Search results for: propensity score matching logit model

Authors: Arezoo Fallahi

Abstract:

Introduction: Exposure to second-hand smoke is an important global health problem and threatens the health of people, especially children and women. The aim of this study was to determine the effect of education based on the Health Belief Model on preventive behaviors of exposure to second-hand smoke in women. Materials and Methods: This experimental study was performed in 2022 in Sanandaj, west of Iran. Seventy-four people were selected by simple random sampling and divided into an intervention group (37 people) and a control group (37 people). Data collection tools included demographic characteristics and a second-hand smoke exposure questionnaire based on the Health Beliefs Model. The training in the intervention group was conducted in three one-hour sessions in the comprehensive health service centers in the form of lectures, pamphlets, and group discussions. Data were analyzed using SPSS software version 21 and statistical tests such as correlation, paired t-test, and independent t-test. Results: The intervention and control groups were homogeneous before education. They were similar in terms of mean scores of the Health Belief Model. However, after an educational intervention, some of the scores increased, including the mean perceived sensitivity score (from 17.62±2.86 to 19.75±1.23), perceived severity score (28.40±4.45 to 31.64±2), perceived benefits score (27.27±4.89 to 31.94±2.17), practice score (32.64±4.68 to 36.91±2.32) perceived barriers from 26.62±5.16 to 31.29±3.34, guide for external action (from 17.70±3.99 to 22/89 ±1.67), guide for internal action from (16.59±2.95 to 1.03±18.75), and self-efficacy (from 19.83 ±3.99 to 23.37±1.43) (P <0.05). Conclusion: The educational intervention designed based on the Health Belief Model in women was effective in performing preventive behaviors against exposure to second-hand smoke.

Keywords: education, women, exposure to secondhand smoke, health belief model

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

Abstract:

A simple adaptive voice activity detector (VAD) is implemented using Gabor and gammatone atomic decomposition of speech for high Gaussian noise environments. Matching pursuit is used for atomic decomposition, and is shown to achieve optimal speech detection capability at high data compression rates for low signal to noise ratios. The most active dictionary elements found by matching pursuit are used for the signal reconstruction so that the algorithm adapts to the individual speakers dominant time-frequency characteristics. Speech has a high peak to average ratio enabling matching pursuit greedy heuristic of highest inner products to isolate high energy speech components in high noise environments. Gabor and gammatone atoms are both investigated with identical logarithmically spaced center frequencies, and similar bandwidths. The algorithm performs equally well for both Gabor and gammatone atoms with no significant statistical differences. The algorithm achieves 70% accuracy at a 0 dB SNR, 90% accuracy at a 5 dB SNR and 98% accuracy at a 20dB SNR using 30dB SNR as a reference for voice activity.

Keywords: atomic decomposition, gabor, gammatone, matching pursuit, voice activity detection

Procedia PDF Downloads 290

Authors: Ramanish Ravishankar, Azar Hussain, Mahmoud Loubani, Mubarak Chaudhry

Abstract:

Background and Aims: Currently, there are no strict guidelines in cardiopulmonary bypass temperature management in cardiac surgery not involving the aortic arch. This study aims to compare patient outcomes undergoing mild hypothermia and normothermia. The aim of this study was to compare patient outcomes between mild hypothermia and normothermia undergoing on-pump cardiac surgery not involving the aortic arch. Methods: This was a retrospective cohort study from January 2015 until May 2023. Patients who underwent cardiac surgery with cardiopulmonary bypass temperatures ≥32oC were included and stratified into mild hypothermia (32oC – 35oC) and normothermia (>35oC) cohorts. Propensity matching was applied through the nearest neighbour method (1:1) using the risk factors detailed in the EuroScore using RStudio. The primary outcome was mortality. Secondary outcomes included post-op stay, intensive care unit readmission, re-admission, stroke, and renal complications. Patients who had major aortic surgery and off-pump operations were excluded. Results: Each cohort had 1675 patients. There was a significant increase in overall mortality with the mild hypothermia cohort (3.59% vs. 2.32%; p=0.04912). There was also a greater stroke incidence (2.09% vs. 1.13%; p=0.0396) and transient ischaemic attack (TIA) risk (3.1% vs. 1.49%; p=0.0027). There was no significant difference in renal complications (9.13% vs. 7.88%; p=0.2155). Conclusions: Patient’s who underwent mild hypothermia during cardiopulmonary bypass have a significantly greater mortality, stroke, and transient ischaemic attack incidence. Mild hypothermia does not appear to provide any benefit over normothermia and does not appear to provide any neuroprotective benefits. This shows different results to that of other major studies; further trials and studies need to be conducted to reach a consensus.

