclusion following an examination against inclusion/ exclusion criteria. Executive functioning, psychomotor speed, and memory were closely related to the psychosocial deficits in the phase of MDD remission. Similarly, Executive function, divided attention, and inhibition were closely related to the relapse in the phase of MDD remission. The limitations of the present review include limited and contradicting evidence that led to fewer studies being included. The implications of this review include an understanding of the difference between clinical and full-functional recovery. This evidence can be the basis for incorporating treatment measures that focus on neurocognitive and psychosocial deficits along with the affective symptoms of MDD.

Keywords: depression, MDD, remission, relapse, neurocognitive functioning, psychosocial deficits

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Authors: Abdalla Mansour, Dan Brown, Adel Helmy, Rikin Trivedi, Mathew Guilfoyle

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Introduction: Diagnosing delayed cerebral ischaemia (DCI) following aneurysmal subarachnoid haemorrhage (SAH) can be challenging, particularly in poor-grade patients. Objectives: This study sought to assess the value of routine CTP in identifying (or excluding) DCI and in guiding management. Methods: Eight-year retrospective neuroimaging study at a large UK neurosurgical centre. Subjects included a random sample of adult patients with confirmed aneurysmal SAH that had a CTP scan during their inpatient stay, over a 8-year period (May 2014 - May 2022). Data collected through electronic patient record and PACS. Variables included age, WFNS scale, aneurysm site, treatment, the timing of CTP, radiologist report, and DCI management. Results: Over eight years, 916 patients were treated for aneurysmal SAH; this study focused on 466 patients that were randomly selected. Of this sample, 181 (38.84%) had one or more CTP scans following brain aneurysm treatment (Total 318). The first CTP scan in each patient was performed at 1-20 days following ictus (median 4 days). There was radiological evidence of DCI in 83, and no reversible ischaemia was found in 80. Findings were equivocal in the remaining 18. Of the 103 patients treated with clipping, 49 had DCI radiological evidence, in comparison to 31 of 69 patients treated with endovascular embolization. The remaining 9 patients are either unsecured aneurysms or non-aneurysmal SAH. Of the patients with radiological evidence of DCI, 65 had a treatment change following the CTP directed at improving cerebral perfusion. In contrast, treatment was not changed for (61) patients without radiological evidence of DCI. Conclusion: CTP is a useful adjunct to clinical assessment in the diagnosis of DCI and is helpful in identifying patients that may benefit from intensive therapy and those in whom it is unlikely to be effective.

Keywords: SAH, vasospasm, aneurysm, delayed cerebral ischemia

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Authors: Sandeep Mohan Ahuja, Gulshan Kumar Jawa

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Cyclone separators are crucial components in various industries tasked with efficiently separating particulate matter from gas streams. Achieving optimal performance hinges on a deep understanding of flow dynamics and particle behaviour within these separators. In this investigation, Computational Fluid Dynamics (CFD) simulations are conducted utilizing the Discrete Phase Model (DPM) to dissect the intricate flow patterns, particle trajectories, and separation efficiency within cyclone separators. The study delves into the influence of pivotal parameters like inlet velocity, particle size distribution, and cyclone geometry on separation efficiency. Through numerical simulations, a comprehensive comprehension of fluid-particle interaction phenomena within cyclone separators is attained, allowing for the assessment of solid collection efficiency across diverse operational conditions and geometrical setups. The insights gleaned from this study promise to advance our understanding of the complex interplay between fluid and particle within cyclone separators, thereby enabling optimization across a wide array of industrial applications. By harnessing the power of CFD simulations and the DPM, this research endeavours to furnish valuable insights for designing, operating, and evaluating the performance of cyclone separators, ultimately fostering greater efficiency and environmental sustainability within industrial processes.

