Search results for: enhanced data encryption

Authors: Stephen Osei Akyiaw, Divine Kwabena Atta Kyere-Owusu

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Malaria has been a worldwide menace of a health condition to human beings for several decades with majority of people on the African continent with most causalities where Ghana is no exception. Therefore, this study employed the use of animation to enhance awareness creation on the spread and prevention of Malaria in Effutu Communities in the Central Region of Ghana. Working with the interpretivist paradigm, this study adopted Art-Based Research, where the AIDA Model and Cognitive Theory of Multimedia Learning (CTML) served as the theories underpinning the study. Purposive and convenience sampling techniques were employed in selecting sample for the study. The data collection instruments included document review and interviews. Besides, the study developed an animation using the local language of the people as the voice over to foster proper understanding by the rural community folks. Also, indigenous characters were used for the animation for the purpose of familiarization with the local folks. The animation was publicized at Health Town Halls within the communities. The outcomes of the study demonstrated that the use of animation was effective in enhancing the awareness creation for preventing and controlling malaria disease in rural communities in Effutu Communities in the Central Region of Ghana. Health officers and community folks expressed interest and desire to practice the preventive measures outlined in the animation to help reduce the spread of Malaria in their communities. The study, therefore, recommended that animation could be used to curtail the spread and enhanced the prevention of Malaria.

Keywords: malaria, animation, prevention, communities

Procedia PDF Downloads 55

Authors: Talha A. Taj, Talha A. Khan, M. Imran Khalid

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Optimization techniques attract researchers to formulate a problem and determine its optimum solution. This paper presents an Enhanced Harmony Search (ENHS) algorithm for solving optimization problems. The proposed algorithm increases the convergence and is more efficient than the standard Harmony Search (HS) algorithm. The paper discusses the novel techniques in detail and also provides the strategy for tuning the decisive parameters that affects the efficiency of the ENHS algorithm. The algorithm is tested on various benchmark functions, a real world optimization problem and a constrained objective function. Also, the results of ENHS are compared to standard HS, and various other optimization algorithms. The ENHS algorithms prove to be significantly better and more efficient than other algorithms. The simulation and testing of the algorithms is performed in MATLAB.

Keywords: optimization, harmony search algorithm, MATLAB, electronic

Procedia PDF Downloads 434

Authors: Jai Prakash, Promod Kumar, Chantel Swart, J. H. Neethling, A. Janse van Vuuren, H. C. Swart

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Ag nanoparticles (NPs) have been used as functional nanomaterials due to their optical and antibacterial properties. Similarly, TiO2 photocatalysts have also been used as suitable nanomaterials for killing cancer cells, viruses and bacteria. Here, we report on multifunctional plasmonic Ag-TiO2 nano-biocomposite synthesized by the sol-gel technique and their optical, surface enhanced Raman scattering (SERS) and antibacterial activities. The as-prepared composites of Ag–TiO2 with different silver content and TiO2 nanopowder were characterized by X-ray diffraction, scanning electron microscopy, high-resolution transmission electron microscopy, energy-dispersed X-ray analysis (EDX), UV-vis and Raman spectroscopy. The Ag NPs were found to be uniformly distributed and strongly attached to the TiO2 matrix. The novel optical response of the Ag-TiO2 nanocomposites is due to the strong electric field from the surface plasmon excitation of the Ag NPs. The Raman spectrum of Ag-TiO2 nanocomposite was found to be enhanced as compared to TiO2. The enhancement of the low frequency band is evident. This indicates the SERS effect of the TiO2 NPs in close vicinity of Ag NPs. In addition, nanocomposites showed enhancement in the SERS signals of methyl orange (MO) dye molecules with increasing Ag content. The localized electromagnetic field from the surface plasmon excitation of the Ag NPs was responsible for the SERS signals of the TiO2 NPs and MO molecules. The antimicrobial effect of the Ag–TiO2 nanocomposites with different silver content and TiO2 nanopowder were carried out against the bacterium Staphylococcus aureus. The Ag–TiO2 composites showed antibacterial activity towards S. aureus with increasing Ag content as compared to the TiO2 nanopowder. These results foresee promising applications of the functional plasmonic metal−semiconductor based nanobiocomposites for both chemical and biological samples.

Keywords: metal-Semiconductor, nano-Biocomposites, anti-microbial activity, surface enhanced Raman scattering

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Authors: Zina Saheb, Ezz El-Masry, Jean-François Bousquet

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This paper presents an enhanced efficiency simultaneous dual band energy harvesting system for wireless body area network. A bulk biasing is used to enhance the efficiency of the adapted rectifier design to reduce V_th of MOSFET. The presented circuit harvests the radio frequency (RF) energy from two frequency bands: 1 GHz and 2.4 GHz. It is designed with TSMC 65-nm CMOS technology and high quality factor dual matching network to boost the input voltage. Full circuit analysis and modeling is demonstrated. The simulation results demonstrate a harvester with an efficiency of 23% at 1 GHz and 46% at 2.4 GHz at an input power as low as -30 dBm.

