Search results for: forecast accuracy unemployment rate

Authors: Adekunle Adesina, Dorcas Adesina

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This Research investigated the influence of alcohol consumption on attention in Wister albino rats. It was designed to test whether or not alcohol consumption affected visual and auditory attention. The sample of this study comprise of 3males albino rats and 3 females albino rats which were randomly assigned to 3 (male/female each) groups, 1, 2 and 3. The first group which was experimental Group 1 received 4ml of alcohol ingestion with cannula twice daily (morning and evening). The second group which was experimental group 2 received 2ml of alcohol ingestion with cannula twice daily (morning and evening). Third group which was the control group only received water (placebo), all these happened within a period of 2 days. Three hypotheses were advanced and testedf in the study. Hypothesis 1 stated that there will be no significant difference between the response speed of albino rats that consume alcohol and those that consume water on visual attention using 5-CSRTT. This was confirmed (DF (2, 9) = 0.72, P <.05). Hypothesis 2 stated that albino rats who consumed alcohol will perform better than those who consume water on auditory accuracy using 5-CSRTT. This was also tested but not confirmed (DF (2, 9) = 2.10, P< .05). The third hypothesis which stated that female albino rats who consumed alcohol would not perform better than male albino rats who consumed alcohol on auditory accuracy using 5-CSRTT was tested and not confirmed. (DF (4) = 0.17, P < .05). Data was analyzed using one-way ANOVA and T-test for independent measures. It was therefore recommended that government policies and programs should be directed at reducing to the barest minimum the rate of alcohol consumption especially among males as it is detrimental to the human auditory attentional organ.

Keywords: alcohol, attention, influence, rats, Wistar

Procedia PDF Downloads 257

Authors: Fernando Maass, Pablo Martin, Jorge Olivares

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The Bessel function J₀(x) is very important in Electrodynamics and Physics, as well as its zeros. In this work, a method to obtain high accuracy approximation is presented through an application to that function. In most of the applications of this function, the values of the zeros are very important. In this work, analytic approximations for this function have been obtained valid for all positive values of the variable x, which have high accuracy for the function as well as for the zeros. The approximation is determined by the simultaneous used of the power series and asymptotic expansion. The structure of the approximation is a combination of two rational functions with elementary functions as trigonometric and fractional powers. Here us in Pade method, rational functions are used, but now there combined with elementary functions us fractional powers hyperbolic or trigonometric functions, and others. The reason of this is that now power series of the exact function are used, but together with the asymptotic expansion, which usually includes fractional powers trigonometric functions and other type of elementary functions. The approximation must be a bridge between both expansions, and this can not be accomplished using only with rational functions. In the simplest approximation using 4 parameters the maximum absolute error is less than 0.006 at x ∼ 4.9. In this case also the maximum relative error for the zeros is less than 0.003 which is for the second zero, but that value decreases rapidly for the other zeros. The same kind of behaviour happens for the relative error of the maximum and minimum of the functions. Approximations with higher accuracy and more parameters will be also shown. All the approximations are valid for any positive value of x, and they can be calculated easily.

Keywords: analytic approximations, asymptotic approximations, Bessel functions, quasirational approximations

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Authors: Migael van Zyl, Stefanie Visser, Awelani Phaswana

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The electricity landscape in South Africa is characterized by frequent occurrences of loadshedding, a measure implemented by Eskom to manage electricity generation shortages by curtailing demand. Loadshedding, classified into stages ranging from 1 to 8 based on severity, involves the systematic rotation of power cuts across municipalities according to predefined schedules. However, this practice introduces distortions in recorded electricity demand, posing challenges to accurate forecasting essential for budgeting, network planning, and generation scheduling. Addressing this challenge requires the development of a methodology to quantify the impact of loadshedding and integrate it back into metered electricity demand data. Fortunately, comprehensive records of loadshedding impacts are maintained in a database, enabling the alignment of Loadshedding effects with hourly demand data. This adjustment ensures that forecasts accurately reflect true demand patterns, independent of loadshedding's influence, thereby enhancing the reliability of electricity supply management in South Africa. This paper presents a methodology for determining the hourly impact of load scheduling and subsequently adjusting historical demand data to account for it. Furthermore, two forecasting models are developed: one utilizing the original dataset and the other using the adjusted data. A comparative analysis is conducted to evaluate forecast accuracy improvements resulting from the adjustment process. By implementing this methodology, stakeholders can make more informed decisions regarding electricity infrastructure investments, resource allocation, and operational planning, contributing to the overall stability and efficiency of South Africa's electricity supply system.

