Search results for: real time pest tracking

Authors: Lāsma Cielava, Daina Jonkus, Līga Paura

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The age of first calving (AFC) is one of the most important factors that have a significant impact on cow productivity in different lactations and its whole life. A belated AFC leads to reduced reproductive performance and it is one of the main reasons for reduced longevity. Cows that calved in time period from 2001-2007 and in this time finished at least four lactations were included in the database. Data were obtained from 68841 crossbred Holstein Black and White (HM), crossbred Latvian Brown (LB), and Latvian Brown genetic resources (LBGR) cows. Cows were distributed in four groups depending on age at first calving. The longest lifespan was conducted for LBGR cows, but they were also characterized with lowest lifetime milk yield and life day milk yield. HM breed cows had the shortest lifespan, but in the lifespan of 2862.2 days was obtained in average 37916.4 kg milk accordingly 13.2 kg milk in one life day. HM breed cows were also characterized with longer calving intervals (CI) in first four lactations, but LBGR cows had the shortest CI in the study group. Age at first calving significantly affected the length of CI in different lactations (p<0.05). HM cows that first time calved >30 months old in the fourth lactation had the longest CI in all study groups (421.4 days). The LBGR cows were characterized with the shortest CI, but there was slight increase in second and third lactation. Age at first calving had a significant impact on cows’ age in each calving time. In the analysis, cow group was conducted that cows with age at first calving <24 months or in average 580.5 days at the time of fifth calving were 2156.7 days (5.9 years) old, but cows with age at first calving >30 months (932.6 days) at the time of fifth calving were 2560.9 days (7.3 years) old.

Keywords: age at first calving, calving interval, longevity, milk yield

Procedia PDF Downloads 218

Authors: Chongtham Jiten, K. Chandramani Singh, Radhapiyari Laishram

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Nanocrystalline powders of the lead-free piezoelectric material, tantalum-substituted potassium sodium niobate (K0.5Na0.5)(Nb0.9Ta0.1)O3 (KNNT), were produced using a Retsch PM100 planetary ball mill by setting the milling time to 15h, 20h, 25h, 30h, 35h and 40h, at a fixed speed of 250rpm. The average particle size of the milled powders was found to decrease from 12nm to 3nm as the milling time increases from 15h to 25h, which is in agreement with the existing theoretical model. An anomalous increase to 98nm and then a drop to 3nm in the particle size were observed as the milling time further increases to 30h and 40h respectively. Various sizes of these starting KNNT powders were used to investigate the effect of milling time on the microstructure, dielectric properties, phase transitions and piezoelectric properties of the resulting KNNT ceramics. The particle size of starting KNNT was somewhat proportional to the grain size. As the milling time increases from 15h to 25h, the resulting ceramics exhibit enhancement in the values of relative density from 94.8% to 95.8%, room temperature dielectric constant (εRT) from 878 to 1213, and piezoelectric charge coefficient (d33) from 108pC/N to 128pC/N. For this range of ceramic samples, grain size refinement suppresses the maximum dielectric constant (εmax), shifts the Curie temperature (Tc) to a lower temperature and the orthorhombic-tetragonal phase transition (Tot) to a higher temperature. Further increase of milling time from 25h to 40h produces a gradual degradation in the values of relative density, εRT, and d33 of the resulting ceramics.

Keywords: perovskite, dielectric, ceramics, high-energy milling

Procedia PDF Downloads 325

Authors: Anton V. Bourdine, Vladimir A. Burdin, Oleg R. Delmukhametov

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This work presents a fast and simple method for the design of large core silica optical fibers with differential mode delay (DMD) management. Some results are reported concerned with refractive index profile optimization for 42 µm core 16-LP-mode optical fiber for next-generation optical networks. Here special refractive index profile form provides total DMD reducing over all mode staff under desired enhanced mode effective area. Method for the simulation of 'real manufactured' few-mode optical fiber (FMF) core geometry differing from the desired optimized structure by core non-symmetrical ellipticity and refractive index profile deviation including local fluctuations is proposed. Results of the following analysis of optimized FMF with inserted geometry distortions performed by earlier on developed modification of rigorous mixed finite-element method showed strong DMD degradation that requires additional higher-order mode management. In addition, this work also presents a method for design mode division multiplexer channel precision spatial positioning scheme at FMF core end that provides one of the potentiality solutions of described DMD degradation problem concerned with 'distorted' core geometry due to features of optical fiber manufacturing techniques.

