Search results for: dataset quality

Authors: Hailemikael Negussie, Sebla Arın Ensarioğlu

Abstract:

In February 2023 Southeastern Türkiye and Northwestern Syria were hit by two consecutive earthquakes with high magnitude leaving thousands dead and thousands more homeless. The housing crisis in the affected areas has resulted in the need for a fast and qualified solution. There are a number of solutions, one of which is the use of modular designs to rebuild the cities that have been affected. Modular designs are prefabricated building components that can be quickly and efficiently assembled on-site, making them ideal to build structures with faster speed and higher quality. These structures are flexible, adaptable, and can be customized to meet the specific needs of the inhabitants, in addition to being more energy-efficient and sustainable. The prefabricated nature also assures that the quality of the products can be easily controlled. The reason for the collapse of most of the buildings during the earthquakes was found out to be the lack of quality during the construction stage. Using modular designs allows a higher control over the quality of the construction materials being used. The use of modular designs for a project of this scale presents some challenges, including the high upfront cost to design and manufacture components. However, if implemented correctly, modular designs can offer an effective and efficient solution to the urgent housing needs. The aim of this paper is to explore the potential of modular housing for mid- and long-term earthquake-resistant housing needs in the affected disaster zones after the earthquakes of February 2023. In the scope of this paper the adaptability of modular, prefabricated housing designs for the post-disaster environment, the advantages and disadvantages of this system will be examined. Elements such as; the current conditions of the region where the destruction happened, climatic data, topographic factors will be examined. Additionally, the paper will examine; examples of similar local and international modular post-earthquake housing projects. The region is projected to enter a rapid reconstruction phase in the following periods. Therefore, this paper will present a proposal for a system that can be used to produce safe and healthy urbanization policies without causing new aggrievements while meeting the housing needs of the people in the affected regions.

Keywords: post-disaster housing, earthquake-resistant design, modular design, housing, Türkiye

Procedia PDF Downloads 84

Authors: Mustahsan Mir, Ahmed Hassanin, Mohammed A. Al-Saleh

Abstract:

The layout optimization of building blocks of unequal areas has applications in many disciplines including VLSI floorplanning, macrocell placement, unequal-area facilities layout optimization, and plant or machine layout design. A number of heuristics and some analytical and hybrid techniques have been published to solve this problem. This paper presents an efficient high-quality building-block layout design technique especially suited for solving large-size problems. The higher efficiency and improved quality of optimized solutions are made possible by introducing the concept of Promising Infant Clusters in a constructive placement procedure. The results presented in the paper demonstrate the improved performance of the presented technique for benchmark problems in comparison with published heuristic, analytic, and hybrid techniques.

Keywords: block layout problem, building-block layout design, CAD, optimization, search techniques

Procedia PDF Downloads 381

Authors: Arya Prakash Padhi, Anupam Chakrabarti, Rajib Chowdhury

Abstract:

Topology or layout optimization often gives better performing economic structures and is very helpful in the conceptual design phase. But traditionally it is being done in finite element-based optimization schemes which, although gives a good result, is very time-consuming especially in 3D structures. Among other alternatives machine learning, especially deep learning-based methods, have a very good potential in resolving this computational issue. Here convolutional neural network (3D-CNN) based variational auto encoder (VAE) is trained using a dataset generated from commercially available topology optimization code ABAQUS Tosca using solid isotropic material with penalization (SIMP) method for compliance minimization. The encoded data in latent space is then fed to a 3D generative adversarial network (3D-GAN) to generate the outcome in 64x64x64 size. Here the network consists of 3D volumetric CNN with rectified linear unit (ReLU) activation in between and sigmoid activation in the end. The proposed network is seen to provide almost optimal results with significantly reduced computational time, as there is no iteration involved.

