Search results for: building detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7318

Search results for: building detection

3358 Indigenous Patch Clamp Technique: Design of Highly Sensitive Amplifier Circuit for Measuring and Monitoring of Real Time Ultra Low Ionic Current through Cellular Gates

Authors: Moez ul Hassan, Bushra Noman, Sarmad Hameed, Shahab Mehmood, Asma Bashir

Abstract:

The importance of Noble prize winning “Patch Clamp Technique” is well documented. However, Patch Clamp Technique is very expensive and hence hinders research in developing countries. In this paper, detection, processing and recording of ultra low current from induced cells by using transimpedence amplifier is described. The sensitivity of the proposed amplifier is in the range of femto amperes (fA). Capacitive-feedback is used with active load to obtain a 20MΩ transimpedance gain. The challenging task in designing includes achieving adequate performance in gain, noise immunity and stability. The circuit designed by the authors was able to measure current in the rangeof 300fA to 100pA. Adequate performance shown by the amplifier with different input current and outcome result was found to be within the acceptable error range. Results were recorded using LabVIEW 8.5®for further research.

Keywords: drug discovery, ionic current, operational amplifier, patch clamp

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3357 Energy-Efficient Clustering Protocol in Wireless Sensor Networks for Healthcare Monitoring

Authors: Ebrahim Farahmand, Ali Mahani

Abstract:

Wireless sensor networks (WSNs) can facilitate continuous monitoring of patients and increase early detection of emergency conditions and diseases. High density WSNs helps us to accurately monitor a remote environment by intelligently combining the data from the individual nodes. Due to energy capacity limitation of sensors, enhancing the lifetime and the reliability of WSNs are important factors in designing of these networks. The clustering strategies are verified as effective and practical algorithms for reducing energy consumption in WSNs and can tackle WSNs limitations. In this paper, an Energy-efficient weight-based Clustering Protocol (EWCP) is presented. Artificial retina is selected as a case study of WSNs applied in body sensors. Cluster heads’ (CHs) selection is equipped with energy efficient parameters. Moreover, cluster members are selected based on their distance to the selected CHs. Comparing with the other benchmark protocols, the lifetime of EWCP is improved significantly.

Keywords: WSN, healthcare monitoring, weighted based clustering, lifetime

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3356 Impact Assessment of Tropical Cyclone Hudhud on Visakhapatnam, Andhra Pradesh

Authors: Vivek Ganesh

Abstract:

Tropical cyclones are some of the most damaging events. They occur in yearly cycles and affect the coastal population with three dangerous effects: heavy rain, strong wind and storm surge. In order to estimate the area and the population affected by a cyclone, all the three types of physical impacts must be taken into account. Storm surge is an abnormal rise of water above the astronomical tides, generated by strong winds and drop in the atmospheric pressure. The main aim of the study is to identify the impact by comparing three different months data. The technique used here is NDVI classification technique for change detection and other techniques like storm surge modelling for finding the tide height. Current study emphasize on recent very severe cyclonic storm Hud Hud of category 3 hurricane which had developed on 8 October 2014 and hit the coast on 12 October 2014 which caused significant changes on land and coast of Visakhapatnam, Andhra Pradesh. In the present study, we have used Remote Sensing and GIS tools for investigating and quantifying the changes in vegetation and settlement.

Keywords: inundation map, NDVI map, storm tide map, track map

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3355 An Alternative Approach for Assessing the Impact of Cutting Conditions on Surface Roughness Using Single Decision Tree

Authors: S. Ghorbani, N. I. Polushin

Abstract:

In this study, an approach to identify factors affecting on surface roughness in a machining process is presented. This study is based on 81 data about surface roughness over a wide range of cutting tools (conventional, cutting tool with holes, cutting tool with composite material), workpiece materials (AISI 1045 Steel, AA2024 aluminum alloy, A48-class30 gray cast iron), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev), depth of cut (0.05-0.15 mm) and tool overhang (41-65 mm). A single decision tree (SDT) analysis was done to identify factors for predicting a model of surface roughness, and the CART algorithm was employed for building and evaluating regression tree. Results show that a single decision tree is better than traditional regression models with higher rate and forecast accuracy and strong value.

Keywords: cutting condition, surface roughness, decision tree, CART algorithm

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3354 Insight on Passive Design for Energy Efficiency in Commercial Building for Hot and Humid Climate

Authors: Aravind J.