Keywords: differential mode delay, few-mode optical fibers, nonlinear Shannon limit, optical fiber non-circularity, ‘real manufactured’ optical fiber core geometry simulation, refractive index profile optimization

Procedia PDF Downloads 157

Authors: Mohamed A. Deyab, Omnia El-Shamy

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The main objective of this case study is to integrate the advantages of cathodic protection technologies in order to lessen chloride-induced corrosion in reinforced concrete. This research employs potentiodynamic polarisation, impedance spectroscopy (EIS), and surface characteristics. The results showed how effectively the new cathodic control strategy is preventing corrosion of the concrete iron rods. Over time, the protective system becomes more reliable and effective. The potentials of the zinc electrode persist still more negative after 30 days, implying that the zinc electrode can maintain powerful electrocatalytic behavior for a long period of time. As per the electrochemical impedance spectroscopy (EIS), using the CP technique reduces the rate of corrosion of rebar iron in cementitious materials over time.

Keywords: cathodic protection, corrosion, reinforced concrete, chloride

Procedia PDF Downloads 86

Authors: Maud Tixier

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Societal issues are at stake for cruises anywhere, whatever the size of the ships and their destinations are. However, the Mediterranean sea is the main region where many operate and the challenges are both social and environmental. The presentation focuses on small ships, accounting for market niches, aimed at more specific cruise passengers and calling at less visited areas. How they cope with the benefit of all stakeholders is a persistent issue of our time.

Keywords: environment, management, social, societal, safety

Procedia PDF Downloads 331

Authors: Elias Nemer, Greg Vines

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Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

Procedia PDF Downloads 233

Authors: A. M. Tiara, Sudipto Chakraborty, S. K. Pal

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Impinging jets and their different configurations are important from the viewpoint of the fluid flow characteristics and their influence on heat transfer from metal surfaces due to their complex flow characteristics. Such flow characteristics results in highly variable heat transfer from the surface, resulting in varying cooling rates which affects the mechanical properties including hardness and strength. The overall objective of the current research is to conduct a fundamental investigation of the heat transfer mechanisms for an impinging coolant jet. Numerical simulation of the cooling process gives a detailed analysis of the different parameters involved even though employing Computational Fluid Dynamics (CFD) to simulate the real time process, being a relatively new research area, poses many challenges. The heat transfer mechanism in the current research is actuated by jet cooling. The computational tool used in the ongoing research for simulation of the cooling process is ANSYS Workbench software. The temperature and heat flux distribution along the steel strip with the effect of various flow parameters on the heat transfer rate can be observed in addition to determination of the jet impingement patterns, which is the major aim of the present analysis. Modelling both jet and air atomized cooling techniques using CFD methodology and validating with those obtained experimentally- including trial and error with different models and comparison of cooling rates from both the techniques have been included in this work. Finally some concluding remarks are made that identify some gaps in the available literature that have influenced the path of the current investigation.

Keywords: CFD, heat transfer, impinging jets, numerical simulation

Procedia PDF Downloads 235

Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

Procedia PDF Downloads 321

Authors: Chalachew Gashu, Yoseph Kassa, Habtamu Geremew, Mengestie Mulugeta

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Background and Aims: Severe acute malnutrition remains a significant health challenge, particularly in low‐ and middle‐income countries. The aim of this study was to determine the survival time of under‐five children with severe acute malnutrition. Methods: A retrospective cohort study was conducted at a hospital, focusing on under‐five children with severe acute malnutrition. The study included 322 inpatients admitted to the Chiro hospital in Chiro, Ethiopia, between September 2019 and August 2020, whose data was obtained from medical records. Survival functions were analyzed using Kaplan‒Meier plots and log‐rank tests. The survival time of severe acute malnutrition was further analyzed using the Cox proportional hazards model and Bayesian parametric survival models, employing integrated nested Laplace approximation methods. Results: Among the 322 patients, 118 (36.6%) died as a result of severe acute malnutrition. The estimated median survival time for inpatients was found to be 2 weeks. Model selection criteria favored the Bayesian Weibull accelerated failure time model, which demonstrated that age, body temperature, pulse rate, nasogastric (NG) tube usage, hypoglycemia, anemia, diarrhea, dehydration, malaria, and pneumonia significantly influenced the survival time of severe acute malnutrition. Conclusions: This study revealed that children below 24 months, those with altered body temperature and pulse rate, NG tube usage, hypoglycemia, and comorbidities such as anemia, diarrhea, dehydration, malaria, and pneumonia had a shorter survival time when affected by severe acute malnutrition under the age of five. To reduce the death rate of children under 5 years of age, it is necessary to design community management for acute malnutrition to ensure early detection and improve access to and coverage for children who are malnourished.