Keywords: cyclone separator, computational fluid dynamics, enhancing efficiency, discrete phase model

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Authors: Deepak Mohan, Sushma Sharma, Mohammad Asif

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Diclofenac sodium being one of the most common non-steroidal anti-inflammatory drugs is normally used as painkiller and to reduce inflammation. The drug is known to alter the enzymatic activities of acid and alkaline phosphatase, glutamate oxaloacetate transaminase and glutamate pyruvate transaminases. The drug also results in change in the concentration of proteins and lipids in the body. The present study is an attempt to study different biochemical changes electrophoretically due to administration of different doses of diclofenac (4mg/kg/body weight and 14mg/kg/body weight) on liver and testes of mice from 7-28 days of investigation. Homogenization of the tissue was done, supernatant separated was loaded in the gel and native polyacrylamide gel electrophoresis was conducted. Diclofenac administration resulted in alterations of all these biochemical parameters which were observed in native polyacrylamide gel electrophoretic studies. The severe degenerative changes as observed during later stages of the experiment showed correlation with increase or decrease in the activities of all the enzymes studied in the present investigation. Image analysis of gel in liver showed a decline of 7.4 and 5.3 % in low and high dose group after 7 days whereas a decline of 9.6 and 7.5% was registered after 28 days of investigation. Similar analysis for testis also showed an appreciable decline in the activity of alkaline phosphatase after 28 days. Gel analysis of serum was also performed to find a correlation in the enzymatic activities between the tissue and blood.

Keywords: diclofenac, inflammation, polyacrylamide, phosphatase

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Authors: Krishna Mohan Bathula, Fatou Bintou Loucoubar, FNU Kaleemunnisa, Christelle Scharff, Mark Anthony De Castro

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Voice recognition algorithms such as automatic speech recognition and text-to-speech systems with African languages can play an important role in bridging the digital divide of Artificial Intelligence in Africa, contributing to the establishment of a fully inclusive information society. This paper proposes a Deep Learning model that can classify the user responses as inputs for an interactive voice response system. A dataset with Wolof language words ‘yes’ and ‘no’ is collected as audio recordings. A two stage Data Augmentation approach is adopted for enhancing the dataset size required by the deep neural network. Data preprocessing and feature engineering with Mel-Frequency Cepstral Coefficients are implemented. Convolutional Neural Networks (CNNs) have proven to be very powerful in image classification and are promising for audio processing when sounds are transformed into spectra. For performing voice response classification, the recordings are transformed into sound frequency feature spectra and then applied image classification methodology using a deep CNN model. The inference model of this trained and reusable Wolof voice response recognition system can be integrated with many applications associated with both web and mobile platforms.

Keywords: automatic speech recognition, interactive voice response, voice response recognition, wolof word classification

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Authors: Natalia Fijol, Aji P. Mathew

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We present the processing and characterisation of three-dimensional (3D) monolith filters based on polylactic acid (PLA) reinforced with various nature-derived nanospecies such as hydroxyapatite, modified cellulose fibers and chitin fibers. The nanospecies of choice were dispersed in PLA through Thermally Induced Phase Separation (TIPS) method. The biocomposites were developed via solvent-assisted blending and the obtained pellets were further single-screw extruded into 3D-printing filaments and processed into various geometries using Fused Deposition Modelling (FDM) technique. The printed prototypes included cubic, cylindrical and hour-glass shapes with diverse patterns of printing infill as well as varying pore structure including uniform and multiple level gradual pore structure. The pores and channel structure as well as overall shape of the prototypes were designed in attempt to optimize the flux and maximize the adsorption-active time. FDM is a cost and energy-efficient method, which does not require expensive tools and elaborated post-processing maintenance. Therefore, FDM offers the possibility to produce customized, highly functional water purification filters with tuned porous structures suitable for removal of wide range of common water pollutants. Moreover, as 3D printing becomes more and more available worldwide, it allows producing portable filters at the place and time where they are most needed. The study demonstrates preparation route for the PLA-based, fully biobased composite and their processing via FDM technique into water purification filters, addressing water treatment challenges on an industrial scale.