Keywords: energy harvester, simultaneous, dual band, CMOS, differential rectifier, voltage boosting, TSMC 65nm

Procedia PDF Downloads 380

Authors: Ahmad Idi

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The biosynthesis and properties of polyhydroxyalkanoate (PHA) are determined by the bacterial strain and the culture condition. Hence this study elucidates the structure and properties of PHA produced by a newly isolated strain of photosynthetic bacterium, Rhodobacter sphaeroides ADZ101 grown under the optimized culture condition. The properties of the accumulated PHA were determined via FTIR, NMR, TGA, and GCMS analyses. The results showed that acetate and ammonia chloride had the highest PHA accumulation with a ratio of 32.5 mM at neutral pH. The structural analyses showed that the polymer comprises both short and medium-chain length monomers ranging from C5, C13, C14, and C18, as well as the presence of novel PHA monomers. The thermal analysis revealed that the maximum temperature of decomposition occurred at 395°C and 454°C, indicating two major decomposition reactions. Thus this bacterial strain, optimized culture condition, and the abundance of novel monomers enhanced the thermostability of the accumulated PHA.

Keywords: bioplastic polyhydroxyalkanoates Rhodobacter sphaeroides ADZ101 thermostable PHA

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Authors: Rajashree Bothale, Venkateswara Rao

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Indian Himalayas also known as third pole with 0.9 Million SQ km area, contain the largest reserve of ice and snow outside poles and affect global climate and water availability in the perennial rivers. The variations in the extent of snow are indicative of climate change. The snow melt is sensitive to climate change (warming) and also an influencing factor to the climate change. A study of the spatio-temporal dynamics of snow cover and melt/freeze conditions is carried out using space based observations in visible and microwave bands. An analysis period of 2003 to 2015 is selected to identify and map the changes and trend in snow cover using Indian Remote Sensing (IRS) Advanced Wide Field Sensor (AWiFS) and Moderate Resolution Imaging Spectroradiometer(MODIS) data. For mapping of wet snow, microwave data is used, which is sensitive to the presence of liquid water in the snow. The present study uses Ku-band scatterometer data from QuikSCAT and Oceansat satellites. The enhanced resolution images at 2.25 km from the 13.6GHz sensor are used to analyze the backscatter response to dry and wet snow for the period of 2000-2013 using threshold method. The study area is divided into three major river basins namely Brahmaputra, Ganges and Indus which also represent the diversification in Himalayas as the Eastern Himalayas, Central Himalayas and Western Himalayas. Topographic variations across different zones show that a majority of the study area lies in 4000–5500 m elevation range and the maximum percent of high elevated areas (>5500 m) lies in Western Himalayas. The effect of climate change could be seen in the extent of snow cover and also on the melt/freeze status in different parts of Himalayas. Melt onset day increases from east (March11+11) to west (May12+15) with large variation in number of melt days. Western Himalayas has shorter melt duration (120+15) in comparison to Eastern Himalayas (150+16) providing lesser time for melt. Eastern Himalaya glaciers are prone for enhanced melt due to large melt duration. The extent of snow cover coupled with the status of melt/freeze indicating solar radiation can be used as precursor for monsoon prediction.

Keywords: Indian Himalaya, Scatterometer, Snow Melt/Freeze, AWiFS, Cryosphere

Procedia PDF Downloads 232

Authors: Mahesh Hariharan, Rajan Balasubramaniam, Sharath Kumar Shetty, Shanthala Yadavalli, Mohammed Ahetasham, Sravya Devarapalli

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Acute abdomen is one of the most common clinical conditions requiring a radiological investigation. Ultrasound is the primary modality of choice which can diagnose some of the common causes of acute abdomen. However, sometimes the underlying cause for the pain is far more complicated than expected to mandate a high degree of suspicion to suggest further investigation with contrast-enhanced computed tomography or magnetic resonance imaging. Here, we have compiled a comprehensive series of selected cases to highlight the conditions which can be easily overlooked unless carefully sought for. This also emphasizes the importance of multimodality approach to arrive at the final diagnosis with an increased overall diagnostic accuracy which in turn improves patient management and prognosis.