Keywords: cardiac surgery, therapeutic hypothermia, neuroprotection, cardiopulmonary bypass

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Authors: Abdullah AlGhazali, Richard Fairchild, Yilmaz Guney

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We examine the effect of managerial overconfidence on UK firms’ payout policy for the period 2000 to 2012. The analysis incorporates, in addition to common firm-specific factors, a wide range of corporate governance factors and managerial characteristics that have been documented to affect the relationship between overconfidence and payout policy. Our results are robust to several estimation considerations. The findings show that the influence of overconfident CEOs on the amount of, and the propensity to pay, dividends is significant within the UK context. Specifically, we detect that there is a reduction in dividend payments in firms managed by overconfident managers compared to their non-overconfident counterparts. Moreover, we affirm that cash flows, firm size and profitability are positively correlated, while leverage, firm growth and investment are negatively correlated with the amount of and propensity to pay dividends. Interestingly, we demonstrate that firms with the potential for undervaluation reduce dividend payments. Some of the corporate governance factors are shown to motivate firms to pay more dividends while these factors seem to have no influence on the propensity to pay dividends. The results also show that in general higher overconfidence leads to more share repurchases but the lower total payout. Overall, managerial overconfidence should be considered as an important factor influencing payout policy in addition to other known factors.

Keywords: dividends, repurchases, UK firms, overconfidence, corporate governance, undervaluation

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Authors: Prajamitra Bhuyan

Abstract:

Transport operators have a range of intervention options available to improve or enhance their networks. But often such interventions are made in the absence of sound evidence on what outcomes may result. Cycling superhighways were promoted as a sustainable and healthy travel mode which aims to cut traffic congestion. The estimation of the impacts of the cycle superhighways on congestion is complicated due to the non-random assignment of such intervention over the transport network. In this paper, we analyse the causal effect of cycle superhighways utilising pre-innervation and post-intervention information on traffic and road characteristics along with socio-economic factors. We propose a modeling framework based on the propensity score and outcome regression model. The method is also extended to doubly robust set-up. Simulation results show the superiority of the performance of the proposed method over existing competitors. The method is applied to analyse a real dataset on the London transport network, and the result would help effective decision making to improve network performance.

Keywords: average treatment effect, confounder, difference-in-difference, intelligent transportation system, potential outcome

Procedia PDF Downloads 240

Authors: Arezoo Fallahi

Abstract:

Introduction: Exposure to second-hand smoke is an important global health problem and threatens the health of people, especially children and women. The aim of this study was to determine the effect of education based on the Health Belief Model on preventive behaviors of exposure to secondhand smoke in women. Materials and Methods: This experimental study was performed in 2023in Sanandaj, west of Iran. Seventy-four people were selected by simple random sampling and divided into an intervention group (37 people) and a control group (37 people). Data collection tools included demographic characteristics and a second-hand smoke exposure questionnaire based on the Health Beliefs Model. The training in the intervention group was conducted in three one-hour sessions in the comprehensive health service centers in the form of lectures, pamphlets, and group discussions. Data were analyzed using SPSS software version 21 and statistical tests such as correlation, paired t-test, and independent t-test. Results: The intervention and control groups were homogeneous before education. They were similar in terms of mean scores of the Health Belief Model. However, after an educational intervention, some of the scores increased, including the mean perceived sensitivity score (from 17.62±2.86 to 19.75±1.23), perceived severity score (28.40±4.45 to 31.64±2), perceived benefits score (27.27±4.89 to 31.94±2.17), practice score (32.64±4.68 to 36.91±2.32) perceived barriers from 26.62±5.16 to 31.29±3.34, guide for external action (from 17.70±3.99 to 22/89 ±1.67), guide for internal action from (16.59±2.95 to 1.03±18.75), and self-efficacy (from 19.83 ±3.99 to 23.37±1.43) (P <0.05). Conclusion: The educational intervention designed based on the Health Belief Model in women was effective in performing preventive behaviors against exposure to secondhand smoke.

