Browse Items (11858 total)
Sort by:
-
New frontiers in polyphenol analysis: A review of electrochemical sensors and commercial devices enhancing food and beverage analysis
Food safety concerns arise from outbreaks of foodborne illnesses and contamination within the food supply. Polyphenols, naturally occurring compounds in plants, are characterized by multiple phenolic (hydroxyl) groups and are prevalent in fruits, vegetables, tea, coffee, and wine. While beneficial in moderation, excessive polyphenol intake is harmful, and they classified as secondary pollutants in environment. Therefore, accurate quantification of polyphenols is essential for ensuring product safety, quality, and nutritional value, which is the focus of this review. Electrochemical sensors offer a sensitive, selective, and cost-effective method for detecting polyphenols in food and beverages. The review examines advanced voltammetric techniques for identifying polyphenols in various food samples, including beverages and dietary products. Additionally, total antioxidant capacity (TAC) sensors are highlighted as valuable tools for assessing the antioxidant potential of foods, aiding in nutritional analysis and quality control. This review, for the first time, catalogs around ten commercially available devices and twenty assay kits for detecting antioxidant polyphenols, highlighting their significance in advancing food safety, bolstering consumer confidence, and supporting ongoing nutritional research. Additionally, made efforts to bridge a crucial gap between conventional research and industry needs by expanding the existing body of knowledge and providing fresh insights into polyphenol analysis. 2025 Elsevier Inc. -
Recent trends in the electrochemical sensors on ?- and calcium channel blockers for hypertension and angina pectoris: A comprehensive review
Stress, ingrained human behaviors, an inactive lifestyle, and poor dietary decisions are the primary causes of hypertension and the related coronary artery disease (CAD), which is also commonly referred to as angina pectoris. Effective high blood pressure (BP) treatment represents a substantial approach to reducing the burden of hypertension-related cardiovascular and renal diseases. A group of drugs known as ?-blockers and calcium channel blockers (CCBs) are frequently used to treat diseases like hypertension (high blood pressure), cardiac arrhythmias and heart failure. For efficient therapeutic use and to reduce potential side effects, ?-blocker concentration monitoring is essential. Chromatographic techniques are employed in a wide range to detect ?-blockers and CCBs without interference, among other analytical methods that have been described. For the detection of ?-blockers and CCBs, electrochemical sensors provide numerous benefits including sensitivity, selectivity, rapidity, and cost-effectiveness. These sensors can help with patient monitoring in clinical settings, ensuring that the prescription ?-blocker dosage is within the therapeutic range. Since ?-blockers are frequently consumed by people, the contamination can be occurred through discharge of wastewater. The presence and measurement of ?-blockers in water samples enables researchers to evaluate potential risks to aquatic life and public health. In this regard, this review addresses recently developed electrochemical (voltammetric) methodologies and measurement protocols for the determination of both ?-blockers and CCBs in pharmaceuticals, biological fluids, and environmental samples. Additionally, this review also provides an overview of the various advanced nanomaterials such as carbon nanotubes, graphene oxide, metal and metal oxide nanoparticles, polymeric structures, zeolite materials, ionic liquids, perovskite semiconductor-based materials, MXenes, Quantum dots, Nano MIPs and various dimensional materials applied to fabricate chemically modified electrodes/electrochemical sensors to determine the ?-blockers and CCBs. Moreover supplied are tables listing the analyte, modified electrode, measurement method, measuring medium pH, linear detection range (LDR), limit of detection (LOD) and sensitivity as they are cited in the original research. Furthermore, important conclusions are made from the published reports in the last decade and some future perspectives are also suggested. 2023 Elsevier B.V. -
5G Technology Empowering Wireless Technology
Wireless Communication is the means of transferring data from one point to another without the use of any wired means. With reference to wireless communication, wireless sensor Networks (WSN) have also developed in recent times. It can be referred as an infrastructure-less system of wireless devices which can gather and exchange information with the help of a wireless link. The information which is gathered is sent respectively to the base stations and sinks for further developments. Recently, the 5G generation network, the latest Wireless Communication Network operates at a higher frequency range than its predecessor. In this paper, a detailed analysis on the 5G generation cellular network, which is expected to be a key instrument of wireless technologies in the near future is outlined. Also a comparative analysis of different kinds of networks in context to wireless scenario is discussed. It was found that 5G provides the best outcome in terms of high speed and network spectrum bandwidth. 2023 IEEE. -