Keywords: acute abdomen, contrast-enhanced computed tomography scan, magnetic resonance imaging, plain radiographs, ultrasound

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Authors: Meenu Mehta, Munish Garg

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The use of oral anticancer drugs from AYUSH system of medicine is widely increased among the society due to their low cost, enhanced efficacy, increased patient preference, lack of inconveniences related to infusion and they provide an opportunity to develop chronic treatment regimens. However, oral delivery of these drugs usually laid down by the limited bioavailability of the drug, which is associated with a wide variation. As most of the cytotoxic agents have a narrow therapeutic window and are dosed at or near the maximum tolerated dose, a wide variability in the bioavailability can negatively affect treatment result. It is estimated that 40% of active substances are poorly soluble in water. The improvement of bio-availability of drugs with such properties presents one of the greatest challenges in drug formulations. There are several techniques reported in literature. Among all these Self Emulsifying Drug Delivery System (SEDDS) has gained more attention due to enhanced oral bio-availability enabling a reduction in dose. Thus, SEDDS anticancer drugs will have the increased bioavailability and efficacy. These dosage form will provide societal benefit in a cost-effective manner as compared to other oral dosage forms. Present study reflects on the formulation strategies as SEDDS for oral anticancer agents of AYUSH system for enhanced bioavailability with proven efficacy by cancer cell lines.

Keywords: anticancer agents, AYUSH system, bioavailability, SEDDS

Procedia PDF Downloads 279

Authors: Zeeshan Ahmed, Ajinkya Sarode, Pratik Basarkar, Atul Bhargav, Debjyoti Banerjee

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The use of CO₂ in oil recovery and in CO₂ capture and storage is gaining traction in recent years. These applications involve heat transfer between CO₂ and the base fluid, and hence, there arises a need to improve the thermal conductivity of CO₂ to increase the process efficiency and reduce cost. One way to improve the thermal conductivity is through nanoparticle addition in the base fluid. The nanofluid model in this study consisted of copper (Cu) nanoparticles in varying concentrations with CO₂ as a base fluid. No experimental data are available on thermal conductivity of CO₂ based nanofluid. Molecular dynamics (MD) simulations are an increasingly adopted tool to perform preliminary assessments of nanoparticle (NP) fluid interactions. In this study, the effect of the formation of a nanolayer (or molecular layering) at the gas-solid interface on thermal conductivity is investigated using equilibrium MD simulations by varying NP diameter and keeping the volume fraction (1.413%) of nanofluid constant to check the diameter effect of NP on the nanolayer and thermal conductivity. A dense semi-solid fluid layer was seen to be formed at the NP-gas interface, and the thickness increases with increase in particle diameter, which also moves with the NP Brownian motion. Density distribution has been done to see the effect of nanolayer, and its thickness around the NP. These findings are extremely beneficial, especially to industries employed in oil recovery as increased thermal conductivity of CO₂ will lead to enhanced oil recovery and thermal energy storage.

Keywords: copper-CO2 nanofluid, molecular dynamics simulation, molecular interfacial layer, thermal conductivity

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Authors: Murtaza Adil, Sen Yang, Zhou Chao, Song Xiaoping

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The morphotropic phase boundary (MPB) recently has attracted constant interest in ferromagnetic systems for obtaining enhanced large magnetoelastic response. In the present study, structural and magnetoelastic properties of MPB involved ferromagnetic Tb_1-xGd_xFe₂ (0≤x≤1) system has been investigated. The change of easy magnetic direction from <111> to <100> with increasing x up MPB composition of x=0.9 is detected by step-scanned [440] synchrotron X-ray diffraction reflections. The Gd substitution for Tb changes the composition for the anisotropy compensation near MPB composition of x=0.9, which was confirmed by the analysis of detailed scanned XRD, magnetization curves and the calculation of the first anisotropy constant K₁. The spin configuration diagram accompanied with different crystal structures for Tb_1-xGd_xFe₂ was designed. The calculated first anisotropy constant K₁ shows a minimum value at MPB composition of x=0.9. In addition, the large ratio between magnetostriction, and the absolute values of the first anisotropy constant │λ_S∕K₁│ appears at MPB composition, which makes it a potential material for magnetostrictive application. Based on experimental results, a theoretically approach was also proposed to signify that the facilitated magnetization rotation and enhanced magnetoelastic effect near MPB composition are a consequence of the anisotropic flattening of free energy of ferromagnetic crystal. Our work specifies the universal existence of MPB in ferromagnetic materials which is important for substantial improvement of magnetic and magnetostrictive properties and may provide a new route to develop advanced functional materials.

