Search results for: total floating time (TFT)

Authors: Blessing Olamide Taiwo, Andrew Palangio, Chirag Savaliya, Jenil Patel

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Oversized material resulting from blasting presents a notable drawback in the transportation of run-off-mine material due to increased expenses associated with handling, decreased efficiency in loading, and greater wear on digging equipment. Its irregular size and weight demand additional resources and time for secondary breakage, impacting overall productivity and profitability. This paper addresses the limitations of interpreting image analysis software results and applying them to the assessment of blast-generated oversized materials. This comprehensive guide utilizes both ortho mosaic and digital photos to provide critical approaches for optimizing fragmentation analysis and improving decision-making in mining operations. It briefly covers post-blast assessment, blast block heat map interpretation, and material loading decision-making recommendations.

Keywords: blast result assessment, WipFrag, oversize identification, orthomosaic images, production optimization

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Authors: Tadele Araya, Tsehaye Asmelash, Girmatsion Fiseha

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Background: Hepatitis B virus (HBV), Hepatitis C virus (HCV) and Human Immunodeficiency Virus (HIV) constitute serious healthcare problems worldwide. Blood-borne pathogens HBV, HCV and HIV are commonly associated with infections among substance or Injection Drug Users (IDUs). The objective of this study was to determine the prevalence of HBV, HCV, and HIV infections among substance users in Mekelle Substance users Treatment and Rehabilitation Centers. Methods: A cross-sectional study design was used from Dec 2020 to Sep / 2021 to conduct the study. A total of 600 substance users were included. Data regarding the socio-demographic, clinical and sexual behaviors of the substance users were collected using a structured questionnaire. For laboratory analysis, 5-10 ml of venous blood was taken from the substance users. The laboratory analysis was performed by Enzyme-Linked Immunosorbent Assay (ELISA) at Mekelle University, Department of Medical Microbiology and Immunology Research Laboratory. The Data was analyzed using SPSS and Epi-data. The association of variables with HBV, HCV and HIV infections was determined using multivariate analysis and a P value < 0.05 was considered statistically significant. Result: The overall prevalence rate of HBV, HCV and HIV infections were 10%, 6.6%, and 7.5%, respectively. The mean age of the study participants was 28.12 ± 6.9. A higher prevalence of HBV infection was seen in participants who were users of drug injections and in those who were infected with HIV. HCV was comparatively higher in those who had a previous history of unsafe surgical procedures than their counterparts. Homeless participants were highly exposed to HCV and HIV infections than their counterparts. The HBV/HIV Co-infection prevalence was 3.5%. Those doing unprotected sexual practices [P= 0.03], Injection Drug users [P= 0.03], those who had an HBV-infected person in their family [P=0.02], infected with HIV [P= 0.025] were statistically associated with HBV infection. HCV was significantly associated with Substance users and previous history of unsafe surgical procedures [p=0.03, p=0.04), respectively. HIV was significantly associated with unprotected sexual practices and being homeless [p=0.045, p=0.05) respectively. Conclusion-The highly prevalent viral infection was HBV compared to others. There was a High prevalence of HBV/HIV co-infection. The presence of HBV-infected persons in a family, unprotected sexual practices and sharing of needles for drug injection were the risk factors associated with HBV, HIV, and HCV. Continuous health education and screening of the viral infection coupled with medical and psychological treatment is mandatory for the prevention and control of the infections.

Keywords: hepatitis b virus, hepatitis c virus, HIV, substance users

Procedia PDF Downloads 71

Authors: Ahlem Abid, Farah Jemili

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Intrusion detection has been the subject of numerous studies in industry and academia, but cyber security analysts always want greater precision and global threat analysis to secure their systems in cyberspace. To improve intrusion detection system, the visualisation of the security events in form of graphs and diagrams is important to improve the accuracy of alerts. In this paper, we propose an approach of an IDS based on cloud computing, big data technique and using a machine learning graph algorithm which can detect in real time different attacks as early as possible. We use the MAWILab intrusion detection dataset . We choose Microsoft Azure as a unified cloud environment to load our dataset on. We implement the k2 algorithm which is a graphical machine learning algorithm to classify attacks. Our system showed a good performance due to the graphical machine learning algorithm and spark structured streaming engine.