Keywords: fused deposition modelling, water treatment, biomaterials, 3D printing, nanocellulose, nanochitin, polylactic acid

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Authors: Sajan Antony Mathew, Bhukya Ramdas

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Abstract—The impetus of wind energy deployment over the last few decades has seen potential sites being harvested very actively for wind farm development. Due to the scarce availability of highly potential sites, the turbines are getting more optimized in its location wherein minimum spacing between the turbines are resorted without comprising on the optimization of its energy yield. The optimization of the energy yield from a wind turbine is achieved by effective micrositing techniques. These time-tested techniques which are applied from site to site on terrain conditions that meet the requirements of the International standard for power performance measurements of wind turbines result in the positioning of wind turbines for optimized energy yields. The international standard for Power Curve Measurements has rules of procedure and methodology to evaluate the terrain, obstacles and sector for measurements. There are many challenges at the sites for complying with the requirements for terrain, obstacles and sector for measurements. Studies are being attempted to carry out these measurements within the scope of the international standard as various other procedures specified in alternate standards or the integration of LIDAR for Power Curve Measurements are in the nascent stage. The paper strives to assist in the understanding of the fact that if positioning of a wind turbine at a site is based on an optimized output, then there are no wake effects seen on the power curve of an adjacent wind turbine. The paper also demonstrates that an invalid sector for measurements could be used in the analysis in alteration to the requirement as per the international standard for power performance measurements. Therefore the paper strives firstly to demonstrate that if a wind turbine is optimally positioned, no wake effects are seen and secondly the sector for measurements in such a case could include sectors which otherwise would have to be excluded as per the requirements of International standard for power performance measurements.

Keywords: micrositing, optimization, power performance, wake effects

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Authors: Pratheeba Subramanian, Anjula Gurtoo, Mary Mathew

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Transaction of patents in emerging patent markets is gaining momentum. Pricing patents for a transaction say patent sale remains a challenge. Patents vary in their pricing with some patents fetching higher prices than others. Sale of patents in portfolios further complicates pricing with multiple patents playing a role in pricing a bundle. In this paper, a set of 138 US patents sold individually as single invention lots and 462 US patents sold in bundles of 120 portfolios are investigated to understand the dynamics of selling prices of singletons and portfolios and their determinants. Firstly, price variations when patents are sold individually as singletons and portfolios are studied. Multivariate statistical techniques are used for analysis both at the lot level as well as at the individual patent level. The results show portfolios fetching higher prices than singletons at the lot level. However, at the individual patent level singletons show higher prices than per patent price of individual patent members within the portfolio. Secondly, to understand the price determinants, the effect of patent, seller, and bundling related characteristics on selling prices is studied separately for singletons and portfolios. The results show differences in the set of characteristics determining prices of singletons and portfolios. Selling prices of singletons are found to be dependent on the patent related characteristics, unlike portfolios whose prices are found to be dependent on all three aspects – patent, seller, and bundling. The specific patent, seller and bundling characteristics influencing selling price are discussed along with the implications.

Keywords: auction, patents, portfolio bundling, seller type, selling price, singleton

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Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs, and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine-learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient but not the magnitude. A neural network with two hidden layers were then used to learn the coefficient magnitudes along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction

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Authors: Prerna Mohan Saxena, Avni Joshi, Raju K Parasher

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Disability is a state of decreased functioning associated with disease, disorder, injury, or other health condition, which in the context of one’s environment is experienced as an impairment, activity limitation, or participation restriction. With the concept of disability evolving over the years, the current ICF model of disability has integrated this concept into a comprehensive whole of multiple dimensions of human functioning, including biological, psychological, social, and environmental aspects. Wheelchair basketball is one of the greatest examples of adapted sports for the disabled. Through this study, we aim to evaluate the functional performance and self-esteem levels in differently-abled pediatric wheelchair basketball players, providing an insight on their abilities and deficits and how they can be worked on at a larger level to improve overall performance. The study was conducted on 9 pediatric wheelchair basketball players at Amar Jyoti school for inclusive education Delhi their physical performance was assessed using a battery of tests, and physical self esteem was assessed using the Physical self-description instrument (PSDQ-S). Results showed that 9 participants age ranged between 10-21 years, mostly males with BMI ranging between 16.7 to 28.9 kg/m2 most of them had the experience of 5 to 6 years of playing the sport. The data showed physical performance in accordance to years of experience of playing, physical self esteem showed a different perspective, with experience players scoring less on it. This study supports a multidimensional construct of physical performance and physical self-esteem, suggesting that both may be applied on the wheelchair basketball players at competitive levels.