Abstract:

Passive design can be referred to a way of designing buildings that takes advantage of the prevailing climate and natural energy resources. Which will be a key to reduce the increasing energy usage in commercial buildings. Most of the small scale commercial buildings made are merely a thermal mass inbuilt with active systems to bring lively conditions. By bringing the passive design strategies for energy efficiency in commercial buildings will reduce the usage of active systems. Thus the energy usage can be controlled through analysis of daylighting and improved living conditions in the indoor spaces by using passive techniques. And comparative study on different passive design systems and conventional methods will be approached for commercial buildings in hot and humid region. Possible effects of existing risks implied with solution for those problems is also a part of the paper. The result will be carried on with the design programme to prove the workability of the strategies.

Keywords: passive design, energy efficiency, commercial buildings, hot and humid climate

Procedia PDF Downloads 362
3353 Manufacturing Commercial Bricks with Construction and Demolition Wastes

Authors: Mustafa Kara, Yasemin Kilic, Bahattin Murat Demir, Ümit Ustaoglu, Cavit Unal

Abstract:

This paper reports utilization of different kind of construction and demolition wastes (C&D) in the production of bricks at industrial scale. Plastered brick waste and tile wastes were collected from ISTAÇ Co. Compost and Recovery Plant, Istanbul, Turkey. Plastered brick waste and tile waste are mixed with brick clay in the proportion of 0-30% and fired at 900ºC. The physical and mechanical properties of the produced bricks were determined and evaluated according to IKIZLER Brick Company Production values, Brick Industry Association (BIA) and Turkish Standards (TS). The resulted showed that plastered brick waste and tile waste can be used to produce good quality brick for various engineering applications in construction and building. The replacement of brick clay by plastered brick waste and tile waste at the levels of 30% has good effects on the compressive strength of the bricks.

Keywords: commercial brick, construction and demolition waste, manufacturing, recycling

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3352 Determination of Weathering at Kilistra Ancient City by Using Non-Destructive Techniques, Central Anatolia, Turkey

Authors: İsmail İnce, Osman Günaydin, Fatma Özer

Abstract:

Stones used in the construction of historical structures are exposed to various direct or indirect atmospheric effects depending on climatic conditions. Building stones deteriorate partially or fully as a result of this exposure. The historic structures are important symbols of any cultural heritage. Therefore, it is important to protect and restore these historical structures. The aim of this study is to determine the weathering conditions at the Kilistra ancient city. It is located in the southwest of the Konya city, Central Anatolia, and was built by carving into pyroclastic rocks during the Byzantine Era. For this purpose, the petrographic and mechanical properties of the pyroclastic rocks were determined. In the assessment of weathering of structures in the ancient city, in-situ non-destructive testing (i.e., Schmidt hardness rebound value, relative humidity measurement) methods were applied.

Keywords: cultural heritage, Kilistra ancient city, non-destructive techniques, weathering

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3351 Energy Intensity of a Historical Downtown: Estimating the Energy Demand of a Budapest District

Authors: Viktória Sugár, Attila Talamon, András Horkai, Michihiro Kita

Abstract:

The dense urban fabric of the 7th district of Budapest -known as the former Jewish Quarter-, contains mainly historical style, multi-story tenement houses with courtyards. The high population density and the unsatisfactory energetic state of the buildings result high energy consumption. As a preliminary survey of a complex rehabilitation plan, the authors aim to determine the energy demand of the area. The energy demand was calculated by analyzing the structure and the energy consumption of each building by using Geographic Information System (GIS) methods. The carbon dioxide emission was also calculated, to assess the potential of reducing the present state value by complex structural and energetic rehabilitation. As a main focus of the survey, an energy intensity map has been created about the area.

Keywords: CO₂, energy intensity map, geographic information system (GIS), Hungary, Jewish quarter, rehabilitation

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3350 Improving Physical, Social, and Mental Health Outcomes for People Living with an Intellectual Disability through Cycling

Authors: Sarah Faulkner, Patrick Faulkner, Caroline Ellison

Abstract:

Improved mental and physical health, community connection, and increased life satisfaction has been strongly associated with bike riding for those with and without a disability. However, much evidence suggests that people living with a disability face increased barriers to engaging in cycling compared to members of the general population. People with an intellectual disability often live more sedentary and socially isolated lives that negatively impact their mental and physical health, as well as life satisfaction. This paper is based on preliminary findings from a three-year intervention cycling project funded by the South Australian Government. The cycling project was developed in partnership with community stakeholders that provided weekly instruction, training, and support to individuals living with intellectual disabilities to increase their capacity in cycling. This project aimed to support people living with intellectual disabilities to foster and facilitate improved physical and mental health, confidence, and independence and enhance social networking through their engagement in community cycling. The program applied principles of social role valorisation (SRV) theory as its guiding framework. Preliminary data collected is based on qualitative interviews with over 50 program participants, results from two participant wellness questionnaires, as well as a perceptually regulated exercise test administered throughout the project implementation. Preliminary findings are further supplemented with ethnographic analyses by the researchers who took a phenology of life experience approach. Preliminary findings of the program suggest a variety of social motivations behind participants' desire to learn cycling that acknowledges previous barriers to engagement and cycling’s role to address feelings of loneliness and social isolation. Meaningful health benefits can be achieved as demonstrated by increases in predicted V02 max measures, suggesting that physical intervention can not only improve physical health outcomes but also provide a variety of other social benefits. Initial engagement in the project has demonstrated an increase in participants' sense of confidence, well-being, and physical fitness. Implementation of the project in partnership with a variety of community stakeholders has identified a number of critical factors and processes necessary for future service replication, sustainability, and success. Findings from this intervention study contribute to the development of a knowledge base on how best to support individuals living with an intellectual disability to partake in bike riding and increase positive outcomes associated with their capacity building, social interaction, increased physical activity, physical health, and mental well-being. The initial findings of this study provide critical academic insights into the social and physical benefits of cycling for people living with a disability, as well as practical advice for future human service applications.

Keywords: cycling, disability, social inclusion, capacity building

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3349 Combination of Electrochemical Impedance Spectroscopy and Electromembrane Extraction for the Determination of Zolpidem Using Modified Screen-Printed Electrode

Authors: Ali Naeemy, Mir Ghasem Hoseini

Abstract:

In this study, for the first time, an analytical method developed and validated by combining electrochemical impedance spectroscopy and electromembrane extraction (EIS-EME) by Vulcan/poly pyrrole nanocomposite modified screen-printed electrode (PPY–VU/SPE) for accurately quantifying zolpidem. EME parameters optimized, including solvent composition, voltage, pH adjustments and extraction time. Zolpidem was transferred from a donor solution (pH 5) to an acceptor solution (pH 13) using a hollow fiber in 1-octanol as a membrane, driven by a 60 V voltage for 25 minutes, ensuring precise and selective extraction. In comparison with SPE, VU/SPE and PPY/SPE, the PPY–VU/SPE was much more efficient for ZP oxidation. Calibration curves with good linearity were obtained in the concentration range of 2-75 µmol L-1 using the EIS-EME with the detection limit of 0.5 µmol L-1 . Finally, the EIS-EME by using the PPY– VU/SPE was successfully used to determine ZP in tablet dosage form, urine and plasma samples. Keywords: Electrochemical impedance spectroscopy, Electromembrane extraction, Zolpidem, Vulcan, poly pyrrole, Screen printed electrode

Keywords: electrochemical impedance spectroscopy, electromembrane extraction, screen printed electrode, zolpidem

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3348 Investigation on Morphologies, Forming Mechanism, Photocatalytic and Electronic Properties of Co-Zn Ferrite Nanostructure Grown on the Reduced Graphene Oxide Support

Authors: Qinglei Liu, Ali Charkhesht, Tiva Sharifi, Ashkan Bahadoran

Abstract:

Graphene sheets are promising nanoscale building blocks as a support material for the dispersion of nanoparticles. In this work, a solvothermal method employed to directly grow Co1-xZnxFe2O4 ferrite nanospheres on graphene oxide support that is subsequently reduced to graphene. The samples morphology, structure and crystallography were investigated using field-emission scanning electron microscopy (FE-SEM) and powder X-ray diffraction (XRD). The influences of the Zn2+ content on photocatalytic activity, electrical conductivity and magnetic property of the samples are also investigated. The results showed that Co1-x Znx Fe2 O4 nanoparticles are dispersed on graphene sheets and obtained nanocomposites are soft magnetic materials. In addition the samples showed excellent photocatalytic activity under visible light irradiation.

Keywords: reduced graphene oxide, ferrite, magnetic nanocomposite, photocatalytic activity, solvothermal method

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3347 A Context-Centric Chatbot for Cryptocurrency Using the Bidirectional Encoder Representations from Transformers Neural Networks

Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li

Abstract:

Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.

