Search results for: dynamic network flow

Authors: Muhammad Umer, Aishwariya Giri, Umaiyma Rakha

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Mimicked from the humpback whale flippers, the application of tubercle technology is seen to be particularly advantageous at high angles of attack. This particular advantage is of paramount importance when it comes to structures producing lift at high angles of attack. This characteristic of the technology makes it ideal for horizontal stabilizers and selecting the same as the subject of study to identify and exploit the advantage highlighted by researchers on airfoils, this project aims in establishing a foundation for the application of the bio-mimicked technology on an existing aircraft. Using a baseline and 2 tubercle configuration integrated models, the project targets to achieve the twin aim of highlighting the possibility and merits over the base model and also choosing the right configuration in providing the best characteristic suitable for high angles of attack. To facilitate this study, the required models are generated using Solidworks followed by trials in a virtual aerodynamic environment using Fluent in Ansys for resolving the project objectives. Following a structured plan, the aim is to initially identify the advantages mathematically and then selecting the optimal configuration, simulate the end configuration at angles mimicking the actual operation envelope for the particular structure. Upon simulating the baseline configuration at various angles of attack, the stall angle was determined to be 22 degrees. Thus, the tubercle configurations will be simulated and compared at 4 different angles of attacks: 0, 10, 20, and 24. Further, after providing the optimum configuration of horizontal stabilizers, this study aims at the integration of aircraft structure so that the results better imply the end deliverables of real life application. This draws the project scope closer at this point into longitudinal static stability considerations and improvements in the manoeuvrability characteristics. The objective of the study is to achieve a complete overview ready for real life application with marked benefits obtainable from bio morphing of the tubercle technology.

Keywords: flow simulation, horizontal stabilizer, stability enhancement, tubercle

Procedia PDF Downloads 305

Authors: Chih-Ping Chang

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Different from traditional objective evidence, social media evidence has its own characteristics with easily tampering, recoverability, and cannot be read without using other devices (such as a computer). Simply taking a screenshot from social network sites must be questioned its original identity. When the police search and seizure digital information, a common way they use is to directly print out digital data obtained and ask the signature of the parties at the presence, without taking original digital data back. In addition to the issue on its original identity, this conduct to obtain evidence may have another two results. First, it will easily allege that is tampering evidence because the police wanted to frame the suspect and falsified evidence. Second, it is not easy to discovery hidden information. The core evidence associated with crime may not appear in the contents of files. Through discovery the original file, data related to the file, such as the original producer, creation time, modification date, and even GPS location display can be revealed from hidden information. Therefore, how to show this kind of evidence in the courtroom will be arguably the most important task for ruling social media evidence. This article, first, will introduce forensic software, like EnCase, TCT, FTK, and analyze their function to prove the identity with another digital data. Then turning back to the court, the second part of this article will discuss legal standard for authentication of social media evidence and application of that forensic software in the courtroom. As the conclusion, this article will provide a rethinking, that is, what kind of authenticity is this rule of evidence chase for. Does legal system automatically operate the transcription of scientific knowledge? Or furthermore, it wants to better render justice, not only under scientific fact, but through multivariate debating.

Keywords: federal rule of evidence, internet forensic, printouts as evidence, social media evidence, United States v. Vayner

Procedia PDF Downloads 278

Authors: Babar Rasheed

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The organizations are in continuous effort to increase their yield and to retain their associates, employees. Technology is considered an integral part of attaining apposite work practices, work environment, and employee engagement. Unconsciously, these advanced practices like work from home, personalized intra-network are disturbing employee work-life balance which ultimately increases psychological pressure on employees. The smart work practice is to develop business models and organizational practices with enhanced employee engagement, minimum trouncing of organization resources with persistent revenue and positive addition in global societies. Need of smart work practices comes from increasing employee turnover rate, global economic recession, unnecessary job pressure, increasing contingent workforce and advancement in technologies. Current practices are not enough elastic to tackle global changing work environment and organizational competitions. Current practices are causing many reciprocal problems among employee and organization mechanically. There is conscious understanding among business sectors smart work practices that will deal with new century challenges with addressing the concerns of relevant issues. It is aimed in this paper to endorse customized and smart work practice tools along knowledge framework to manage the growing concerns of employee engagement, use of technology, orgaization concerns and challenges for the business. This includes a Smart Management Information System to address necessary concerns of employees and combine with a framework to extract the best possible ways to allocate companies resources and re-align only required efforts to adopt the best possible strategy for controlling potential risks.

Keywords: employees engagement, management information system, psychological pressure, current and future HR practices

Procedia PDF Downloads 173

Authors: Hala S. Mekawy

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Affordable housing delivery for low and lower middle income families is a prominent problem in many developing countries; governments alone are unable to address this challenge due to diverse financial and regulatory constraints, and the private sector's contribution is rare and assists only middle-income households even when institutional and legal reforms are conducted to persuade it to go down market. Also, the market-enabling policy measures advocated by the World Bank since the early nineties have been strongly criticized and proven to be inappropriate to developing country contexts, where it is highly unlikely that the formal private sector can reach low income population. In addition to governments and private developers, affordable housing delivery systems involve an intricate network of relationships between diverse ranges of actors. Collaboration between them was proven to be vital, and hence, an approach towards partnership schemes for affordable housing delivery has emerged. The basic premise of this paper is that addressing housing affordability challenges in Egypt demands direct public support, as markets and market actors alone would never succeed in delivering decent affordable housing to low and lower middle income groups. It argues that this support would ideally be through local level partnership schemes, with a leading decentralized local government role, and partners being identified according to specific local conditions. It attempts to identify major attributes that would ensure the fulfilment of the goals of such schemes in the Egyptian context. This is based upon evidence from diversified worldwide experiences, in addition to the main outcomes of a questionnaire that was conducted to specialists and chief actors in the field.

