Search results for: hardy cross networks accuracy

Authors: David Jurado, Carlos Ávila

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Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.

Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis

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Authors: Isaac Makundi, Kazuo Nishigaki

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The Tsushima leopard cat (TLC) Prionailurus bengalensis euptilurus, designated a National Natural Monument of Japan, inhabits Tsushima Island, Nagasaki Prefecture, Japan. TLC is considered a subspecies of P. bengalensis, and lives only on Tsushima Island. TLCs are threatened by various infectious diseases. Feline leukemia virus (FeLV) causes a serious infectious disease with a poor prognosis in cats. Therefore, the transmission of FeLV from Tsushima domestic cats (TDCs) to TLCs may threaten the TLC population. We investigated the FeLV infection status of both TDCs and TLCs on Tsushima Island by screening blood samples for FeLV p27 antigen and using PCR to amplify the full-length FeLV env gene. The prevalence of FeLV was 6.4% in TDCs and 0% in TLCs. We also demonstrated that the virus can replicate in the cells of TLCs, suggesting its potential cross-species transmission. The viruses in TDCs were classified as genotype I/clade 3, which is prevalent on a nearby island, based on previous studies of FeLV genotypes and FeLV epidemiology. The FeLV viruses identified on Tsushima Island can be further divided into two lineages within genotype I/clade 3, which are geographically separated in Kamijima and Shimojima, indicating that FeLV may have been transmitted to Tsushima Island at least twice. Monitoring FeLV infection in the TDC and TLC populations is highly recommended as part of the TLC surveillance and management strategy.

Keywords: epidemiology, Feline leukemia virus, Tsushima Island, wildlife management

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Authors: Baghdasaryan Marinka, Ulikyan Azatuhi

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The efficient usage of the compensation abilities of the electrical drive synchronous motors used in production processes can essentially improve the technical and economic indices of the process.  Reducing the flows of the reactive electrical energy due to the compensation of reactive power allows to significantly reduce the load losses of power in the electrical networks. As a result of analyzing the scientific works devoted to the issues of regulating the excitation of the synchronous motors, the need for comprehensive investigation and estimation of the excitation mode has been substantiated. By means of the obtained transmission functions, in the Simulink environment of the software package MATLAB, the transition processes of the excitation mode have been studied. As a result of obtaining and estimating the graph of the Nyquist plot and the transient process, the necessity of developing the Proportional-Integral-Derivative (PID) regulator has been justified. The transient processes of the system of the PID regulator have been investigated, and the amplitude–phase characteristics of the system have been estimated. The analysis of the obtained results has shown that the regulation indices of the developed system have been improved. The developed system can be successfully applied for regulating the excitation voltage of different-power synchronous motors, operating with a changing load, ensuring a value of the power coefficient close to 1.

Keywords: transition process, synchronous motor, excitation mode, regulator, reactive power

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Authors: Zhuang Hou, Xiaolei Cao

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The general public and medical professionals recognized the importance of accurately measuring and storing blood oxygen levels and heart rate during the COVID-19 pandemic. The demand for accurate contactless devices was motivated by the need for cross-infection reduction and the shortage of conventional oximeters, partially due to the global supply chain issue. This paper evaluated a contactless mini program HealthyPai’s heart rate (HR) and oxygen saturation (SpO2) measurements compared with other wearable devices. In the HR study of 185 samples (81 in the laboratory environment, 104 in the real-life environment), the mean absolute error (MAE) ± standard deviation was 1.4827 ± 1.7452 in the lab, 6.9231 ± 5.6426 in the real-life setting. In the SpO2 study of 24 samples, the MAE ± standard deviation of the measurement was 1.0375 ± 0.7745. Our results validated that HealthyPai utilizing the Integrated Image Deep Learning Solution (IIDLS) framework, can accurately measure HR and SpO2, providing the test quality at least comparable to other FDA-approved wearable devices in the market and surpassing the consumer-grade and research-grade wearable standards.