Keywords: bidirectional encoder representations from transformers, BERT, chatbot, cryptocurrency, deep learning

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3346 A Distinct Reversed-Phase High-Performance Liquid Chromatography Method for Simultaneous Quantification of Evogliptin Tartrate and Metformin HCl in Pharmaceutical Dosage Forms

Authors: Rajeshkumar Kanubhai Patel, Neha Sudhirkumar Mochi

Abstract:

A simple and accurate stability-indicating, reversed-phase high-performance liquid chromatography (RP-HPLC) method was developed and validated for the simultaneous quantitation of Evogliptin tartrate and Metformin HCl in pharmaceutical dosage forms, following ICH guidelines. Forced degradation was performed under various stress conditions including acid, base, oxidation, thermal, and photodegradation. The method utilized an Eclipse C18 column (250 mm × 4.6 mm, 5 µm) with a mobile phase of 5 mM 1-hexane sulfonic acid sodium salt in water and 0.2% v/v TEA (45:55 %v/v), adjusted to pH 3.0 with OPA, at a flow rate of 1.0 mL/min. Detection at 254.4 nm using a PDA detector showed good resolution of degradation products and both drugs. Linearity was observed within 1-5 µg/mL for Evogliptin tartrate and 100-500 µg/mL for Metformin HCl, with % recovery between 99-100% and precision within acceptable limits (%RSD < 2%). The method proved to be specific, precise, accurate, and robust for routine analysis of these drugs.

Keywords: stability indicating RP-HPLC, evogliptin tartrate, metformin HCl, validation

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3345 The Fabrication of Scintillator Column by Hydraulic Pressure Injection Method

Authors: Chien Chon Chen, Chun Mei Chu, Chuan Ju Wang, Chih Yuan Chen, Ker Jer Huang

Abstract:

Cesiumiodide with Na doping (CsI(Na)) solution or melt is easily forming three- dimension dendrites on the free surface. The defects or bobbles form inside the CsI(Na) during the solution or melt solidification. The defects or bobbles can further effect the x-ray path in the CsI(Na) crystal and decrease the scintillation characteristics of CsI(Na). In order to enhance the CsI(Na) scintillated property we made single crystal of CsI(Na) column in the anodic aluminum oxide (AAO) template by hydraulic pressure injection method. It is interesting that when CsI(Na) melt is confined in the small AAO channels, the column grow as stable single column without any dendrites. The high aspect ratio (100~10000) of AAO and nano to sub-micron channel structure which is a suitable template for single of crystal CsI(Na) formation. In this work, a new low-cost approach to fabricate scintillator crystals using anodic aluminum oxide (AAO) rather than Si is reported, which can produce scintillator crystals with a wide range of controllable size to optimize their performance in X-ray detection.

Keywords: cesiumiodide, AAO, scintillator, crystal, X-ray

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3344 Gamification to Enhance Learning Using Gagne's Learning Model

Authors: M. L. McLain, R. Sreelakshmi, Abhishek, Rajeshwaran, Bhavani Rao, Kamal Bijlani, R. Jayakrishnan

Abstract:

Technology enhanced learning has brought drastic changes in the field of education in the modern world. In this study we explore a novel way to improve how high school students learn by building a serious game that uses a pedagogical model developed by Robert Gagne. By integrating serious game with principles of Gagne’s learning model can provide engaging and meaningful instructions to students. The game developed in this study is a waste sorting game that can easily and succinctly demonstrate the principles of this learning model. All the tasks in the game that the player has to accomplish correspond to Gagne’s “Nine Events of Learning”. A quiz is incorporated in order to get data on the progress made by the player in understanding the concept and as well as to assess them. Additionally, an experimental study was conducted which demonstrates that game based learning using Gagne’s event is more effective than a traditional classroom setup.

Keywords: game based learning, sorting and recycling of waste, Gagne’s learning model, e-Learning, technology enhanced learning

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3343 Eco-Infrastructures: A Multidimensional System Approach for Urban Ecology

Authors: T. A. Mona M. Salem, Ali F. Bakr

Abstract:

Given the potential devastation associated with future climate change related disasters, it is vital to change the way we build and manage our cities, through new strategies to reconfigure them and their infrastructures in ways that help secure their reproduction. This leads to a kaleidoscopic view of the city that recognizes the interrelationships of energy, water, transportation, and solid waste. These interrelationships apply across sectors and with respect to the built form of the city. The paper aims at a long-term climate resilience of cities and their critical infrastructures, and sets out an argument for including an eco-infrastructure-based approach in strategies to address climate change. As these ecosystems have a critical role to play in building resilience and reducing vulnerabilities in cities, communities and economies at risk, the enhanced protection and management of ecosystems, biological resources and habitats can mitigate impacts and contribute to solutions as nations and cities strive to adapt to climate change.