Keywords: affordable housing, partnership schemes, housing, urban environments

Procedia PDF Downloads 206

Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

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Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: human machine interface, industrial internet of things, internet of things, optical character recognition, video analytics

Procedia PDF Downloads 94

Authors: Fuad Abdullah Alatawi

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Microbial infections-based diseases are a significant public health issue around the world, mainly when antibiotic-resistant bacterium types evolve. In this research, we explored the anti-bacterial and anti-cancer potency of iron-oxide (Fe₂O₃) nanoparticles prepared from F. macrocarpa fruit extract. The chemical composition of F. macrocarpa fruit extract was used as a reducing and capping agent for nanoparticles’ synthesis was examined by GC-MS/MS analysis. Then, the prepared nanoparticles were confirmed by various biophysical techniques, including X-ray powder diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), UV-Vis Spectroscopy, and Transmission Electron Microscopy (TEM) and Energy Dispersive Spectroscopy (EDAX), and Dynamic Light Scattering (DLS). Also, the antioxidant capacity of fruit extract was determined through 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS), Fluorescence Recovery After Photobleaching (FRAP), Superoxide Dismutase (SOD) assays. Furthermore, the cytotoxicity activities of Fe₂O₃ NPs were determined using the (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) (MTT) test on MCF-7 cells. In the antibacterial assay, lethal doses of the Fe₂O₃NPs effectively inhibited the growth of gram-negative and gram-positive bacteria. The surface damage, ROS production, and protein leakage are the antibacterial mechanisms of Fe₂O₃NPs. Concerning antioxidant activity, the fruit extracts of F. macrocarpa had strong antioxidant properties, which were confirmed by DPPH, ABTS, FRAP, and SOD assays. In addition, the F. microcarpa-derived iron oxide nanomaterials greatly reduced the cell viability of (MCF-7). The GC-MS/MS analysis revealed the presence of 25 main bioactive compounds in the F. microcarpa extract. Overall, the finding of this research revealed that F. microcarpa-derived Fe₂O₃ nanoparticles could be employed as an alternative therapeutic agent to cure microbial infection and breast cancer in humans.

Keywords: ficus microcarpa, iron oxide, antibacterial activity, cytotoxicity

Procedia PDF Downloads 103

Authors: Stefano Barone

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Seismic retrofit of buildings through base isolation represents a consolidated protection strategy against earthquakes. It consists in decoupling the ground motion from that of the structure and introducing anti-seismic devices at the base of the building, characterized by high horizontal flexibility and medium/high dissipative capacity. This allows to protect structural elements and to limit damages to non-structural ones. For these reasons, full functionality is guaranteed after an earthquake event. Base isolation is applied extensively to both new and existing buildings. For the latter, it usually does not require any interruption of the structure use and occupants evacuation, a special advantage for strategic buildings such as schools, hospitals, and military buildings. This paper describes the application of seismic isolation to three existing masonry buildings in Italy: Villa “La Maddalena” in Macerata (Marche region), “Giacomo Matteotti” and “Plinio Il Giovane” school buildings in Perugia (Umbria region). The seismic hazard of the sites is characterized by a Peak Ground Acceleration (PGA) of 0.213g-0.287g for the Life Safety Limit State and between 0.271g-0.359g for the Collapse Limit State. All the buildings are isolated with a combination of free sliders type TETRON® CD with confined elastomeric disk and anti-seismic rubber isolators type ISOSISM® HDRB to reduce the eccentricity between the center of mass and stiffness, thus limiting torsional effects during a seismic event. The isolation systems are designed to lengthen the original period of vibration (i.e., without isolators) by at least three times and to guarantee medium/high levels of energy dissipation capacity (equivalent viscous damping between 12.5% and 16%). This allows the structures to resist 100% of the seismic design action. This article shows the performances of the supplied anti-seismic devices with particular attention to the experimental dynamic response. Finally, a special focus is given to the main site activities required to isolate a masonry building.

Keywords: retrofit, masonry buildings, seismic isolation, energy dissipation, anti-seismic devices

Procedia PDF Downloads 53

Authors: María del Carmen Recio-Ruiz, Ramiro Ruiz-Rosas, Juana María Rosas, José Rodríguez-Mirasol, Tomás Cordero