Keywords: 3D generative adversarial network, deep learning, structural topology optimization, variational auto encoder

Procedia PDF Downloads 168

Authors: Radhika Jain, Sangeeta Goomer

Abstract:

In the present study an attempt has been made to re-engineer traditional wadi into wholesome ready-to-use cereal-pulse-based chunks rich in protein quality and fibre content. Chunks were made using extrusion-dehydration combination. Two formulations i.e., whole green gram dhal with instant oats and washed green gram dhal with whole oats were formulated. These chunks are versatile in nature as they can be easily incorporated in day-to-day home-made preparations such as pulao, potato curry and kadhi. Cereal-pulse ratio was calculated using NDpCal%. Limiting amino acids such as lysine, tryptophan, methionine, cysteine and threonine were calculated for maximum amino acid profile in cereal-pulse combination. Time-temperature combination for extrusion at 130^oC and dehydration at 65^oC for 7 hours and 15 minutes were standardized to obtain maximum protein and fibre content. Proximate analysis such as moisture, fat and ash content were analyzed. Protein content of formulation was 62.10% and 68.50% respectively. Fibre content of formulations was 2.99% and 2.45%, respectively. Using a 5-point hedonic scale, consumer preference trials of 102 consumers were conducted and analyzed. Evaluation of chunks prepared in potato curry, kadi and pulao showed preferences for colour 82%, 87%, 86%, texture and consistency 80%, 81%, 88%, flavour and aroma 74%, 82%, 86%, after taste 70%, 75%, 86% and overall acceptability 77%, 75%, 88% respectively. High temperature inactivates antinutritional compounds such as trypsin inhibitors, lectins, saponins etc. Hence, availability of protein content was increased. Developed products were palatable and easy to prepare.

Keywords: extrusion, NDpCal%, protein quality, wadi

Procedia PDF Downloads 222

Authors: Supattra Kanchanopast

Abstract:

The purpose of this research was to identify factors that influenced the trust of e-commerce within retail businesses. In order to achieve the objectives of this research, the researcher collected data from random e-commerce users in Bangkok. The data was comprised of the results of 382 questionnaires. The data was analyzed by using descriptive statistics, which included frequency, percentages, and the standard deviation of pertinent factors. Multiple regression analysis was also used. The findings of this research revealed that the majority of the respondents were female, 25-40 years old, and graduated a bachelor degree. The respondents mostly worked in private sectors and had monthly income between 15,000-25,000 baht. The findings also indicate that information quality factors, website design factors, service quality factor, security factor and advertising factors as significant factors effecting customer trust of e-commerce in online retail. The hypotheses testing revealed that these factors in e-commerce had an effect on customer’s trust in the same direction with high level.

Keywords: e-commerce, online retail, Retail business, trust, website

Procedia PDF Downloads 189

Authors: A. Llopis Alvarez, D. Muller-Eie

Abstract:

Participatory GIS (geographic information systems) are designed for community mapping exercises in order to produce spatial representations of local knowledge. Ideally, participatory GIS caters to public participation through the use of spatial data in order to increase community-led policy-and decision-making. Having defined a spatial object, such as a neighborhood, subjective mapping involves attaining a description of the spatial, physical, social and psychological characteristics of that spatial object. This paper highlights an emerging appreciation of the subjective component, particularly in spatial analyses. The beliefs, feelings, and behaviors associated with an urban area reflect its sense of place for an individual or a group. It is important therefore to understand what types of beliefs, emotions, and behavioral patterns are relevant to particular resident, groups and urban scales. In this sense, resident’s emotional attachment to their urban areas motivates civic engagement and facilitates awareness of its strengths and its problems. Similarly, subjective perceptions act in complex ways to influence the formation and maintenance of social identity and quality of life. This paper reports on findings from a case study of immigrant population in Norwegian cities, their residential conditions and their relationship to quality of urban life. Cognitive mapping methodologies are used in this study to understand local perceptions of urban qualities. Thus, measures to alleviate disadvantages and improve quality of urban life are more likely to be effective when they are informed by an understanding of a place as constructed by those who live in it, meaning their subjective perceptions about it.