Keywords: remote photoplethysmography, heart rate, oxygen saturation, contactless measurement, mini program

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Authors: Chowdhury Md. Navim Kabir

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Renal impairment is one of the most severe non-communicable diseases around the world. Especially patients with diagnosed/newly diagnosed renal impairment who need surgery are more focused on preoperative and postoperative preparation. Serum creatinine is the prime biochemical marker for assessing renal function, and the level of impairment is widely measured by this marker as well as Glomerular Filtration Rate (GFR). Objective: Factors responsible for fluctuating serum creatinine during preoperative and postoperative periods and minimizing the process of serum creatinine is the ultimate goal of this study. Method: 37 patients participated in this cross-sectional study who were previously diagnosed/newly diagnosed. They were admitted to different tertiary-level hospitals for emergency or elective surgery. Fifteen patients were admitted in the renal function impairment stage and 22 were admitted as normal patients’. Values of creatinine at the pre-admission stage and 2nd/3rd post-admission follow-up were compared. Results: 0.41 was the average of 22 patients' creatinine between pre-admission and 2nd/3rd follow-up. The responsible factor like prolonged staying, immobilization, co-morbidities, different preoperative antibiotics and Non-Steroidal Anti Inflammatory Drugs (NSAIDs) were also inducers for creatinine elevation. After postoperative hemodialysis rapid decrease of creatinine is seen in normal patients, but this decrease is very much minor in Chronic Kidney Disease (CKD) diagnosed patients.

Keywords: CKD, Meropenam, NSAID, comorbidities, immobilized

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Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

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In this paper, a new robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics and using the weighted sum-squared prediction error as the residual. The recursive orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. The several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control

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Authors: Pooja Khanal, Huaming Zhang

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Labeling of issues/bugs, also known as bug classification, plays a vital role in software engineering. Some known labels/classes of bugs are 'User Interface', 'Security', and 'API'. Most of the time, when a reporter reports a bug, they try to assign some predefined label to it. Those issues are reported for a project, and each project is a repository in GitHub/GitLab, which contains multiple issues. There are many software project repositories -ranging from individual projects to commercial projects. The labels assigned for different repositories may be dependent on various factors like human instinct, generalization of labels, label assignment policy followed by the reporter, etc. While the reporter of the issue may instinctively give that issue a label, another person reporting the same issue may label it differently. This way, it is not known mathematically if a label in one repository is similar or different to the label in another repository. Hence, the primary goal of this research is to find the semantic differences between bug labeling of different repositories via machine learning. Independent optimal classifiers for individual repositories are built first using the text features from the reported issues. The optimal classifiers may include a combination of multiple classifiers stacked together. Then, those classifiers are used to cross-test other repositories which leads the result to be deduced mathematically. The produce of this ongoing research includes a formalized open-source GitHub issues database that is used to deduce the similarity of the labels pertaining to the different repositories.

Keywords: bug classification, bug labels, GitHub issues, semantic differences

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Authors: Fatemeh Abdollahi, Munn-Sann Lye, Jamshid Yazdani Charati, Mehran Zarghami

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Both obesity and intimate partner violence (IPV) are growing health threats. This study aimed to assess the prevalence and risk factors of both IPV and obesity and their association. In this cross-sectional study, 530 women aged 16-65 years attending Mazandaran primary health centers were recruited through the stratified random sampling method (2019-2020). Data were collected using the modified World Health Organization Domestic Violence questionnaire, Perceived Stress Scale, and socio-demographic, obstetric, and anthropometric questionnaires. The data were analyzed using descriptive statistics, the chi-square test, and multiple logistic regression. The prevalence of overweight, obesity and psychological, physical, and sexual IPV were 47.6%, 26.7%, 70.4%, 17.9%, and 6.4%, respectively. Increasing women’s educational level and exposure to violence during their lifespan increased the odds of any type of IPV while living in a nuclear family reduced it. In groups of women who were subjected to any type of IPV and only psychological IPV, experiencing violence during the lifespan was significant in predicting obesity. The alarming prevalence of IPV and obesity-overweight in this study points to the need for collaborative socio-political and health intervention. The link between experiencing violence during lifespan and obesity in some subgroups of women highlights the detrimental consequences of chronic violence and the urgent need for effective preventive programs.

Keywords: intimate partner violence, body mass index, obesity, risk factor, women

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Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

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The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.

Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing

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Authors: Tanveer Hussain, Khan Muhammad, Amin Ullah, Mi Young Lee, Sung Wook Baik

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The Big Data generated from distributed vision sensors installed on large scale in smart cities create hurdles in its efficient and beneficial exploration for browsing, retrieval, and indexing. This paper presents a three-folded framework for effective video summarization of such data and provide a compact and representative format of Big Video Data. In the first fold, the paper acquires input video data from the installed cameras and collect clues such as type and count of objects and clarity of the view from a chunk of pre-defined number of frames of each view. The decision of representative view selection for a particular interval is based on fuzzy inference system, acquiring a precise and human resembling decision, reinforced by the known clues as a part of the second fold. In the third fold, the paper forwards the selected view frames to the summary generation mechanism that is supported by a saliency-aware convolution neural network (CNN) model. The new trend of fuzzy rules for view selection followed by CNN architecture for saliency computation makes the multi-view video summarization (MVS) framework a suitable candidate for real-world practice in smart cities.

Keywords: big video data analysis, fuzzy logic, multi-view video summarization, saliency detection

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Authors: José María Renteria, Vania Salas

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This study explores the impact of inclusive education on the educational outcomes of students without Special Educational Needs (non-SEN) in Peru, utilizing official Ministry of Education data and implementing cross-sectional regression analyses. Inclusive education is a complex issue that, without appropriate adaptations and comprehensive understanding, can present substantial challenges to the educational community. While prior research from developed nations offers diverse perspectives on the effects of inclusive education on non-SEN students, limited evidence exists regarding its impact in developing countries. Our study addresses this gap by examining inclusive education in Peru and its effects on non-SEN students, thereby contributing to the existing literature. the findings reveal that, on average, the presence of SEN students in regular classrooms does not significantly affect their non-SEN counterparts. However, we uncover heterogeneous effects contingent on the specific type of SEN and students’ academic placement. These results emphasize the importance of targeted resources, specialized teachers, and parental involvement in facilitating successful inclusive education, particularly for specific SEN types and students positioned at the lower end of the academic achievement spectrum. In summary, this study underscores the need for tailored strategies and additional resources to foster the success of inclusive education and calls for further research in this field to expand our understanding and enhance educational policy.

Keywords: inclusive education, special educational needs, learning achievement, Peru, Basic education

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

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Authors: Khitem Amiri, Mohamed Farah

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Image classification is a challenging task and is gaining lots of interest since it helps us to understand the content of images. Recently Deep Learning (DL) based methods gave very interesting results on several benchmarks. For Hyperspectral images (HSI), the application of DL techniques is still challenging due to the scarcity of labeled data and to the curse of dimensionality. Among other approaches, Deep Belief Network (DBN) based approaches gave a fair classification accuracy. In this paper, we address the problem of the curse of dimensionality by reducing the number of bands and replacing the HSI channels by the channels representing radiometric indices. Therefore, instead of using all the HSI bands, we compute the radiometric indices such as NDVI (Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), etc, and we use the combination of these indices as input for the Deep Belief Network (DBN) based classification model. Thus, we keep almost all the pertinent spectral information while reducing considerably the size of the image. In order to test our image representation, we applied our method on several HSI datasets including the Indian pines dataset, Jasper Ridge data and it gave comparable results to the state of the art methods while reducing considerably the time of training and testing.

Keywords: hyperspectral images, deep belief network, radiometric indices, image classification

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Authors: Swathi M. Vanniarajan

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Reading research suggests that online contextual vocabulary comprehension while reading is an interactive and integrative process. One’s success in it depends on a variety of factors including the amount and the nature of available linguistic and nonlinguistic cues, his/her analytical and integrative skills, schema memory (content familiarity), and processing speed characterized along the continuum of controlled to automatic processing. The experiment reported here, conducted with 30 native speakers as one group and 30 nonnative speakers as another group (all graduate students), hypothesized that while working on (24) tasks which required them to comprehend an unfamiliar word in real time without backtracking, due to the differences in the nature of their respective reading processes, the nonnative subjects would be less able to construct the meanings of the unknown words by integrating the multiple but sufficient contextual cues provided in the text but the native subjects would be able to. The results indicated that there were significant inter-group as well as intra-group differences in terms of the quality of definitions given. However, when given additional time, while the nonnative speakers could significantly improve the quality of their definitions, the native speakers in general would not, suggesting that all things being equal, time is a significant factor for success in nonnative vocabulary and reading comprehension processes and that accuracy precedes automaticity in the development of nonnative reading processes also.