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Nowadays, fossil resources are main precursors for fuel production. Due to their contribution to the greenhouse effect and their future depletion, there is a constant search for environmentally friendly feedstock alternatives. Biomass residues constitute an interesting replacement for fossil resources because of their zero net CO₂ emissions. One of the main routes to convert biomass into energy and chemicals is pyrolysis. In this work, conventional pyrolysis of different biomass residues highly available such as almond shells, hemp hurds, olive stones, and Kraft lignin, was studied. In a typical experiment, the biomass was crushed and loaded into a fixed bed reactor under continuous nitrogen flow. The influence of temperature (400-800 ºC) and heating rate (10 and 20 ºC/min) on the pyrolysis yield and composition of the different fractions has been studied. In every case, the mass yields revealed that the solid fraction decreased with temperature, while liquid and gas fractions increased due to depolymerization and cracking reactions at high temperatures. The composition of every pyrolysis fraction was studied in detail. The results showed that the composition of the gas fraction was mainly CO, CO₂ when working at low temperatures, and mostly CH₄ and H₂at high temperatures. The solid fraction developed an incipient microporosity, with narrow micropore volume of 0.21 cm³/g. Regarding the liquid fraction, pyrolysis of almond shell, hemp hurds, and olive stones led mainly to a high content in aliphatic acids and furans, due to the high volatile matter content of these biomass (>74 %wt.), and phenols to a lesser degree, which were formed due to the degradation of lignin at higher temperatures. However, when Kraft lignin was used as bio-oil precursor, the presence of phenols was very prominent, and aliphatic compounds were also detected in a lesser extent.

Keywords: Bio-oil, biomass, conventional pyrolysis, lignocellulosic

Procedia PDF Downloads 123

Authors: Jamal Radaideh

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Al-Asfar Lake is located about 14 km east of Al-Ahsa and is one of the most important wetland lakes in the Al Ahsa/Eastern Province of Saudi Arabia. Al-Ahsa is may be the largest oasis in the world, having an area of 20,000 hectares, in addition, it is of the largest and oldest agricultural centers in the region. The surplus farm irrigation water beside additional water supplied by treated wastewater from Al-Hofuf sewage station is collected by a drainage network and discharged into Al-Asfar Lake. The lake has good wetlands, sand dunes as well as large expanses of open and shallow water. Salt tolerant vegetation is present in some of the shallow areas around the lake, and huge stands of Phragmites reeds occur around the lake. The lake presents an important habitat for wildlife and birds, something not expected to find in a large desert. Although high evaporation rates in the range of 3250 mm are common, the water remains in the evaporation lakes during all seasons of the year is used to supply cattle with drinking water and for aquifer recharge. Investigations showed that high concentrations of nitrogen (N), phosphorus (P), biological oxygen demand (BOD), chemical oxygen demand (COD) and salinity discharge to Al Asfar Lake from the D2 drain exist. It is expected that the majority of BOD, COD and N originates from wastewater discharge and leachate from surplus irrigation water which also contribute to the majority of P and salinity. The significant content of nutrients and biological oxygen demand reduces available oxygen in the water. The present project aimed to improve the water quality of the lake using constructed wetland trains which will be built around the lake. Phragmites reeds, which already occur around the lake, will be used.

Keywords: Al Asfar lake, constructed wetland, water quality, water treatment

Procedia PDF Downloads 424

Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

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Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

Procedia PDF Downloads 87

Authors: Anshu Bahl, Saroj Kaler, Shivani Gupta, S B Ray

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Background: Somatostatin is an endogenous regulatory neuropeptide. Somatostatin and its analogues play an important role in neuropathic and inflammatory pain. Neuropeptide Y is extensively distributed in the mammalian nervous system. NPY has an important role in blood pressure, circadian rhythm, obesity, appetite and memory. The purpose was to investigate somatostatin and NPY expression in dorsal root ganglia during pain. The plantar incision model in rats is similar to postoperative pain in humans. Methods: 24 adult male Sprague dawley rats were distributed randomly into two groups – Control (n=6) and incision (n=18) groups. Using Hargreaves apparatus, thermal hyperalgesia behavioural test for nociception was done under basal condition and after surgical incision in right hind paw at different time periods (day 1, 3 and 5). The plantar incision was performed as per standard protocol. Perfusion was done using 4% paraformaldehyde followed by extraction of dorsal root ganglia at L4 level. The tissue was processed for immunohistochemical localisation for somatostatin and neuropeptide Y. Results: Post incisional groups (day 1, 3 and 5) exhibited significant decrease of paw withdrawal latency as compared to control groups. Somatostatin expression was noted under basal conditions. It decreased on day 1, but again gradually increased on day 3 and further on day five post incision. The expression of Neuropeptide Y was noted in the cytoplasm of dorsal root ganglia under basal conditions. Compared to control group, expression of neuropeptide Y decreased on day one after incision, but again gradually increased on day 3. Maximum expression was noted on day five post incision. Conclusion: Decrease in paw withdrawal latency indicated nociception, particularly on day 1. In comparison to control, somatostatin and NPY expression was decreased on day one post incision. This could be correlated with increased axoplasmic flow towards the spinal cord. Somatostatin and NPY expression was maximum on day five post incision. This could be due to decreased migration from the site of synthesis towards the spinal cord.