Keywords: free energy, magnetic anisotropy, magnetostriction, morphotropic phase boundary (MPB)

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Authors: Abigail Gragg

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The goal of this research study was to adjudicate if implementing Howard Gardner’s multiple levels of intelligence would enhance student achievement levels in an Algebra 1 College Preparatory class. This was conducted within every class by incorporating one level of the eight levels of intelligence into small group work in stations. Every class was conducted utilizing small-group instruction. Achievement levels were measured through various forms of collected data that expressed student understandings in class through formative assessments versus student understandings on summative assessments. The data samples included: assessments (i.e. summative and formative assessments), observable data, video recordings, a daily log book, student surveys, and checklists kept during the observation periods. Formative assessments were analyzed during each class period to measure in-class understanding. Summative assessments were dissected per question per accuracy to review the effects of each intelligence implemented. The data was collated into a coding workbook for further analysis to conclude the resulting themes of the research. These themes include 1) there was no correlation to multiple levels of intelligence enhancing student achievement, 2) bodily-kinesthetic intelligence showed to be the intelligence that had the most improvement on test questions and 3) out of all of the bits of intelligence, interpersonal intelligence enhanced student understanding in class.

Keywords: stations, small group instruction, multiple levels of intelligence, Mathematics, Algebra 1, student achievement, secondary school, instructional Pedagogies

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Authors: K. Sathishkumar, V. Thiagarasu

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Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

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Authors: ِAbdallah A. A. Shaheen

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Gaza Strip faces economic and political issues such as conflict, siege and urbanization; all these have led to an increase in the air pollution over Gaza Strip. In this study, Particulate matter 10 (PM10) concentration over Gaza Strip has been estimated by Landsat Thematic Mapper (TM) and Landsat Enhanced Thematic Mapper Plus (ETM+) data, based on a multispectral algorithm. Simultaneously, in-situ measurements for the corresponding particulate are acquired for selected time period. Landsat and ground data for eleven years are used to develop the algorithm while four years data (2002, 2006, 2010 and 2014) have been used to validate the results of algorithm. The developed algorithm gives highest regression, R coefficient value i.e. 0.86; RMSE value as 9.71 µg/m³; P values as 0. Average validation of algorithm show that calculated PM10 strongly correlates with measured PM10, indicating high efficiency of algorithm for the mapping of PM10 concentration during the years 2000 to 2014. Overall results show increase in minimum, maximum and average yearly PM10 concentrations, also presents similar trend over urban area. The rate of urbanization has been evaluated by supervised classification of the Landsat image. Urban sprawl from year 2000 to 2014 results in a high concentration of PM10 in the study area.

Keywords: PM10, landsat, atmospheric reflectance, Gaza strip, urbanization

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Authors: Chang-Hsing Lee, Cheng-Chang Lien, Chin-Chuan Han

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In this paper, an edge-strength guided multiscale retinex (EGMSR) approach will be proposed for color image contrast enhancement. In EGMSR, the pixel-dependent weight associated with each pixel in the single scale retinex output image is computed according to the edge strength around this pixel in order to prevent from over-enhancing the noises contained in the smooth dark/bright regions. Further, by fusing together the enhanced results of EGMSR and adaptive multiscale retinex (AMSR), we can get a natural fused image having high contrast and proper tonal rendition. Experimental results on several low-contrast images have shown that our proposed approach can produce natural and appealing enhanced images.

Keywords: image enhancement, multiscale retinex, image fusion, EGMSR

Procedia PDF Downloads 433

Authors: K. Thamizhmaran, Akshaya Devi Arivazhagan, M. Anitha

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On the case of most important systematic issue that must need to be solved in means of implementing a data transmission algorithm on the source of Mobile adhoc networks (MANETs). That is, how to save mobile nodes energy on meeting the requirements of applications or users as the mobile nodes are with battery limited. On while satisfying the energy saving requirement, hence it is also necessary of need to achieve the quality of service. In case of emergency work, it is necessary to deliver the data on mean time. Achieving quality of service in MANETs is also important on while. In order to achieve this requirement, Hence, we further implement the Energy-Aware routing protocol for system of Mobile adhoc networks were it being proposed, that on which saves the energy as on every node by means of efficiently selecting the mode of energy efficient path in the routing process by means of Enhanced AODV routing protocol.

Keywords: Ad-Hoc networks, MANET, routing, AODV, EAODV

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Authors: Ahmed Atef, Mohamed Alhasheem, Eman Beshr

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In this paper, an enhanced DC microgrid design is proposed using the DAB converter as a conversion unit in order to harvest the maximum power from the PV array. Each connected DAB converter is controlled with an enhanced control strategy. The controller is based on the artificial intelligence (AI) technique to regulate the terminal PV voltage through the phase shift angle of each DAB converter. In this manner, no need for a Maximum Power Point Tracking (MPPT) unit to set the reference of the PV terminal voltage. This strategy overcomes the stability issues of the DC microgrid as the response of converters is superior compared to the conventional strategies. The proposed PV interface system is modelled and simulated using MATLAB/SIMULINK. The simulation results reveal an accurate and fast response of the proposed design in case of irradiance changes.