Keywords: reading, second language processing, vocabulary comprehension

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Authors: Tesfaw Belayneh Abebe

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Integrating low-altitude earth orbit (LEO) satellites and unmanned aerial vehicles (UAVs) within a non-terrestrial network (NTN) with the assistance of reconfigurable intelligent surfaces (RIS), we investigate the problem of how to enhance throughput through integrated LEO satellites and UAVs with the assistance of RIS. We propose a method to jointly optimize the associations with the LEO satellite, the 3D trajectory of the UAV, and the phase shifts of the RIS to maximize communication throughput for RIS-assisted integrated LEO satellite and UAV-enabled wireless communications, which is challenging due to the time-varying changes in the position of the LEO satellite, the high mobility of UAVs, an enormous number of possible control actions, and also the large number of RIS elements. Utilizing a multi-agent double deep Q-network (MADDQN), our approach dynamically adjusts LEO satellite association, UAV positioning, and RIS phase shifts. Simulation results demonstrate that our method significantly outperforms baseline strategies in maximizing throughput. Lastly, thanks to the integrated network and the RIS, the proposed scheme achieves up to 65.66x higher peak throughput and 25.09x higher worst-case throughput.

Keywords: integrating low-altitude earth orbit (LEO) satellites, unmanned aerial vehicles (UAVs) within a non-terrestrial network (NTN), reconfigurable intelligent surfaces (RIS), multi-agent double deep Q-network (MADDQN)

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Authors: Maciej Bialorudzki, Zbigniew Izdebski, Alicja Kozakiewicz, Joanna Mazur

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The quality of sleep is extremely important for physical and mental health, especially among professional groups exposed to the suffering of the people they serve. The aim of the study is to assess sleep quality and various aspects of physical and mental health. A nationwide cross-sectional survey conducted in the first quarter of 2022 included 2227 healthcare professionals from 114 Polish hospitals and specialized outpatient clinics. The following distribution for each professional group was obtained (22% doctors; 52.6% nurses; 7.3% paramedics; 10.1% other medical professionals; 7.9% other non-medical professionals). The mean age of the respondents was 46.24 (SD=11.53). The Jenkins Sleep Scale with four items (JSS-4) was used to assess sleep quality, yielding a mean value of 5.35 (SD=5.20) in the study group and 13.7% of subjects with poor sleep quality using the cutoff point of the mean JSS-4 sum score as >11. More often, women than men reported poorer sleep quality (14,8% vs. 9,1% p=0,002). Respondents with poor sleep quality were more likely to report occupational burnout as measured by the BAT-12 (43.1% vs. 12.9% p<0.001) and high levels of stress as measured by the PSS-4 (72.5% vs. 27.5% p<0.001). In addition, those who declare experiencing a traumatic event compared to those who have not experienced it has an almost two times higher risk of poorer sleep quality (OR:1.958; 95% CI:1.509-2.542; p<0.001). In contrast, those with occupational burnout had more than five times the risk of those without occupational burnout (OR:5.092; 95% CI: 3.763-6.889; p<0.001). Sleep quality remains an important predictor of stress levels, job burnout, and quality of life assessment.

Keywords: quality of sleep, medical staff, mental health, physical health, occupational burnout, stress

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Authors: Mostafa Mjahed

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Tilt Rotor UAVs (Unmanned Aerial Vehicles) are naturally unstable and difficult to maneuver. The purpose of this paper is to design controllers for the stabilization and trajectory tracking of this type of UAV. To this end, artificial intelligence methods have been exploited. First, the dynamics of this UAV was modeled using the Lagrange-Euler method. The conventional method based on Proportional, Integral and Derivative (PID) control was applied by decoupling the different flight modes. To improve stability and trajectory tracking of the Tilt Rotor, the fuzzy approach and the technique of multilayer neural networks (NN) has been used. Thus, Fuzzy Proportional Integral and Derivative (FPID) and Neural Network-based Proportional Integral and Derivative controllers (NNPID) have been developed. The meta-heuristic approach based on Particle Swarm Optimization (PSO) method allowed adjusting the setting parameters of NNPID controller, giving us an improved NNPID-PSO controller. Simulation results under the Matlab environment show the efficiency of the approaches adopted. Besides, the Tilt Rotor UAV has become stable and follows different types of trajectories with acceptable precision. The Fuzzy, NN and NN-PSO-based approaches demonstrated their robustness because the presence of the disturbances did not alter the stability or the trajectory tracking of the Tilt Rotor UAV.