Keywords: dorsal root ganglia, neuropeptide y, postoperative pain, somatostatin

Procedia PDF Downloads 159

Authors: Nora Geczy

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In today’s architectural practice, during the process of designing public, educational, healthcare and cultural space, human-centered architectural designs helping spatial orientation, safe space usage and the appropriate spatial sequence of actions are gaining increasing importance. Related to the methodology of designing public buildings, several scientific experiments in spatial recognition, spatial analysis and spatial psychology with regard to the components of space producing mental and physiological effects have been going on at the Department of Architectural Design and the Interdisciplinary Student Workshop (IDM) at the Széchenyi István University, Győr since 2013. Defining the creation of preventive, anticipated spatial design and the architectural tools of spatial comfort of public buildings and their practical usability are in the limelight of our research. In the experiments applying eye-tracking cameras, we studied the way public spaces are used, especially concentrating on the characteristics of spatial behaviour, orientation, recognition, the sequence of actions, and space usage. Along with the role of mental maps, human perception, and interaction problems in public spaces (at railway stations, galleries, and educational institutions), we analyzed the spatial situations influencing psychological and ergonomic factors. We also analyzed the eye movements of the experimental subjects in dynamic situations, in spatial procession, using stairs and corridors. We monitored both the consequences and the distorting effects of the ocular dominance of the right eye on spatial orientation; we analyzed the gender-based differences of women and men’s orientation, stress-inducing spaces, spaces affecting concentration and the spatial situation influencing territorial behaviour. Based on these observations, we collected the components of creating public interior spaces, which -according to our theory- contribute to the optimal usability of public spaces. We summed up our research in criteria for design, including 10 points. Our further goals are testing design principles needed for optimizing orientation and space usage, their discussion, refinement, and practical usage.

Keywords: architecture, eye-tracking, human-centered spatial design, public interior spaces, visual perception

Procedia PDF Downloads 98

Authors: Genevaive Melendres

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School administrators face the reality of teachers losing their engagement, or schools losing the teachers. This study is then conducted to identify a structural model that best predict work engagement of private secondary teachers in Davao City. Ninety-three teachers from four sectarian schools and 56 teachers from four non-sectarian schools were involved in the completion of four survey instruments namely Organizational Climate Questionnaire, Leader Behavior Descriptive Questionnaire, Organizational Commitment Scales, and Utrecht Work Engagement Scales. Data were analyzed using frequency distribution, mean, standardized deviation, t-test for independent sample, Pearson r, stepwise multiple regression analysis, and structural equation modeling. Results show that schools have high level of organizational climate dimensions; leaders oftentimes show work-oriented and people-oriented behavior; teachers have high normative commitment and they are very often engaged at their work. Teachers from non-sectarian schools have higher organizational commitment than those from sectarian schools. Organizational climate and leadership behavior are positively related to and predict work engagement whereas commitment did not show any relationship. This study underscores the relative effects of three variables on the work engagement of teachers. After testing network of relationships and evaluating several models, a best-fitting model was found between leadership behavior and work engagement. The noteworthy findings suggest that principals pay attention and consistently evaluate their behavior for this best predicts the work engagement of the teachers. The study provides value to administrators who take decisions and create conditions in which teachers derive fulfillment.

Keywords: leadership behavior, organizational climate, organizational commitment, private secondary school teachers, structural model on work engagement

Procedia PDF Downloads 247

Authors: Ethan James

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Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

Procedia PDF Downloads 161

Authors: Abdullah Faqihi, John Hedley

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Biosensors play a significant role in the healthcare sectors, scientific and technological progress. Developing electrodes that are easy to manufacture and deliver better electrochemical performance is advantageous for diagnostics and biosensing. They can be implemented extensively in various analytical tasks such as drug discovery, food safety, medical diagnostics, process controls, security and defence, in addition to environmental monitoring. Development of biosensors aims to create high-performance electrochemical electrodes for diagnostics and biosensing. A biosensor is a device that inspects the biological and chemical reactions generated by the biological sample. A biosensor carries out biological detection via a linked transducer and transmits the biological response into an electrical signal; stability, selectivity, and sensitivity are the dynamic and static characteristics that affect and dictate the quality and performance of biosensors. In this research, a developed experimental study for laser scribing technique for graphene oxide inside a vacuum chamber for processing of graphene oxide is presented. The processing of graphene oxide (GO) was achieved using the laser scribing technique. The effect of the laser scribing on the reduction of GO was investigated under two conditions: atmosphere and vacuum. GO solvent was coated onto a LightScribe DVD. The laser scribing technique was applied to reduce GO layers to generate rGO. The micro-details for the morphological structures of rGO and GO were visualised using scanning electron microscopy (SEM) and Raman spectroscopy so that they could be examined. The first electrode was a traditional graphene-based electrode model, made under normal atmospheric conditions, whereas the second model was a developed graphene electrode fabricated under a vacuum state using a vacuum chamber. The purpose was to control the vacuum conditions, such as the air pressure and the temperature during the fabrication process. The parameters to be assessed include the layer thickness and the continuous environment. Results presented show high accuracy and repeatability achieving low cost productivity.

Keywords: laser scribing, lightscribe DVD, graphene oxide, scanning electron microscopy

Procedia PDF Downloads 100

Authors: Mohamed Khiatine, Amal Medjnoun, Ramdane Bahar

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The North Algeria is a highly seismic zone, as evidenced by the historical seismicity. During the past two decades, it has experienced several moderate to strong earthquakes. Therefore, the geotechnical engineering problems that involve dynamic loading of soils and soil-structure interaction system requires, in the presence of saturated loose sand formations, liquefaction studies. Bejaia city, located in North-East of Algiers, Algeria, is a part of the alluvial plain which covers an area of approximately 750 hectares. According to the Algerian seismic code, it is classified as moderate seismicity zone. This area had not experienced in the past urban development because of the different hazards identified by hydraulic and geotechnical studies conducted in the region. The low bearing capacity of the soil, its high compressibility and the risk of liquefaction and flooding are among these risks and are a constraint on urbanization. In this area, several cases of structures founded on shallow foundations have suffered damages. Hence, the soils need treatment to reduce the risk. Many field and laboratory investigations, core drilling, pressuremeter test, standard penetration test (SPT), cone penetrometer test (CPT) and geophysical down hole test, were performed in different locations of the area. The major part of the area consists of silty fine sand , sometimes heterogeneous, has not yet reached a sufficient degree of consolidation. The ground water depth changes between 1.5 and 4 m. These investigations show that the liquefaction phenomenon is one of the critical problems for geotechnical engineers and one of the obstacles found in design phase of projects. This paper presents an analysis to evaluate the liquefaction potential, using the empirical methods based on Standard Penetration Test (SPT), Cone Penetration Test (CPT) and shear wave velocity and numerical analysis. These liquefaction assessment procedures indicate that liquefaction can occur to considerable depths in silty sand of harbor zone of Bejaia.