Keywords: women, health behaviour, smoke, belive

Procedia PDF Downloads 54

Authors: Simone B. K. Aires, Cinthia O. de A. Freitas, Luiz E. S. Oliveira

Abstract:

This paper contributes to the CBIR systems applied to trademark retrieval. The proposed model includes aspects from visual perception of the shapes, by means of feature extractor associated to a non-symmetrical perceptual zoning mechanism based on the Principles of Gestalt. Thus, the feature set were performed using Scale Invariant Feature Transform (SIFT). We carried out experiments using four different zonings strategies (Z = 4, 5H, 5V, 7) for matching and retrieval tasks. Our proposal method achieved the normalized recall (Rn) equal to 0.84. Experiments show that the non-symmetrical zoning could be considered as a tool to build more reliable trademark retrieval systems.

Keywords: CBIR, Gestalt, matching, non-symmetrical zoning, SIFT

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Authors: Ayesha Sanjana Kawser Parsha

Abstract:

S-acylation is an irreversible bond in which cysteine residues are linked to fatty acids palmitate (74%) or stearate (22%), either at the COOH or NH2 terminal, via a thioester linkage. There are several experimental methods that can be used to identify the S-palmitoylation site; however, since they require a lot of time, computational methods are becoming increasingly necessary. There aren't many predictors, however, that can locate S- palmitoylation sites in Arabidopsis Thaliana with sufficient accuracy. This research is based on the importance of building a better prediction tool. To identify the type of machine learning algorithm that predicts this site more accurately for the experimental dataset, several prediction tools were examined in this research, including the GPS PALM 6.0, pCysMod, GPS LIPID 1.0, CSS PALM 4.0, and NBA PALM. These analyses were conducted by constructing the receiver operating characteristics plot and the area under the curve score. An AI-driven deep learning-based prediction tool has been developed utilizing the analysis and three sequence-based input data, such as the amino acid composition, binary encoding profile, and autocorrelation features. The model was developed using five layers, two activation functions, associated parameters, and hyperparameters. The model was built using various combinations of features, and after training and validation, it performed better when all the features were present while using the experimental dataset for 8 and 10-fold cross-validations. While testing the model with unseen and new data, such as the GPS PALM 6.0 plant and pCysMod mouse, the model performed better, and the area under the curve score was near 1. It can be demonstrated that this model outperforms the prior tools in predicting the S- palmitoylation site in the experimental data set by comparing the area under curve score of 10-fold cross-validation of the new model with the established tools' area under curve score with their respective training sets. The objective of this study is to develop a prediction tool for Arabidopsis Thaliana that is more accurate than current tools, as measured by the area under the curve score. Plant food production and immunological treatment targets can both be managed by utilizing this method to forecast S- palmitoylation sites.

Keywords: S- palmitoylation, ROC PLOT, area under the curve, cross- validation score

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Authors: Adnan A. Y. Mustafa

Abstract:

In this paper we present a quick technique to measure the similarity between binary images. The technique is based on a probabilistic mapping approach and is fast because only a minute percentage of the image pixels need to be compared to measure the similarity, and not the whole image. We exploit the power of the Probabilistic Matching Model for Binary Images (PMMBI) to arrive at an estimate of the similarity. We show that the estimate is a good approximation of the actual value, and the quality of the estimate can be improved further with increased image mappings. Furthermore, the technique is image size invariant; the similarity between big images can be measured as fast as that for small images. Examples of trials conducted on real images are presented.

Keywords: big images, binary images, image matching, image similarity

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Authors: Young-Hyun Seo, Hyunwoo Park, Dong-Kyu Kim, Seung-Young Kho

Abstract:

The purpose of this study is providing an improved mode choice model considering parameters including age grouping of prime-aged and old age. In this study, 2010 Household Travel Survey data were used and improper samples were removed through the analysis. Chosen alternative, date of birth, mode, origin code, destination code, departure time, and arrival time are considered from Household Travel Survey. By preprocessing data, travel time, travel cost, mode, and ratio of people aged 45 to 55 years, 55 to 65 years and over 65 years were calculated. After the manipulation, the mode choice model was constructed using LIMDEP by maximum likelihood estimation. A significance test was conducted for nine parameters, three age groups for three modes. Then the test was conducted again for the mode choice model with significant parameters, travel cost variable and travel time variable. As a result of the model estimation, as the age increases, the preference for the car decreases and the preference for the bus increases. This study is meaningful in that the individual and households characteristics are applied to the aggregate model.

