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Genotoxic repercussion of high-intensity radiation (x-rays) on hospital radiographers
Recent technological advances in the medical field have increased the plausibility of exposing humans to high-intensity wavelength radiations like x-rays and gamma rays while diagnosing or treating specific medical maladies. These radiations induce nucleotide changes and chromosomal alterations in the exposed population, intentionally or accidentally. A radiological investigation is regularly used in identifying the disease, especially by the technicians working in intensive care units. The current study observes the genetic damages like chromosomal abnormalities (CA) in clinicians who are occupationally exposed to high-intensity radiations (x-rays) at their workplaces using universal cytogenetic tools like micronucleus assay (MN), sister chromatid exchange and comet assay. The study was conducted between 100 exposed practitioners from the abdominal scanning, chest scanning, cranial and orthopedic or bone scanning department and age-matched healthy controls. We observed a slightly higher rate of MN and CA (p <.05) in orthopedic and chest department practitioners than in other departments concerning increasing age and duration of exposure at work. Our results emphasize taking extra precautionary measures in clinical and hospital radiation laboratories to protect the practitioners. 2022 The Authors. Environmental and Molecular Mutagenesis published by Wiley Periodicals LLC on behalf of Environmental Mutagen Society. -
Prioritizing the Essentials: The MBA Aspirants Dilemma
Objective decision-making while choosing an appropriate college for a Master in Business Administration (MBA) is only half-done. It is critical that the student be able to find the best placement at the end of the course by acquiring the most critical skills/specializations affecting placements and involves data-driven decision-making based on past placement trends. Viti and Vania have done their preliminary selection, of ABC College for their MBA course, based on the colleges credence quality. However, they are trying to understand the key success factors (KSFs) affecting placements at ABC to focus their next two years on getting most placement-ready. Having been provided with the placement details of the outgoing batch, they are looking to analyze the data to discover the most critical parameters affecting placements. NeilsonJournals Publishing 2023. -
Network Based Detection of IoT Attack Using AIS-IDS Model
In recent days Internet of Things attained more familiarity. Although it is a promising technology, it tends to lead to a variety of security issues. Conventional methods such as IoT ecosystem based solutions were not suitable to give dilemmas to the system. A new system model called adaptive and intelligent Artificial Immune System (AIS) imitates the process of human being an immune system that consists of eligible properties of this varying environment. Therefore, it enhanced IoT security. Conventionally classifiers such as Random Forest Classifier, Recurrent Neural Network and K-nearest neighbours are used to classify the signals as normal or abnormal and predict malicious attacks. But unfortunately, these classifiers generated a high false alarm rate. Thus, a framework with maximum accuracy and minimum false alarm rate was required. In this work, the AIS model adopts the benefits of the Hopfield Neural Network (HNN) for classification. HNN classifier has a fixed weight, as it cannot be changed for its backpropagation property. This work optimally selects the fixed weight using Fast- Particle Swarm Optimization (F-PSO) and helps to enhance the accuracy of the HNN classifier. This classifier model then differentiates IoT attacks with a high detection rate and normal signal. Three datasets are taken to execute the proposed model and define its accuracy. The proposed Artificial Immune system using HNN for Intrusion Detection System (AIS-IDS) model exhibits 99.8% accuracy for the first dataset and minimum error value. The false alarm rate was minimized using danger theory and its high activation function; thus, the false alarm rate was minimized by up to 8% more than previous classifiers. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Research on secure workload execution scheme in heterogeneous cloud environment
The increasing demand for the hardware, software and infrastructure is playing a big role in the information technology domain towards the need of customers specific requirements. Cloud computing is a major backbone for providing such services over the internet. It includes the services such as applications, storage, network, scalability, sharing, virtualization, confidentiality, security, authentication, and integrity. A large number of data intensive workflow applications uses heterogeneous cloud environment for communication and computation operation. An intruder/attacker will utilize these environments for their benefit by flooding malicious links, unwanted information and others. In cloud environment, detecting a malicious device/packet during workflow execution is a critical and challenging task. The various workflow method with security, service level agreement (SLA) and quality of service (QoS) have been modelled in recent time; However, these models are not efficient in detecting malicious users and maintaining high level of QoS or workflow applications. This article focus is on addressing research future direction, issues and challenges of work in meeting secure and efficient workflow execution model for heterogeneous cloud environment. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