Keywords: earthquake, modeling, liquefaction potential, laboratory investigations

Procedia PDF Downloads 343

Authors: Moses C. Siame, Kazutoshi Haga, Atsushi Shibayama

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This study investigates the removal of silica, alumina and phosphorus as impurities from Sanje iron ore using wet high-intensity magnetic separation (WHIMS). Sanje iron ore contains low-grade hematite ore found in Nampundwe area of Zambia from which iron is to be used as the feed in the steelmaking process. The chemical composition analysis using X-ray Florence spectrometer showed that Sanje low-grade ore contains 48.90 mass% of hematite (Fe₂O₃) with 34.18 mass% as an iron grade. The ore also contains silica (SiO₂) and alumina (Al₂O₃) of 31.10 mass% and 7.65 mass% respectively. The mineralogical analysis using X-ray diffraction spectrometer showed hematite and silica as the major mineral components of the ore while magnetite and alumina exist as minor mineral components. Mineral particle distribution analysis was done using scanning electron microscope with an X-ray energy dispersion spectrometry (SEM-EDS) and images showed that the average mineral size distribution of alumina-silicate gangue particles is in order of 100 μm and exists as iron-bearing interlocked particles. Magnetic separation was done using series L model 4 Magnetic Separator. The effect of various magnetic separation parameters such as magnetic flux density, particle size, and pulp density of the feed was studied during magnetic separation experiments. The ore with average particle size of 25 µm and pulp density of 2.5% was concentrated using pulp flow of 7 L/min. The results showed that 10 T was optimal magnetic flux density which enhanced the recovery of 93.08% of iron with 53.22 mass% grade. The gangue mineral particles containing 12 mass% silica and 3.94 mass% alumna remained in the concentrate, therefore the concentrate was further treated in the second stage WHIMS using the same parameters from the first stage. The second stage process recovered 83.41% of iron with 67.07 mass% grade. Silica was reduced to 2.14 mass% and alumina to 1.30 mass%. Accordingly, phosphorus was also reduced to 0.02 mass%. Therefore, the two stage magnetic separation process was established using these results.

Keywords: Sanje iron ore, magnetic separation, silica, alumina, recovery

Procedia PDF Downloads 244

Authors: S. Junaid S. Qazi, Denice C. Bay, Raymond Chew, Raymond J. Turner

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EmrE, a member of the small multidrug resistance protein family in bacteria is considered to be the archetypical member of its family. It confers host resistance to a wide variety of quaternary cation compounds (QCCs) driven by proton motive force. Generally, purification yield is a challenge in all membrane proteins because of the difficulties in their expression, isolation and solubilization. EmrE is extremely hydrophobic which make the purification yield challenging. We have purified EmrE protein using two different approaches: organic solvent membrane extraction and hexahistidine (his6) tagged Ni-affinity chromatographic methods. We have characterized changes present between ligand affinity of untagged and his6-tagged EmrE proteins in similar membrane mimetic environments using biophysical experimental techniques. Purified proteins were solubilized in a buffer containing n-dodecyl-β-D-maltopyranoside (DDM) and the conformations in the proteins were explored in the presence of four QCCs, methyl viologen (MV), ethidium bromide (EB), cetylpyridinium chloride (CTP) and tetraphenyl phosphonium (TPP). SDS-Tricine PAGE and dynamic light scattering (DLS) analysis revealed that the addition of QCCs did not induce higher multimeric forms of either proteins at all QCC:EmrE molar ratios examined under the solubilization conditions applied. QCC binding curves obtained from the Trp fluorescence quenching spectra, gave the values of dissociation constant (Kd) and maximum specific one-site binding (Bmax). Lower Bmax values to QCCs for his6-tagged EmrE shows that the binding sites remained unoccupied. This lower saturation suggests that the his6-tagged versions provide a conformation that prevents saturated binding. Our data demonstrate that tagging an integral membrane protein can significantly influence the protein.