Keywords: electricity demand forecasting, load shedding, demand side management, data science

Procedia PDF Downloads 56

Authors: H. A. Alzomor, B. K. Ouda, A. M. Eldeib

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Successful regional anesthesia depends upon precise location of the peripheral nerve or nerve plexus. Locating peripheral nerves is preferred to be done using nerve stimulation. In order to generate a nerve impulse by electrical means, a minimum threshold stimulus of current “rheobase” must be applied to the nerve. The technique depends on stimulating muscular twitching at a close distance to the nerve without actually touching it. Success rate of this operation depends on the accuracy of current intensity pulses used for stimulation. In this paper, we will discuss a circuit and algorithm for closed loop control for the current, theoretical analysis and test results and compare them with previous techniques.

Keywords: Close Loop Control (CLC), constant current, nerve locator, rheobase

Procedia PDF Downloads 250

Authors: Toshifumi Hiramatsu, Satoshi Morita, Manuel Pencelli, Marta Niccolini, Matteo Ragaglia, Alfredo Argiolas

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Automation technologies for agriculture field are needed to promote labor-saving. One of the most relevant problems in automated agriculture is represented by controlling the robot along a predetermined path in presence of rough terrain or incline ground. Unfortunately, disturbances originating from interaction with the ground, such as slipping, make it quite difficult to achieve the required accuracy. In general, it is required to move within 5-10 cm accuracy with respect to the predetermined path. Moreover, lateral velocity caused by gravity on the incline field also affects slipping. In this paper, a path-tracking controller for tracked mobile robots moving on rough terrains of incline field such as vineyard is presented. The controller is composed of a disturbance observer and an adaptive controller based on the kinematic model of the robot. The disturbance observer measures the difference between the measured and the reference yaw rate and linear velocity in order to estimate slip. Then, the adaptive controller adapts “virtual” parameter of the kinematics model: Instantaneous Centers of Rotation (ICRs). Finally, target angular velocity reference is computed according to the adapted parameter. This solution allows estimating the effects of slip without making the model too complex. Finally, the effectiveness of the proposed solution is tested in a simulation environment.

Keywords: the agricultural robot, autonomous control, path-tracking control, tracked mobile robot

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Authors: J. B. Clapp, S. Croarkin, C. Dolphin, S. K. Lyons

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Chronic pain or stress in farm animals impacts both on their welfare and productivity. Measuring chronic pain or stress can be problematic using hormonal or behavioural changes because hormones are modulated by homeostatic mechanisms and observed behaviour can be highly subjective. We propose that heart rate variability (HRV) can quantify chronic pain or stress in farmed animal and represents a more robust and objective measure of their welfare.

Keywords: dairy calf, welfare, heart rate variability, non-invasive, biomonitor

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Authors: Md. Shahriar Sabuz

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Bangladesh, a South Asian developing country, has experienced an increasing rate of contraceptive use in the last few decades. But one-third of the pregnancies are still unintended, and the fertility rate surpasses the desired rate of children. It may be because of the discontinuation of the use of contraceptive methods. So, it is necessary to find out the reasons for the discontinuation of the use of contraceptives. Moreover, the rate of contraception discontinuation varies from rural to urban, region to region. In this study, our objectives are to find out the reasons behind the discontinuation of the use of the contraceptive method, and the regional variations of the rate of those reasons. We are using the dataset of Bangladesh Demographic and Health Surveys (BDHS) 2014 for this study and the ever-married women of Bangladesh who have discontinued the use of contraceptive methods aged 15-49. The data was collected from the seven districts of the country. The finding shows that currently there are 23% of women have stopped using their contraception. The most common reasons for stopping using the method are that either they are pregnant or want to be pregnant. A significant number of people are not using the contraceptive method because of the fear of side effects. Though the rate of non-user is higher in rural areas than in urban areas, reasons for method discontinuation are not significantly different between urban and rural areas. However, reasons for discontinuing contraceptive methods significantly vary from region to region.