Keywords: DC microgrid, DAB converter, parallel operation, artificial intelligence, fast response

Procedia PDF Downloads 754

Authors: Hoda A. Abdel Hafez

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Mining big data represents a big challenge nowadays. Many types of research are concerned with mining massive amounts of data and big data streams. Mining big data faces a lot of challenges including scalability, speed, heterogeneity, accuracy, provenance and privacy. In telecommunication industry, mining big data is like a mining for gold; it represents a big opportunity and maximizing the revenue streams in this industry. This paper discusses the characteristics of big data (volume, variety, velocity and veracity), data mining techniques and tools for handling very large data sets, mining big data in telecommunication and the benefits and opportunities gained from them.

Keywords: mining big data, big data, machine learning, telecommunication

Procedia PDF Downloads 374

Authors: Yana Snegireva

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Carbonate reservoirs are known for their heterogeneity, resulting from various geological processes such as diagenesis and fracturing. These complexities may cause great challenges in understanding fluid flow behavior and predicting the production performance of naturally fractured reservoirs. The investigation of carbonate reservoirs is crucial, as many petroleum reservoirs are naturally fractured, which can be difficult due to the complexity of their fracture networks. This can lead to geological uncertainties, which are important for global petroleum reserves. The problem outlines the key challenges in carbonate reservoir modeling, including the accurate representation of fractures and their connectivity, as well as capturing the impact of fractures on fluid flow and production. Traditional reservoir modeling techniques often oversimplify fracture networks, leading to inaccurate predictions. Therefore, there is a need for a modern approach that can capture the complexities of carbonate reservoirs and provide reliable predictions for effective reservoir management and production optimization. The modern approach to carbonate reservoir modeling involves the utilization of the hybrid fracture modeling approach, including the discrete fracture network (DFN) method and implicit fracture network, which offer enhanced accuracy and reliability in characterizing complex fracture systems within these reservoirs. This study focuses on the application of the hybrid method in the Nepsko-Botuobinskaya anticline of the Eastern Siberia field, aiming to prove the appropriateness of this method in these geological conditions. The DFN method is adopted to model the fracture network within the carbonate reservoir. This method considers fractures as discrete entities, capturing their geometry, orientation, and connectivity. But the method has significant disadvantages since the number of fractures in the field can be very high. Due to limitations in the amount of main memory, it is very difficult to represent these fractures explicitly. By integrating data from image logs (formation micro imager), core data, and fracture density logs, a discrete fracture network (DFN) model can be constructed to represent fracture characteristics for hydraulically relevant fractures. The results obtained from the DFN modeling approaches provide valuable insights into the East Siberia field's carbonate reservoir behavior. The DFN model accurately captures the fracture system, allowing for a better understanding of fluid flow pathways, connectivity, and potential production zones. The analysis of simulation results enables the identification of zones of increased fracturing and optimization opportunities for reservoir development with the potential application of enhanced oil recovery techniques, which were considered in further simulations on the dual porosity and dual permeability models. This approach considers fractures as separate, interconnected flow paths within the reservoir matrix, allowing for the characterization of dual-porosity media. The case study of the East Siberia field demonstrates the effectiveness of the hybrid model method in accurately representing fracture systems and predicting reservoir behavior. The findings from this study contribute to improved reservoir management and production optimization in carbonate reservoirs with the use of enhanced and improved oil recovery methods.

Keywords: carbonate reservoir, discrete fracture network, fracture modeling, dual porosity, enhanced oil recovery, implicit fracture model, hybrid fracture model

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Authors: Temesgen Geremew

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This study investigates the evolution of polythiophene nanoparticles (PThNPs) as surface-enhanced Raman spectroscopy (SERS) sensors for Pb²⁺ detection in river water. We analyze the PThNPs' optical, structural, and morphological properties at different stages of their development to understand their SERS performance. Techniques like UV-Vis spectroscopy, Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) are employed for characterization. The SERS sensitivity towards Pb²⁺ is evaluated by monitoring the peak intensity of a specific Raman band upon increasing metal ion concentration. The study aims to elucidate the relationship between the PThNPs' characteristics and their SERS efficiency for Pb²⁺ detection, paving the way for optimizing their design and fabrication for improved sensing performance in real-world environmental monitoring applications.