Influence of media messages on voters behaviour, a study on people's perception of the Loksabha election 2014 /
Including, all private, public, regional and national news media there are more than 100 news, channels are available in India. Compare to previous Loksabha elections; on the 16thLoksabha election the role of media was exceptional. On Loksabha election 2014, the effect of media messages and the news representation was very much visible. -
Hybrid Model Using Interacted-ARIMA andANN Models forEfficient Forecasting
When two models applied to the same dataset produce two different sets of forecasts, it is a good practice to combine the forecasts rather than using the better one and discarding the other. Alternatively, the models can also be combined to have a hybrid model to obtain better forecasts than the individual forecasts. In this paper, an efficient hybrid model with interacted ARIMA (INTARIMA) and ANN models is proposed for forecasting. Whenever interactions among the lagged variables exist, the INTARIMA model performs better than the traditional ARIMA model. This is validated through simulation studies. The proposed hybrid model combines forecasts obtained through the INTARIMA model from the dataset, and those through the ANN model from the residuals of INTARIMA, and produces better forecasts than the individual models. The quality of the forecasts is evaluated using three error metrics viz., Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). Empirical results from the application of the proposed model on the real dataset - lynx - suggest that the proposed hybrid model gives superior forecasts than either of the individual models when applied separately. The methodology is replicable to any dataset having interactions among the lagged variables.. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Digital Watermarking Techniques for Secure Image Distribution
In the contemporary era of digital advancements, it is of utmost importance to prioritize the establishment of robust security measures and traceability protocols for photos. This necessity arises from the inherent risk associated with the effortless diffusion of unlicensed information. Digital watermarking, which implants hidden data into digital photographs to verify their validity, is frequently used. This level emphasizes the need of safe photo distribution, digital platform problems, and unauthorized reproductions. The purpose of this research is to explain digital watermarking fundamentals. It emphasizes verification, IP protection, and digital watermarking monitoring. This research compares spatial and frequency domain watermarking approaches. Direct pixel manipulation in spatial domain techniques is vulnerable to attacks. Integrating watermarks with transform domains like Discrete Cosine Transform improves robustness in frequency domain techniques. The study also studies adaptive watermarking, which adjusts the watermark to the image's content to balance visibility and durability. The purpose of this research is to explore watermark identification methods. These methods use blind and non-blind watermarking. We discuss the security risks that might compromise watermarked photographs and the ways to reduce their likelihood. 2024 IEEE. -
ON BLOCK-RELATED DERIVED GRAPHS
This paper introduces and analyses the block-degree of a vertex and the cut-degree of a block. The block-degree of a vertex v is the number of blocks containing v. The cut-degree of a block b is the number of cut vertices of G contained in b. The block-degree sequence of cut vertices of the graph and the cut-degree sequence of the graph are defined. A few characterizations of the block-degree and cut-degree sequence of the graph are established. Given a graph, its block graph (B(G)) is a graph where each vertex represents a block, and two vertices are connected if their blocks intersect. The number of cut vertices of B(G) is determined. Further, an investigation is carried out on the traversability of B(G). A block cutpoint graph (BC(G)) of a graph represents a graph where each vertex corresponds to either a block or a cut vertex, and two vertices are connected if one represents a block and the other represents a cut vertex contained within that block. The properties of BC(G) and its iterations are studied. The graph G for which BC(G) is a perfect m-ary tree is characterized. 2024, Canadian University of Dubai. All rights reserved. -