Keywords: discontinuation of contraceptive, health, pregnant, fertility

Procedia PDF Downloads 94

Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

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This paper introduces a methodology for advancing Italian speech vowels landmark detection within the distinctive feature-based speech recognition domain. Leveraging the legacy tool 'xkl' by integrating combined convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the study presents a comprehensive enhancement to the 'xkl' legacy software. This integration incorporates re-assigned spectrogram methodologies, enabling meticulous acoustic analysis. Simultaneously, our proposed model, integrating combined CNNs and RNNs, demonstrates unprecedented precision and robustness in landmark detection. The augmentation of re-assigned spectrogram fusion within the 'xkl' software signifies a meticulous advancement, particularly enhancing precision related to vowel formant estimation. This augmentation catalyzes unparalleled accuracy in landmark detection, resulting in a substantial performance leap compared to conventional methods. The proposed model emerges as a state-of-the-art solution in the distinctive feature-based speech recognition systems domain. In the realm of deep learning, a synergistic integration of combined CNNs and RNNs is introduced, endowed with specialized temporal embeddings, harnessing self-attention mechanisms, and positional embeddings. The proposed model allows it to excel in capturing intricate dependencies within Italian speech vowels, rendering it highly adaptable and sophisticated in the distinctive feature domain. Furthermore, our advanced temporal modeling approach employs Bayesian temporal encoding, refining the measurement of inter-landmark intervals. Comparative analysis against state-of-the-art models reveals a substantial improvement in accuracy, highlighting the robustness and efficacy of the proposed methodology. Upon rigorous testing on a database (LaMIT) speech recorded in a silent room by four Italian native speakers, the landmark detector demonstrates exceptional performance, achieving a 95% true detection rate and a 10% false detection rate. A majority of missed landmarks were observed in proximity to reduced vowels. These promising results underscore the robust identifiability of landmarks within the speech waveform, establishing the feasibility of employing a landmark detector as a front end in a speech recognition system. The synergistic integration of re-assigned spectrogram fusion, CNNs, RNNs, and Bayesian temporal encoding not only signifies a significant advancement in Italian speech vowels landmark detection but also positions the proposed model as a leader in the field. The model offers distinct advantages, including unparalleled accuracy, adaptability, and sophistication, marking a milestone in the intersection of deep learning and distinctive feature-based speech recognition. This work contributes to the broader scientific community by presenting a methodologically rigorous framework for enhancing landmark detection accuracy in Italian speech vowels. The integration of cutting-edge techniques establishes a foundation for future advancements in speech signal processing, emphasizing the potential of the proposed model in practical applications across various domains requiring robust speech recognition systems.

Keywords: landmark detection, acoustic analysis, convolutional neural network, recurrent neural network

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Authors: Rami Rami Mahmoud Bakr

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The constant rate of strain (CRS) test is a rapid technique that effectively measures specific properties of cohesive soil, including the rate of consolidation, hydraulic conductivity, compressibility, and stress history. Its simple operation and frequent readings enable efficient definition, especially of the compression curve. However, its limitations include an inability to handle strain-rate-dependent soil behavior, initial transient conditions, and pore pressure evaluation errors. There are currently no effective techniques for interpreting CRS data. In this study, experiments were performed to evaluate the effects of different parameters on CRS results. Extensive tests were performed on two types of clay to analyze the soil behavior during strain consolidation at a constant rate. The results were used to evaluate the transient conditions and pore pressure system.

Keywords: constant rate of strain (CRS), resedimented boston blue clay (RBBC), resedimented vicksburg buckshot clay (RVBC), compression index

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Authors: Cristian Chacha, David Asiain, Jesús Ponce de León, José Ramón Beltrán

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This work explores and characterizes the behavior of the AFE AD5941 in impedance measurement using an embedded algorithm with a constant current AC source. The main aim of this research is to improve the exact measurement of impedance values for their application in EDA-focused wearable devices. Through comprehensive study and characterization, it has been observed that employing a measurement sequence with a constant current source produces results with increased dispersion but higher accuracy. As a result, this approach leads to a more accurate system for impedance measurement.

Keywords: EDA, constant current AC source, wearable, precision, accuracy, impedance

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Authors: Mehmet Erdi Korkmaz, Mustafa Günay

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Nowadays, grinding is frequently replaced with hard turning for reducing set up time and higher accuracy. This paper focused on mathematical modeling of average surface roughness (Ra) in hard turning of AISI L2 grade (DIN 1.2210) cold work tool steel with ceramic tools. The steel was hardened to 60±1 HRC after the heat treatment process. Cutting speed, feed rate, depth of cut and tool nose radius was chosen as the cutting conditions. The uncoated ceramic cutting tools were used in the machining experiments. The machining experiments were performed according to Taguchi L27 orthogonal array on CNC lathe. Ra values were calculated by averaging three roughness values obtained from three different points of machined surface. The influences of cutting conditions on surface roughness were evaluated as statistical and experimental. The analysis of variance (ANOVA) with 95% confidence level was applied for statistical analysis of experimental results. Finally, mathematical models were developed using the artificial neural networks (ANN). ANOVA results show that feed rate is the dominant factor affecting surface roughness, followed by tool nose radius and cutting speed.