Keywords: ase series, physical performance, physical self-esteem, wheelchair basketball

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Authors: Jayashree S. Bhat, Megha Mohan

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Play is any activity spontaneously chosen, inherently motivated, and personally directed. There is a wide range of literature and research supporting the concept of play in promoting healthy development in young children. Modern children are experiencing nurture that has more structure and adult involvement than previous generations and free, unstructured, and child directed play is under peril. Play behaviors serve as a reflection of a child’s cultural and ethnic background and can be an index of a child’s development. The influence and impact of culture in children’s play is diverse. The culturally variable dimensions of play includes the choice of objects, the involvement of specific play partners, the amount of child initiations of social pretend play with caregivers along with its the components, and sequences and specific themes involved during play. India is a country well known for its cultural diversity. In this study, a cross sectional study design with convenient sampling was adopted. The mother child free play interaction was video clipped at their residence among typically developing children between 12 to 24 months in an urban city from South India. It was ascertained that all the children were first born and mothers were unemployed belonging to middle socioeconomic status. The video clippings were coded and analysed using SPSS software version 17. The results revealed interesting behaviors demonstrated by the mother as well as the child during the play interaction. The results high light the need for focusing on the play behaviors of children during their developmental assessment, especially so for children with challenges.

Keywords: culture, free play, interaction, typically developing

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Authors: Meena Kumari, Ajitha Sharma, Mohan Babu Amberkar, Hasitha Manohar, Joseph Thomas, K. L. Bairy

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Aim: To evaluate the pattern of occurrence of adverse drug reactions (ADRs) with platinum compounds in cancer chemotherapy at a tertiary care hospital. Methods: It was a retrospective, descriptive case record study done on patients admitted to the medical oncology ward of Kasturba Hospital, Manipal from July to November 2012. Inclusion criteria comprised of patients of both sexes and all ages diagnosed with cancer and were on platinum compounds, who developed at least one adverse drug reaction during or after the treatment period. CDSCO proforma was used for reporting ADRs. Causality was assessed using Naranjo Algorithm. Results: A total of 65 patients was included in the study. Females comprised of 67.69% and rest males. Around 49.23% of the ADRs were seen in the age group of 41-60 years, followed by 20 % in 21-40 years, 18.46% in patients over 60 years and 12.31% in 1-20 years age group. The anticancer agents which caused adverse drug reactions in our study were carboplatin (41.54%), cisplatin (36.92%) and oxaliplatin (21.54%). Most common adverse drug reactions observed were oral candidiasis (21.53%), vomiting (16.92%), anaemia (12.3%), diarrhoea (12.3%) and febrile neutropenia (0.08%). The results of the causality assessment of most of the cases were probable. Conclusion: The adverse effect of chemotherapeutic agents is a matter of concern in the pharmacological management of cancer as it affects the quality of life of patients. This information would be useful in identifying and minimizing preventable adverse drug reactions while generally enhancing the knowledge of the prescribers to deal with these adverse drug reactions more efficiently.

Keywords: adverse drug reactions, platinum compounds, cancer, chemotherapy

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Authors: Mdoe Mwajuma Bakari, Mselle Lilian Teddy, Kibusi Stephen Mathew