Keywords: Bayesian analysis, severe acute malnutrition, survival data analysis, survival time

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Authors: Ayad Al-Mahturi, Herman Wahid

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This paper presents an optimal state feedback controller based on Linear Quadratic Regulator (LQR) for a two-rotor aero-dynamical system (TRAS). TRAS is a highly nonlinear multi-input multi-output (MIMO) system with two degrees of freedom and cross coupling. There are two parameters that define the behavior of LQR controller: state weighting matrix and control weighting matrix. The two parameters influence the performance of LQR. Particle Swarm Optimization (PSO) is proposed to optimally tune weighting matrices of LQR. The major concern of using LQR controller is to stabilize the TRAS by making the beam move quickly and accurately for tracking a trajectory or to reach a desired altitude. The simulation results were carried out in MATLAB/Simulink. The system is decoupled into two single-input single-output (SISO) systems. Comparing the performance of the optimized proportional, integral and derivative (PID) controller provided by INTECO, results depict that LQR controller gives a better performance in terms of both transient and steady state responses when PSO is performed.

Keywords: LQR controller, optimal control, particle swarm optimization (PSO), two rotor aero-dynamical system (TRAS)

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Authors: Sifan Guo, Xuesen Zheng

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Visitors as the vital research group have been mentioned in high frequency in the field of museum studies. With the rise of the New Museology Movement, new challenges in the museum appeared, ranging from how to eliminate the cliché class prejudices in museums to how to make visitor-oriented museums more welcome. In line with this new situation, to create a successful visiting experience is the focus of museums in today. National museums as tourist attractions always attract flooded attention, however the local museums may have the different situations. The residents could be one of the main visitors to the local museums how to attract them returned should be considered here. There are various people with different cultural, education and religion backgrounds, it is necessary to keep the balance of the education and entertainment to reach visitors’ expectations. Regarding these questions, a mixed methods research approach has been adopted: observations, tracking and questionnaires. Based on analysing some museums’ cases in the UK, it can be argued that: 1) Audiences’ accessibility support their options and judgments during the visiting. 2) Highly inclusive architecture and narrative expressions could encourage the visitors to proceed deeply understanding and alleviate conflicts. In addition, the main characteristics of the local museums and the interlinks between museums and urban renaissance will be clarified. The conclusion informs not only practical suggestions for reachable characteristic design, but also potential future research subjects.

Keywords: accessibility, challenging visitors, new museology movement, visiting experience

Procedia PDF Downloads 116

Authors: Isaac Owusu Asante, Yushi Jiang, Hailin Tao

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Live streaming marketing, the new electronic commerce element, became an optional marketing channel following the COVID-19 pandemic. Many sellers have leveraged the features presented by live streaming to increase sales. Studies on live streaming have focused on gaming and consumers’ loyalty to brands through live streaming, using interview questionnaires. This study, however, was conducted to measure real-time observable interactions between consumers and sellers. Based on the affordance theory, this study conceptualized constructs representing the interactive features and examined how they drive consumers’ purchase willingness during live streaming sessions using 1238 datasets from Amazon Live, following the manual observation of transaction records. Using structural equation modeling, the ordinary least square regression suggests that live viewers, new followers, live chats, and likes positively affect purchase willingness. The Sobel and Monte Carlo tests show that new followers, live chats, and likes significantly mediate the relationship between live viewers and purchase willingness. The study introduces a new way of measuring interactions in live streaming commerce and proposes a way to manually gather data on consumer behaviors in live streaming platforms when the application programming interface (API) of such platforms does not support data mining algorithms.

Keywords: livestreaming marketing, live chats, live viewers, likes, new followers, purchase willingness

Procedia PDF Downloads 81

Authors: Carla Pérez-Chirinos Buxadé, Bruno Fernández-Valdés, Mónica Morral-Yepes, Sílvia Tuyà Viñas, Josep Maria Padullés Riu, Gerard Moras Feliu

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There is a long way to explore all the possible applications inertial measurement units (IMUs) have in the sports field. The aim of this study was to evaluate the validity of a new application on the use of these wearable sensors, specifically it was to evaluate a magnet-based timing system (M-BTS) for timing gate-to-gate in an alpine ski slalom using the magnetometer embedded in an IMU. This was a validation study. The criterion validity of time measured by the M-BTS was assessed using the 95% error range against actual time obtained from photocells. The experiment was carried out with first-and second-year junior skiers performing a ski slalom on a ski training slope. Eight alpine skiers (17.4 ± 0.8 years, 176.4 ± 4.9 cm, 67.7 ± 2.0 kg, 128.8 ± 26.6 slalom FIS-Points) participated in the study. An IMU device was attached to the skier’s lower back. Skiers performed a 40-gate slalom from which four gates were assessed. The M-BTS consisted of placing four bar magnets buried into the snow surface on the inner side of each gate’s turning pole; the magnetometer built into the IMU detected the peak-shaped magnetic field when passing near the magnets at a certain speed. Four magnetic peaks were detected. The time compressed between peaks was calculated. Three inter-gate times were obtained for each system: photocells and M-BTS. The total time was defined as the time sum of the inter-gate times. The 95% error interval for the total time was 0.050 s for the ski slalom. The M-BTS is valid for timing gate-to-gate in an alpine ski slalom. Inter-gate times can provide additional data for analyzing a skier’s performance, such as asymmetries between left and right foot.