Keywords: neural network, fuzzy logic, PSO, PID, trajectory tracking, tilt-rotor UAV

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Authors: Gabriele Iannotta

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This paper investigates credit cycles by means of an experiment based on a Kiyotaki & Moore (1997) model with heterogeneous expectations. The aim is to examine how a credit squeeze caused by high lender-level risk perceptions affects the real prices of a collateralised asset, with a special focus on the macroeconomic implications of rising price volatility in terms of total welfare and the number of bankruptcies that occur. To do that, a learning-to-forecast experiment (LtFE) has been run where participants are asked to predict the future price of land and then rewarded based on the accuracy of their forecasts. The setting includes one lender and five borrowers in each of the twelve sessions split between six control groups (G1) and six treatment groups (G2). The only difference is that while in G1 the lender always satisfies borrowers’ loan demand (bankruptcies permitting), in G2 he/she closes the entire credit market in case three or more bankruptcies occur in the previous round. Experimental results show that negative risk-driven supply shocks amplify the volatility of collateral prices. This uncertainty worsens the agents’ ability to predict the future value of land and, as a consequence, the number of defaults increases and the total welfare deteriorates.

Keywords: Behavioural Macroeconomics, Credit Cycle, Experimental Economics, Heterogeneous Expectations, Learning-to-Forecast Experiment

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Authors: Yoftahe Nigussie Worku

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This study focused on designing a Fire tube boiler to generate saturated steam with a 2000kg/h capacity at a 12bar design pressure. The primary project goal is to achieve efficient steam production while minimizing costs. This involves selecting suitable materials for component parts, employing cost-effective construction methods, and optimizing various parameters. The analysis phase employs iterative processes and relevant formulas to determine key design parameters. This includes optimizing the diameter of tubes for overall heat transfer coefficient, considering a two-pass configuration due to tube and shell size, and using heavy oil fuel no.6 with specific heating values. The designed boiler consumes 140.37kg/hr of fuel, producing 1610kw of heat at an efficiency of 85.25%. The fluid flow is configured as cross flow, leveraging its inherent advantages. The tube arrangement involves welding the tubes inside the shell, which is connected to the tube sheet using a combination of gaskets and welding. The design of the shell adheres to the European Standard code for pressure vessels, accounting for weight and supplementary accessories and providing detailed drawings for components like lifting lugs, openings, ends, manholes, and supports.

Keywords: efficiency, coefficient, saturated steam, fire tube

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Authors: Thizwilondi Madzaga, Jabu Tsakani Mabunda, Takalani Tshitangano

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Hypertension is a global public health problem. In most cases, hypertension individuals are not aware of their condition, and they only detected it accidentally during public awareness programmes. The aim of the study was to determine the prevalence, awareness and control of hypertension among University of Venda academic staff. UNIVEN is situated in Thohoyandou, South Africa. A cross-sectional study was conducted to determine the prevalence, awareness and control of hypertension among University of Venda academic staff. Slovin’s formula was used to randomly select 179 academic staff (male=104 and female=75). WHO stepwise Questionnaire version 23.0 was used to get information on demographic information. Blood pressure was measured twice after five minutes rest using electronic blood pressure monitor. In this study, hypertension referred to self-reported to be on hypertension medication or having blood pressure equal or exceeding 140 over 90 mmHg. Statistical Package of Social Sciences version 23.0 was used to analyse data. Prevalence of hypertension was 20% and 46% prehypertension. Only 34% had a normal blood pressure. About 34% were not sure of their current blood pressure status (within 12 months). About 10% of the total respondents had been previously diagnosed with hypertension and half of them who were hypertensive were not aware that they had it. Among those who were aware that they are hypertensive, about 90% were on treatment whereas 10% had stopped taking treatment. About 13% of those who were on treatment had controlled blood pressure. There is a need for health education programmes to increase hypertension awareness.