Keywords: mapping methodologies, participatory GIS, perceptual maps, public participation, spatial analysis, subjective perceptions

Procedia PDF Downloads 139

Authors: Anung Style Bukhori, Ani Dijah Rahajoe

Abstract:

Poverty poses a significant challenge in Indonesia, requiring an effective analytical approach to understand and address this issue. In this research, we applied the Naïve Bayes classification method to examine and classify poverty data in Indonesia. The main focus is on classifying data using RapidMiner, a powerful data analysis platform. The analysis process involves data splitting to train and test the classification model. First, we collected and prepared a poverty dataset that includes various factors such as education, employment, and health..The experimental results indicate that the Naïve Bayes classification model can provide accurate predictions regarding the risk of poverty. The use of RapidMiner in the analysis process offers flexibility and efficiency in evaluating the model's performance. The classification produces several values to serve as the standard for classifying poverty data in Indonesia using Naive Bayes. The accuracy result obtained is 40.26%, with a moderate recall result of 35.94%, a high recall result of 63.16%, and a low recall result of 38.03%. The precision for the moderate class is 58.97%, for the high class is 17.39%, and for the low class is 58.70%. These results can be seen from the graph below.

Keywords: poverty, classification, naïve bayes, Indonesia

Procedia PDF Downloads 49

Authors: Diafat Abdelouahab, Ekhalfi A Hammoudia, Meribai Abdelmalek A, Bahloul Ahmedb

Abstract:

The present study aimed to characterize 30 honey samples from the Bordj Bou Arreridj region (Algeria) regarding their floral origins, physicochemical parameters, mineral composition and microbial safety. Mean values obtained for physicochemical parameters were: pH 4.11, 17.17% moisture, 0.0061% ash, 370.57μS cm−1 electrical conductivity, 21.98 meq/kg free acidity, and 9.703 mg/kg HMF. The mineral content was determined by atomic absorption spectrometry. The mean values obtained were (mg/kg): Fe, 7.5714; Mg, 37.68; Na, 186,63; Zn, 3,86; Pb, 0,4869 × 10-3 ; Cd, 267 × 10-3. Aerobic mesophiles, fecal coliforms and sulphite-reducing clostridia were the microbial contaminants of interest studied. Microbiologically, the honey quality was considered good and all samples showed to be negative in respect to safety parameters. The results obtained for physicochemical characteristics of Bordj Bou Arreridj honey indicate a good quality level, adequate processing, good maturity and freshness.

Keywords: pollen analysis, physicochemical analysis, mineral content, microbial contaminants

Procedia PDF Downloads 82

Authors: Uchegbu Nneka Nkechi, Okoye Ogochukwu Peace

Abstract:

The evaluation of the visco-elastic properties and microbial quality of a formulated oat-based dietetic food were investigated. Oat flour, pumpkin seed flour, carrot flour and skimmed milk powder were blended in varying proportions to formulate a product with codes OCF, which contains 70% oat flour, 10 % carrot flour, 10 % pumpkin seed flour and 10% skimmed milk powder, OCF which contains 65 % oat flour, 10 % carrot flour, 10 % pumpkin seed flour and 15 % skimmed milk powder, OCF which contains 60 % oat flour, 10 % carrot flour, 10 % pumpkin seed flour and 20 % skimmed milk powder, OCF which contains 55 % oat flour, 10 % carrot flour, 10 % pumpkin seed flour and 25 % skimmed milk powder and OF with 95 % oat as the commercial control. All the samples were assessed for their proximate composition, microbial quality and visco-elastic properties. The moisture content was highest at sample OF (10.73%) and lowest at OCF (7.10%) (P<0.05). Crude protein ranged from 13.38%-22.86%, with OCF having the highest (P<0.05) protein content and OF having the lowest. Crude fat was 3.74% for OCF and 6.31% for OF. Crude fiber ranged from 3.58% - 17.39% with OF having the lowest (P<0.05) fiber content and OCF having the highest. Ash content was 1.30% for OCF and 2.75% for OCF. There was no mold growth in the samples. The total viable ml/wl count ranged from 1.5×10³ cfu/g - 2.6×10³ cfu/g, with OCF having the lowest and OF having the highest (P<0.05) total viable count. The peak viscosity of the sample ranged from 75.00 cP-2895.00 cP, with OCF having the lowest and OF having the highest value. The final viscosity was 130.50 cP in OCF and 3572.50 cP in OF. The setback viscosity was 58.00 cP in OCF and 1680.50 cP in OF. The peak time was 6.93 mins in OCF to 5.57 mins in OF. There was no pasting temperature for all samples except the OF, which had 86.43. Sample OF was the highest in terms of overall acceptability. This study showed that the oat-based composite flour produced had a nutritional profile that would be acceptable for the aged population.