Keywords: age grouping, aging, mode choice model, multinomial logit model

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Authors: Meltem Ucal

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It is obvious that with limited resources and increasing of energy consumption from day to day, increase in amount of greenhouse gases in the atmosphere will increase risk of climate change. The objective of “Raising Awareness in Energy Efficiency of Household Appliances and Climate Change” paper is to make the connection between climate change and energy saving to be understood. First of all, research and evaluation aiming improvement of women’s behaviors of purchasing and using household appliances and also educate next generations who will be faced risks of climate change, with their mothers will be done.

Keywords: energy efficiency, climate change, wareness, household appliences, econometrics model, logit model

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Authors: Pedro M. A. Vitoriano, Tito. G. Amaral

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Automated Optical Inspection (AOI) Systems are commonly used on Printed Circuit Boards (PCB) manufacturing. The use of this technology has been proven as highly efficient for process improvements and quality achievements. The correct extraction of the component for posterior analysis is a critical step of the AOI process. Nowadays, the Pattern Matching Algorithm is commonly used, although this algorithm requires extensive calculations and is time consuming. This paper will present an improved algorithm for the component localization process, with the capability of implementation in a parallel execution system.

Keywords: AOI, automated optical inspection, SMD, surface mounting devices, pattern matching, parallel execution

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Authors: Dimiter M. Dimitrov, Abdullah Sadaawi

Abstract:

The National Assessment for Schools (NAFS) in Saudi Arabia consists of standardized tests in Mathematics, Reading, and Science for school grade levels 3, 6, and 9. One main goal is to classify students into four categories of NAFS performance (minimal, basic, proficient, and advanced) by schools and the entire national sample. The NAFS scoring and equating is performed on a bounded scale (D-scale: ranging from 0 to 1) in the framework of the recently developed “D-scoring method of measurement.” The specificity of the NAFS measurement framework and data complexity presented both challenges and opportunities to (a) the estimation of score reliability for schools, (b) setting cut-scores for the classification of students into categories of performance, and (c) generating plausible values for distributions of student performance on the D-scale. The estimation of score reliability at the school level was performed in the framework of generalizability theory (GT), with students “nested” within schools and test items “nested” within test forms. The GT design was executed via a multilevel modeling syntax code in R. Cut-scores (on the D-scale) for the classification of students into performance categories was derived via a recently developed method of standard setting, referred to as “Response Vector for Mastery” (RVM) method. For each school, the classification of students into categories of NAFS performance was based on distributions of plausible values for the students’ scores on NAFS tests by grade level (3, 6, and 9) and subject (Mathematics, Reading, and Science). Plausible values (on the D-scale) for each individual student were generated via random selection from a statistical logit-normal distribution with parameters derived from the student’s D-score and its conditional standard error, SE(D). All procedures related to D-scoring, equating, generating plausible values, and classification of students into performance levels were executed via a computer program in R developed for the purpose of NAFS data analysis.

Keywords: large-scale assessment, reliability, generalizability theory, plausible values

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Authors: Armana Huq

Abstract:

Railway networks have a significant role in the economy of any country. Similar to other transportation modes, many lives suffer from fatalities or injuries caused by accidents related to the railway. Railway accidents are not as common as roadway accidents yet they are more devastating and damaging than other roadway accidents. Despite that, issues related to railway accidents are not taken into consideration with significant attention as a major threat because of their less frequency compared to other accident categories perhaps. However, the Federal Railroad Administration reported nearly twelve thousand train accidents related to the railroad in the year 2014, resulting in more than eight hundred fatalities and thousands of injuries in the United States alone of which nearly one third fatalities resulted from railway crossing accidents. From an analysis of railway accident data of six years (2005-2010), it has been revealed that 344 numbers of the collision were occurred resulting 200 people dead and 443 people injured in Bangladesh. This paper includes a comprehensive overview of the railway safety situation in Bangladesh from 1998 to 2015. Each year on average, eight fatalities are reported in at-grade level crossings due to railway accidents in Bangladesh. In this paper, the number of railway accidents that occurred in Bangladesh has been presented and a fatality rate of 58.62% has been estimated as the percentage of total at-grade railway level crossing accidents. For this study, analysis of railway accidents in Bangladesh for the period 1998 to 2015 was obtained from the police reported accident database using MAAP (Microcomputer Accident Analysis Package). Investigation of the major contributing factors to the railway accidents has been performed using the Multinomial Logit model. Furthermore, hotspot analysis has been conducted using ArcGIS. Eventually, some suggestions have been provided to mitigate those accidents.