Keywords: Apache Spark Streaming, Graph, Intrusion detection, k2 algorithm, Machine Learning, MAWILab, Microsoft Azure Cloud

Procedia PDF Downloads 133

Authors: Huei Jiun Chen, Hui Mei Huan

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Introduction: Pain is an unpleasant experience for hospitalized patients that impacts both their physical and mental well-being. It is important to select appropriate pain assessment tools to ensure effective pain management. Therefore, it is suggested to use Verbal Rating Scale (VRS) instead for better assessment. The Wong-Baker FACES Pain Rating Scale(WBS) is a widely used pain assessment tool in Taiwan to help individuals communicate the intensity of their pain. However, in clinical practice, even when using various assessment tools to evaluate pain, Numeric Rating Scale-11 (NRS-11) is still commonly utilized to quantify the intensity of pain. The correlation between NRS and other pain assessment tools has not been extensively explored in Taiwan. Additionally, the influence of gender and education level on pain assessment among elderly individuals has not been extensively studied in Taiwan. The aim of this study is to investigate the correlation between pain assessment scales (NRS-11, VRS, WBS) in assessing pain intensity among elderly inpatients. The secondary objective of this study is to examine how gender and education level influence pain assessment among individuals, as well as to explore their preferences regarding pain assessment tools. Method: In this study, a questionnaire survey and purposive sampling were employed to recruit participants from a medical center located in central Taiwan. Participants were requested to assess their pain intensity in the past 24 hours using NRS-11, VRS, and WBS. Additionally, the study investigated their preferences for pain assessment tools. Result: A total of 252 participants were included in this study, with a mean age of 71.1 years (SD=6.2). Of these participants, 135 were male (53.6%), and 44.4% had a primary level or below education. Participants were asked to use NRS-11, VRS, and WBS to assess their current, maximum, and minimum pain intensity experienced in the past 24 hours. The findings indicated a significant correlation (p< .01) among all three pain assessment tools. No significant differences were observed in gender across the three pain assessment scales. For severe pain, there were significant differences in self-rated pain scales among the elderly participants with different education levels (F=3.08, p< .01; X²=17.25, X²=17.21, p< .01), but there were no significant differences observed for mild pain. Regarding preferences for pain assessment tools, 158 participants (62.7%) favored VRS, followed by WBS; gender and education level had no influence on their preferences. Conclusion: Most elderly participants prefer using VRS (Verbal Rating Scale) to self-reported their pain. The reason for this preference may be attributed to the verbal nature of VRS, as it is simple and easy to understand. Furthermore, it could be associated with the level of education among the elderly participants. The pain assessment using VRS demonstrated a significant correlation with NRS-11 and WBS, and gender was not found to have any influence on these assessment. Further research is needed to explore the effect of different education levels on self-reported pain intensity among elderly people in Taiwan.

Keywords: pain assessment, elderly, gender, education

Procedia PDF Downloads 55

Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

Procedia PDF Downloads 142

Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

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In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

Procedia PDF Downloads 370

Authors: J. Vitku, L. Kolatorova, T. Chlupacova, J. Heracek, M. Hill, M. Duskova, L. Starka

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Background: 7β-hydroxy-epiandrosterone (7β–OH-EpiA) is an endogenous steroid, that has been shown to exert neuroprotective and anti-inflammatory effects in vitro as well as in animal models. However, to the best of our knowledge no information is available about concentration of this androgen metabolite in human population. The aim of the study was to measure and compare levels of 7β–OH-EpiA in men and pregnant women in different biological fluids and evaluate the relationship between 7β–OH-EpiA in men and their sperm quality. Methods: First, a sensitive isotope dilution high performance liquid chromatography-mass spectrometry method for measurement of 7β–OH-EpiA in different biological fluids was developed. Validation of the method met the requirements of FDA guidelines. Afterwards 7β–OH-EpiA in plasma and seminal plasma of 191 men with different degree of infertility (healthy men, lightly infertile men, moderately infertile men, severely infertile men) was analysed. Furthermore, the levels of 7β–OH-EpiA in plasma of 34 pregnant women in 37th week of gestation and corresponding cord plasma that reflects steroid levels in the fetus were measured. Results: Concentrations of 7β–OH-EpiA in seminal plasma were significantly higher in severely infertile men in comparison with healthy men and lightly infertile men. The same trend was observed when blood plasma was evaluated. Furthermore, plasmatic 7β –OH-EpiA negatively correlated with concentration (-0.215; p < 0.01) and total count (-0.15; p < 0.05). Seminal 7β–OH-EpiA was negatively associated with motility (-0.26; p < 0.01), progressively motile sperms (-0.233; p < 0.01) and nonprogressively motile sperms (-0.188; p < 0.05). Plasmatic 7β –OH-EpiA levels in men were generally higher in comparison with pregnant women. Levels 7β–OH-EpiA were under the lower limit of quantification (LLOQ) in majority of samples of pregnant women and cord plasma. Only 4 plasma samples of pregnant women and 7 cord blood plasma samples were above LLOQ and where in range of units of pg/ml. Conclusion: Based on available information, this is the first study measuring 7β–OH-EpiA in human samples. 7β–OH-EpiA is associated with lower sperm quality and certainly it is worth to explore its role in this field thoroughly. Interestingly, levels of 7β–OH-EpiA in pregnant women were extremely low despite the fact that steroid levels including androgens are generally higher during pregnancy. Acknowledgements: This work was supported by the project MH CR 17-30528 A from the Czech Health Research Council, MH CZ - DRO (Institute of Endocrinology - EU, 00023761) and by the MEYS CR (OP RDE, Excellent research - ENDO.CZ).