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Background: Due to the increase of caesarean section (CS), many women are discharge early to their home. Women should be aware on how to take care of themselves at home after CS. Evidence shows non-uniform health education on home care after CS are provided to post CS mothers because of lack of standard home care guideline on home after CS; as existing guidelines explore only care of women in hospital setting, for health care workers. There is a need to develop post CS home care guide; exploring contents of home based care education after CS provided by nurse midwives will inform the development of the guide. Objective: To explore the content of health education provided by nurse midwives to post CS mother about home care after hospital discharge in Dodoma, Tanzania. Methodology: An exploratory qualitative study using in-depth interview was conducted in this study using triangulation of data collection method; where 14 nurse midwives working in maternity unit and 11 post CS mother attending their post-natal clinic were recruited. Content analysis was used to generate themes that describe health education information provided by nurse midwives to post CS mother about home care after hospital discharge. Results: The study found that, nutrition health education, maternal and newborn hygiene care of caesarean wound at home were the component of health education provided to post CS mothers by nurse midwives. Contradicting instruction were found to be provided to post CS mothers. Conclusion: This study reported non-uniform health education provided by the nurse midwives on home care after CS. Despite of the fact that nurse midwives recognizes the need to provide health education to the post CS mothers, there is a need to develop home care guideline as a reference for their education to ensure uniform package of education is provided to post CS mothers in order to improve recovery of post CS mothers from CS.

Keywords: caesarean section, home care, discharge education, homecare after caesarean section

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Authors: Aneesh Mathew, Arunab K. S., Atul Kumar Sharma

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The uncontrolled rise in population has led to unplanned, swift, and unsustainable urban expansion, causing detrimental environmental impacts on both local and global ecosystems. This research delves into a comprehensive examination of the Urban Heat Island (UHI) phenomenon in Bengaluru and Hyderabad, India. It centers on the spatial and temporal distribution of UHI and its correlation with air pollutants. Conducted across summer and winter seasons from 2001 to 2021 in Bangalore and Hyderabad, this study discovered that UHI intensity varies seasonally, peaking in summer and decreasing in winter. The annual maximum UHI intensities range between 4.65 °C to 6.69 °C in Bengaluru and 5.74 °C to 6.82 °C in Hyderabad. Bengaluru particularly experiences notable fluctuations in average UHI intensity. Introducing the Urban Thermal Field Variance Index (UTFVI), the study indicates a consistent strong UHI effect in both cities, significantly impacting living conditions. Moreover, hotspot analysis demonstrates a rising trend in UHI-affected areas over the years in Bengaluru and Hyderabad. This research underscores the connection between air pollutant concentrations and land surface temperature (LST), highlighting the necessity of comprehending UHI dynamics for urban environmental management and public health. It contributes to a deeper understanding of UHI patterns in swiftly urbanizing areas, providing insights into the intricate relationship between urbanization, climate, and air quality. These findings serve as crucial guidance for policymakers, urban planners, and researchers, facilitating the development of innovative, sustainable strategies to mitigate the adverse impacts of uncontrolled expansion while promoting the well-being of local communities and the global environment.

Keywords: urban heat island effect, land surface temperature, air pollution, urban thermal field variance index

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Authors: Ram Mohan, Richard Haney, Ajit Kelkar

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Current developments in computing have shown the advantage of using one or more Graphic Processing Units (GPU) to boost the performance of many computationally intensive applications but there are still limits to these GPU-enhanced systems. The major factors that contribute to the limitations of GPU(s) for High Performance Computing (HPC) can be categorized as hardware and software oriented in nature. Understanding how these factors affect performance is essential to develop efficient and robust applications codes that employ one or more GPU devices as powerful co-processors for HPC computational modeling. This research and technical presentation will focus on the analysis and understanding of the intrinsic interrelationship of both hardware and software categories on computational performance for single and multiple GPU-enhanced systems using a computationally intensive application that is representative of a large portion of challenges confronting modern HPC. The representative application uses unstructured finite element computations for transient composite resin infusion process flow modeling as the computational core, characteristics and results of which reflect many other HPC applications via the sparse matrix system used for the solution of linear system of equations. This work describes these various software and hardware factors and how they interact to affect performance of computationally intensive applications enabling more efficient development and porting of High Performance Computing applications that includes current, legacy, and future large scale computational modeling applications in various engineering and scientific disciplines.