Keywords: dietetic, pumpkin, visco-elastic, microbial

Procedia PDF Downloads 194

Authors: Jonathan H. Westover, Ruthann Cunningham, Jaron Harvey

Abstract:

Purpose: Job satisfaction is one of the most critical attitudes among employees. Understanding whether employees are satisfied with their jobs and what is driving that satisfaction is important for any employer, but particularly for healthcare organizations. This study looks at the question of job satisfaction and drivers of job satisfaction among healthcare professionals at a global scale, looking for trends that generalize across 37 countries. Study: This study analyzed job satisfaction responses to the 2015 Work Orientations IV wave of the International Social Survey Programme (ISSP) to understand differences in antecedents for and levels of job satisfaction among healthcare professionals. A total of 18,716 respondents from 37 countries participated in the annual survey. Findings: Respondents self-identified their occupational category based on corresponding International Standard Classification of Occupations (ISCO-08) codes. Results suggest that mean overall job satisfaction was highest among health service managers and generalist medical practitioners and lowest among environmental hygiene professionals and nursing professionals. Originality: Many studies have addressed the issue of job satisfaction in healthcare, examining small samples of specific healthcare workers. In this study, using a large international dataset, we are able to examine questions of job satisfaction across large groups of healthcare workers in different occupations within the healthcare field.

Keywords: job satisfaction, healthcare industry, global comparisons, workplace

Procedia PDF Downloads 140

Authors: Mohd Ayyub Khan, Nadeem Akhtar

Abstract:

Due to recent advances in wireless communication technologies and hand-held devices, there is a huge demand for video-based applications such as video surveillance, video conferencing, remote surgery, Digital Video Broadcast (DVB), IPTV, online learning courses, YouTube, WhatsApp, Instagram, Facebook, Interactive Video Games. However, the raw videos posses very high bandwidth which makes the compression a must before its transmission over the wireless channels. The High Efficiency Video Codec (HEVC) (also called H.265) is latest state-of-the-art video coding standard developed by the Joint effort of ITU-T and ISO/IEC teams. HEVC is targeted for high resolution videos such as 4K or 8K resolutions that can fulfil the recent demands for video services. The compression ratio achieved by the HEVC is twice as compared to its predecessor H.264/AVC for same quality level. The compression efficiency is generally increased by removing more correlation between the frames/pixels using complex techniques such as extensive intra and inter prediction techniques. As more correlation is removed, the chances of interdependency among coded bits increases. Thus, bit errors may have large effect on the reconstructed video. Sometimes even single bit error can lead to catastrophic failure of the reconstructed video. In this paper, we study the performance of HEVC bitstream over additive white Gaussian noise (AWGN) channel. Moreover, HEVC over Quadrature Amplitude Modulation (QAM) combined with forward error correction (FEC) schemes are also explored over the noisy channel. The video will be encoded using HEVC, and the coded bitstream is channel coded to provide some redundancies. The channel coded bitstream is then modulated using QAM and transmitted over AWGN channel. At the receiver, the symbols are demodulated and channel decoded to obtain the video bitstream. The bitstream is then used to reconstruct the video using HEVC decoder. It is observed that as the signal to noise ratio of channel is decreased the quality of the reconstructed video decreases drastically. Using proper FEC codes, the quality of the video can be restored up to certain extent. Thus, the performance analysis of HEVC presented in this paper may assist in designing the optimized code rate of FEC such that the quality of the reconstructed video is maximized over wireless channels.