Keywords: 7β-hydroxy-epiandrosterone, steroid, sperm quality, pregnancy

Procedia PDF Downloads 236

Authors: Raied, Badr Al-Fulaiti, E. I. El-Shafey

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Cyclodextrin (CD) derivatives (αCD, βCD, ϒCD and hp-βCD) were successfully immobilized on silica gel surface via epichlorohydrin as a cross linker. The ratio of silica to CD was optimized in preliminary experiments based on best performance of iodine adsorption capacity. Selected adsorbents with ratios of silica to CD derivatives, in this study, include Si-αCD (3:2), Si-βCD (4:1), Si-ϒCD (4:1) and Si-hp-βCD (4:1). The adsorption of iodine (I2/KI) solution was investigated in terms of initial pH, contact time, iodine concentration and temperature. No significant variations was noticed for iodine adsorption at different pH values, thus, initial pH 6 was selected for further studies. Equilibrium adsorption was reached faster on Si-hp-βCD than other adsorbents with kinetic adsorption data fitting well pseudo second order model. Activation energy (Ea) was found to be in the range of 12.7 - 23.4 kJ/mol. Equilibrium adsorption data were found to fit well the Langmuir adsorption model with lower uptake as temperature rises. Iodine uptake follows the order: Si-hp-βCD (714 mg/g) >Si-αCD (625 mg/g) >Si-βCD (555.6 mg/g)> Si-ϒCD (435 mg/g). Thermodynamic study showed that iodine adsorption is exothermic and spontaneous. Adsorbents reuse exhibited excellent performance for iodine adsorption with a decrease in iodine uptake of ~ 2- 4 % in the third adsorption cycle.

Keywords: adsorption, iodine, silica, cyclodextrin, functionalization, epichlorohydrin

Procedia PDF Downloads 117

Authors: Maria Joseph Israel, Ahmed Amer

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Our work aims to broaden the application of provenance technology beyond its traditional domains of scientific workflow management and database systems by offering a general provenance framework to capture richer and extensible metadata in unstructured textual data sources such as literary texts, commentaries, translations, and digital humanities. Specifically, we demonstrate the feasibility of capturing and representing expressive provenance metadata, including more of the context for citing scholarly works (e.g., the authors’ explicit or inferred intentions at the time of developing his/her research content for publication), while also supporting subsequent augmentation with similar additional metadata (by third parties, be they human or automated). To better capture the nature and types of possible citations, in our proposed provenance scheme metaScribe, we extend standard provenance conceptual models to form our proposed provCite ontology. This provides a conceptual framework which can accurately capture and describe more of the functional and rhetorical properties of a citation than can be achieved with any current models.

Keywords: knowledge representation, provenance architecture, ontology, metadata, bibliographic citation, semantic web annotation

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Authors: Kavyadevi N., Kaviya G., Gowsalya P., Janani M., Mohanraj S.

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Hevea brasiliensis, also known as the rubber tree, is one of the foremost assets of crops in the world. One of the most significant advantages of the Rubber Plant in terms of air oxygenation is its capacity to reduce the likelihood of an individual developing respiratory allergies like asthma. To construct such a system that can properly identify crop diseases and pests and then create a database of insecticides for each pest and disease, we must first give treatment for the illness that has been detected. We shall primarily examine three major leaf diseases since they are economically deficient in this article, which is Bird's eye spot, algal spot and powdery mildew. And the recommended work focuses on disease identification on rubber tree leaves. It will be accomplished by employing one of the superior algorithms. Input, Preprocessing, Image Segmentation, Extraction Feature, and Classification will be followed by the processing technique. We will use time-consuming procedures that they use to detect the sickness. As a consequence, the main ailments, underlying causes, and signs and symptoms of diseases that harm the rubber tree are covered in this study.