Doable production of highly fluorescent, heteroatom-doped graphene material from fuel coke for cellular bioimaging: An eco-sustainable cradle-to-gate approach
The manifold usage of fluorescent materials and their pliable association with optical imaging techniques have made great strides in unfolding the incredible potential of biotechnological research, particularly in cancer treatment, from point-of-care assay to clinical applications. Enlarged nuclei or numerous counts often indicate tumor growth activity, and these expressions can be visualized with the aid of fluorescence imaging. Therefore, developing highly fluorescent, biocompatible, and sustainable biomarkers for imaging is a vital necessity for their extensive application in cancer diagnosis and therapy. In this work, we have demonstrated the cradle-to-gate transformation of abundant and cheap fossil fuel coke into a fluorescent probe for bioimaging. Herein, for the first time, a facile strategy for modulating the emission characteristics of coke-derived graphene system via doping of heteroatoms has been reported. It is found that the doping of nitrogen atoms could strongly influence photophysical properties, giving rise to increased quantum yield (16%), extended fluorescence lifetime (8.51 ns), and higher photostability (92%). Moreover, the as-synthesized nitrogen-doped graphene derivative is used as a potential labelling agent for the cellular imaging of cancerous cells, as well as normal cells, at concentrations ranging from 0 to 100 ?g/mL. For 24h incubation, the cells cultured with a concentration of 25 ?g/mL were observed to have an appreciable fluorescence accompanied by significant biocompatibility, with a viability value of ?85%. Considering the heteroatom-induced emission characteristics and bioanalytical acuities, it is prospective that the coke-derived graphene system can be further explored to elucidate its significance in biomedical applications, without compromising on economic and environmental sustainability. 2022 Elsevier Ltd -
Effective time context based collaborative filtering recommender system inspired by Gowers coefficient
The fast growth of Internet technology in recent times has led to a surge in the number of users and amount of information generated. This substantially contributes to the popularity of recommendation systems (RS), which provides personalized recommendations to users based on their interests. A RS assists the user in the decision-making process by suggesting a suitable product from various alternatives. The collaborative filtering (CF) technique of RS is the most prevalent because of its high accuracy in predicting users' interests. The efficacy of this technique mainly depends on the similarity calculation, determined by a similarity measure. However, the traditional and previously developed similarity measures in CF techniques are not able to adequately reveal the change in users' interests; therefore, an efficient measure considering time into context is proposed in this paper. The proposed method and the existing approaches are compared on the MovieLens-100k dataset, showing that the proposed method is more efficient than the comparable methods. Besides this, most of the CF approaches only focus on the historical preference of the users, but in real life, the people's preferences also change over time. Therefore, a time-based recommendation system using the proposed method is also developed in this paper. We implemented various time decay functions, i.e., exponential, convex, linear, power, etc., at various levels of the recommendation process, i.e., similarity computation, rating matrix, and prediction level. Experimental results over three real datasets (MovieLens-100k, Epinions, and Amazon Magazine Subscription) suggest that the power decay function outperforms other existing techniques when applied at the rating matrix level. 2022, The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden. -
Decolonising the Gateway of India
This article interrogates how a colonial monument, the Gateway of India in Mumbai, former Bombay, continues to carry and be endowed with a title that is a misplaced embodiment of Indian social histories. Built in the 1920s, this monument, definitely a work of architectural grandeur, continues to carry its erroneous rendition and confines Indias vast social histories to the colonial moment, with an anglo-centric focus. As the monument symbolises the memory of the colonial regime, it also signifies its oppression as well as its exit from the subcontinent, rather than witnessing anyone coming to India, except King George in 1911, as the monuments title seems to suggest. A mnemonic device of colonialism, this misleading label needs to be seriously revisited, for it not only romanticises the colonial past but also fails to lead our memories back to certain crucial episodes in earlier social histories, from which the monument and its specific place, Mumbai, are more or less fully absent. 2023 The Author(s). -
Discovering patterns of live birth occurrence before in vitro fertilisation treatment using association rule mining