Keywords: ANN, hard turning, DIN 1.2210, surface roughness, Taguchi method

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Authors: Mohd Asrul Affendi Bin Abdullah

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Sample size calculation is especially important for zero inflated models because a large sample size is required to detect a significant effect with this model. This paper verify how to present percentage of power approximation for categorical and then extended to zero inflated models. Wald test was chosen to determine power sample size of AIDS death rate because it is frequently used due to its approachability and its natural for several major recent contribution in sample size calculation for this test. Power calculation can be conducted when covariates are used in the modeling ‘excessing zero’ data and assist categorical covariate. Analysis of AIDS death rate study is used for this paper. Aims of this study to determine the power of sample size (N = 945) categorical death rate based on parameter estimate in the simulation of the study.

Keywords: power sample size, Wald test, standardize rate, ZINBDR

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Authors: Zina Ghiloufi, Tahar Khir

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A transient three-dimensional computational fluid dynamics (CFD) model is developed to determine the velocity and temperature distribution in different positions cold room during pre-cooling of dates. The turbulence model used is the k-ω Shear Stress Transport (SST) with the standard wall function, the air. The numerical results obtained show that cooling rate is not uniform inside the room; the product at the medium of room has a slower cooling rate. This cooling heterogeneity has a large effect on the energy consumption during cold storage.

Keywords: CFD, cold room, cooling rate, dDates, numerical simulation, k-ω (SST)

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Authors: Eiji Okano, Kazuyuki Inagaki

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We revisit Uribe's `Fiscal Theory of Sovereign Risk' advocating that there is a trade-off between stabilizing inflation and suppressing default. We develop a class of dynamic stochastic general equilibrium (DSGE) model with nominal rigidities and compare two de facto inflation stabilization policies, optimal monetary policy and optimal monetary and fiscal policy with the minimizing interest rate spread policy which completely suppress the default. Under the optimal monetary and fiscal policy, not only the nominal interest rate but also the tax rate work to minimize welfare costs through stabilizing inflation. Under the optimal monetary both inflation and output gap are completely stabilized although those are fluctuating under the optimal monetary policy. In addition, volatility in the default rate under the optimal monetary policy is considerably lower than one under the optimal monetary policy. Thus, there is not the SI-SD trade-off. In addition, while the minimizing interest rate spread policy makes inflation rate severely volatile, the optimal monetary and fiscal policy stabilize both the inflation and the default. A trade-off between stabilizing inflation and suppressing default is not so severe what pointed out by Uribe.

Keywords: sovereign risk, optimal monetary policy, fiscal theory of the price level, DSGE

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Authors: Alexander David Natanson

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This paper focuses on the effect of Sanctuary and Immigration and Customs Enforcement (ICE) policies on local economies. "Sanctuary cities" refers to municipal jurisdictions that limit their cooperation with the federal government's efforts to enforce immigration. Using county-level data from the American Community Survey and ICE data on economic indicators from 2006 to 2018, this study isolates the effects of local immigration policies on U.S. counties. The investigation is accomplished by simultaneously studying the policies' effects in counties where immigrants' families are persecuted via collaboration with Immigration and Customs Enforcement (ICE), in contrast to counties that provide protections. The analysis includes a difference-in-difference & two-way fixed effect model. Results are robust to nearest-neighbor matching, after the random assignment of treatment, after running estimations using different cutoffs for immigration policies, and with a regression discontinuity model comparing bordering counties with opposite policies. Results are also robust after restricting the data to a single-year policy adoption, using the Sun and Abraham estimator, and with event-study estimation to deal with the staggered treatment issue. In addition, the study reverses the estimation to understand what drives the decision to choose policies to detect the presence of reverse causality biases in the estimated policy impact on economic factors. The evidence demonstrates that providing protections to undocumented immigrants increases economic activity. The estimates show gains in per capita income ranging from 3.1 to 7.2, median wages between 1.7 to 2.6, and GDP between 2.4 to 4.1 percent. Regarding labor, sanctuary counties saw increases in total employment between 2.3 to 4 percent, and the unemployment rate declined from 12 to 17 percent. The data further shows that ICE policies have no statistically significant effects on income, median wages, or GDP but adverse effects on total employment, with declines from 1 to 2 percent, mostly in rural counties, and an increase in unemployment of around 7 percent in urban counties. In addition, results show a decline in the foreign-born population in ICE counties but no changes in sanctuary counties. The study also finds similar results for sanctuary counties when separating the data between urban, rural, educational attainment, gender, ethnic groups, economic quintiles, and the number of business establishments. The takeaway from this study is that institutional inclusion creates the dynamic nature of an economy, as inclusion allows for economic expansion due to the extension of fundamental freedoms to newcomers. Inclusive policies show positive effects on economic outcomes with no evident increase in population. To make sense of these results, the hypothesis and theoretical model propose that inclusive immigration policies play an essential role in conditioning the effect of immigration by decreasing uncertainties and constraints for immigrants' interaction in their communities, decreasing the cost from fear of deportation or the constant fear of criminalization and optimize their human capital.