Keywords: image processing, python, convolution neural network (CNN), machine learning

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Authors: Ali A. Ukasha

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Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression, salt and peppers attacks, bitplanes decomposition, Arnold transform, lossless image encryption

Procedia PDF Downloads 482

Authors: Ali Ateş, Ansar B. Mwimbo, Ali H. Abdulkarim

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General transport equation has a wide range of application in Fluid Mechanics and Heat Transfer problems. In this equation, generally when φ variable which represents a flow property is used to represent fluid velocity component, general transport equation turns into momentum equations or with its well known name Navier-Stokes equations. In these non-linear differential equations instead of seeking for analytic solutions, preferring numerical solutions is a more frequently used procedure. Finite difference method is a commonly used numerical solution method. In these equations using velocity and pressure gradients instead of stress tensors decreases the number of unknowns. Also, continuity equation, by integrating the system, number of equations is obtained as number of unknowns. In this situation, velocity and pressure components emerge as two important parameters. In the solution of differential equation system, velocities and pressures must be solved together. However, in the considered grid system, when pressure and velocity values are jointly solved for the same nodal points some problems confront us. To overcome this problem, using staggered grid system is a referred solution method. For the computerized solutions of the staggered grid system various algorithms were developed. From these, two most commonly used are SIMPLE and SIMPLER algorithms. In this study Navier-Stokes equations were numerically solved for Newtonian flow, whose mass or gravitational forces were neglected, for incompressible and laminar fluid, as a hydro dynamically fully developed region and in two dimensional cartesian coordinate system. Finite difference method was chosen as the solution method. This is a parametric study in which varying values of velocity components, pressure and Reynolds numbers were used. Differential equations were discritized using central difference and hybrid scheme. The discritized equation system was solved by Gauss-Siedel iteration method. SIMPLE and SIMPLER were used as solution algorithms. The obtained results, were compared for central difference and hybrid as discritization methods. Also, as solution algorithm, SIMPLE algorithm and SIMPLER algorithm were compared to each other. As a result, it was observed that hybrid discritization method gave better results over a larger area. Furthermore, as computer solution algorithm, besides some disadvantages, it can be said that SIMPLER algorithm is more practical and gave result in short time. For this study, a code was developed in DELPHI programming language. The values obtained in a computer program were converted into graphs and discussed. During sketching, the quality of the graph was increased by adding intermediate values to the obtained result values using Lagrange interpolation formula. For the solution of the system, number of grid and node was found as an estimated. At the same time, to indicate that the obtained results are satisfactory enough, by doing independent analysis from the grid (GCI analysis) for coarse, medium and fine grid system solution domain was obtained. It was observed that when graphs and program outputs were compared with similar studies highly satisfactory results were achieved.

Keywords: finite difference method, GCI analysis, numerical solution of the Navier-Stokes equations, SIMPLE and SIMPLER algoritms

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Authors: Abeer Toheed Quadri, Maria Abubakar, Mehreen Sirshar

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Component Based Software Development (CBSD) is a new trend in software development. Selection of quality components is not enough to ensure software quality in Component Based Software System (CBSS). A software product is considered to be a quality product if it satisfies its customer’s needs and has minimum defects. Authors’ survey different research papers and analyzes various techniques which ensure software quality in component based software development. This paper includes an investigation about how to improve the quality of a component based software system without effecting quality attributes. The reported information is identified from literature survey. The developments of component based systems are rising as they reduce the development time, effort and cost by means of reuse. After analysis, it has been explored that in order to achieve the quality in a CBSS we need to have the components that are certified through software measure because the predictability of software quality attributes of system depend on the quality attributes of the constituent components, integration process and the framework used.

Keywords: CBSD (component based software development), CBSS (component based software system), quality components, SQA (software quality assurance)

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Authors: Angela Justina Kumalaputri

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Indonesia, as a maritime country, has abundant marine living resources yet has not been optimally utilized. So far, we only focusing on fisheries. In the other hand, Indonesia, as the country with the fourth longest coastline, is a very good cultivation place for microalgae. Microalgae can be diversified to many important products, such as food, fuel, pharmaceutical products, functional food, and cosmetics.This research is focusing on the literature study about types of microalgae as sources for functional foods (such as antioxidants), including the contents and the separation methods. The research methods which we use are: (1) Literature study about various microalgaes (2) Literature study about extractions using supercritical fluid of CO₂, which are free from toxic organic solvents, environmentally friendly, and safe for food products. Supercritical fluid extraction using CO₂ (low critical points: temperature at 31.1 oC and pressure at 72.9 bars) could be done at a low temperature which are suitable for temperature labile compounds, low energy, and faster extraction time compared with conventional method of extraction.