Keywords: academic staff, awareness, control, hypertension, prevalence

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Authors: Mohamamd Shahjahan

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Background: Cybercrime is common phenomenon at present both developed and developing countries. Young generation, especially adolescents now engaged internet frequently and they commit cybercrime frequently in Bangladesh. Objective: In this regard, the present study on the pattern of cybercrime among youngers of Bangladesh has been conducted. Methods and tools: This study was a cross-sectional study, descriptive in nature. Non-probability accidental sampling technique has been applied to select the sample because of the nonfinite population and the sample size was 167. A printed semi-structured questionnaire was used to collect data. Results: The study shows that adolescents mainly do hacking (94.6%), pornography (88.6%), software piracy (85 %), cyber theft (82.6%), credit card fraud (81.4%), cyber defamation (75.6%), sweet heart swindling (social network) (65.9%) etc. as cybercrime. According to findings the major causes of cybercrime among the respondents in Bangladesh were- weak laws (88.0%), defective socialization (81.4%), peer group influence (80.2%), easy accessibility to internet (74.3%), corruption (62.9%), unemployment (58.7%), and poverty (24.6%) etc. It is evident from the study that 91.0% respondents used password cracker as the techniques of cyber criminality. About 76.6%, 72.5%, 71.9%, 68.3% and 60.5% respondents’ technique was key loggers, network sniffer, exploiting, vulnerability scanner and port scanner consecutively. Conclusion: The study concluded that pattern of cybercrimes is frequently changing and increasing dramatically. Finally, it is recommending that the private public partnership and execution of existing laws can be controlling this crime.

Keywords: cybercrime, adolescents, pattern, internet

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Authors: Rui Liu, Pengyu Cui, Nan Jiang

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At present, there is much research on the application of centralized management and cross-integration application of basic geographic information. However, the idea of information integration and sharing between land, sea, and air navigation targets is not deeply applied into the research of navigation information service, especially in the information expression. Targeting at this problem, the paper carries out works about the expression pattern of navigation electronic map for ground vehicles under air and land united navigation mechanism. At first, with the support from multi-source information fusion of GIS vector data, RS data, GPS data, etc., an air and land united information expression pattern is designed aiming at specific navigation task of emergency rescue in the earthquake. And then, the characteristics and specifications of the united expression of air and land navigation information under the constraints of map load are summarized and transferred into expression rules in the rule bank. At last, the related navigation experiment is implemented to evaluate the effect of the expression pattern. The experiment selects evaluation factors of the navigation task accomplishment time and the navigation error rate as the main index, and make comparisons with the traditional single information expression pattern. To sum up, the research improved the theory of navigation electronic map and laid a certain foundation for the design and realization of united navigation system in the aspect of real-time navigation information delivery.

Keywords: navigation electronic map, united navigation, multi-element expression pattern, multi-source information fusion

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Authors: Mastawal Melese, Yismaw Assefa Lakew

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This study aims to identify household-level determinants of solid waste disposal (SWD) practices in Bure Town, north-western Ethiopia. Using a cross-sectional design and a mixed-methods approach, data were collected from 238 randomly selected households through structured interviews, focus group discussions, and field observations. Descriptive analysis revealed that 14.7% of households used composting as a primary SWD method, 37.4% practiced open dumping, 25.6% used burning, and 22.3% resorted to burial. Multinomial logistic regression showed that factors such as monthly income, age, family size, length of residence, sex, home ownership, solid waste sorting procedures, and education significantly influenced the choice of disposal method. Households with lower education, income, home ownership, and shorter residence times were more likely to use improper disposal methods. Females were found to be more likely to engage in better waste disposal practices than males. These findings underscore the need for context-specific interventions in newly developing towns to enhance household-level SWM systems by addressing key socio-economic factors.