Keywords: inclusive and exclusive institutions, post matching, fixed effect, time trend, regression discontinuity, difference-in-difference, randomization inference and sun, Abraham estimator

Procedia PDF Downloads 79

Authors: Kofi Nkonkonya Mpuangnan, Samantha Govender, Hlengiwe Romualda Mhlongo

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In recent years, a noticeable and worrisome pattern has emerged in numerous developing nations which is a steady and persistent rise in unemployment rates. This escalation of economic struggles has become a cause of great concern for parents who, having invested significant resources in their children's education, harboured hopes of achieving economic prosperity and stability for their families through secure employment. To effectively tackle this pressing unemployment issue, it is imperative to adopt a holistic approach, and a pivotal aspect of this approach involves incorporating entrepreneurial education seamlessly into the entire educational system. In this light, the authors explored approaches to integrating entrepreneurial education into school curriculum focusing on the following questions. How can an entrepreneurial mindset among learners be promoted in school? And how far have pedagogical approaches improved entrepreneurship in schools? To find answers to these questions, a systematic literature review underpinned by Human Capital Theory was adopted. This method was supported by the three stages of guidelines like planning, conducting, and reporting. The data were specifically sought from publishers with expansive coverage of scholarly literature like Sage, Taylor & Francis, Emirate, and Springer, covering publications from 1965 to 2023. The search was supported by two broad terms such as promoting entrepreneurial mindset in learners and pedagogical strategies for enhancing entrepreneurship. It was found that acquiring an entrepreneurial mindset through an innovative classroom environment, resilience, and guest speakers and industry experts. Also, teachers can promote entrepreneurial education through the adoption of pedagogical approaches such as hands-on learning and experiential activities, role-playing, business simulation games and creative and innovative teaching. It was recommended that the Ministry of Education should develop tailored training programs and workshops aimed at empowering educators with the essential competencies and insights to deliver impactful entrepreneurial education.

Keywords: education, entrepreneurship, school curriculum, pedagogical approaches, integration

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Authors: Lei Lei, Hongbo Zhang, Donald J. Bergstrom, Bing Zhang, K. Y. Song, W. J. Zhang

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This paper presents a model for a modified T-junction device for microspheres generation. The numerical model is developed using a commercial software package: COMSOL Multiphysics. In order to test the accuracy of the numerical model, multiple variables, such as the flow rate of cross-flow, fluid properties, structure, and geometry of the microdevice are applied. The results from the model are compared with the experimental results in the diameter of the microsphere generated. The comparison shows a good agreement. Therefore the model is useful in further optimization of the device and feedback control of microsphere generation if any.

Keywords: CFD modeling, validation, microsphere generation, modified T-junction

Procedia PDF Downloads 698

Authors: D. Tassalit, N. Chekir, O. Benhabiles, N. A. Laoufi, F. Bentahar

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In the setting of the waters purification, some molecules appear recalcitrant to the traditional treatments. The exploitation of the properties of some catalysts permits to amplify the oxidization performances with ultraviolet radiance and to remove this pollution by a non biological way. This study was conducted to investigate the effect of a photocatalysis oxidation system for organic pollutants treatment using a new reactor design and ZnO/TiO2 as a catalyst under UV light. Oxidative degradation of tylosin by hydroxyl radicals (OH°) was studied in aqueous medium using suspended forms of ZnO and TiO2. The results improve that the treatment was affected by many factors such as flow-rate of solution, initial pollutant concentration and catalyst concentration. The rate equation for the tylosin degradation followed first order kinetics and the rate-constants were determined. The reaction rate fitted well with Langmuir–Hinshelwood model and the removed ratio of tylosin was 97 % in less than 60 minutes. To determine the optimum catalyst loading, a series of experiments were carried out by varying the amount of catalyst from 0.05 to 0.5 g/L. The results demonstrate that the rate of photodegradation is optimum with catalyst loading of 0.1 g/L, reaction flow rate of 3.79 mL/s and solution natural pH. The rate was found to increase with the decrease in tylosin concentration from 30 to 5 mg/L. Therefore, this simple photoreactor design for the removal of organic pollutants has the potential to be used in wastewater treatment.