Keywords: antioxidants, supercritical fluid extraction, solvent-free extraction, microalgae

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Authors: Armenuhi Ghazaryan, Qnarik Poghosyan, Tadevos Markosyan

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We have considered the high-order harmonic generation in-plane graphene quantum dots of hexagonal shape by the independent quasiparticle approximation-tight binding model. We have investigated how such a nonlinear effect is affected by a strong optical wave field, quantum dot typical band gap and lateral size, and dephasing processes. The equation of motion for the density matrix is solved by performing the time integration with the eight-order Runge-Kutta algorithm. If the optical wave frequency is much less than the quantum dot intrinsic band gap, the main aspects of multiphoton high harmonic emission in quantum dots are revealed. In such a case, the dependence of the cutoff photon energy on the strength of the optical pump wave is almost linear. But when the wave frequency is comparable to the bandgap of the quantum dot, the cutoff photon energy shows saturation behavior with an increase in the wave field strength.

Keywords: strong wave field, multiphoton, bandgap, wave field strength, nanostructure

Procedia PDF Downloads 134

Authors: Ifa Sirrhu Samsudin, Ramalinggam Rajamanickam, Rohaida Nordin

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The practice of chain remand would cause human rights violations if the application was granted without reasonable cause and reason. This chain remand problem was tried to be addressed in 2007, which was amongst the factors that led to the amendment of the Criminal Procedure Code (CPC) at that time due to the defilement of human liberty. In Malaysia, there are governmental and non-governmental bodies that are active in ensuring that the human rights of the entire community are protected from being violated. The issue of wrongful detention involving chain remand during an investigation is not a new issue. This issue is constantly highlighted and efforts to address it are often raised by the responsible parties. This study aims to analyse the roles of these bodies in dealing with chain remand complaints in Malaysia using a qualitative research approach by way of in-depth interviews, roundtable discussions and documents analysis. The study discovered that these bodies were able to investigate the complaints but did not have a role in taking any actions. Their role is only to provide recommendations to the complainants to take action. Therefore, this study suggested the function should be given to certain bodies to curb the problem based on solid evidence.

Keywords: liberty, complaints, chain remand, government

Procedia PDF Downloads 169

Authors: Neda Mehdipour, Mohammad Hasan Gerami, Reza Rahnama, Ali Hamzehpour, Hanieh Nemati

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Laurencia caspica (red macroalgae) Enteromorpha intestinalis and Cladophora glomerata (green macroalgae) are three major macroalgae that grow along the southern coasts of the Caspian Sea. We investigated spatial and temporal variation of these three macroalgal species on hard substrates and their relation with environmental factors in 2014. Sampling was done seasonally from spring to winter 2014 from eight sites. Results indicated that of these three species had heterogeneity distribution along southern parts of the Caspian Sea. In addition, C. glomerata was dominant taxa in all stations and had maximum contribution in dissimilarities between sampling sites. According to BIO-ENV salinity, pH and Silicate were the best subset variables for explaining changes in the abundance over time of the hard-substrates macroalgae fauna under study. However, the position of species in Redundancy Analysis (RDA) plot revealed that L. caspica associated with temperature, E. intestinalis with pH and C. glomerata associated with phosphate and silicate.

Keywords: macroalgae, distribution, environmental factors, Caspian Sea

Procedia PDF Downloads 362

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

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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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Authors: Francesco Coraci, Abdul-Hadi G. Abulrub

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Digital technology is transforming the landscape of the industrial sector at a precedential level by connecting people, processes, and machines in real-time. It represents the means for a new pathway to achieve innovative, dynamic competitive advantages, deliver unique customers’ values, and sustain critical relationships. Thus, success in a constantly changing environment is governed by the ability of an organization to revolutionize their business models, deliver innovative solutions, and capture values from big data analytics and insights. Businesses need to re-strategize operations and develop extra capabilities to cope with the necessity for additional flexibility and agility. The traditional “command and control” leadership style is structurally and operationally incompatible with the digital era. In this paper, the authors discuss how transformational leaders can act as a glue in the social, organizational context, which is crucial to enable the workforce and develop a psychological attachment to the digital vision.