Keywords: gate crossing time, inertial measurement unit, timing system, wearable sensor

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Authors: Fatemeh Aghamohammadzadeh, Mahdi Asghari Ozma

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SARS-CoV-2 was transmitted from animals to humans in China and through air transport to almost all world countries, including Iran, creating the first pandemic of the 21st century. The virus was spread through droplets from sneezing, coughing, loud talking, and exhalation of sick and asymptomatic people, even during incubation. It was transmitted from human to human directly by inhalation of viruses in droplets or indirectly through contact with infected surfaces, resulting in the death of a significant number of patients, especially the elderly and those with underlying diseases. The virus is more likely to be transmitted in places with high population densities. The chain of transmission of infection can be broken by observing the following: risk perception, reduced travel, complete quarantine in a particular area, home quarantine, social distancing, use of personal protective equipment (PPE), prevention of gatherings, cleaning and disinfection of public utilities and busy places, identifying, isolating and treating infected people, tracking calls, continuing health education, following health principles by people, especially in poor areas, and washing their hands frequently with soap and water or disinfecting them with 70% ethanol.

Keywords: COVID-19, transmission, population density, home quarantine, social distancing

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Authors: Khaled I. Nawafleh

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In this paper, it provide the canonical approach for studying dissipated oscillators based on the doubling of degrees of freedom. Clearly, expressions for Lagrangians of the elementary modes of the system are given, which ends with the familiar classical equations of motion for the dissipative oscillator. The equation for one variable is the time reversed of the motion of the second variable. it discuss in detail the extended Bateman Lagrangian specifically for a dual extended damped oscillator time-dependent. A Hamilton-Jacobi analysis showing the equivalence with the Lagrangian approach is also obtained. For that purpose, the techniques of separation of variables were applied, and the quantization process was achieved.

Keywords: doubling of degrees of freedom, dissipated harmonic oscillator, Hamilton-Jacobi, time-dependent lagrangians, quantization

Procedia PDF Downloads 69

Authors: Sinem Bagce, Ensar Yilmaz

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As a well-known fact, neoclassical economics excludes 'what is humanized' out of the literature for a long time. Rationality is defined in a very narrow context in the mainstream economics. Identity economics is one of the challenges raised against this tradition. The concept of 'identity' has been introduced to economics by Akerlof and Kranton (2000). The identity-based analysis mainly searches the links between economic welfare and decision of the actors in question related to ethnic, racial, gender and immigrant issues. This is more about discrimination and its repercussions on economic decisions of the relevant actors in a social sphere. In this article, we, in the context of identity economics, search the economic welfare and decisions of Romani people in Turkey. It is plainly observed that identity is clearly the major determinant for Romani people in economic and social life. They have their own distinctive rationality in making economic decisions. For a more scrutinized and academic analysis, we aim to trace their economic identity in their real social environment. This study is an extension of surveys conducted on Romani people in Turkey. Using data similar to SILC (Statistics for Income and Living Conditions) conducted on Romani people across the whole Turkey, we look for some questions about the income/welfare distribution among them, consumer preferences/habits, living conditions, occupations, education and as such. For this, by employing econometric and statistical analytical tools, we aim to obtain the answers for these questions. We think these analytic results will provide us to evaluate the links between their economic state and their identity more thoroughly. JEL Codes: D1, J 15, R23.

Keywords: identity economics, Romani people, discrimination, social identity and preferences

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Authors: Yoshiaki Shikata, Nobutane Hanayama

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We present a prioritized, limited multi-server processor sharing (PS) system where each server has various capacities, and N (≥2) priority classes are allowed in each PS server. In each prioritized, limited server, different service ratio is assigned to each class request, and the number of requests to be processed is limited to less than a certain number. Routing strategies of such prioritized, limited multi-server PS systems that take into account the capacity of each server are also presented, and a performance evaluation procedure for these strategies is discussed. Practical performance measures of these strategies, such as loss probability, mean waiting time, and mean sojourn time, are evaluated via simulation. In the PS server, at the arrival (or departure) of a request, the extension (shortening) of the remaining sojourn time of each request receiving service can be calculated by using the number of requests of each class and the priority ratio. Utilising a simulation program which executes these events and calculations, the performance of the proposed prioritized, limited multi-server PS rule can be analyzed. From the evaluation results, most suitable routing strategy for the loss or waiting system is clarified.