Distance based properties of the semi splitting block graph of graph
The bounds on the radius and diameter of the semi splitting block graph (SB(G)) of graphs are investigated. The diametral paths and self-centeredness of semi splitting block graph of any connected graph are analyzed. The graphs where the diameter of G and SB(G) are the same are characterized and the number of blocks in the diametral path of such graphs is analyzed. 2023 Author(s). -
Eccentricity splitting graph of a graph
Let G = (V, E) be any connected graph with (Figure presented.) for all uj, uk ? Si if e(uj) = e(uk)(1 ? i ? t) with each | Si |? 2 and (Figure presented.). The eccentricity splitting graph of a graph denoted by ES(G) is obtained by taking a copy of G and adding vertices w 1, w 2, , wt such that wi is adjacent only to the vertices of Si for 1 ? i ? t. We initiate the study on eccentricity splitting graph ES(G) and examine its structural properties. We also analyze diameter, girth and chromatic number of eccentricity splitting graphs of certain classes of graphs. 2021 Taru Publications. -
Numerical and sensitivity analysis of MHD bioconvective slip flow of nanomaterial with binary chemical reaction and Newtonian heating
The impact of Stefan blowing on the MHD bioconvective slip flow of a nanofluid towards a sheet is explored using numerical and statistical tools. The governing partial differential equations are nondimensionalized and converted to similarity equations using apposite transformations. These transformed equations are solved using the RungeKuttaFehlberg method with the shooting technique. Graphical visualizations are used to scrutinize the effect of the controlling parameters on the flow profiles, skin friction coefficient, local Nusselt, and Sherwood number. Moreover, the sensitivities of the reduced Sherwood and Nusselt number to the input variables of interest are explored by adopting the response surface methodology. The outcomes of the limiting cases are emphatically in corroboration with the outcomes from preceding research. It is found that the heat transfer rate has a positive sensitivity towardsthe haphazard motion of the nanoparticles and a negative sensitivity towardsthe thermomigration. The thermal field is enhanced by the Stefan blowing aspect. Moreover, the fluid velocity can be controlled by the applied magnetic field. 2021 Wiley Periodicals LLC -
Segmentation and identification of MRI Brain segment in digital image
Brain image segmentation is important in the area of clinical diagnosis. MRI Brain image segmentation is time consuming and there is always a chance of occurrence of error when the segmentation is done manually. It is always possible to detect the infected tissues easily in the current medical field. However, the accuracy and the characteristics of abnormalities of the tissues are not precise. In the past, many researchers have identified the drawbacks of manual segmentation and hence proposed the semiautomatic and fully automatic segmentation methods in the field of medical imaging. The amount of precision about the detection of defective tissues leads to acceptance of a particular image segmentation method. In this article three segmentation methods are hybridized to get the optimum extraction of the region of interest (ROI) in brain MRI image. Further, the region properties of segment is extracted and stored as knowledgebase. The proposed algorithm integrates multiple segmentation methods and identifies the Brain Outer layer in MRI image. This identification AIDS medical experts for optimum diagnosis of defective tissues in the brain. IAEME Publication. -
Design, development, and analysis of segment support system for TMT primary mirror
The Thirty Meter Telescope (TMT) adopts a recently developed technology known as Stressed Mirror Polishing for the polishing of its 492 mirror segments. In this process, first the meniscus type spherical shape glass blanks are converted in to a desired aspheric shape by the application of forces around the edges using warping arms followed by spherical polishing in the stressed condition. After that, the blank edges will be cut in to its final hexagonal shape. These warping as well as the hex cutting process generate significant stress within the glass which in later stage, will cause the propagation of micro cracks and results in blank breakage. So prior and after the hex cutting process, it is essential to ensure that the glass blanks are free from stress accumulation. Hence the glass blanks need to be stress relieved before the hex cutting process. To achieve this stress relaxation, the glass blanks need to be kept over a platform or a support system which will provide a zero gravity condition for a time period of at least 48 hours. As a part of this, we designed, developed and analyzed a whiffletree based support system which will equally distribute the entire mirror blank mass into three points which are equally separated by 120 from each other and thus balance itself as if it is in a floating condition. This support system which additionally gives optimized support for the glass blank which in turn minimizes the surface deformation due to its self weight sagging. This paper also discusses the positional sensitivity, reaction force sensitivity and alignment sensitivity analyses which are essential to obtain the tolerance values in the fabrication point of view. 2020 SPIE. -