Keywords: internet of things, strategy, change leadership, dynamic competitive advantage, digital transformation

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Authors: Piedad Garrido, Fernando Repulles, Andy Bloor, Julio A. Sanguesa, Jesus Gallardo, Vicente Torres, Jesus Tramullas

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With the emergence and development of Information and Communications Technologies (ICTs), Higher Education is experiencing rapid changes, not only in its teaching strategies but also in student’s learning skills. However, we have noticed that students often have difficulty when seeking innovative, useful, and interesting learning resources for their work. This is due to the lack of supervision in the selection of good query tools. This paper presents AINA, an Information Retrieval (IR) computer system aimed at providing motivating and stimulating content to both students and teachers working on different areas and at different educational levels. In particular, our proposal consists of an open virtual resource environment oriented to the vast universe of Disney comics and cartoons. Our test suite includes Disney’s long and shorts films, and we have performed some activities based on the Just In Time Teaching (JiTT) methodology. More specifically, it has been tested by groups of university and secondary school students.

Keywords: information retrieval, animation, educational resources, JiTT

Procedia PDF Downloads 330

Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

Procedia PDF Downloads 26

Authors: Dipanshu Sur, Ratnabali Chakravorty, Rimi Pal, Siddhartha Chatterjee, Joyshree Chaterjee, Amal Mallik

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Background: Polycystic ovary syndrome (PCOS) is a common endocrine disease in reproductive women with a complex hormonal disturbance that affects the menstrual cycle and leads to metabolic consequences in later life. Hyperandrogenaemia is noticeable features of PCOS and influence the process of folliculogenesis in women. The levels of Antimüllerian Hormone (AMH) reflect the number of pre-antral follicles and thus are a marker of oocyte pool – germinal reserve of the ovary for reproduction. Besides its utilization in IVF (In-vitro fertilization), determination of AMH may serve as an additional marker in the diagnostics of PCOS, where increased AMH levels reflect the severity of the disease. The positive correlation of serum AMH with the number of antral follicles was found also in patients with PCOS. Objective: The objective of this study was to investigate the relationship between AMH androgens and whether AMH contributes to altered folliculogenesis in non-obese women with PCOS. Methods: We designed a prospective study which included a total of 65 IVF individuals. It enrolled 26 cases of PCOS based on 2003 Rotterdam criteria and 39 ovulatory normal- non PCOS, healthy, age-matched controls. AMH levels and ovarian morphology were assessed. The relationships between AMH and androgenaemia in patients with and without PCOS were studied. Results: Mean age of PCOS patients were slightly higher than controls (32±4 and 28±3 years, respectively). AMH generally increased with antral follicle count (AFC) [P=0.001], testosterone, and luteinising hormone, and decreased with age, and serum sex hormone binding globulin (SHBG). No significant relationships were found between circulating AMH levels and BMI between PCOS and non-PCOS patients. The calculation of AMH production per antral follicle (AMH/AF) showed that there was a significant difference in median AMH/AF between PCOS and non-PCOS (P =0.001). Both PCOS and non-PCOS groups showed a very similar increase in AMH with increases in AFC, but the PCOS patients had consistently higher AMH across all AFC levels. Conclusions: These observations indicate that there is a connection between AMH and androgens levels between PCOS and non-PCOS East Indian women. Excessive granulosa cell activity may be implicated in the abnormal follicular dynamic of the syndrome. They are higher in women with PCOS and, on the other hand, very low in women with an ovarian failure.

Keywords: anti-Mullerian hormone, polycystic ovary syndrome, antral follicle count, androgens

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Authors: Hamed Ahari, Sepideh Farokhi, Mohamad Reza Abedini

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This paper focuses on inactivation of the growth of the bacterial mixture, Salmonella enteritidis, Staphylococcus aureus, Bacillus cereus and Escherichia coli, experimentally subjected to the chicken eggshell by two types of nano particle-Ag, composite film and colloidal spray carried out at concentrations of 500, 1000 and 2000 ppm over 28 days. The GLM, Repeated Measurement-ANOVA procedure was used to analyze the effect of time and concentration of nano groups on inactivation of bacteria, simultaneously. The maximum reduction of the bacterial growth was respected to the group “spray 2000 ppm” for which the value of the bacteria reached the minimum (0.93±0.42) on day 7, calculated to be 0.0 on days14 and 28 and followed by the group “spray 1000 ppm”. It was obviously concluded that increasing the dilution of nano coating in spray and film created a significant decrease in the number of bacteria colonies on the eggshells but the effect of packaging in different concentrations of nanocomposite was not statistically significant in different days of the study.