Keywords: processor sharing, multi-server, various capacity, N-priority classes, routing strategy, loss probability, mean sojourn time, mean waiting time, simulation

Procedia PDF Downloads 332

Authors: R. L. David, E. C. P. Tan, M. A. Ferenczi

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This study aimed to investigate the effect of a 'one-time' optional Information Literacy (IL) workshop to enhance Year 1 medical students' literature search, writing, and citation management skills as directed by a customized five-year IL framework developed for LKC Medicine students. At the end of the IL workshop, the overall rated 'somewhat difficult' when finding, citing, and using information from sources. The study method is experimental using a standardized IL test to study the cohort effect of a 'one-time' optional IL workshop on Year 1 students; experimental group in comparison to Year 2 students; control group. Test scores from both groups were compared and analyzed using mean scores and one-way analysis of variance (ANOVA). Unexpectedly, there were no statistically significant differences between group means as determined by One-Way ANOVA (F₁,₁₉₃ = 3.37, p = 0.068, ηp² = 0.017). Challenges and shortfalls posed by 'one-time' interventions raised a rich discussion to adopt an 'embedded librarianship' approach, which shifts the medial librarians' role into the curriculum and uses Team Based Learning to teach IL skills to medical students. The customized five-year IL framework developed for LKC Medicine students becomes a useful librarian-faculty model for embedding and bringing IL into the classroom.

Keywords: information literacy, 'one-time' interventions, medical students, standardized tests, embedded librarianship, curriculum, medical librarians

Procedia PDF Downloads 113

Authors: Asif Zaman, Moinul Islam Zaber, Amin Ahsan Ali

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In recent years of industrialization, the South Asian countries are being affected by air pollution due to a severe increase in fine particulate matter 2.5 (PM₂.₅). Among them, Bangladesh is one of the most polluting countries. In this paper, statistical analyses were conducted on the time series of PM₂.₅ from various districts in Bangladesh, mostly around Dhaka city. Research has been conducted on the dynamic interactions and relationships between PM₂.₅ concentrations in different zones. The study is conducted toward understanding the characteristics of PM₂.₅, such as spatial-temporal characterization, correlation of other contributors behind air pollution such as human activities, driving factors and environmental casualties. Clustering on the data gave an insight on the districts groups based on their AQI frequency as representative districts. Seasonality analysis on hourly and monthly frequency found higher concentration of fine particles in nighttime and winter season, respectively. Cross correlation analysis discovered a phenomenon of correlations among cities based on time-lagged series of air particle readings and visualization framework is developed for observing interaction in PM₂.₅ concentrations between cities. Significant time-lagged correlations were discovered between the PM₂.₅ time series in different city groups throughout the country by cross correlation analysis. Additionally, seasonal heatmaps depict that the pooled series correlations are less significant in warmer months, and among cities of greater geographic distance as well as time lag magnitude and direction of the best shifted correlated particulate matter time series among districts change seasonally. The geographic map visualization demonstrates spatial behaviour of air pollution among districts around Dhaka city and the significant effect of wind direction as the vital actor on correlated shifted time series. The visualization framework has multipurpose usage from gathering insight of general and seasonal air quality of Bangladesh to determining the pathway of regional transportation of air pollution.

Keywords: air quality, particles, cross correlation, seasonality

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Authors: Pavel A. Strizhak, Geniy V. Kuznetsov, Ivan S. Voytkov, Dmitri V. Antonov

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This paper presents the results of experiments carried out at a specialized test site for establishing macroscopic patterns of heat and mass transfer processes at localizing model combustion sources of ground forest fires with the use of barrier lines in the form of a wetted lay of material in front of the zone of flame burning and thermal decomposition. The experiments were performed using needles, leaves, twigs, and mixtures thereof. The dimensions of the model combustion source and the ranges of heat release correspond well to the real conditions of ground forest fires. The main attention is paid to the complex analysis of the effect of dispersion of water aerosol (concentration and size of droplets) used to form the barrier line. It is shown that effective conditions for localization and subsequent suppression of flame combustion and thermal decomposition of forest fuel can be achieved by creating a group of barrier lines with different wetting width and depth of the material. Relative indicators of the effectiveness of one and combined barrier lines were established, taking into account all the main characteristics of the processes of suppressing burning and thermal decomposition of forest combustible materials. We performed the prediction of the necessary and sufficient parameters of barrier lines (water volume, width, and depth of the wetted lay of the material, specific irrigation density) for combustion sources with different dimensions, corresponding to the real fire extinguishing practice.