Keywords: polythiophene, Pb2+, SERS, nanoparticles

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Authors: Abder-Rahman Ali, Adélaïde Albouy-Kissi, Manuel Grand-Brochier, Viviane Ladan-Marcus, Christine Hoeffl, Claude Marcus, Antoine Vacavant, Jean-Yves Boire

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In this paper, we present a new segmentation approach for focal liver lesions in contrast enhanced ultrasound imaging. This approach, based on a two-cluster Fuzzy C-Means methodology, considers type-II fuzzy sets to handle uncertainty due to the image modality (presence of speckle noise, low contrast, etc.), and to calculate the optimum inter-cluster threshold. Fine boundaries are detected by a local recursive merging of ambiguous pixels. The method has been tested on a representative database. Compared to both Otsu and type-I Fuzzy C-Means techniques, the proposed method significantly reduces the segmentation errors.

Keywords: defuzzification, fuzzy clustering, image segmentation, type-II fuzzy sets

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Authors: Yaseen Muhammad, Zhenxia Zhao, Zhangfa Tong

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A key problem with hydrodesulfurization (HDS) process of fuel oils is the application of severe operating conditions. In this study, we proposed the catalytic HDS of dibenzothiophene (DBT) integrated with ionic liquids (ILs) application at mild temperature and pressure over low loaded (0.5 wt.%) Pd promoted Co-Mo@Al₂O₃ and Ni-Mo@Al₂O₃ catalysts. Among the thirteen ILs tested, [BMIM]BF₄, [(CH₃)₄N]Cl, [EMIM]AlCl₄, and [(C₈H₁₇)(C₃H₇)₃P]Br enhanced the catalytic HDS efficiency while the latest ranked the top of activity list as confirmed by DFT studies as well. Experimental results revealed that Pd incorporation greatly enhanced the HDS activity of classical Co or Ni based catalysts. At mild optimized experimental conditions of 1 MPa H₂ pressure, 120 oC, IL:oil ratio of 1:3 and 4 h reaction time, the % DBT conversion (21 %) by Ni-Mo@Al₂O₃ was enhanced to 69 % (over Pd-Ni-Mo@ Al₂O₃) using [(C₈H₁₇) (C₃H₇)₃P]Br. The fresh and spent catalysts were characterized for textural properties using XPS, SEM, EDX, XRD and BET surface area techniques. An overall catalytic HDS activity followed the order of: Pd-Ni-Mo@Al₂O₃ > Pd-Co-Mo@Al₂O₃ > Ni-Mo@Al₂O₃ > Co-Mo@Al₂O₃. [(C₈H₁₇) (C₃H₇)₃P]Br.could be recycled four times with minimal decrease in HDS activity. Reaction products were analyzed by GC-MS which helped in proposing reaction mechanism for the IL coupled HDS process. The present approach attributed to its cost-effective nature, ease of operation with less mechanical requirements in terms of mild operating conditions, and high efficiency could be deemed as an alternative approach for the HDS of DBT on industrial level applications.

Keywords: DFT simulation, GC-MS and reaction mechanism, Ionic liquid coupled HDS of DBT, low Pd loaded catalyst, mild operating condition

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Authors: Anthony Overmars, Sitalakshmi Venkatraman

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This paper presents a method for determining all of the co-prime right angle triangles in the Euclidean field by looking at the intersection of the Pythagorean and Platonic right angle triangles and the corresponding lattice that this produces. The co-prime properties of each lattice point representing a unique right angle triangle are then considered. This paper proposes a conjunction between these two ancient disparaging theorists. This work has wide applications in information security where cryptography involves improved ways of finding tuples of prime numbers for secure communication systems. In particular, this paper has direct impact in enhancing the encryption and decryption algorithms in cryptography.

Keywords: Pythagorean triples, platonic triples, right angle triangles, co-prime numbers, cryptography

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Authors: Ahmed Elgharably, Nivien Nafady

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Arbuscular mycorrhizal fungi (AMF) and plant growth promoting microbes (PGPM) can promote plant growth under saline conditions. This study investigated how AMF and PGPM affected the growth and grain yield of wheat at different soil salinity levels (0, 75 and 150 mM NaCl). AMF colonization percentage, grain yield and dry weights and lengths of shoot and root, N, P K, Na, malondialdehyde, chlorophyll and proline contents and shoot relative permeability were determined. Salinity reduced NPK uptake and malondialdehyde and chlorophyll contents, and increased shoot Na concentration, relative permeability, and proline content, and thus declined plant growth. PGPM inoculation enhanced AMF colonization, P uptake, and K/Na ratio, but alone had no significant effect on plant growth and grain yield. AMF inoculation significantly enhanced NPK uptake, increased chlorophyll content and decreased shoot relative permeability, proline and Na contents, and thus promoted the plant growth. The inoculation of PGPM significantly enhanced the positive effects of AMF in controlling Na uptake and in increasing chlorophyll and NPK contents. Compared to AMF inoculation alone, dual inoculation with AMF and PGPM resulted in approximately 10, 25 and 25% higher grain yield at 0, 75 and 150 mM NaCl, respectively. The results provide that PGPM inoculation can maximize the effects of AMF inoculation in alleviating the deleterious effects of NaCl salts on wheat growth.