Keywords: small multidrug resistance (SMR) protein, EmrE, integral membrane protein folding, quaternary ammonium compounds (QAC), quaternary cation compounds (QCC), nickel affinity chromatography, hexahistidine (His6) tag

Procedia PDF Downloads 362

Authors: Lauren A. Bailey, Amber R. Childs, Nicola C. James, Murray I. Duncan, Alexander Winkler, Warren M. Potts

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For the persistence of fished populations in the Anthropocene, it is critical to predict how fished populations will respond to the coupled threats of exploitation and climate change for adaptive management. The resilience of fished populations will depend on their capacity for physiological plasticity and acclimatization in response to environmental shifts. However, there is evidence for the selection of physiological traits by capture fisheries. Hence, fish populations may have a limited scope for the rapid expansion of their tolerance ranges or physiological adaptation under fishing pressures. To determine the physiological vulnerability of fished populations in the Anthropocene, the metabolic performance was compared between a fished and spatially protected Chrysoblephus laticeps population in response to thermal variability. Individual aerobic scope phenotypes were quantified using intermittent flow respirometry by comparing changes in energy expenditure of each individual at ecologically relevant temperatures, mimicking variability experienced as a result of upwelling and downwelling events. The proportion of high and low-performance individuals were compared between the fished and spatially protected population. The fished population had limited aerobic scope phenotype diversity and fewer high-performance phenotypes, resulting in a significantly lower aerobic scope curve across low (10 °C) and high (24 °C) thermal treatments. The performance of fished populations may be compromised with predicted future increases in cold upwelling events. This requires the conservation of the physiologically fittest individuals in spatially protected areas, which can recruit into nearby fished areas, as a climate resilience tool.

Keywords: climate change, fish physiology, metabolic shifts, over-fishing, respirometry

Procedia PDF Downloads 112

Authors: Tatiana A. Pozdniakova, Maria A. P. Cechinel, Luciana P. Mazur, Rui A. R. Boaventura, Vitor J. P. Vilar.

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Two brown macroalgae, Laminaria hyperborea and Pelvetia canaliculata, were employed as natural cation exchangers in a fixed-bed column for Zn(II) removal from a galvanization wastewater. The column (4.8 cm internal diameter) was packed with 30-59 g of previously hydrated algae up to a bed height of 17-27 cm. The wastewater or eluent was percolated using a peristaltic pump at a flow rate of 10 mL/min. The effluent used in each experiment presented similar characteristics: pH of 6.7, 55 mg/L of chemical oxygen demand and about 300, 44, 186 and 244 mg/L of sodium, calcium, chloride and sulphate ions, respectively. The main difference was nitrate concentration: 20 mg/L for the effluent used with L. hyperborean and 341 mg/L for the effluent used with P. canaliculata. The inlet zinc concentration also differed slightly: 11.2 mg/L for L. hyperborean and 8.9 mg/L for P. canaliculata experiments. The breakthrough time was approximately 22.5 hours for both macroalgae, corresponding to a service capacity of 43 bed volumes. This indicates that 30 g of biomass is able to treat 13.5 L of the galvanization wastewater. The uptake capacities at the saturation point were similar to that obtained in batch studies (unpublished data) for both algae. After column exhaustion, desorption with 0.1 M HNO3 was performed. Desorption using 9 and 8 bed volumes of eluent achieved an efficiency of 100 and 91%, respectively for L. hyperborean and P. canaliculata. After elution with nitric acid, the column was regenerated using different strategies: i) convert all the binding sites in the sodium form, by passing a solution of 0.5 M NaCl, until achieve a final pH of 6.0; ii) passing only tap water in order to increase the solution pH inside the column until pH 3.0, and in this case the second sorption cycle was performed using protonated algae. In the first approach, in order to remove the excess of salt inside the column, distilled water was passed through the column, leading to the algae structure destruction and the column collapsed. Using the second approach, the algae remained intact during three consecutive sorption/desorption cycles without loss of performance.

Keywords: biosorption, zinc, galvanization wastewater, packed-bed column

Procedia PDF Downloads 302

Authors: Abhilash Sahu, Amit Priyadarshi

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In this paper, we will discuss the existence of weak solutions of the Kirchhoff type boundary value problem on the Sierpinski gasket. Where S denotes the Sierpinski gasket in R² and S₀ is the intrinsic boundary of the Sierpinski gasket. M: R → R is a positive function and h: S × R → R is a suitable function which is a part of our main equation. ∆p denotes the p-Laplacian, where p > 1. First of all, we will define a weak solution for our problem and then we will show the existence of at least two solutions for the above problem under suitable conditions. There is no well-known concept of a generalized derivative of a function on a fractal domain. Recently, the notion of differential operators such as the Laplacian and the p-Laplacian on fractal domains has been defined. We recall the result first then we will address the above problem. In view of literature, Laplacian and p-Laplacian equations are studied extensively on regular domains (open connected domains) in contrast to fractal domains. In fractal domains, people have studied Laplacian equations more than p-Laplacian probably because in that case, the corresponding function space is reflexive and many minimax theorems which work for regular domains is applicable there which is not the case for the p-Laplacian. This motivates us to study equations involving p-Laplacian on the Sierpinski gasket. Problems on fractal domains lead to nonlinear models such as reaction-diffusion equations on fractals, problems on elastic fractal media and fluid flow through fractal regions etc. We have studied the above p-Laplacian equations on the Sierpinski gasket using fibering map technique on the Nehari manifold. Many authors have studied the Laplacian and p-Laplacian equations on regular domains using this Nehari manifold technique. In general Euler functional associated with such a problem is Frechet or Gateaux differentiable. So, a critical point becomes a solution to the problem. Also, the function space they consider is reflexive and hence we can extract a weakly convergent subsequence from a bounded sequence. But in our case neither the Euler functional is differentiable nor the function space is known to be reflexive. Overcoming these issues we are still able to prove the existence of at least two solutions of the given equation.