Keywords: forest fire, barrier water lines, pyrolysis front, flame front

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Authors: M. Şahi̇n, E. Erdem, M. Saçak

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In this study, Na-smectite crystals purificated of bentonite were used after being swelling with benzyltributylammonium bromide (BTBAB) as alkyl ammonium salt. Swelling process was carried out using 0.2 g of BTBAB for smectite of 0.8 g with 4 h of mixing time after investigated conditions such as mixing time, the swelling agent amount. Then, the conductive poly(o-anisidine) (POA)/smectite nanocomposite was prepared in the presence of swollen Na-smectite using ammonium persulfate (APS) as oxidant in aqueous acidic medium. The POA content and conductivity of the prepared nanocomposite were systematically investigated as a function of polymerization conditions such as the treatment time of swollen smectite in monomer solution and o-anisidine/APS mol ratio. POA/smectite nanocomposite was characterized by XRD, FTIR and SEM techniques and was compared separately with components of composite.

Keywords: clay, composite, conducting polymer, poly(o-anisidine)

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Authors: Seong Jun Yoon, Jasurbek Doliev, Sang Min Oh, Rodi Hartono, Kyoojae Shin

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Electric power steering (EPS), which is commonly used in electric vehicles recently, is an electric-driven steering device for vehicles. Compared to hydraulic systems, EPS offers advantages such as simple system components, easy maintenance, and improved steering performance. However, because the EPS system is a nonlinear model, difficult problems arise in controller design. To address these, various machine learning and artificial intelligence approaches, notably artificial neural networks (ANN), have been applied. ANN can effectively determine relationships between inputs and outputs in a data-driven manner. This research explores two main areas: designing an EPS identifier using an ANN-based backpropagation (BP) algorithm and enhancing the EPS system controller with an ANN-based Levenberg-Marquardt (LM) algorithm. The proposed ANN-based BP algorithm shows superior performance and accuracy compared to linear transfer function estimators, while the LM algorithm offers better input angle reference tracking and faster response times than traditional PID controllers. Overall, the proposed ANN methods demonstrate significant promise in improving EPS system performance.

Keywords: ANN backpropagation modelling, electric power steering, transfer function estimator, electrical vehicle driving system

Procedia PDF Downloads 44

Authors: Ren Moses, Emmanuel Kidando, Eren Ozguven, Yassir Abdelrazig

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Although older drivers (defined as those of age 65 and above) are less involved with speeding, alcohol use as well as night driving, they are more vulnerable to severe crashes. The major contributing factors for severe crashes include frailty and medical complications. Several studies have evaluated the contributing factors on severity of crashes. However, few studies have established the impact of travel time reliability (TTR) on road safety. In particular, the impact of TTR on senior adults who face several challenges including hearing difficulties, decreasing of the processing skills and cognitive problems in driving is not well established. Therefore, this study focuses on determining possible impacts of TTR on the traffic safety with focus on elderly drivers. Historical travel speed data from freeway links in the study area were used to calculate travel time and the associated TTR metrics that is, planning time index, the buffer index, the standard deviation of the travel time and the probability of congestion. Four-year information on crashes occurring on these freeway links was acquired. The binary logit model estimated using the Markov Chain Monte Carlo (MCMC) sampling technique was used to evaluate variables that could be influencing elderly crash severity. Preliminary results of the analysis suggest that TTR is statistically significant in affecting the severity of a crash involving an elderly driver. The result suggests that one unit increase in the probability of congestion reduces the likelihood of the elderly severe crash by nearly 22%. These findings will enhance the understanding of TTR and its impact on the elderly crash severity.

Keywords: highway safety, travel time reliability, elderly drivers, traffic modeling

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Authors: Areti Okalidou, Paul D. Hatzigiannakoglou, Aikaterini Vatou, George Kyriafinis