Keywords: mycorrhizal fungi, salinity, sodium, wheat

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Authors: Abebe Mulugojam Negash, Yongbin Yu, Ekong Favour, Bekalu Nigus Dawit, Molla Woretaw Teshome, Aynalem Birtukan Yirga

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Breast cancer remains a significant health concern, necessitating advancements in diagnostic methodologies. Addressing this, our paper confronts the notable challenges in breast cancer classification, particularly the imbalance in datasets and the constraints in the accuracy and interpretability of prevailing deep learning approaches. We proposed an attention-based residual neural network (ResNet), which effectively combines the robust features of ResNet with an advanced attention mechanism. Enhanced through strategic data augmentation and positive weight adjustments, this approach specifically targets the issue of data imbalance. The proposed model is tested on the BreakHis dataset and achieved accuracies of 99.00%, 99.04%, 98.67%, and 98.08% in different magnifications (40X, 100X, 200X, and 400X), respectively. We evaluated the performance by using different evaluation metrics such as precision, recall, and F1-Score and made comparisons with other state-of-the-art methods. Our experiments demonstrate that the proposed model outperforms existing approaches, achieving higher accuracy in breast cancer classification.

Keywords: residual neural network, attention mechanism, positive weight, data augmentation

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Authors: Osama Madkhali

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GdAl₃(BO₃)₄ phosphors, incorporating Dy³+ and Dy³+/Eu³+ activators, were successfully synthesized via the gel combustion method. Powder X-ray diffraction (XRD) was utilized to ascertain phase purity and assess the impact of dopant concentration on the crystallographic structure. Photoluminescence (PL) measurements revealed that luminescence properties' intensity and lifetime varied with Dy³+ and Eu³+ ion concentrations. The relationship between luminescence intensity and doping concentration was explored in the context of the energy transfer process between Eu³+ and Dy³+ ions. An increase in Eu³+ co-doping concentrations resulted in a decrease in luminescence lifetime. Energy transfer efficiency was significantly enhanced from 26% to 84% with Eu³+ co-doping, as evidenced by decay curve analysis. These findings position GdAl₃(BO₃)4: Dy³+, Eu³+ phosphors as promising candidates for LED applications in solid-state lighting and displays.

Keywords: GdAl₃(BO₃)₄ phosphors, Dy³+/Eu³+ co-doping, photoluminescence (PL) measurements, luminescence properties, LED applications, solid-state lighting

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Authors: Dharmit Viroja, Prerakkumar Shah, Rajanikant Gajera, Ruchit Shah

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With present scenario of aging oil and gas fields with high water cuts, volatile oil prices and increasing greenhouse gas emission, the need for alleviating such issues has necessitated for oil and gas industry to make the maximum out of available assets, infrastructure and reserves in mother Earth. Study undertaken emphasizes on utilizing Geothermal Energy under specific reservoir conditions for Enhanced oil Recovery (EOR) to boost up production. Allied benefits of this process include mitigation of electricity problem in remote fields and controlled CO-emission. Utilization of this energy for EOR and increasing economic life of field could surely be rewarding. A new way to value oil lands would be considered if geothermal co-production is integrated in the field development program. Temperature profile of co-produced fluid across its journey is a pivotal issue which has been studied. Geo pressured reservoirs resulting from trapped brine under an impermeable bed is also a frontier for exploitation. Hot geothermal fluid is a by-product of large number of oil and gas wells, historically this hot water has been seen as an inconvenience; however, it can be looked at as a useful resource. The production of hot fluids from abandoned and co-production of hot fluids from producing wells has potential to prolong life of oil and gas fields. The study encompasses various factors which are required for use of this technology and application of this process across various phases of oil and gas value chain. Interdisciplinary approach in oil and gas value chain has shown potential for economic production of estimated oil and gas reserves.

Keywords: enhanced oil recovery, geo-pressured reservoirs, geothermal energy, oil and gas value chain

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Authors: Theertha Chandroth

Abstract:

This paper presents a comparative study on how to check JSON (JavaScript Object Notation) data against XML (eXtensible Markup Language) data from a software testing point of view. JSON and XML are widely used data interchange formats, each with its unique syntax and structure. The objective is to explore various techniques and methodologies for validating comparison and integration between JSON data to XML and vice versa. By understanding the process of checking JSON data against XML data, testers, developers and data practitioners can ensure accurate data representation, seamless data interchange, and effective data validation.