Keywords: Euler functional, p-Laplacian, p-energy, Sierpinski gasket, weak solution

Procedia PDF Downloads 221

Authors: Gulnaz Erkomaishvili

Abstract:

Introduction: The pandemic and the current economic crisis have created problems for entrepreneurship and, therefore for start-up entrepreneurs. The paper presents the challenges of start-up entrepreneurs in Georgia in the time of pandemic and the analysis of the state economic policy measures. Despite many problems, the study found that in 54.2% of start-ups surveyed under the pandemic, innovation opportunities were growing. It can be stated that the pandemic was a good opportunity to increase the innovative capacity of the enterprise. 52% of the surveyed start-up entrepreneurs managed to adapt to the current situation and increase the sale of their products/services through remote channels. As for the assessment of state support measures by start-up entrepreneurs, a large number of Georgian start-ups do not assess the measures implemented by the state positively. Methodology: The research process uses methods of analysis and synthesis, quantitative and qualitative, interview/survey, grouping, relative and average values, graphing, comparison, data analysis, and others. Main Findings: Studies have shown that for the start-up entrepreneurs, the main problem remains: inaccessible funding, workers' qualifications gap, inflation, taxes, regulation, political instability, inadequate provision of infrastructure, amount of taxes, and other factors. Conclusions: The state should take the following measures to support business start-ups: create an attractive environment for investment, availability of soft loans, creation of an insurance system, infrastructure development, increase the effectiveness of tax policy (simplicity of the tax system, clarity, optimal tax level ); promote export growth (develop strategy for opening up international markets, build up a broad marketing network, etc.).

Keywords: start-up entrepreneurs, startups, start-up entrepreneurs support programs, start-up entrepreneurs support economic policy

Procedia PDF Downloads 101

Authors: Sreetama Ghosh, Sundara Ramaprabhu

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Carbon dioxide gas has been a major cause for the worldwide increase in green house effect, which leads to climate change and global warming. So CO₂ capture & sequestration has become an effective way to reduce the concentration of CO₂ in the environment. One such way to capture CO₂ in porous materials is by adsorption process. A potential material in this aspect is porous hexagonal boron nitride or 'white graphene' which is a well-known two-dimensional layered material with very high thermal stability. It had been investigated that the sample with hierarchical pore structure and high specific surface area shows excellent performance in capturing carbon dioxide gas and thereby mitigating the problem of environmental pollution to the certain extent. Besides, the presence of sulfur as well as nitrogen in the sample synergistically helps in the increase in adsorption capacity. In this work, a cost effective single step synthesis of highly porous boron nitride nanosheets doped with sulfur had been demonstrated. Besides, the CO₂ adsorption-desorption studies were carried on using a pressure reduction technique. The studies show that the nanosheets exhibit excellent cyclic stability in storage performance. Thermodynamic studies suggest that the adsorption takes place mainly through physisorption. The studies show that the nanosheets exhibit excellent cyclic stability in storage performance. Further, the surface modification of the highly porous nano sheets carried out by incorporating ionic liquids had further enhanced the capturing capability of CO₂ gas in the nanocomposite, revealing that this particular material has the potential to be an excellent adsorbent of carbon dioxide gas.

Keywords: CO₂ capture, hexagonal boron nitride nanosheets, porous network, sulfur doping

Procedia PDF Downloads 229

Authors: Hsin-Chieh Lee, Fen-Ling Kuo, Jui-Chi Lin

Abstract:

Background: Upper extremity functional impairment that occurs after stroke includes hemiplegia, synergy movement, muscle hypertonicity, and somatosensory impairment, which result in inefficient and inaccurate movement. Robot-assisted rehabilitation is an intensive training approach that is effective in sensorimotor and hand function recovery. However, these systems mostly focused on the proximal part of the upper limb rather than the distal part. The device used in our study was Gloreha Sinfonia, which focuses on the distal part of the upper limb and uses a dynamic support system to facilitate the whole limb function. The objective of this study was to investigate the effects of robot-assisted therapy (RT) with Gloreha device on sensorimotor, and ADLs in patients with stroke. Method: Patients with stroke (N=25) participated AB or BA (A = 12 RT sessions and B = 12 conventional therapy (CT) sessions) for 6 weeks (60 min at each session, twice a week), with 1-month break for washout period. The performance of the patients was assessed by a blinded assessor at 4 time points (pretest 1, posttest 1, pretest 2, posttest 2) which including the Fugl–Meyer Assessment-upper extremity (FMA-UE), box and block test, electromyography of the extensor digitorum communis (EDC) and brachioradialis, a grip dynamometer for motor evaluation; Semmes–Weinstein hand monofilament and Revision of the Nottingham Sensory Assessment for sensory evaluation; and the Modified Barthel Index (MBI) for assessing the ADL ability. Result: RT group significantly improved FMA-UE proximal scores (p = 0.038), FMA-UE total scores (p = 0.046), and MBI (p = 0.030). The EDC exhibited higher efficiency during the small block grasping task in the RT group than in the CT group (p = 0.050). Conclusions: RT with the Gloreha device might lead to beneficial effects on arm motor function, ADL ability, and EDC muscle recruitment efficacy in patients with subacute to chronic stroke.