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Young children are nowadays adept at using technology. Hence, computer-based auditory training programs (CBATPs) have become increasingly popular in aural rehabilitation for children with hearing loss and/or with cochlear implants (CI). Yet, their clinical utility for prognostic, diagnostic, and monitoring purposes has not been explored. The purposes of the study were: a) to develop an updated version of the auditory rehabilitation tool for Greek-speaking children with cochlear implants, b) to develop a database for behavioral responses, and c) to compare accuracy rates and reaction times in children differing in hearing status and other medical and demographic characteristics, in order to assess the tool’s clinical utility in prognosis, diagnosis, and progress monitoring. The updated version of the auditory rehabilitation tool was developed on a tablet, retaining the User-Centered Design approach and the elements of the Virtual Reality (VR) serious game. The visual stimuli were farm animals acting in simple game scenarios designed to trigger children’s responses to animal sounds, names, and relevant sentences. Based on an extended version of Erber’s auditory development model, the VR game consisted of six stages, i.e., sound detection, sound discrimination, word discrimination, identification, comprehension of words in a carrier phrase, and comprehension of sentences. A familiarization stage (learning) was set prior to the game. Children’s tactile responses were recorded as correct, false, or impulsive, following a child-dependent set up of a valid delay time after stimulus offset for valid responses. Reaction times were also recorded, and the database was in Εxcel format. The tablet version of the auditory rehabilitation tool was piloted in 22 preschool children with Νormal Ηearing (ΝΗ), which led to improvements. The study took place in clinical settings or at children’s homes. Fifteen children with CI, aged 5;7-12;3 years with post-implantation 0;11-5;1 years used the auditory rehabilitation tool. Eight children with CI were monolingual, two were bilingual and five had additional disabilities. The control groups consisted of 13 children with ΝΗ, aged 2;6-9;11 years. A comparison of both accuracy rates, as percent correct, and reaction times (in sec) was made at each stage, across hearing status, age, and also, within the CI group, based on presence of additional disability and bilingualism. Both monolingual Greek-speaking children with CI with no additional disabilities and hearing peers showed high accuracy rates at all stages, with performances falling above the 3rd quartile. However, children with normal hearing scored higher than the children with CI, especially in the detection and word discrimination tasks. The reaction time differences between the two groups decreased in language-based tasks. Results for children with CI with additional disability or bilingualism varied. Finally, older children scored higher than younger ones in both groups (CI, NH), but larger differences occurred in children with CI. The interactions between familiarization of the software, age, hearing status and demographic characteristics are discussed. Overall, the VR game is a promising tool for tracking the development of auditory skills, as it provides multi-level longitudinal empirical data. Acknowledgment: This work is part of a project that has received funding from the Research Committee of the University of Macedonia under the Basic Research 2020-21 funding programme.

Keywords: VR serious games, auditory rehabilitation, auditory training, children with cochlear implants

Procedia PDF Downloads 89

Authors: Laleh Boroumand, Muhammad Shiraz, Abdullah Gani, Rashid Hafeez Khokhar

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Cloud computing being the use of hardware and software that are delivered as a service over a network has its application in the area of health care. Due to the emergency cases reported in most of the medical centers, prompt for an efficient scheme to make health data available with less response time. To this end, we propose a mobile global healthcare village (MGHV) model that combines the components of three deployment model which include country, continent and global health cloud to help in solving the problem mentioned above. In the creation of continent model, two (2) data centers are created of which one is local and the other is global. The local replay the request of residence within the continent, whereas the global replay the requirements of others. With the methods adopted, there is an assurance of the availability of relevant medical data to patients, specialists, and emergency staffs regardless of locations and time. From our intensive experiment using the simulation approach, it was observed that, broker policy scheme with respect to optimized response time, yields a very good performance in terms of reduction in response time. Though, our results are comparable to others when there is an increase in the number of virtual machines (80-640 virtual machines). The proportionality in increase of response time is within 9%. The results gotten from our simulation experiments shows that utilizing MGHV leads to the reduction of health care expenditures and helps in solving the problems of unqualified medical staffs faced by both developed and developing countries.

Keywords: cloud computing (MCC), e-healthcare, availability, response time, service broker policy

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Authors: Noah Odion, Honest Jimu, Blessing Atinuke Afuape

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Introduction: Motor control and gait abnormalities are commonly observed in individuals with autism spectrum disorder (ASD), affecting their mobility and coordination. Understanding the underlying neurological and biomechanical factors is essential for designing effective interventions. This study focuses on developing microchip-integrated wearable devices to capture real-time movement data from individuals with autism. By applying computational models to the collected data, we aim to analyze motor control patterns and gait abnormalities, bridging a crucial knowledge gap in autism-related motor dysfunction. Methods: We designed microchip-enabled wearable devices capable of capturing precise kinematic data, including joint angles, acceleration, and velocity during movement. A cross-sectional study was conducted on individuals with ASD and a control group to collect comparative data. Computational modelling was applied using machine learning algorithms to analyse motor control patterns, focusing on gait variability, balance, and coordination. Finite element models were also used to simulate muscle and joint dynamics. The study employed descriptive and analytical methods to interpret the motor data. Results: The wearable devices effectively captured detailed movement data, revealing significant gait variability in the ASD group. For example, gait cycle time was 25% longer, and stride length was reduced by 15% compared to the control group. Motor control analysis showed a 30% reduction in balance stability in individuals with autism. Computational models successfully predicted movement irregularities and helped identify motor control deficits, particularly in the lower limbs. Conclusions: The integration of microchip-based wearable devices with computational models offers a powerful tool for diagnosing and treating motor control deficits in autism. These results have significant implications for patient care, providing objective data to guide personalized therapeutic interventions. The findings also contribute to the broader field of neuroscience by improving our understanding of the motor dysfunctions associated with ASD and other neurodevelopmental disorders.