Keywords: safety, human factors, multinomial logit model, railway

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Authors: Alok Kumar, Raviraj Patil

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The ability to respond to an incident of a disastrous event in a vulnerable area is very crucial an aspect of emergency management. The ability to constantly predict the likelihood of an event along with its severity in an area and react to those significant events which are likely to have a high impact allows the authorities to respond by allocating resources optimally in a timely manner. It provides for measuring, monitoring, and modeling facilities that integrate underlying systems into one solution to improve operational efficiency, planning, and coordination. We were particularly involved in this innovative incubation work on the current state of research and development in collaboration. technologies & systems for a disaster.

Keywords: predictive analytics, advanced analytics, area flood likelihood model, area flood severity model, level of impact model, mortality score, economic loss score, resource allocation, crew allocation

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Authors: G. Balakrishnan

Abstract:

Stereo Correspondence plays a major role in estimation of distance of an object from the stereo camera pair for various applications. In this paper, a stereo correspondence algorithm based on block-matching technique is presented. Initially, an energy matrix is calculated for every disparity obtained using modified Sum of Absolute Difference (SAD). Higher energy matrix errors are removed by using threshold value in order to reduce the mismatch errors. A smoothening filter is applied to eliminate unreliable disparity estimate across the object boundaries. The purpose is to improve the reliability of calculation of disparity map. The experimental results obtained shows that the final depth map produce better results and can be used to all the applications using stereo cameras.

Keywords: stereo matching, filters, energy matrix, disparity

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Authors: Welawat Tienpratarn, Chaiyaporn Yuksen, Rungrawin Promkul, Chetsadakon Jenpanitpong, Pajit Bunta, Suthap Jaiboon

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Supraventricular tachycardia (SVT) is an abnormally fast atrial tachycardia characterized by narrow (≤ 120 ms) and constant QRS. Adenosine was the drug of choice; the first dose was 6 mg. It can be repeated with the second and third doses of 12 mg, with greater than 90% success. The study found that patients observed at 4 hours after normal sinus rhythm was no recurrence within 24 hours. The objective of this study was to investigate the factors that influence the recurrence of SVT after adenosine in the emergency department (ED). The study was conducted retrospectively exploratory model, prognostic study at the Emergency Department (ED) in Faculty of Medicine, Ramathibodi Hospital, a university-affiliated super tertiary care hospital in Bangkok, Thailand. The study was conducted for ten years period between 2010 and 2020. The inclusion criteria were age > 15 years, visiting the ED with SVT, and treating with adenosine. Those patients were recorded with the recurrence SVT in ED. The multivariable logistic regression model developed the predictive model and prediction score for recurrence PSVT. 264 patients met the study criteria. Of those, 24 patients (10%) had recurrence PSVT. Five independent factors were predictive of recurrence PSVT. There was age>65 years, heart rate (after adenosine) > 100 per min, structural heart disease, and dose of adenosine. The clinical risk score to predict recurrence PSVT is developed accuracy 74.41%. The score of >6 had the likelihood ratio of recurrence PSVT by 5.71 times. The clinical predictive score of > 6 was associated with recurrence PSVT in ED.

Keywords: supraventricular tachycardia, recurrance, emergency department, adenosine

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Authors: Langa Hendrick Musawenkosi, Twala Bhekisipho

Abstract:

The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.

Keywords: FSASEC, academic environment model, decision trees, k-nearest neighbor, machine learning, popularity index, support vector machine

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Authors: Eke Balla Sophie Michelle

Abstract:

Forest provides a wide range of environmental goods and services among which, biodiversity or consumption goods and constitute public goods. Despite the importance of non-timber forest products (NTFPs) in sustaining livelihood and poverty smoothening in rural communities, they are highly depleted and poorly conserved. Yokadouma is a town where NTFPs is a renewable resource in active exploitation. It has been found that such exploitation is done in the same conditions as other localities that have experienced a rapid depletion of their NTFPs in destination to cities across Cameroon, Central Africa, and overseas. Given these realities, it is necessary to access the consequences of this overexploitation through negative effects on both the population and the environment. Therefore, to enhance participatory conservation initiatives, this study determines the household’s willingness to pay in community forest (CF) of Morikouali-ye, eastern region of Cameroon, for sustainable exploitation of NTFPs using contingent valuation method (CVM) through two approaches, one parametric (Logit model) and the other non-parametric (estimator of the Turnbull lower bound). The results indicate that five species are the most collected in the study area: Irvingia gabonensis, the Ricinodendron heudelotii, Gnetum, the Jujube and bark, their sale contributes significantly to 41 % of total household income. The average willingness to pay through the Logit model and the Turnbull estimator is 6845.2861 FCFA and 4940 FCFA respectively per household per year with a social cost of degradation estimated at 3237820.3253 FCFA years. The probability to pay increases with income, gender, number of women in the household, age, the commercial activity of NTFPs and decreases with the concept of sustainable development.

Keywords: non timber forest product, contingent valuation method, willingness to pay, sustainable development

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Authors: H. Zidoum, A. AlShareedah, S. Al Sawafi, A. Al-Ansari, B. Al Lawati

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Systemic lupus erythematosus (SLE) is an autoimmune disease with genetic and environmental components. SLE is characterized by a wide variability of clinical manifestations and a course frequently subject to unpredictable flares. Despite recent progress in classification tools, the early diagnosis of SLE is still an unmet need for many patients. This study proposes an interpretable disease classification model that combines the high and efficient predictive performance of CatBoost and the model-agnostic interpretation tools of Shapley Additive exPlanations (SHAP). The CatBoost model was trained on a local cohort of 219 Omani patients with SLE as well as other control diseases. Furthermore, the SHAP library was used to generate individual explanations of the model's decisions as well as rank clinical features by contribution. Overall, we achieved an AUC score of 0.945, F1-score of 0.92 and identified four clinical features (alopecia, renal disorders, cutaneous lupus, and hemolytic anemia) along with the patient's age that was shown to have the greatest contribution on the prediction.

Keywords: feature selection, classification, systemic lupus erythematosus, model interpretation, SHAP, Catboost

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Authors: Dojoon Jung, Kiwoong Moon, Joong Lee

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The height of criminals is one of the important clues that can determine the scope of the suspect's search or exclude the suspect from the search target. Although measuring the height of criminals by video alone is limited by various reasons, the 3D data of the scene and the Closed Circuit Television (CCTV) footage are matched, the height of the criminal can be measured. However, it is still difficult to measure the height of CCTV footage in the non-contact type measurement method because of variables such as position, posture, and head shape of criminals. In this paper, we propose a method of matching the CCTV footage with the 3D data on the crime scene and measuring the height of the person using the 3D human body model in the matched data. In the proposed method, the height is measured by using 3D human model in various scenes of the person in the CCTV footage, and the measurement value of the target person is corrected by the measurement error of the replay CCTV footage of the reference person. We tested for 20 people's walking CCTV footage captured from an indoor and an outdoor and corrected the measurement values with 5 reference persons. Experimental results show that the measurement error (true value-measured value) average is 0.45 cm, and this method is effective for the measurement of the person's height in CCTV footage.

Keywords: human height, CCTV footage, 2D/3D matching, 3D human body model

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Authors: Yin Zhang, Kai Qiao, Xiyang Zhi, Jinnan Gong, Jianming Hu

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In order to effectively detect aerial targets over long distances, an optimal matching design method of space-based optical payload is proposed. Firstly, main factors affecting optical detectability of small targets under complex environment are analyzed based on the full link of a detection system, including band center, band width and spatial resolution. Then a performance characterization model representing the relationship between image signal-to-noise ratio (SCR) and the above influencing factors is established to describe a detection system. Finally, an optimal matching design example is demonstrated for a typical aerial target by simulating and analyzing its SCR under different scene clutter coupling with multi-scale characteristics, and the optimized detection band and spatial resolution are presented. The method can provide theoretical basis and scientific guidance for space-based detection system design, payload specification demonstration and information processing algorithm optimization.

Keywords: space-based detection, aerial targets, optical system design, detectability characterization

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Authors: H. Nabaei, M. Joghataie

Abstract:

In this article, we study the design methods of matched filter with commercial software including CST Studio and ADS in specific frequency: 900 MHz. At first, we select two amounts of impedance for studying matching of them. Then, using by matched filter utility tool in ADS software, we simulate and deviate the elements of matched filters. In the following, we implement matched filter in CST STUDIO software. The simulated results show the great conformity in this field. Also, we peruse scattering and Impedance parameters in the Derivative structure. Finally, the layout of matched filter is obtained by the schematic tool of CST STUDIO. In fact, here, we present the design process of matched filters in the specific frequency.