According to estimates, in-vitro fertilisation (IVF) is credited for the delivery of over 9 million children globally, constituting it to be a highly remarkable as well as commercialised advanced healthcare treatment. Nonetheless, the majority of IVF treatments are now constrained by factors such as expense, access and most notably, labour-intensive, technically demanding processes carried out by qualified professionals. Advancement is thus crucial to maintaining the IVF markets rapid growth while also streamlining current procedures. This might also improve access, cost, and effectiveness while also managing therapeutic time efficiently and at a reasonable cost. IVF has become a renowned technique for addressing problems like endometriosis, poor embryo development, hereditary diseases of the parents, issues with the biological function, problems with counteracting agents that harm either eggs or sperm, the limited capacity of semen to penetrate cervical bodily fluid, and lower sperm count that lead to infertility in humans. Copyright 2023 Inderscience Enterprises Ltd. -
IIRM: Intelligent Information Retrieval Model for Structured Documents by One-Shot Training Using Computer Vision
Various information retrieval algorithms have matured in recent years to facilitate data extraction from structured (with a predefined template) digital document images, primarily to manage and automate different organizations invoice and bill reimbursement processes. The algorithms are designated either rule-based or machine-learning-based. Both approaches have respective advantages and disadvantages. The rule-based algorithms struggle to generalize and need periodic adjustments, whereas machine learning-based supervised approaches need extensive data for training and substantial time and effort for manual annotation. The proposed system attempts to address both problems by providing a one-shot training approach using image processing, template matching, and optical character recognition. The model is extensible for any structured documents such as closing disclosure, bill, tax receipt, besides invoices. The model is validated against six different structured document types obtained from a reputed title insurance (TI) company. The comprehensive analysis of the experimental results confirms entity-wise extraction accuracy between 73.91 and 100% and straight through pass 81.81%, which is within business acceptable precision for a live environment. Out of total 32 tested entities, 17 outperformed all state-of-the-art techniques, where max accuracy has been 93 % with only invoices or sales receipts. The system has been set operational to assist the robotic process automation of the TI mentioned above based on the experimental results. 2022, King Fahd University of Petroleum & Minerals. -
Perceived stress and fatigue in software developers: Examining the benefits of gratitude
Software development demands creativity and adept problem-solving skills. However, long-term stress and fatigue might impede these skills in software developers. From the perspective of positive psychology, this cross-sectional study investigated the effects of gratitude, age, and gender on stress and fatigue in 421 participants, 244 males (58 %) and 177 females (42 %), aged between 21 and 57 years (M = 36.20; SD = 7.56). The tools employed included the multi-component gratitude measure, perceived stress scale and fatigue assessment scale. Multiple linear regressions confirmed the beneficial effects of gratitude, and they indicated higher levels of perceived stress and fatigue in women and younger professionals. These findings have positive implications for organisational psychologists, as they signify the favourable impacts of gratitude in mitigating stress and fatigue in software developers. The authors recommend that organisational practitioners should focus on enhancing the professionals' well-being by strategizing and implementing gratitude training programmes. 2022 Elsevier Ltd -
Does Sentiments Impact the Returns of Commodity Derivatives? An Evidence from Multi-commodity Exchange India
The advancements in technology, increased accessibility to various modes and platforms of communication, and increased willingness on the part of participants to share their ideas/opinions has resulted in huge amounts of data on the World Wide Web, hence, easily available to impact decision-making. Furthermore, commodity prices are primarily driven by demand and supply, wherein such news is open to the cognitive thinking of individuals. Thus, using the principles of natural language processing, which combines concepts of linguistics, computer science and artificial intelligence, helps in improving the accuracy of price determination. Therefore, this article aims to examine the relationship between sentiments conveyed through various sources and the performance of Indias largest commodity market, multi-commodity exchange (MCX). The correlation and causation between sentiment scores extracted from such textual content and the daily returns of select commodity derivatives are analysed. The results show varying levels of significance of sentiments on the returns of commodity contracts and imply that there is an increased scope of using such unstructured content in the field of finance. 2021 MDI. -
Investigation of electrical properties of developed indigenous natural ester liquid used as alternate to transformer insulation
The performance of every electrical system depends on the different electrical devices especially transformers. Petroleum-based mineral oil is widely used for insulation and cooling purpose. The disadvantage of mineral oil is its low biodegradability and is a major threat to the ecosystem due to its poor oxidative stability. To remedy the drawbacks, focus on alternative fluids that can replace traditional mineral oil. Alternative liquids such as natural esters are used which do not panic the ecosystem. With the support of additives in natural esters liquids, the productivity of the oil can be increased, paving the path for the green conversion of liquids in high voltage applications. The purpose of this article is to analyze the electrical properties of the newly developed indigenous oil. The inhibited oil was insulating oil to which antioxidants were added such as 2,6-ditertiary-butylparacresol, butylated hydroxyl anisole and tertiary butyl hydro qunine to slow down the oxidation rate and to check the electrical properties. This article discusses the electrical properties of mineral oil, developed indigenous oil with and without antioxidants as per IEC62770 standards. A 1.1 kVA transformer was then designed in a laboratory for load tests and Indigenous oil performance under load was evaluated. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