Comparative Analysis Study of 43-point and 27-point Buyoff Stations for Stressed Mirror Polishing (SMP) Metrology
As a collaborative effort within the Thirty Meter Telescope (TMT) project, India is committed to supplying 84 polished segments for the primary mirror, employing the innovative Stressed Mirror Polishing (SMP) technology obtained from Coherent Inc., USA. SMP allows for the efficient polishing of highly aspheric non-axisymmetrical glass blanks at an accelerated rate. India-TMT (I-TMT) successfully applied SMP to qualify three glass roundels at Coherent's facility in Richmond, CA. The study focuses on a comparative analysis of Buyoff Stations (BOS) used in the SMP process. It contrasts results from the 43-point hydraulic-based BOS at Coherent with simulated outcomes from the 27-point whiffletree-based BOS at I-TMT. This analysis assesses efficacy and performance differences between the two BOS configurations, involving a comprehensive examination of a 1520mm diameter polished glass roundel. The study integrates Finite Element Method (FEM) simulations with experimental data, providing insights into the efficiency of the respective BOS setups. 2024 SPIE. -
Artificial Intelligence Revolution in Supply Chain Management
Artificial Intelligence (AI) is a buzzword everywhere in every domain, as it is an emerging technology in all business sectors. It is essential for achieving productivity, business benefits, less human efforts in the required business sectors instead of a large workforce and many more artificial intelligence applications that are scaling up with large scale business sectors. AI capacity to identify the trade patterns, the study's business occurrence, and analyze the information. AI is necessary for today's life and as well as for upcoming generations. Artificial intelligence helps to resolve the most complex problems and difficult situations where humans have not achieved so far, as it is the artificial brainpower of humans. We have seen technological changes happening faster and progressively by AI. The supply chain vastly gained from interest and investments in AI. The digital supply chain initiation, a shift in manufacturing is up and running. Advantageous supply chain management is essential in business sectors, customers, and governments. A combination of Artificial intelligence and supply chain management is put together in making decisions. This article will discuss the overview of AI advancements in supply chain management end-to-end processes. We also reviewed the supply chain operations using AI. 2023 American Institute of Physics Inc.. All rights reserved. -
A LSTM based model for stock price analysis and prediction
The share market in India is exceedingly unpredictable and volatile, with an infinite range of factors regulating the share market's orientations and tendencies; hence, forecasting the upswing and downturn is a difficult procedure. Because of several essential aspects, the principles of share market have always been unclear for shareholders. This study aims to significantly reduce the likelihood of analysis and forecasting with Long Short-term Memory (LSTM) model approach that is both resilient yet easy is still suggested. LSTM is a complete Learning Model that is a Predictive Method. Conversely, advancements in technology have opened the way for more efficient and precise share market forecasting in current times. Using the provided historical data sets, the results showed that the LSTM model has considerable potential for forecasting. 2023 Author(s). -
Leveraging Robotic Process Automation (RPA) in Business Operations and its Future Perspective
Robotic Process Automation (RPA) is used to automate the business process operations including its capabilities to mimic the routine tasks, which requires less human intervention. RPA has seen crucial take-up practically throughout the last few years because of its capacity to reduce expenses and quickly associate heritage applications. Fundamentally RPA would perform automated tasks much like as an individual to accomplish objectives productively and adequately. This article analyses the features in current business conditions to comprehend the movement of RPA and automated interaction has carried to substitute the businesses with automated tasks. RPA is an innovative technology which utilizes software programming to execute enormous capacity assignments that are routine and time-consuming in the business cycle. RPA streamlines by playing out those undertakings proficiently as it reduces cost and saves assets of an association as programming works till the finishing of the assignment. This study aligns with the descriptive approach and leveraging Robotic Process Automation into business operations. This article also addresses the different players in the RPA Technological segment. This study also discussed and suggested selecting RPA Vendors in a future perspective. 2023 American Institute of Physics Inc.. All rights reserved. -