Keywords: nano particle, composite film, eggshell, bacteria

Procedia PDF Downloads 382

Authors: Laura Brennan, Ram Balakumar

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ChatGPT has been developed by Open AI (Nov 2022) as a powerful artificial intelligence (AI) language model which has been designed to produce human-like text from user written prompts. To gain the most from the system, user written prompts must give context specific information. This article aims to give guidance on how to optimise the ChatGPT system in the context of education for otolaryngology. Otolaryngology is a specialist field which sees little time dedicated to providing education to both medical students and doctors. Additionally, otolaryngology trainees have seen a reduction in learning opportunities since the COVID-19 pandemic. In this article we look at these various barriers to medical education in Otolaryngology training and suggest ways that ChatGPT can overcome them and assist in simulation-based training. Examples provide how this can be achieved using the Authors’ experience to further highlight the practicalities. What this article has found is that while ChatGPT cannot replace traditional mentorship and practical surgical experience, it can serve as an invaluable supplementary resource to simulation based medical education in Otolaryngology.

Keywords: artificial intelligence, otolaryngology, surgical training, medical education

Procedia PDF Downloads 138

Authors: Ahmed Elaksher, Islam Omar

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Accurate geometric relation algorithms are imperative in Earth and planetary satellite and aerial image processing, particularly for high-resolution images that are used for topographic mapping. Most of these satellites carry push-broom sensors. These sensors are optical scanners equipped with linear arrays of CCDs. These sensors have been deployed on most EOSs. In addition, the LROC is equipped with two push NACs that provide 0.5 meter-scale panchromatic images over a 5 km swath of the Moon. The HiRISE carried by the MRO and the HRSC carried by MEX are examples of push-broom sensor that produces images of the surface of Mars. Sensor models developed in photogrammetry relate image space coordinates in two or more images with the 3D coordinates of ground features. Rigorous sensor models use the actual interior orientation parameters and exterior orientation parameters of the camera, unlike approximate models. In this research, we generate a generic push-broom sensor model to process imageries acquired through linear array cameras and investigate its performance, advantages, and disadvantages in generating topographic models for the Earth, Mars, and the Moon. We also compare and contrast the utilization, effectiveness, and applicability of available photogrammetric techniques and softcopies with the developed model. We start by defining an image reference coordinate system to unify image coordinates from all three arrays. The transformation from an image coordinate system to a reference coordinate system involves a translation and three rotations. For any image point within the linear array, its image reference coordinates, the coordinates of the exposure center of the array in the ground coordinate system at the imaging epoch (t), and the corresponding ground point coordinates are related through the collinearity condition that states that all these three points must be on the same line. The rotation angles for each CCD array at the epoch t are defined and included in the transformation model. The exterior orientation parameters of an image line, i.e., coordinates of exposure station and rotation angles, are computed by a polynomial interpolation function in time (t). The parameter (t) is the time at a certain epoch from a certain orbit position. Depending on the types of observations, coordinates, and parameters may be treated as knowns or unknowns differently in various situations. The unknown coefficients are determined in a bundle adjustment. The orientation process starts by extracting the sensor position and, orientation and raw images from the PDS. The parameters of each image line are then estimated and imported into the push-broom sensor model. We also define tie points between image pairs to aid the bundle adjustment model, determine the refined camera parameters, and generate highly accurate topographic maps. The model was tested on different satellite images such as IKONOS, QuickBird, and WorldView-2, HiRISE. It was found that the accuracy of our model is comparable to those of commercial and open-source software, the computational efficiency of the developed model is high, the model could be used in different environments with various sensors, and the implementation process is much more cost-and effort-consuming.

Keywords: photogrammetry, push-broom sensors, IKONOS, HiRISE, collinearity condition

Procedia PDF Downloads 53

Authors: Latef M. Ali, Farah A. Abed, Zheen L. Mohammed

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In this paper, the effect of the Barium fluoride (BaF2) layer on the absorption efficiency of GaAs/InAs nanowire solar cells was investigated using the finite difference time domain (FDTD) method. By inserting the BaF2 as antireflection with the dominant size of 10 nm to fill the space between the shells of wires on the Si (111) substrate. The absorption is significantly improved due to the strong reabsorption of light reflected at the shells and compared with the reference cells. The present simulation leads to a higher absorption efficiency (Qabs) and reaches a value of 97%, and the external quantum efficiencies (EQEs) above 92% are observed. The current density (Jsc) increases by 0.22 mA/cm2 and the open-circuit voltage (Voc) is enhanced by 0.11 mV. it explore the design and optimization of high-efficiency solar cells on low-reflective absorption efficiency of GaAs/InAs using simulation software tool. The changes in the core and shell diameters profoundly affects the generation and recombination process, thus affecting the conversion efficiency of solar cells.