Keywords: motor control, gait abnormalities, autism, wearable devices, microchips, computational modeling, kinematic analysis, neurodevelopmental disorders

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Authors: Ben-Caleb Egbide, Egharevba Mathew, Achugamonu Uzoma, Faboyede Samuel

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The importance of budgeting in government and corporate entities as medium for the efficient management of scarce resources is self-evident. But when it comes to home or personal budgeting, there seem to be lingering misconceptions as regards its relevance. While most people view personal budgeting merely as a tool for tracking expenses and schedule for paying bills and indebtedness, very few consider it as one of the most important device for sound financial planning, money management instrument and/or wealth-creation mechanism. This paper is conceptualised to investigate the association between personal budgeting and financial well-being among staffers of tertiary institution in the South West Nigeria. Underpinned by the individualistic/cultural theory of well-being and the adoption of a survey research design, a structured questionnaire was used to gather data from a cross section of staff of tertiary Institutions in Ogun State. A Spearman Rank Correlation was utilised for analysis of data. The result indicates a high positive relationship between personal budgeting and tendencies for enhanced financial well-being among staff. The paper established that a change of value and behavioural pattern by individuals and household, especially in the areas of personal spending and budgeting could drastically reduce the incidence of the severity of financial stress, hence, enhanced wellness among staff.

Keywords: personal budgeting, financial well-being, tertiary institutions staffers, Nigeria

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Authors: Hiroshi Ikeda

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In this research, a questionnaire survey was conducted to measure nap, drowsiness and fatigue of drivers who work long shifts, to discuss about the work environment and health conditions for taxi and bus drivers who work at night time. The questionnaire sheet used for this research was organized into the following categories: tension/tiredness, drowsiness while driving, and the nap situation during night-time work. The number of taxi drivers was 127 and the number of bus drivers was 40. Concerning the results of a comparison of nap hours of taxi and bus drivers, the taxi drivers’ nap hours are overwhelmingly shorter, and also the frequency of drivers who feel drowsiness is higher. The burden on bus drivers does not change because of the system of a two-driver rotation shift. In particular, the working environment of the taxi driver may lead to greater fatigue accumulation than the bus driver’s environment.

Keywords: bus and taxi, drowsiness, fatigue, nap

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: Avi Shrivastava

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Our world continues to grapple with a lot of social issues. Economic growth and scientific advancements have not completely eradicated poverty, homelessness, discrimination and bias, gender inequality, health issues, mental illness, addiction, and other social issues. So, how do we improve the human condition in a world driven by advanced technology? The answer is simple: we will have to leverage technology to address some of the most important social challenges of the day. AI, or artificial intelligence, has emerged as a critical tool in the battle against issues that deprive marginalized and disadvantaged groups of the right to enjoy benefits that a society offers. Social work professionals can transform their lives by harnessing it. The lack of reliable data is one of the reasons why a lot of social work projects fail. Social work professionals continue to rely on expensive and time-consuming primary data collection methods, such as observation, surveys, questionnaires, and interviews, instead of tapping into AI-based technology to generate useful, real-time data and necessary insights. By leveraging AI’s data-mining ability, we can gain a deeper understanding of how to solve complex social problems and change lives of people. We can do the right work for the right people and at the right time. For example, AI can enable social work professionals to focus their humanitarian efforts on some of the world’s poorest regions, where there is extreme poverty. An interdisciplinary team of Stanford scientists, Marshall Burke, Stefano Ermon, David Lobell, Michael Xie, and Neal Jean, used AI to spot global poverty zones – identifying such zones is a key step in the fight against poverty. The scientists combined daytime and nighttime satellite imagery with machine learning algorithms to predict poverty in Nigeria, Uganda, Tanzania, Rwanda, and Malawi. In an article published by Stanford News, Stanford researchers use dark of night and machine learning, Ermon explained that they provided the machine-learning system, an application of AI, with the high-resolution satellite images and asked it to predict poverty in the African region. “The system essentially learned how to solve the problem by comparing those two sets of images [daytime and nighttime].” This is one example of how AI can be used by social work professionals to reach regions that need their aid the most. It can also help identify sources of inequality and conflict, which could reduce inequalities, according to Nature’s study, titled The role of artificial intelligence in achieving the Sustainable Development Goals, published in 2020. The report also notes that AI can help achieve 79 percent of the United Nation’s (UN) Sustainable Development Goals (SDG). AI is impacting our everyday lives in multiple amazing ways, yet some people do not know much about it. If someone is not familiar with this technology, they may be reluctant to use it to solve social issues. So, before we talk more about the use of AI to accomplish social work objectives, let’s put the spotlight on how AI and social work can complement each other.

Keywords: social work, artificial intelligence, AI based social work, machine learning, technology

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