Keywords: ecology, ecosystem, infrastructure, climate change, urban

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3342 Damage Localization of Deterministic-Stochastic Systems

Authors: Yen-Po Wang, Ming-Chih Huang, Ming-Lian Chang

Abstract:

A scheme integrated with deterministic–stochastic subspace system identification and the method of damage localization vector is proposed in this study for damage detection of structures based on seismic response data. A series of shaking table tests using a five-storey steel frame has been conducted in National Center for Research on Earthquake Engineering (NCREE), Taiwan. Damage condition is simulated by reducing the cross-sectional area of some of the columns at the bottom. Both single and combinations of multiple damage conditions at various locations have been considered. In the system identification analysis, either full or partial observation conditions have been taken into account. It has been shown that the damaged stories can be identified from global responses of the structure to earthquakes if sufficiently observed. In addition to detecting damage(s) with respect to the intact structure, identification of new or extended damages of the as-damaged (ill-conditioned) counterpart has also been studied. The proposed scheme proves to be effective.

Keywords: damage locating vectors, deterministic-stochastic subspace system, shaking table tests, system identification

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3341 Inverse Problem Method for Microwave Intrabody Medical Imaging

Authors: J. Chamorro-Servent, S. Tassani, M. A. Gonzalez-Ballester, L. J. Roca, J. Romeu, O. Camara

Abstract:

Electromagnetic and microwave imaging (MWI) have been used in medical imaging in the last years, being the most common applications of breast cancer and stroke detection or monitoring. In those applications, the subject or zone to observe is surrounded by a number of antennas, and the Nyquist criterium can be satisfied. Additionally, the space between the antennas (transmitting and receiving the electromagnetic fields) and the zone to study can be prepared in a homogeneous scenario. However, this may differ in other cases as could be intracardiac catheters, stomach monitoring devices, pelvic organ systems, liver ablation monitoring devices, or uterine fibroids’ ablation systems. In this work, we analyzed different MWI algorithms to find the most suitable method for dealing with an intrabody scenario. Due to the space limitations usually confronted on those applications, the device would have a cylindrical configuration of a maximum of eight transmitters and eight receiver antennas. This together with the positioning of the supposed device inside a body tract impose additional constraints in order to choose a reconstruction method; for instance, it inhabitants the use of well-known algorithms such as filtered backpropagation for diffraction tomography (due to the unusual configuration with probes enclosed by the imaging region). Finally, the difficulty of simulating a realistic non-homogeneous background inside the body (due to the incomplete knowledge of the dielectric properties of other tissues between the antennas’ position and the zone to observe), also prevents the use of Born and Rytov algorithms due to their limitations with a heterogeneous background. Instead, we decided to use a time-reversed algorithm (mostly used in geophysics) due to its characteristics of ignoring heterogeneities in the background medium, and of focusing its generated field onto the scatters. Therefore, a 2D time-reversed finite difference time domain was developed based on the time-reversed approach for microwave breast cancer detection. Simultaneously an in-silico testbed was also developed to compare ground-truth dielectric properties with corresponding microwave imaging reconstruction. Forward and inverse problems were computed varying: the frequency used related to a small zone to observe (7, 7.5 and 8 GHz); a small polyp diameter (5, 7 and 10 mm); two polyp positions with respect to the closest antenna (aligned or disaligned); and the (transmitters-to-receivers) antenna combination used for the reconstruction (1-1, 8-1, 8-8 or 8-3). Results indicate that when using the existent time-reversed method for breast cancer here for the different combinations of transmitters and receivers, we found false positives due to the high degrees of freedom and unusual configuration (and the possible violation of Nyquist criterium). Those false positives founded in 8-1 and 8-8 combinations, highly reduced with the 1-1 and 8-3 combination, being the 8-3 configuration de most suitable (three neighboring receivers at each time). The 8-3 configuration creates a region-of-interest reduced problem, decreasing the ill-posedness of the inverse problem. To conclude, the proposed algorithm solves the main limitations of the described intrabody application, successfully detecting the angular position of targets inside the body tract.