Keywords: advanced oxidation, photocatalysis, TiO2, ZnO, UV light, pharmaceuticals pollutants, Spiramycin, tylosin, wastewater treatment

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: artificial neural networks, breast cancer, classifiers, cervical cancer, f-score, machine learning, precision, recall

Procedia PDF Downloads 274

Authors: J. Y. Tan, L. C. Lum, M. G. Lee, S. Mansouri, K. Hapgood, X. D. Chen, M. W. Woo

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Folic acid (FA) is known to be an important supplement to prevent neural tube defect (NTD) in pregnant women. Similar to some commercial formulations, sodium bicarbonate solution is used as a solvent for FA. This work uses the antisolvent vapor precipitation (AVP), incorporating ethanol vapor as the convective drying medium in place of air to produce branch-like micro-structure FA particles. Interestingly, the dissolution rate of the resultant particle is 2-3 times better than the particle produce from conventional air drying due to the higher surface area of particles produced. The higher dissolution rate could possibly improve the delivery and absorption of FA in human body. This application could potentially be extended to other commercial products, particularly in less soluble drugs to improve its solubility.

Keywords: absorption, antisolvent vapor precipitation, dissolution rate, folic acid

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Authors: Zhihong Luo, Guangbin Zhu, Lulu Guo, Zhujun Lyu, Kun Luo

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Cycling life has become the threshold for the prospective application of Li-O₂ batteries, and the protection of Li anode has recently regarded as the key factor to the performance. Herein, a simple low rate pre-activation (20 cycles at 0.5 Ag⁻¹ and a capacity of 200 mAh g⁻¹) was employed to effectively improve the performance and cyclability of Li-O₂ batteries. The charge/discharge cycles at 1 A g⁻¹ with a capacity of 1000 mAh g⁻¹ were maintained for up to 290 times versus 55 times for the cell without pre-activation. The ultimate battery capacity and high rate discharge property were also largely enhanced. Morphology, XRD and XPS analyses reveal that the performance improvement is in close association with the formation of the smooth and compact surface layer formed on the Li anode after low rate pre-activation, which apparently alleviated the corrosion of Li anode and the passivation of cathode during battery cycling, and the corresponding mechanism was also discussed.

Keywords: lithium oxygen battery, pre-activation, cyclability, capacity

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Authors: Rahul Malhotra, Anurag Sharma

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Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: FTTH, quad play, play service, access networks, data rate

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Authors: Ella Sèdé Maforikan

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Accurate land cover mapping is essential for effective environmental monitoring and natural resources management. This study focuses on assessing the classification performance of two satellite datasets and evaluating the impact of different input feature combinations on classification accuracy in the Beterou catchment, situated in the northern part of Benin. Landsat-8 and Sentinel-2 images from June 1, 2020, to March 31, 2021, were utilized. Employing the Random Forest (RF) algorithm on Google Earth Engine (GEE), a supervised classification categorized the land into five classes: forest, savannas, cropland, settlement, and water bodies. GEE was chosen due to its high-performance computing capabilities, mitigating computational burdens associated with traditional land cover classification methods. By eliminating the need for individual satellite image downloads and providing access to an extensive archive of remote sensing data, GEE facilitated efficient model training on remote sensing data. The study achieved commendable overall accuracy (OA), ranging from 84% to 85%, even without incorporating spectral indices and terrain metrics into the model. Notably, the inclusion of additional input sources, specifically terrain features like slope and elevation, enhanced classification accuracy. The highest accuracy was achieved with Sentinel-2 (OA = 91%, Kappa = 0.88), slightly surpassing Landsat-8 (OA = 90%, Kappa = 0.87). This underscores the significance of combining diverse input sources for optimal accuracy in land cover mapping. The methodology presented herein not only enables the creation of precise, expeditious land cover maps but also demonstrates the prowess of cloud computing through GEE for large-scale land cover mapping with remarkable accuracy. The study emphasizes the synergy of different input sources to achieve superior accuracy. As a future recommendation, the application of Light Detection and Ranging (LiDAR) technology is proposed to enhance vegetation type differentiation in the Beterou catchment. Additionally, a cross-comparison between Sentinel-2 and Landsat-8 for assessing long-term land cover changes is suggested.