Keywords: XML, JSON, data comparison, integration testing, Python, SQL

Procedia PDF Downloads 99

Authors: Gule Teri

Abstract:

The effective validation of analytical methods forms a crucial component of pharmaceutical manufacturing. However, traditional validation techniques can occasionally fail to fully account for inherent variations within datasets, which may result in inconsistent outcomes. This deficiency in validation accuracy is particularly noticeable when quantifying low concentrations of active pharmaceutical ingredients (APIs), excipients, or impurities, introducing a risk to the reliability of the results and, subsequently, the safety and effectiveness of the pharmaceutical products. In response to this challenge, we introduce an enhanced, tolerance-based Design of Experiments (DoE) approach for the validation of analytical methods. This approach distinctly measures variability with reference to tolerance or design margins, enhancing the precision and trustworthiness of the results. This method provides a systematic, statistically grounded validation technique that improves the truthfulness of results. It offers an essential tool for industry professionals aiming to guarantee the accuracy of their measurements, particularly for low-concentration components. By incorporating this innovative method, pharmaceutical manufacturers can substantially advance their validation processes, subsequently improving the overall quality and safety of their products. This paper delves deeper into the development, application, and advantages of this tolerance-based DoE approach and demonstrates its effectiveness using High-Performance Liquid Chromatography (HPLC) data for verification. This paper also discusses the potential implications and future applications of this method in enhancing pharmaceutical manufacturing practices and outcomes.

Keywords: tolerance-based design, design of experiments, analytical method validation, quality control, biopharmaceutical manufacturing

Procedia PDF Downloads 46

Authors: Dechen Tshering Vogel, Johannes T. Heverhagen, Bernard Kiss, Spyridon Arampatzis

Abstract:

In addition to computed tomography (CT), contrast enhanced ultrasound (CEUS), and magnetic resonance imaging (MRI) are being increasingly used for imaging of renal lesions. The aim of this prospective study was to compare the classification of complex cystic renal lesions using the Bosniak classification with CEUS and MRI to CT. Forty-eight patients with 65 cystic renal lesions were included in this study. All participants signed written informed consent. The agreement between the Bosniak classifications of complex renal lesions ( ≥ BII-F) on CEUS and MRI were compared to that of CT and were tested using Cohen’s Kappa. Sensitivity, specificity, positive and negative predictive values (PPV/NPV) and the accuracy of CEUS and MRI compared to CT in the detection of complex renal lesions were calculated. Twenty-nine (45%) out of 65 cystic renal lesions were classified as complex using CT. The agreement between CEUS and CT in the classification of complex cysts was fair (agreement 50.8%, Kappa 0.31), and was excellent between MRI and CT (agreement 93.9%, Kappa 0.88). Compared to CT, MRI had a sensitivity of 96.6%, specificity of 91.7%, a PPV of 54.7%, and an NPV of 54.7% with an accuracy of 63.1%. The corresponding values for CEUS were sensitivity 100.0%, specificity 33.3%, PPV 90.3%, and NPV 97.1% with an accuracy 93.8%. The classification of complex renal cysts based on MRI and CT scans correlated well, and MRI can be used instead of CT for this purpose. CEUS can exclude complex lesions, but due to higher sensitivity, cystic lesions tend to be upgraded. However, it is useful for initial imaging, for follow up of lesions and in those patients with contraindications to CT and MRI.

Keywords: Bosniak classification, computed tomography, contrast enhanced ultrasound, cystic renal lesions, magnetic resonance imaging

Procedia PDF Downloads 118

Authors: Nidal H. Abu-Zahra, Murtatha M. Jamel, Parisa Khoshnoud, Subhashini Gunashekar

Abstract:

Two types of glass fibers having different lengths (1/16" and 1/32") were added into rigid PVC foams to enhance the dimensional stability of extruded rigid Polyvinyl Chloride (PVC) foam at different concentrations (0-20 phr) using a single screw profile extruder. PVC foam-glass fiber composites (PVC-GF) were characterized for their dimensional stability, structural, thermal, and mechanical properties. Experimental results show that the dimensional stability, heat resistance, and storage modulus were enhanced without compromising the tensile and flexural strengths of the composites. Overall, foam composites which were prepared with longer glass fibers exhibit better mechanical and thermal properties than those prepared with shorter glass fibers due to higher interlocking between the fibers and the foam cells, which result in better load distribution in the matrix.

Keywords: polyvinyl chloride, PVC foam, PVC composites, polymer composites, glass fiber composites, reinforced polymers

Procedia PDF Downloads 377