Keywords: impedance matching, lumped element, transmission line, maximum power transmission, 3D layout

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Authors: Israa Sh. Tawfic, Sema Koc Kayhan

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Given a large sparse signal, great wishes are to reconstruct the signal precisely and accurately from lease number of measurements as possible as it could. Although this seems possible by theory, the difficulty is in built an algorithm to perform the accuracy and efficiency of reconstructing. This paper proposes a new proved method to reconstruct sparse signal depend on using new method called Least Support Matching Pursuit (LS-OMP) merge it with the theory of Partial Knowing Support (PSK) given new method called Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP). The new methods depend on the greedy algorithm to compute the support which depends on the number of iterations. So to make it faster, the PKLS-OMP adds the idea of partial knowing support of its algorithm. It shows the efficiency, simplicity, and accuracy to get back the original signal if the sampling matrix satisfies the Restricted Isometry Property (RIP). Simulation results also show that it outperforms many algorithms especially for compressible signals.

Keywords: compressed sensing, lest support orthogonal matching pursuit, partial knowing support, restricted isometry property, signal reconstruction

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Authors: Mohamed Jama Madar, Oso Wilis

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E-learning is the application of information technology in the teaching and learning process. This paper presents the Funnel model as a solution for the problems of implementation of e-learning in tertiary education institutions. While existing models such as TAM, theory-based e-learning and pedagogical model have been used over time, they have generally been found to be inadequate because of their tendencies to treat materials development, instructional design, technology, delivery and governance as separate and isolated entities. Yet it is matching components that bring framework of e-learning strategic implementation. The Funnel model enhances all these into one and applies synchronously and asynchronously to e-learning implementation where the only difference is modalities. Such a model for e-learning implementation has been lacking. The proposed Funnel model avoids ad-ad-hoc approach which has made other systems unused or inefficient, and compromised educational quality. Therefore, the proposed Funnel model should help tertiary education institutions adopt and develop effective and efficient e-learning system which meets users’ requirements.

Keywords: e-learning, pedagogical, technology, strategy

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Authors: Anshika Kankane, Dongshik Kang

Abstract:

Marine debris has a significant influence on coastal environments, damaging biodiversity, and causing loss and damage to marine and ocean sector. A functional cost-effective and automatic approach has been used to look up at this problem. Computer vision combined with a deep learning-based model is being proposed to identify and categorize marine debris of seven kinds on different beach locations of Japan. This research compares state-of-the-art deep learning models with a suggested model architecture that is utilized as a feature extractor for debris categorization. The model is being proposed to detect seven categories of litter using a manually constructed debris dataset, with the help of Mask R-CNN for instance segmentation and a shape matching network called HOGShape, which can then be cleaned on time by clean-up organizations using warning notifications of the system. The manually constructed dataset for this system is created by annotating the images taken by fixed KaKaXi camera using CVAT annotation tool with seven kinds of category labels. A pre-trained HOG feature extractor on LIBSVM is being used along with multiple templates matching on HOG maps of images and HOG maps of templates to improve the predicted masked images obtained via Mask R-CNN training. This system intends to timely alert the cleanup organizations with the warning notifications using live recorded beach debris data. The suggested network results in the improvement of misclassified debris masks of debris objects with different illuminations, shapes, viewpoints and litter with occlusions which have vague visibility.

Keywords: computer vision, debris, deep learning, fixed live camera images, histogram of gradients feature extractor, instance segmentation, manually annotated dataset, multiple template matching

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Authors: Ismail Aslantas

Abstract:

Value-Added Models (VAMs), the statistical methods for evaluating the effectiveness of teachers and schools based on student achievement growth, has attracted decision-makers’ and researchers’ attention over the last decades. As a result of this attention, many studies have conducted in recent years to discuss these statistical models from different aspects. This research focused on the importance of conceptual variables in VAM estimations; therefor, this research was undertaken to examine the extent to which value-added effectiveness estimates for teachers can be affected by using context predictions. Using longitudinal data over three years from the international school context, value-added teacher effectiveness was estimated by ordinary least-square value-added models, and the effectiveness of the teachers was examined. The longitudinal dataset in this study consisted of three major sources: students’ attainment scores up to three years and their characteristics, teacher background information, and school characteristics. A total of 1,027 teachers and their 35,355 students who were in eighth grade were examined for understanding the impact of model specifications on the value-added teacher effectiveness evaluation. Models were created using selection methods that adding a predictor on each step, then removing it and adding another one on a subsequent step and evaluating changes in model fit was checked by reviewing changes in R² values. Cohen’s effect size statistics were also employed in order to find out the degree of the relationship between teacher characteristics and their effectiveness. Overall, the results indicated that prior attainment score is the most powerful predictor of the current attainment score. 47.1 percent of the variation in grade 8 math score can be explained by the prior attainment score in grade 7. The research findings raise issues to be considered in VAM implementations for teacher evaluations and make suggestions to researchers and practitioners.

Keywords: model specification, teacher effectiveness, teacher performance evaluation, value-added model

Procedia PDF Downloads 133

Authors: Chia-Yen Lee, Hao-Jen Wang, Jhih-Hao Lai

Abstract:

In recent years, infrared (IR) imaging has been considered as a potential tool to assess the efficacy of chemotherapy and early detection of breast cancer. Regions of tumor growth with high metabolic rate and angiogenesis phenomenon lead to the high temperatures. Observation of differences between the heat maps in long term is useful to help assess the growth of breast cancer cells and detect breast cancer earlier, wherein the multi-time infrared image alignment technology is a necessary step. Representative feature points detection and matching are essential steps toward the good performance of image registration and quantitative analysis. However, there is no clear boundary on the infrared images and the subject's posture are different for each shot. It cannot adhesive markers on a body surface for a very long period, and it is hard to find anatomic fiducial markers on a body surface. In other words, it’s difficult to detect and match features in an IR sequence images. In this study, automated feature detection and matching algorithms with two type of automatic feature points (i.e., vascular branch points and modified Harris corner) are developed respectively. The preliminary results show that the proposed method could identify the representative feature points on the IR breast images successfully of 98% accuracy and the matching results of 93% accuracy.

Keywords: Harris corner, infrared image, feature detection, registration, matching

Procedia PDF Downloads 304

Authors: Moor Avigail

Abstract:

This research examines gender norms that underlie the propensity to commit sexual assault and to carry it out. Factors that have been shown to relate to such propensity will be enumerated and tied to their ramifications. These include sexual objectification of women, endorsement of gender-based rape myths blaming the victim, masculine entitlement, low empathy to victims, along with elevated empathy towards rapists. Heavy use of pornography as well as a misconstruing of the meaning of refusal to sex, have also been implicated. Additionally, a cutting-edge investigation, which we have just completed, examined what seems to occur in the perpetrator's mind during the assault. No research to date has ventured to uncover what essentially allows the rape to be carried out in real time, in the sense of what mental mechanisms go into operation in rapists during the assault itself. Our findings demonstrate that dehumanization and rationalization are pivotal. On the one hand, the perpetrator apparently allows himself to disregard the victim's humanity while simultaneously justifying his actions in relation to the victim's behavior.

Keywords: gender norms, gender psychology, sexual assault, gender

Procedia PDF Downloads 72

Authors: J. Andrade-Garda, A. Anguera, J. Ares-Casal, M. Hidalgo-Lorenzo, J.-A. Lara, D. Lizcano, S. Suárez-Garaboa

Abstract:

In the current constantly changing economic context, collaborative networks allow partners to undertake projects that would not be possible if attempted by them individually. These projects usually involve the performance of a group of tasks (named roles) that have to be distributed among the partners. Thus, an allocation/matching problem arises that will be referred to as Role-Partner Allocation problem. In real life this situation is addressed by negotiation between partners in order to reach ad hoc agreements. Besides taking a long time and being hard work, both historical evidence and economic analysis show that such approach is not recommended. Instead, the allocation process should be automated by means of a centralized matching scheme. However, as a preliminary step to start the search for such a matching mechanism (or even the development of a new one), the problem and its core components must be specified. To this end, this paper establishes (i) the definition of the problem and its constraints, (ii) the key features of the involved elements (i.e., roles and partners); and (iii) how to create preference lists both for roles and partners. Only this way it will be possible to conduct subsequent methodological research on the solution method.     

Keywords: collaborative network, matching, partner, preference list, role

Procedia PDF Downloads 234