Keywords: FDTD, time-reversed, medical imaging, microwave imaging

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3340 Optimization Techniques for Microwave Structures

Authors: Malika Ourabia

Abstract:

A new and efficient method is presented for the analysis of arbitrarily shaped discontinuities. The discontinuities is characterized using a hybrid spectral/numerical technique. This structure presents an arbitrary number of ports, each one with different orientation and dimensions. This article presents a hybrid method based on multimode contour integral and mode matching techniques. The process is based on segmentation and dividing the structure into key building blocks. We use the multimode contour integral method to analyze the blocks including irregular shape discontinuities. Finally, the multimode scattering matrix of the whole structure can be found by cascading the blocks. Therefore, the new method is suitable for analysis of a wide range of waveguide problems. Therefore, the present approach can be applied easily to the analysis of any multiport junctions and cascade blocks. The accuracy of the method is validated comparing with results for several complex problems found in the literature. CPU times are also included to show the efficiency of the new method proposed.

Keywords: segmentation, s parameters, simulation, optimization

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3339 Evaluation of P16, Human Papillomavirus Capsid Protein L1 and Ki67 in Cervical Intraepithelial Lesions: Potential Utility in Diagnosis and Prognosis

Authors: Hanan Alsaeid Alshenawy

Abstract:

Background: Cervical dysplasia, which is potentially precancerous, has increased in young women. Detection of cervical is important for reducing morbidity and mortality in cervical cancer. This study analyzes the immunohistochemical expression of p16, HPV L1 capsid protein and Ki67 in cervical intraepithelial lesions and correlates them with lesion grade to develop a set of markers for diagnosis and detect the prognosis of cervical cancer precursors. Methods: 75 specimens were analyzed including 15 cases CIN 1, 28 CIN 2, 20 CIN 3, and 12 cervical squamous carcinoma, besides 10 normal cervical tissues. They were stained for p16, HPV L1 and Ki-67. Sensitivity, specificity, predictive values and accuracy were evaluated for each marker. Results: p16 expression increased during the progression from CIN 1 to carcinoma. HPV L1 positivity was detected in CIN 2 and decreased gradually as the CIN grade increased but disappear in carcinoma. Strong Ki-67 expression was observed with high grades CIN and carcinoma. p16, HPV L1 and Ki67 were sensitive but with variable specificity in detecting CIN lesions. Conclusions: p16, HPV L1 and Ki67 are useful set of markers in establishing the risk of high-grade CIN. They complete each other to reach accurate diagnosis and prognosis.

Keywords: p16, HPV L1, Ki67, CIN, cervical carcinoma

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3338 Enzyme Linked Immuno Sorbent Assay Based Detection of Aflatoxin M1 and Ochratoxin A in Raw Milk in Punjab, India

Authors: Pallavi Moudgil, J. S. Bedi, R. S. Aulakh, J. P. S. Gill

Abstract:

Mycotoxins in milk are of major public health concern. The present study was envisaged with an aim to monitor the occurrence of aflatoxin M1 and ochratoxin A in raw milk samples collected from individual animals from dairy farms located in Punjab (India). A total of 168 raw milk samples were collected and analysed using competitive ELISA kits. Out of these, 9 (5.4%) samples were found positive for aflatoxin M1 with the mean concentration of 0.006-0.13 ng/ml and 2 (1.2%) samples exceeded the established maximum residue limit of 0.05 ng/ml established by the European Union. For ochratoxin A, 2 (0.1%) samples were found positive with the mean concentration of 0.61-0.83 ng/ml with both the samples below the established maximum residue limit of 2 ng/ml. The results showed that the milk of dairy cattle is safe with respect to ochratoxin A contamination but occurrence of aflatoxin M1 above maximum residue limit suggested that feed contaminated with mycotoxins might have been offered to dairy cattle that can pose serious health risks to consumers.

Keywords: Aflatoxin M1, health risks, maximum residue limit, milk, Ochratoxin A

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3337 A Diagnostic Challenge of Drug Resistant Childhood Tuberculosis in Developing World

Authors: Warda Fatima, Hasnain Javed

Abstract:

The emerging trend of Drug resistance in childhood Tuberculosis is increasing worldwide and now becoming a priority challenge for National TB Control Programs of the world. Childhood TB accounts for 10-15% of total TB burden across the globe and same proportion is quantified in case of drug resistant TB. One third population suffering from MDR TB dies annually because of non-diagnosis and unavailability of appropriate treatment. However, true Childhood MDR TB cannot be estimated due to non-confirmation. Diagnosis of Pediatric TB by sputum Smear Microscopy and Culture inoculation are limited due to paucibacillary nature and difficulties in obtaining adequate sputum specimens. Diagnosis becomes more difficult when it comes to HIV infected child. New molecular advancements for early case detection of TB and MDR TB in adults have not been endorsed in children. Multi centered trials are needed to design better diagnostic approaches and efficient and safer treatments for DR TB in high burden countries. The aim of the present study is to sketch out the current situation of the childhood Drug resistant TB especially in the developing world and to highlight the classic and novel methods that are to be implemented in high-burden resource-limited locations.