Keywords: nanowire solar cells, absorption efficiency, photovoltaic, band structures, FDTD simulation

Procedia PDF Downloads 37

Authors: Derrick Boakye Boadu, Zahra Fakhri

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Transformational leaders are the catalyst of change and focus more importantly on members or followers. Involvement of transformational leadership style in organizational structures can provide interesting nuances to the implementation and enhancement of citizen and customer participation mechanisms in an organization regardless of the time consuming, cost, and delaying process of analyzing the feedback of workers and citizens/customers which stifles good outcome of organization’s department performance. It posits that transformational leadership has a positive direct effect on organization-departmental performance and the intervening role of citizen and customer participation and internal communication. Using the NASP-IV 2007 data, the article finds support for the five hypotheses in a structural equation model, and the findings show that transformational leadership does have a direct impact on organizational-departmental performance a partial mediation effect of the relationship through the role of internal communication and citizen and customer participation.  

Keywords: transformational leaders, departmental performance, internal communication, citizen/customer participation

Procedia PDF Downloads 103

Authors: Hao-Hsiang Ku, Ching-Ho Chi

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Big data applications have become an imperative for many fields. Many researchers have been devoted into increasing correct rates and reducing time complexities. Hence, the study designs and proposes an Ontology-based backpropagation neural network classification and reasoning strategy for NoSQL big data applications, which is called ON4NoSQL. ON4NoSQL is responsible for enhancing the performances of classifications in NoSQL and SQL databases to build up mass behavior models. Mass behavior models are made by MapReduce techniques and Hadoop distributed file system based on Hadoop service platform. The reference engine of ON4NoSQL is the ontology-based backpropagation neural network classification and reasoning strategy. Simulation results indicate that ON4NoSQL can efficiently achieve to construct a high performance environment for data storing, searching, and retrieving.

Keywords: Hadoop, NoSQL, ontology, back propagation neural network, high distributed file system

Procedia PDF Downloads 249

Authors: Lito M. Amit, Venecio U. Ultra, Young-Woong Song

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The business process outsourcing (BPO) in the Philippines is expanding rapidly attracting more than 2% of total employment. Currently, the BPO industry is confronted with several issues pertaining to sustainable productivity such as meeting the staffing gap, high rate of employees’ turnover and workforce retention, and the occupational health and safety (OHS) of call center agents. We conducted a survey of OHS programs and health concerns among call center agents in the Philippines and determined the sociocultural factors that affect the vulnerability of call center agents to occupational health risks and hazards. The majority of the agents affirmed that OHS are implemented and OHS orientation and emergency procedures were conducted at employment initiations, perceived favorable and convenient working environment except for occasional noise disturbances and acoustic shock, visual, and voice fatigues. Male agents can easily adjust to the demands and changes in their work environment and flexible work schedules than female agents. Female agents have a higher tendency to be pressured and humiliated by low work performance, experience a higher incidence of emotional abuse, psychological abuse, and experience more physical stress than male agents. The majority of the call center agents had a night-shift schedule and regardless of other factors, night shift work brings higher stress to agents. While working in a call center, higher incidence of headaches and insomnia, burnout, suppressed anger, anxiety, and depressions were experienced by female, younger (21-25 years old) and those at night shift than their counterpart. Most common musculoskeletal disorders include body pain in the neck, shoulders and back; and hand and wrist disorders and these are commonly experienced by female and younger workers. About 30% experienced symptoms of cardiovascular and gastrointestinal disorders and weakened immune systems. Overall, these findings have shown the variable vulnerability by a different subpopulation of call center agents and are important in the occupational health risk prevention and management towards a sustainable human resource for BPO industry in the Philippines.

Keywords: business process outsourcing industry, health risk of call center agents, socio-cultural determinants, Philippines

Procedia PDF Downloads 482

Authors: Sezin Ekşioğlu

Abstract:

Multilabel classification has a huge importance for several applications, it is also a challenging research topic. It is a kind of supervised learning that contains binary targets. The distance between multilabel and binary classification is having more than one class in multilabel classification problems. Features can belong to one class or many classes. There exists a wide range of applications for multi label prediction such as image labeling, text categorization, gene functionality. Even though features are classified in many classes, they may not always be properly classified. There are many ensemble methods for the classification. However, most of the researchers have been concerned about better multilabel methods. Especially little ones focus on both efficiency of classifiers and pairwise relationships at the same time in order to implement better multilabel classification. In this paper, we worked on modified ensemble methods by getting benefit from k-Nearest Neighbors and neural network structure to address issues within a beneficial way and to get better impacts from the multilabel classification. Publicly available datasets (yeast, emotion, scene and birds) are performed to demonstrate the developed algorithm efficiency and the technique is measured by accuracy, F1 score and hamming loss metrics. Our algorithm boosts benchmarks for each datasets with different metrics.

Keywords: multilabel, classification, neural network, KNN

Procedia PDF Downloads 141