COMPUTATION OF b-CHROMATIC TOPOLOGICAL INDICES OF SOME GRAPHS AND ITS DERIVED GRAPHS
The two fastest-growing subfields of graph theory are graph coloring and topological indices. Graph coloring is assigning the colors/values to the edges/vertices or both. A proper coloring of the graph G is assigning colors/values to the vertices/edges or both so that no two adjacent vertices/edges share the same color/value. Recently, studies involving Chromatic Topological indices that dealt with different graph coloring were studied. In such studies, the vertex degrees get replaced with the colors, and the computation is carried out based on the topological index of our choice. We focus on b-Chromatic Zagreb indices and b-Chromatic irregularity indices in this work. This paper discusses the b-Chromatic Zagreb indices and b-Chromatic irregularity indices of the gear graph, star graph, and its derived graphs such as the line and middle graph. 2023, RAMANUJAN SOCIETY OF MATHEMATICS AND MATHEMATICAL SCIENCES. All rights reserved. -
Study of Influence of Combustion on DarcyBard Convection with Inherent Local Thermal Non-equilibrium Between Phases
This work deals with a DarcyBard convection problem in the presence of combustion and with local thermal non-equilibrium between the fluid and the solid phases. The effects of combustion and local thermal non-equilibrium on the onset of convection is studied in the linear and nonlinear regimes. Unlike all reported local thermal non-equilibrium problems reported so far, the present problem has a unique situation of having thermal non-equilibrium not only in the perturbed state but also in the basic state. Further, we observe that local thermal non-equilibrium does not, under any circumstance, lead to local thermal equilibrium except in an approximate sense when the combustion is quite weak. The effect of combustion is to advance the onset of convection compared to that in its absence. The effect of local thermal non-equilibrium is to reinforce the effect of combustion. In the presence of both these effects, sub-critical instability exists. The results are obtained numerically and have implication in practical porous medium convection problems. 2022, The Author(s), under exclusive licence to Springer Nature B.V. -
Barriers to corporate social responsibility implementation in the medium size manufacturing sector: an interpretive structure modelling approach
Purpose: Corporate social responsibility (CSR) practices are gaining momentum globally but their implementation becomes problematic due to the presence of barriers. So, this study aims to identify the barriers to CSR implementation among manufacturing enterprises, develop their classification and establish relationships among the barriers. Design/methodology/approach: An exhaustive list of barriers was identified from the literature, and following surveys and expert opinions, 19 critical barriers were extracted. Interpretive structure modelling was used to understand the hierarchal and contextual relationships among barriers of CSR implementation. Findings: The results show that are no autonomous variables present in the study. The proposed conceptual framework presents the hierarchy and interlinkage of barriers to CSR implementation in manufacturing enterprises. The results also indicate that rigidity in culture and corruption in the system and within the governance system of the country are the two most influential barriers that impede CSR implementation in manufacturing enterprises. Originality/value: The interactions among CSR barriers provide policymakers, industrial practitioners and managers with a framework to recognise and evaluate mutual relationships and interlinking among barriers. CSR training and undertaking CSR in collaboration can help medium enterprises overcome these barriers and prepare strategies to mitigate their impact. 2021, Emerald Publishing Limited. -
A Novel Deep Learning Approach for Identifying Interstitial Lung Diseases from HRCT Images
Interstitial lung diseases (ILDs) are defined as a group of lung diseases that affect the interstitium and cause death among humans worldwide. It is more serious in underdeveloped countries as it is hard to diagnose due to the absence of specialists. Detecting and classifying ILD is a challenging task and many research activities are still ongoing. High-resolution computed tomography (HRCT) images have essentially been utilized in the diagnosis of this disease. Examining HRCT images is a difficult task, even for an experienced doctor. Information Technology, especially Artificial Intelligence, has started contributing to the accurate diagnosis of ILD from HRCT images. Similar patterns of different categories of ILD confuse doctors in making quick decisions. Recent studies have shown that corona patients with ILD also go on to sudden death. Therefore, the diagnosis of ILD is more critical today. Different deep learning approaches have positively impacted various image classification problems recently. The main objective of this proposed research work was to develop a deep learning model to classify the ILD categories from HRCT images. This proposed work aims to perform binary and multi-label classification of ILD using HRCT images on a customized VGG architecture. The proposed model achieved a high test accuracy of 95.18% on untrained data. 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