Keywords: drug resistant TB, childhood, diagnosis, novel methods

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3336 Coarse-Graining in Micromagnetic Simulations of Magnetic Hyperthermia

Authors: Razyeh Behbahani, Martin L. Plumer, Ivan Saika-Voivod

Abstract:

Micromagnetic simulations based on the stochastic Landau-Lifshitz-Gilbert equation are used to calculate dynamic magnetic hysteresis loops relevant to magnetic hyperthermia applications. With the goal to effectively simulate room-temperature loops for large iron-oxide based systems at relatively slow sweep rates on the order of 1 Oe/ns or less, a coarse-graining scheme is proposed and tested. The scheme is derived from a previously developed renormalization-group approach. Loops associated with nanorods, used as building blocks for larger nanoparticles that were employed in preclinical trials (Dennis et al., 2009 Nanotechnology 20 395103), serve as the model test system. The scaling algorithm is shown to produce nearly identical loops over several decades in the model grain sizes. Sweep-rate scaling involving the damping constant alpha is also demonstrated.

Keywords: coarse-graining, hyperthermia, hysteresis loops, micromagnetic simulations

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3335 Generating Swarm Satellite Data Using Long Short-Term Memory and Generative Adversarial Networks for the Detection of Seismic Precursors

Authors: Yaxin Bi

Abstract:

Accurate prediction and understanding of the evolution mechanisms of earthquakes remain challenging in the fields of geology, geophysics, and seismology. This study leverages Long Short-Term Memory (LSTM) networks and Generative Adversarial Networks (GANs), a generative model tailored to time-series data, for generating synthetic time series data based on Swarm satellite data, which will be used for detecting seismic anomalies. LSTMs demonstrated commendable predictive performance in generating synthetic data across multiple countries. In contrast, the GAN models struggled to generate synthetic data, often producing non-informative values, although they were able to capture the data distribution of the time series. These findings highlight both the promise and challenges associated with applying deep learning techniques to generate synthetic data, underscoring the potential of deep learning in generating synthetic electromagnetic satellite data.

Keywords: LSTM, GAN, earthquake, synthetic data, generative AI, seismic precursors

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3334 The Impact of Artificial Intelligence on the Behavior of Children and Autism

Authors: Sara Fayez Fawzy Mikhael

Abstract:

Inclusive education services for students with Autism remains in its early developmental stages in Thailand. Despite many more children with autism are attending schools since the Thai government introduced the Education Provision for People with Disabilities Act in 2008, the services students with autism and their families receive are generally lacking. This quantitative study used Attitude and Preparedness to Teach Students with Autism Scale (APTSAS) to investigate 110 primary school teachers’ attitude and preparedness to teach students with autism in the general education classroom. Descriptive statistical analysis of the data found that student behavior was the most significant factor in building teachers’ negative attitudes students with autism. The majority of teachers also indicated that their pre-service education did not prepare them to meet the learning needs of children with autism in particular, those who are non-verbal. The study is significant and provides direction for enhancing teacher education for inclusivity in Thailand.

Keywords: attitude, autism, teachers, thailandsports activates, movement skills, motor skills

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3333 Modelling and Simulation of Single Mode Optical Fiber Directional Coupler for Medical Application

Authors: Shilpa Kulkarni, Sujata Patrikar

Abstract:

A single-mode fiber directional coupler is modeled and simulated for its application in medical field. Various fiber devices based on evanescent field absorption, interferometry, couplers, resonators, tip coated fibers, etc, have been developed so far, suitable for medical application. This work focuses on the possibility of sensing by single mode fiber directional coupler. In the preset work, a fiber directional coupler is modeled to detect the changes taking place in the surrounding medium optoelectronically. In this work, waveguiding characteristics of the fiber are studied in depth. The sensor is modeled and simulated by finding photocurrent, sensitivity and detection limit by varying various parameters of the directional coupler. The device is optimized for the best possible output. It is found that the directional coupler shows measurable photocurrents and good sensitivity with coupling length in micrometers. It is thus a miniature device, hence, suitable for medical applications.