Keywords: activities of daily living, hand function, robotic rehabilitation, stroke

Procedia PDF Downloads 99

Authors: Mohd Farooq Naqshbandi

Abstract:

The four fractions of aqueous extract of Sesame Seeds (Sesamum indicum L.) were studied for invitro DNA fragmentation, cell migration, and cellular apoptosis on SW480 and HTC116 human colorectal cancer cell lines. The seeds of Sesamum indicum were extracted with six solvents, including Methanol, Ethanol, Aqueous, Chloroform, Acetonitrile, and Hexane. The aqueous extract (IC₅₀ value 154 µg/ml) was found to be the most active in terms of cytotoxicity with SW480 human colorectal cancer cell lines. Further fractionation of this aqueous extract on flash chromatography gave four fractions. These four fractions were studied for anticancer and DNA binding studies. Cell viability was assessed by colorimetric assay (MTT). IC₅₀ values for all these four fractions ranged from 137 to 548 µg/mL for the HTC116 cancer cell line and 141 to 402 µg/mL for the SW480 cancer cell line. The four fractions showed good anticancer and DNA binding properties. The DNA binding constants ranged from 10.4 ×10⁴ 5 to 28.7 ×10⁴, showing good interactions with DNA. The DNA binding interactions were due to intercalative and π-π electron forces. The results indicate that aqueous extract fractions of sesame showed inhibition of cell migration of SW480 and HTC116 human colorectal cancer cell lines and induced DNA fragmentation and apoptosis. This was demonstrated by calculating the low wound closure percentage in cells treated with these fractions as compared to the control (80%). Morphological features of nuclei of cells treated with fractions revealed chromatin compression, nuclear shrinkage, and apoptotic body formation, which indicate cell death by apoptosis. The flow cytometer of fraction-treated cells of SW480 and HTC116 human colorectal cancer cell lines revealed death due to apoptosis. The results of the study indicate that aqueous extract of sesame seeds may be used to treat colorectal cancer.

Keywords: Sesamum indicum, cell migration inhibition, apoptosis induction, anticancer activity, colorectal cancer

Procedia PDF Downloads 71

Authors: Amy Lebar, Kim L. Trenbath, Bennett Doherty, William Livingood

Abstract:

Plug and process loads (PPLs) account for 47% of U.S. commercial building energy use. There is a huge potential to reduce whole building consumption by targeting PPLs for energy savings measures or implementing some form of plug load management (PLM). Despite this potential, there has yet to be a widely adopted commercial PLM technology. This paper describes the Automatic Type and Location Identification System (ATLIS), a PLM system framework with automatic and dynamic load detection (ADLD). ADLD gives PLM systems the ability to automatically identify devices as they are plugged into the outlets of a building. The ATLIS framework takes advantage of smart, connected devices to identify device locations in a building, meter and control their power, and communicate this information to a central database. ATLIS includes five primary capabilities: location identification, communication, control, energy metering and data storage. A laboratory proof of concept (PoC) demonstrated all but the data storage capabilities and these capabilities were validated using an office building scenario. The PoC can identify when a device is plugged into an outlet and the location of the device in the building. When a device is moved, the PoC’s dashboard and database are automatically updated with the new location. The PoC implements controls to devices from the system dashboard so that devices maintain correct schedules regardless of where they are plugged in within a building. ATLIS’s primary technology application is improved PLM, but other applications include asset management, energy audits, and interoperability for grid-interactive efficient buildings. A system like ATLIS could also be used to direct power to critical devices, such as ventilators, during a brownout or blackout. Such a framework is an opportunity to make PLM more widespread and reduce the amount of energy consumed by PPLs in current and future commercial buildings.

Keywords: commercial buildings, grid-interactive efficient buildings (GEB), miscellaneous electric loads (MELs), plug loads, plug load management (PLM)

Procedia PDF Downloads 118

Authors: S. Sadhu, M. Ramgopal, S. Bhattacharyya

Abstract:

Natural circulation loops (NCLs) are buoyancy driven flow systems without any moving components. NCLs have vast applications in geothermal, solar and nuclear power industry where reliability and safety are of foremost concern. Due to certain favorable thermophysical properties, especially near supercritical regions, carbon dioxide can be considered as an ideal loop fluid in many applications. In the present work, a high temperature NCL that uses supercritical carbon dioxide as loop fluid is analysed. The effects of relevant design and operating variables on loop performance are studied. The system operating under steady state is modelled taking into account the axial conduction through loop fluid and loop wall, and heat transfer with surroundings. The heat source is considered to be a heater with controlled heat flux and heat sink is modelled as an end heat exchanger with water as the external cold fluid. The governing equations for mass, momentum and energy conservation are normalized and are solved numerically using finite volume method. Results are obtained for a loop pressure of 90 bar with the power input varying from 0.5 kW to 6.0 kW. The numerical results are validated against the experimental results reported in the literature in terms of the modified Grashof number (Gr_m) and Reynolds number (Re). Based on the results, buoyancy and friction dominated regions are identified for a given loop. Parametric analysis has been done to show the effect of loop diameter, loop height, ambient temperature and insulation. The results show that for the high temperature loop, heat loss to surroundings affects the loop performance significantly. Hence this conjugate heat transfer between the loop and surroundings has to be considered in the analysis of high temperature NCLs.

Keywords: conjugate heat transfer, heat loss, natural circulation loop, supercritical carbon dioxide

Procedia PDF Downloads 228

Authors: Dhanuja S. Patil, Sanjay B. Waykar

Abstract:

Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

Procedia PDF Downloads 305

Authors: Budhvin T. Withana, Sulochana Rupasinghe

Abstract:

The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 47

Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

Abstract:

In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: continuous wavelet transform, convolution neural net-work, gated recurrent unit, health indicators, remaining useful life

Procedia PDF Downloads 114