Keywords: land cover mapping, Google Earth Engine, random forest, Beterou catchment

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Authors: Etienne Gaborit, Dorothy Durnford, Daniel Deacu, Marco Carrera, Nathalie Gauthier, Camille Garnaud, Vincent Fortin

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A new experimental streamflow forecasting system was recently implemented at the Environment and Climate Change Canada’s (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP). It relies on CaLDAS (Canadian Land Data Assimilation System) for the assimilation of surface variables, and on a surface prediction system that feeds a routing component. The surface energy and water budgets are simulated with the SVS (Soil, Vegetation, and Snow) Land-Surface Scheme (LSS) at 2.5-km grid spacing over Canada. The routing component is based on the Watroute routing scheme at 1-km grid spacing for the Great Lakes and Nelson River watersheds. The system is run in two distinct phases: an analysis part and a forecast part. During the analysis part, CaLDAS outputs are used to force the routing system, which performs streamflow assimilation. In forecast mode, the surface component is forced with the Canadian GEM atmospheric forecasts and is initialized with a CaLDAS analysis. Streamflow performances of this new system are presented over 2019. Performances are compared to the current ECCC’s operational streamflow forecasting system, which is different from the new experimental system in many aspects. These new streamflow forecasts are also compared to persistence. Overall, the new streamflow forecasting system presents promising results, highlighting the need for an elaborated assimilation phase before performing the forecasts. However, the system is still experimental and is continuously being improved. Some major recent improvements are presented here and include, for example, the assimilation of snow cover data from remote sensing, a backward propagation of assimilated flow observations, a new numerical scheme for the routing component, and a new reservoir model.

Keywords: assimilation system, distributed physical model, offline hydro-meteorological chain, short-term streamflow forecasts

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Authors: Thang Minh Le, Hadi Khabbaz

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The coefficient of consolidation is a parameter governing the rate at which saturated soil particularly clay undergoes consolidation when subjected to an increase in pressure. The rate and amount of compression in soil varies with the rate that pore water is lost; and hence depends on soil permeability. Over many years, various methods have been proposed to determine the coefficient of consolidation, cv, which is an indication of the rate of foundation settlement on soft ground. However, defining this parameter is often problematic and heavily relies on graphical techniques, which are subject to some uncertainties. This paper initially presents an overview of many well-established methods to determine the vertical coefficient of consolidation from the incremental loading consolidation tests. An array of consolidation tests was conducted on the undisturbed clay samples, collected at various depths from a site in Nakdong river delta, Busan, South Korea. The consolidation test results on these soft sensitive clay samples were employed to evaluate the targeted methods to predict the settlement rate of Busan clay. In relationship of time-displacement-velocity, a total of 3 method groups from 10 common procedures were classified and compared together. Discussions on study results will be also provided.

Keywords: Busan clay, coefficient of consolidation, constant rate of strain, incremental loading

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Authors: Sebastian Oportus, Fabrizio Alvarez

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3D digitalization of heritage objects is widely used nowadays. However, the most advanced 3D scanners in the market that capture topology and texture at the same time, and are specifically made for this purpose, don’t deliver the accuracy that is needed for scientific research. In the last three years, we have developed a method that combines the use of Metrologic grade laser scans, that allows us to work with a high accuracy topology up to 15 times more precise and combine this mesh with a texture obtained from high definition photogrammetry with up to 100 times more pixel concentrations. The result is an accurate digitalization that promotes heritage preservation, scientific study, high detail reproduction, and digital restoration, among others. In Chile, we have already performed 478 digitalizations of high-value heritage pieces and compared the results with up to five different digitalization methods; the results obtained show a considerable better dimensional accuracy and texture resolution. We know the importance of high precision and resolution for academics and museology; that’s why our proposal is to set a worldwide standard using this open source methodology.

Keywords: 3D digitalization, digital heritage, heritage preservation, digital restauration, heritage reproduction

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Authors: ZeinolAbedin Rahmani, Marzieh Evazi Borazjani, Nooshin Salehi

Abstract:

Organizations are increasingly facing changes and developments scientific, technological, social, cultural changes among these organizations those ones are reckoned successful and effective that in addition to coordinating the development of modern society can forecast future changes and be able to accommodate these changes in order to create favorable developments to build a better future. But we can change that with the changes that occur in the organization of the program it will distinguish. Today's organizations need leaders that change and grow them have to survive. In fact, without transformational managers and leaders, it is certainly difficult to create changes in organizations. Both private and public organizations need to increase knowledge and awareness of the cause widespread changes in the structure, culture and practice for the viability and sustainability of life and growth and development. By now, different signs have determined different causes for a suitable function of employees. However, the important thing is that the commitment of the employees to their organization has always been very important. Since the decrease of organization commitment causes the high rate of absenteeism, turnover intentions, and even to reduce the impact of health staff. and these factors prevent organizations from achieving its goals. If organizations want to retain staff, the organization must find a way to be happy and continue their work with commitment, motivation, and willingness. So here is the need for strong leaders, analysts, creative and transformational upper ranks more than ever is felt. The aim of this study is to revise history, the leadership style of managers shipbuilding company by using the MLQ model.