Keywords: urban household, solid waste, solid waste management, solid waste disposal, multinomial logistic regression

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Authors: S. J. Shahidzadeh Tabatabaei, A. M. Fattahi

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Modal analysis of an FGM plate containing the ceramic phase of Al2O3 and metal phase of stainless steel 304 was performed using ABAQUS, with the assumptions that the material has an elastic mechanical behavior and its Young modulus and density are varying in thickness direction. For this purpose, a subroutine was written in FORTRAN and linked with ABAQUS. First, a simulation was performed in accordance to other researcher’s model, and then after comparing the obtained results, the accuracy of the present study was verified. The obtained results for natural frequency and mode shapes indicate good performance of user-written subroutine as well as FEM model used in present study. After verification of obtained results, the effect of clamping condition and the material type (i.e. the parameter n) was investigated. In this respect, finite element analysis was carried out in fully clamped condition for different values of n. The results indicate that the natural frequency decreases with increase of n, since with increase of n, the amount of ceramic phase in FGM plate decreases, while the amount of metal phase increases, leading to decrease of the plate stiffness and hence, natural frequency, as the Young modulus of Al2O3 is equal to 380 GPa and the Young modulus of stainless steel 304 is equal to 207 GPa.

Keywords: FGM plates, modal analysis, natural frequency, finite element method

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Authors: Azadeh Mohajer Milani

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Urbanization constitutes an irreversible global trend, presenting myriad challenges such as heightened energy consumption, pollution, congestion, and the depletion of natural resources. Today's urban landscapes have emerged as focal points for economic, social, and environmental challenges, underscoring the pressing need for sustainable development. This article delves into the realm of sustainable urban development, concentrating on the pivotal role played by integrated green spaces as an optimal solution to address environmental concerns within cities. The study utilizes Tehran as a case study. Our findings underscore the imperative of preserving and expanding green spaces in urban areas, coupled with the establishment of well-designed ecological networks, to enhance environmental quality and elevate the sustainability of cities. Notably, Tehran's urban green spaces exhibit a disjointed design, lacking a cohesive network to connect various patches and corridors, resulting in significant environmental impacts. The results emphasize the necessity of a balanced and proportional distribution of urban green spaces and the creation of a cohesive patch-corridor-matrix network tailored to the ecological and social needs of residents. This approach is crucial for fostering a more sustainable and livable urban environment for all species, with a specific focus on humans.

Keywords: ecology, sustainable urban development, sustainable landscape, urban green space network

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Authors: Izani Uzair Zubair, Mohd Ismail Ibrahim, Mohd Nazri Shafei, Hassan Merican Omar Naina Merican, Mohamad Sabri Othman, Mohd Izmi Ahmad Ibrahim, Rasilah Ramli, Rajpal Singh Karam Singh

Abstract:

Nurses experience a higher prevalence of low back pain (LBP) and musculoskeletal complaints as compared to other hospital workers. Due to no proper policy related to LBP, the job has exposed them to the problem. Thus, the current study aims to look at the intensity of the problem and factors associated with development of LBP. Method and Tools: A cross sectional study was carried out among 1292 nurses from six public hospitals in Penang. They were randomly selected and those who were pregnant and have been diagnosed to have LBP were excluded. A Malay validated BACK Questionnaire was used. The associated factors were determined by using multiple logistic regression from SPSS version 20.0. Result: Most of the respondents were at mean age 30 years old and had mean working experience 86 months. The prevalence of LBP was identified as 76% (95% CI 74, 82). Factors that were associated with LBP among nurses include lifting a heavy object (OR2.626 (95% CI 1.978, 3.486) p =0.001 and the estimation weight of the lifted object (OR1.443 (95% CI 1.056, 1.970) p =0.021. Conclusion: Nurses who practice lifting heavy object and weight of the object lifted give a significant contribution to the development of LBP. The prevalence of the problem is significantly high. Thus, a proper no weight lifting policy should be considered.

Keywords: low back pain, nurses, Penang public hospital, Penang

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Authors: Farooq Anwar, Gokhan Zengin, Khalid M. Alkharfy

Abstract:

Wild rice (Zizania sp.) is an annual cross-pollinated, emergent, aquatic grass that mainly grows naturally in the Great Lakes region of the North America. The nutritional quality attributes of wild rice are superior to the conventional brown rice (Oryza sativa L.) in terms of higher contents of important minerals (especially phosphorous, potassium, magnesium and calcium), B-complex vitamins, vitamin E and amino acids. In some parts of the world, wild rice is valued as a primary food source. The lipids content of wild rice is reported to be low in the range of 0.7 and 1.1%, however, the lipids are recognized as a rich source of polyunsaturated fatty acids (including linoleic and α-linolenic acid) and phytosterols in addition to containing reasonably good amount of tocols. Besides, wild rice is reported to contain an appreciable amount of high-value compounds such as phenolics with antioxidant properties. Presence of such nutritional bioactives contributes towards medicinal benefits and multiple biological activities of this specialty rice. The present lecture is mainly designed to focus on the detailed nutritional attributes, profile of high-value bioactive components and pharmaceutical/biological activities of wild rice leading to exploring functional food and nutraceutical potential of this food commodity.