Implementation of Time-Series Analysis: Prediction of Stock Prices using Machine Learning and Deep learning models: A Hybrid Approach
Experts in the finance system have long found it difficult to estimate stock values. Despite the Efficient - market hypothesis Principle claim that it is difficult to anticipate share prices with any degree of precision, research has demonstrated that share price movements could be anticipated with the proper levels of precision provided the correct parameters are chosen and the proper predictive models are created. individuals who are adaptable. The share market is unpredictable in essence, making its forecasting a difficult undertaking. Stock prices are affected by more than economic reasons. In this project, Arima, LSTM and Prophet models are used to predict the future way of behaving share price, the datasets has been obtained from NSE, share price prediction algorithms have been created and tested. According to the empirical findings, the LSTM model would be used to anticipate share prices rather well over a substantial amount of time with exactness. 2022 IEEE. -
Mapping the Landscape of Business Intelligence Research: A Bibliometric Approach
The integration of Business Intelligence (BI) is an essential element in contemporary enterprises, facilitating the conversion of voluminous data into valuable insights to support informed decision-making. Consequently, a considerable body of literature has been devoted to investigating the utilization of Business Intelligence (BI) in enhancing company efficiency and competitiveness. The present investigation employs bibliometric methods as a means to examine the research pertaining to Business Intelligence (BI). This includes an examination of the main writers and universities, publication patterns, and the intellectual framework of the domain. This investigation centers on the timeframe spanning from 2000 to 2022 and scrutinizes a corpus of 3729 Scopus articles pertaining to business intelligence. The findings suggest that the domain of Business Intelligence (BI) has experienced a substantial expansion recently. The study's results reveal significant contributors, establishments, nations, and references in the discipline, along with developing research patterns and prospects for further investigation. In general, this research emphasizes the significance of bibliometric evaluation as a means of comprehending the present status of BI research and discovering approaches to enhance the utilization of BI in contemporary organizational decision-making procedures. This study has the potential to provide valuable insights into the present state of research within the field, pinpoint significant trends and themes, and highlight potential avenues for future research. 2023 IEEE. -
Can Artificial Intelligence Accelerate and Improve New Product Development
Today, AI have successfully set up a good foundation in a broad scope of business processes. Associations including AI for product headway processes have uncovered more huge yields on hypotheses, better viability in their cycles, and effective utilization of resources. A sensible headway framework is paramount for capable product development, especially for complex endeavours. AI thinking is in like manner improving new product development. AI is probably going to experience clients in numerous areas. New yield evolution as in collaboration utilizes its capital and capacities to make another item or work on a current one. Product development is viewed as one among the fundamental cycles for progress, endurance, and recharging of associations, especially for firms in, by the same token, quick-moving or cutthroat business sectors. AI assists people's lives by expanding connections creating and multiplying items that can work with individuals' daily exercises in quite a large number of areas. Consequently, the impact of involving Artificial Intelligence for new developments is to induce things simpler. This paper attempts to outline the acceleration of new product development with the help of artificial intelligence technology. This study addressed the tailored AI in product improvement and product development transformation. Lastly, this article points out how AI accelerates product development and future outlook. 2023 American Institute of Physics Inc.. All rights reserved.