Keywords: graphical processing unit, software development and engineering, performance analysis, system architecture and software performance

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Authors: Salam Saudagar, Ankit Kamboj, Niraj Mohan, Satgounda Patil, Nilesh Powar

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Task Assignment and Scheduling is a challenging Operations Research problem when there is a limited number of resources and comparatively higher number of tasks. The Cost Management team at Cummins needs to assign tasks based on a deadline and must prioritize some of the tasks as per business requirements. Moreover, there is a constraint on the resources that assignment of tasks should be done based on an individual skill level, that may vary for different tasks. Another constraint is for scheduling the tasks that should be evenly distributed in terms of number of working hours, which adds further complexity to this problem. The proposed greedy approach to solve assignment and scheduling problem first assigns the task based on management priority and then by the closest deadline. This is followed by an iterative selection of an available resource with the least allocated total working hours for a task, i.e. finding the local optimal choice for each task with the goal of determining the global optimum. The greedy approach task allocation is compared with a variant of Hungarian Algorithm, and it is observed that the proposed approach gives an equal allocation of working hours among the resources. The comparative study of the proposed approach is also done with manual task allocation and it is noted that the visibility of the task timeline has increased from 2 months to 6 months. An interactive dashboard app is created for the greedy assignment and scheduling approach and the tasks with more than 2 months horizon that were waiting in a queue without a delivery date initially are now analyzed effectively by the business with expected timelines for completion.

Keywords: assignment, deadline, greedy approach, Hungarian algorithm, operations research, scheduling

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Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

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The properties of memory representations in artificial neural networks have cognitive implications. Distributed representations that encode instances as a pattern of activity across layers of nodes afford memory compression and enforce the selection of a single point in instance space. These encoding schemes also appear to distort the representational space, as well as trading off the ability to validate that input information is within the bounds of past experience. In contrast, a localist representation which encodes some meaningful information into individual nodes in a network layer affords less memory compression while retaining the integrity of the representational space. This allows the validity of an input to be determined. The validity (or familiarity) of input along with the capacity of localist representation for multiple instance selections affords a memory sampling approach that dynamically balances the bias-variance trade-off. When the input is familiar, bias may be high by referring only to the most similar instances in memory. When the input is less familiar, variance can be increased by referring to more instances that capture a broader range of features. Using this approach in a localist instance memory network, an experiment demonstrates a relationship between representational conflict, generalization performance, and memorization demand. Relatively small sampling ranges produce the best performance on a classic machine learning dataset of visual objects. Combining memory validity with conflict detection produces a reliable confidence judgement that can separate responses with high and low error rates. Confidence can also be used to signal the need for supervisory input. Using this judgement, the need for supervised learning as well as memory encoding can be substantially reduced with only a trivial detriment to classification performance.

Keywords: artificial neural networks, representation, memory, conflict monitoring, confidence

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Authors: Sriram Venkatesh, V. Murali Mohan, T. V. Karthikeyan

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The main advantage of multi-directionally reinforced composites is the freedom to orient selected fibre types and hence derives the benefits of varying fibre volume fractions and there by accommodate the design loads of the final structure of composites. This technology provides the means to produce tailored composites with desired properties. Due to the high level of fibre integrity with through thickness reinforcement those composites are expected to exhibit superior load bearing characteristics with capability to carry load even after noticeable and apparent fracture. However a survey of published literature indicates inadequacy in the design and test data base for the complete characterization of the multidirectional composites. In this paper the research objective is focused on the development and testing of 4-D orthogonal composites with different preform configurations and resin systems. A preform is the skeleton 4D reinforced composite other than the matrix. In 4-D preforms fibre bundles are oriented in three directions at 1200 with respect to each other and they are on orthogonal plane with the fibre in 4th direction. This paper addresses the various types of 4-D composite manufacturing processes and the mechanical test methods followed for the material characterization. A composite analysis is also made, experiments on course and fine woven preforms are conducted and the findings of test results are discussed in this paper. The interpretations of the test results reveal several useful and interesting features. This should pave the way for more widespread use of the perform configurations for allied applications.

Keywords: multi-directionally reinforced composites, 4-D orthogonal preform, course weave, fine weave, fibre bundle spools, unit cell, fibre architecture, fibre volume fraction, fibre distribution

Procedia PDF Downloads 207