Anomalous indirect carrier relaxation in direct band gap atomically thin gallium telluride
We report ultrafast studies on atomically thin Gallium telluride, a 2D metal monochalcogenide that has appeared to display superior photodetection properties in visible frequencies. Pump photon energy-dependent spectroscopic studies reveal that photoinduced carriers in this direct band-gap material undergo indirect relaxation within ?30 ps of photoexcitation, which is at least an order slower than that of most 2D materials. Despite the direct band-gap nature, slow and indirect carrier relaxation places this layered material as a prime candidate in the multitude of atomically thin semiconductor-based photodetectors and highlights the potential for prospective optoelectronic applications. 2023 American Physical Society. -
AUTOMATION OF TEST CASE PRIORITIZATION: A SYSTEMATIC LITERATURE REVIEW AND CURRENT TRENDS
An Important stage in software testing is designing a test suite [18]. The test case repository consists of a large number of test cases. However, only a portion of these test cases would be relevant and can find bugs. Test case prioritization(TCP) is one such technique that can substantially increase the cost-effectiveness of the testing activity. Using test case prioritization, more relevant test cases can be captured and tested in the earlier stages of the testing phase. The objective of the study is to understand different techniques used and a systemic study on the effectiveness of these approaches. The Literature consists of a few relevant articles introducing novel techniques for test case prioritization between 2008 and 2022. Studies show that parameters that are considered for test case prioritization are important. Hence, the current article also focuses on the parameters considered in the literature. 40% of the articles used in the literature review use different test case information as parameters. A systemic review and analysis of data sets involved in the literature are evaluated in the study. The review also focuses on the different approaches used for comparing the newly introduced approach and reveals a novel approach for prioritization. 2023 Little Lion Scientific. All rights reserved. -
Engineering a low-cost diatomite with Zn-Mg-Al Layered triple hydroxide (LTH) adsorbents for the effectual removal of Congo red: Studies on batch adsorption, mechanism, high selectivity, and desorption
In this work, naturally occurring, low-cost diatomite (De) or diatomaceous earth (DE) adsorbent was treated with various molar concentrations (0.05, 0.1, and 0.2 M) of Zn-Mg-Al layered triple hydroxide (LTH) using a co-precipitation approach. The DE-modified samples were named 0.05 LDE, 0.1 LDE, and 0.2 LDE and employed to remove Congo Red (CR) dye from an aqueous solution. The adsorbents were examined using XRD, BET-N2 adsorption-desorption method, ATR-IR, FESEM-EDX, and XPS, and also analyzed for zeta potentials of adsorbents at pH values between 5 and 11 to observe their surface charges. The removal efficiencies of CR were 96.5%, 99.7%, and 94.5% for 20 mg of 0.05 LDE, 0.1 LDE, and 0.2 LDE, respectively, at pH 7. A bare DE, however, showed a removal efficiency of only 7.4%. After CR adsorption, the maximum adsorption capacities (qmax) of the adsorbents were examined using the Langmuir isotherm, and the results showed that 0.1 LDE-CR (44.0 mgg?1) had a higher qmax than 0.05 LDE-CR (35.6 mgg?1), 0.2 LDE-CR (27.9 mgg?1), and DE-CR (0.9 mgg?1). The optimal adsorbent of 0.1 LDE was utilized for the selectivity and salt effects based on the investigation's efficiency in removing contaminants. 0.1 LDE has been studied for reusability of up to five cycles and can remove CR up to three cycles with 77.7% and 79.9% efficiency using NaCl and NaOH, respectively. The adsorbents may therefore be particularly effective at removing CR from water and beneficial in industrial settings where dye is often used. 2023 Elsevier B.V. -
A Study on Experimental Analysis of Best Fit Machine Learning Approach for Smart Agriculture
By 2050, the population is projected to exceed nine billion, necessitating a 70% increase in agricultural output to meet the need. Land, water, and other resources are running out due to the growing world population, making it impossible to maintain the demandsupply cycle. The yield of cultivation is also declining as a result of people's ignorance of the growing crop illnesses. Given that food is the most basic human requirement, future research should focus on revitalizing the agricultural sector. Farming may be made more productive for farmers by applying the right artificial intelligence technologies and datasets. Agronomics can benefit greatly from artificial intelligence. So that we can farm more effectively and be as productive as possible, we need to adopt a better strategy. The objective of this paper is to experimentally analyze the machine learning algorithms and methods already in use and forecast the most effective approach to use in each agricultural sector. In this article, we will present the challenges farmers face when using traditional farming methods and how artificial intelligence is revolutionizing agriculture by replacing the traditional methods. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.