Keywords: single mode fiber directional coupler, modeling and simulation of fiber directional coupler sensor, biomolecular sensing, medical sensor device

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3332 Analysis of Automotive Sensor for Engine Knock System

Authors: Miroslav Gutten, Jozef Jurcik, Daniel Korenciak, Milan Sebok, Matej Kuceraa

Abstract:

This paper deals with the phenomenon of the undesirable detonation combustion in internal combustion engines. A control unit of the engine monitors these detonations using piezoelectric knock sensors. With the control of these sensors the detonations can be objectively measured just outside the car. If this component provides small amplitude of the output voltage it could happen that there would have been in the areas of the engine ignition combustion. The paper deals with the design of a simple device for the detection of this disorder. A construction of the testing device for the knock sensor suitable for diagnostics of knock combustion in internal combustion engines will be presented. The output signal of presented sensor will be described by Bessel functions. Using the first voltage extremes on the characteristics it is possible to create a reference for the evaluation of the polynomial residue. It should be taken into account that the velocity of sound in air is 330 m/s. This sound impinges on the walls of the combustion chamber and is detected by the sensor. The resonant frequency of the clicking of the motor is usually in the range from 5 kHz to 15 kHz. The sensor worked in the field to 37 kHz, which shall be taken into account on an own sensor resonance.

Keywords: diagnostics, knock sensor, measurement, testing device

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3331 Early Detection of Kidney Failure by Using a Distinct Technique for Sweat Analysis

Authors: Saba. T. Suliman, Alaa. H. Osman, Sara. T. Ahmed, Zeinab. A. Mustafa, Akram. I. Omara, Banazier. A. Ibraheem

Abstract:

Diagnosis by sweat is one of the emerging methods whereby sweat can identify many diseases in the human body. Sweat contains many elements that help in the diagnostic process. In this research, we analyzed sweat samples by using a Colorimeter device to identify the disease of kidney failure in its various stages. This analysis is a non-invasive method where the sample is collected from outside the body, and then this sample is analyzed. Urea refers to the disease of kidney failure when its quantity is high in the blood and then in the sweat, and by experience, we found that the amount of urea for males differs from its quantity for females, where there is a noticeable increase for males in normal and pathological cases. In this research, we took many samples from a normal group that does not suffer from renal failure and another who suffers from the disease to compare the percentage of urea, and after analysis, we found that the urea percentage is high in people with kidney failure disease. with an accuracy of results of 85%.

Keywords: sweat analysis, kidney failure, urea, non-invasive, eccrine glands, mineral composition, sweat test

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3330 Multiclass Analysis of Pharmaceuticals in Fish and Shrimp Tissues by High-Performance Liquid Chromatography-Tandem Mass Spectrometry

Authors: Reza Pashaei, Reda Dzingelevičienė

Abstract:

An efficient, reliable, and sensitive multiclass analytical method has been expanded to simultaneously determine 15 human pharmaceutical residues in fish and shrimp tissue samples by ultra-high-performance liquid chromatography-tandem mass spectrometry. The investigated compounds comprise ten classes, namely analgesic, antibacterial, anticonvulsant, cardiovascular, fluoroquinolones, macrolides, nonsteroidal anti-inflammatory, penicillins, stimulant, and sulfonamide. A simple liquid extraction procedure based on 0.1% formic acid in methanol was developed. Chromatographic conditions were optimized, and mobile phase namely 0.1 % ammonium acetate (A), and acetonitrile (B): 0 – 2 min, 15% B; 2 – 5 min, linear to 95% B; 5 – 10 min, 95% B; and 10 – 12 min was obtained. Limits of detection and quantification ranged from 0.017 to 1.371 μg/kg and 0.051 to 4.113 μg/kg, respectively. Finally, amoxicillin, azithromycin, caffeine, carbamazepine, ciprofloxacin, clarithromycin, diclofenac, erythromycin, furosemide, ibuprofen, ketoprofen, naproxen, sulfamethoxazole, tetracycline, and triclosan were quantifiable in fish and shrimp samples.

Keywords: fish, liquid chromatography, mass spectrometry, pharmaceuticals, shrimp, solid-phase extraction

Procedia PDF Downloads 254
3329 Modern Machine Learning Conniptions for Automatic Speech Recognition

Authors: S. Jagadeesh Kumar

Abstract:

This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

Procedia PDF Downloads 437