Keywords: leadership style, managers, organizational, manufacturing company, sustainability of life

Procedia PDF Downloads 489

Authors: Mohammad Anwar, Shah Waliullah

Abstract:

The development of science and technology in the present era has an urgent demand for the training of thinking of undergraduates. This requirement actively promotes research and teaching of basic theories, beneficial to the career development of students. This study clarified the dialectical relation between the thermodynamic equilibrium constant and reaction rate constant through the contrast thinking method. Findings reveal that both the isobaric Van't Hoff equation and the Arrhenius equation had four similar forms, and the change in the trend of both constants showed a similar law. By the derivation of the formation rate constant of the product (KY) and the consumption rate constant of the reactant (KA), the ratio of both constants at the end state indicated the nature of the equilibrium state in agreement with that of the thermodynamic equilibrium constant (K^θ (T)). This study has thus presented that the thermodynamic equilibrium constant contained the characteristics of microscopic dynamics based on the analysis of the reaction mechanism, and both constants are organically connected and unified. The reaction enthalpy and activation energy are closely related to each other with the same connotation.

Keywords: thermodynamic equilibrium constant, reaction rate constant, PBL teaching, dialectical relation, innovative thinking

Procedia PDF Downloads 102

Authors: Ichiro Takahashi

Abstract:

One of the major assumptions of mainstream macroeconomics is the path independence of capital stock. This paper challenges this assumption by employing an agent-based approach. The simulation results showed the existence of multiple "quasi-steady state" equilibria of the capital stock, which may cast serious doubt on the validity of the assumption. The finding would give a better understanding of many phenomena that involve hysteresis, including the causes of poverty. The "market-clearing view" has been widely shared among major schools of macroeconomics. They understand that the capital stock, the labor force, and technology, determine the "full-employment" equilibrium growth path and demand/supply shocks can move the economy away from the path only temporarily: the dichotomy between the short-run business cycles and the long-run equilibrium path. The view then implicitly assumes the long-run capital stock to be independent of how the economy has evolved. In contrast, "Old Keynesians" have recognized fluctuations in output as arising largely from fluctuations in real aggregate demand. It will then be an interesting question to ask if an agent-based macroeconomic model, which is known to have path dependence, can generate multiple full-employment equilibrium trajectories of the capital stock in the super-long run. If the answer is yes, the equilibrium level of capital stock, an important supply-side factor, would no longer be independent of the business cycle phenomenon. This paper attempts to answer the above question by using the agent-based macroeconomic model developed by Takahashi and Okada (2010). The model would serve this purpose well because it has neither population growth nor technology progress. The objective of the paper is twofold: (1) to explore the causes of long-term business cycle, and (2) to examine the super-long behaviors of the capital stock of full-employment economies. (1) The simulated behaviors of the key macroeconomic variables such as output, employment, real wages showed widely diversified macro-economies. They were often remarkably stable but exhibited both short-term and long-term fluctuations. The long-term fluctuations occur through the following two adjustments: the quantity and relative cost adjustments of capital stock. The first one is obvious and assumed by many business cycle theorists. The reduced aggregate demand lowers prices, which raises real wages, thereby decreasing the relative cost of capital stock with respect to labor. (2) The long-term business cycles/fluctuations were synthesized with the hysteresis of real wages, interest rates, and investments. In particular, a sequence of the simulation runs with a super-long simulation period generated a wide range of perfectly stable paths, many of which achieved full employment: all the macroeconomic trajectories, including capital stock, output, and employment, were perfectly horizontal over 100,000 periods. Moreover, the full-employment level of capital stock was influenced by the history of unemployment, which was itself path-dependent. Thus, an experience of severe unemployment in the past kept the real wage low, which discouraged a relatively costly investment in capital stock. Meanwhile, a history of good performance sometimes brought about a low capital stock due to a high-interest rate that was consistent with a strong investment.

Keywords: agent-based macroeconomic model, business cycle, hysteresis, stability

Procedia PDF Downloads 206

Authors: Mohammad A. Obeidat, Ayman M. Mansour

Abstract:

Capturing the dynamic behavior of the heart to improve control performance, enhance robustness, and support diagnosis is very important in establishing real time models for the heart. Control Techniques and strategies have been utilized to improve system costs, reliability, and estimation accuracy for different types of systems such as biomedical, industrial, and other systems that required tuning input/output relation and/or monitoring. Simulations are performed to illustrate potential applications of the technology. In this research, a new control technology scheme is used to enhance the performance of the Af system and meet the design specifications.

Keywords: atrial fibrillation, dynamic behavior, closed loop, signal, filter

Procedia PDF Downloads 417