Keywords: alpha-linolenic acid, phenolics, phytosterols, tocols, wild rice lipids

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Authors: Funmilayo Abiola Opadoja, Samuel Olukayode Awotona

Abstract:

Nursing services costing has been a major interest to nurses for a long period of time. Determination of nursing costing is germane in order to show the effectiveness of nursing practice in an improved and affordable health care delivery system. This has been a major concern of managers that have the mind of quality and affordable health services. The treatment or intervention should be considered as ‘product’ of nursing care and should provide an explainable term for billing. The study was non-experimental, descriptive and went about eliciting the views of nurses on costing nursing care at two public hospitals namely: University College Hospital and Adeoyo Maternity Teaching Hospital. The questionnaire was the instrument used in eliciting nurse’s response. It was administered randomly on 300 selected respondents across various wards within the hospitals. The data was collected and analysed using SPSS20.0 to generate frequency, and cross-tabulations to explore the statistical relationship between variables. The result shows that 89.2% of the respondents viewed costing of nursing care as an important issued to be looked into. The study concluded that nursing care costing is germane to enhancing the status and imagery of the nurses, it is essential because it would enhance the performance of nurses in discharging their duties. There is need to have a procedural manual agreed on by nursing practitioner on costing of each care given.

Keywords: costing, health care delivery system, intervention, nursing care, practitioner

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Authors: Ming Ma, Rui Li

Abstract:

In the highly urbanized district, green open space is playing an important role in human’s health and wellbeing as a physical, aesthetic and natural environment resources. The aim of this paper is to close this gap through providing a comprehensive, qualitative meta-analysis of existing studies related to this issue. A systematic scoping of current quantitative research is conducted which mostly focused on cross-sectional survey and experimental studies. Health benefits from contact with green open space could be categorized into physical health, psychological health and social wellbeing. Mechanism for the health related to green open space could be clearly identified with the regard to natural restoration, physical activities and social capital. These results indicate a multiple pathways framework between the health benefits and mechanism. In order to support design and planning, the most evident relationship was picked up that people could psychologically benefit from green open space through outdoors physical activities. Additionally, three design and planning strategies are put forward. Various and multi-level contacts with green open space would be considered as an explanation of the pathway results and tie to bridge the health to design and planning. There is a need to carry out long-term research emphasizing on causal relationship between health and green open space through excluding cofounding factors such as self-selection.

Keywords: urban green open space, planning and design, health benefit, mechanism, pathway framework

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Authors: M. Kosacka, I. Kudelska

Abstract:

Vehicle is one of the most influential and complex product worldwide, which affects people’s life, state of the environment and condition of the economy (all aspects of sustainable development concept) during each stage of lifecycle. With the increase of vehicles’ number, there is growing potential for management of End of Life Vehicle (ELV), which is hazardous waste. From one point of view, the ELV should be managed to ensure risk elimination, but from another point, it should be treated as a source of valuable materials and spare parts. In order to obtain materials and spare parts, there are established recycling networks, which are an example of sustainable policy realization at the national level. The basic object in the polish recycling network is dismantling facility. The output material streams in dismantling stations include waste, which very often generate costs and spare parts, that have the biggest potential for revenues creation. Both outputs are stored into warehouses, according to the law. In accordance to the revenue creation and sustainability potential, it has been placed a strong emphasis on storage process. We present the concept of storage method, which takes into account the specific of the dismantling facility in order to support decision-making process with regard to the principles of sustainable development. The method was developed on the basis of case study of one of the greatest dismantling facility in Poland.

Keywords: dismantling, end of life vehicles, sustainability, storage

Procedia PDF Downloads 267