Keywords: AWGN, forward error correction, HEVC, video coding, QAM

Procedia PDF Downloads 144

Authors: A.M. Kaja, Q. Yu, H.J.H Brouwers

Abstract:

An increased functionality of concrete towards higher eco-efficiency is nowadays of great importance due to the decreasing air quality in urban areas. Surface modifications of concrete walls and roads, as a coating or an intermixing of the surface layer with TiO₂, provide an opportunity to improve the air quality by reducing NOx via photocatalytic phenomena. Nevertheless, there are still concerns regarding the cost-efficiency as well as the toxicity of intermediate products which can be produced during the photocatalysis, limiting a widespread adoption of these materials. This study addresses the problem of the selectivity of cement mortars towards nitrate in terms of microstructural characteristics and hydration products. The ability of cement mortars matrix intermixed with commercial TiO₂ and TiO₂-SiO₂ composite to abate NO₂ is investigated. The influence of hydration products formed under the carbonation facilitating conditions is discussed and solutions how to optimize the mix design are proposed. The incorporation of the TiO₂-SiO₂ composite into cement mortar is found to increase the nitrate selectivity index.

Keywords: cement matrix, NO₂ abatement, photocatalysis, TiO₂-SiO₂ composite

Procedia PDF Downloads 157

Authors: Gorkem Algan, Ilkay Ulusoy, Saban Gonul, Banu Turgut, Berker Bakbak

Abstract:

Computer vision systems recently made a big leap thanks to deep neural networks. However, these systems require correctly labeled large datasets in order to be trained properly, which is very difficult to obtain for medical applications. Two main reasons for label noise in medical applications are the high complexity of the data and conflicting opinions of experts. Moreover, medical imaging datasets are commonly tiny, which makes each data very important in learning. As a result, if not handled properly, label noise significantly degrades the performance. Therefore, a label-noise-robust learning algorithm that makes use of the meta-learning paradigm is proposed in this article. The proposed solution is tested on retinopathy of prematurity (ROP) dataset with a very high label noise of 68%. Results show that the proposed algorithm significantly improves the classification algorithm's performance in the presence of noisy labels.

Keywords: deep learning, label noise, robust learning, meta-learning, retinopathy of prematurity

Procedia PDF Downloads 154

Authors: C. Chhorn, S. H. Han, S. W. Lee

Abstract:

Roller-compacted concrete (RCC) has been used for decades in many pavement applications due to its economic cost and high construction speed. However, due to the lack of deep researches and experiences, this material has not been widely employed. An RCC mixture with appropriate consistency can induce high compacted density, while high density can induce good aggregate interlock and high strength. Consistency of RCC is mainly known to define its constructability. However, it was not well specified how this property may affect other properties of a constructed RCC pavement (RCCP). This study suggested the possibility of an ideal range of consistency that may provide adequate quality of RCCP. In this research, five sections of RCCP consisted of both 13 mm and 19 mm aggregate sections were investigated. The effects of consistency on compacted depth, strength, international roughness index (IRI), skid resistance are examined. From this study, a new range of consistency is suggested for RCCP application.

Keywords: compacted depth, consistency, international roughness index (IRI), pavement, roller-compacted concrete (RCC), skid resistance, strength

Procedia PDF Downloads 238

Authors: Muhammad Naeem Chaudhry, Fahim Nawaz, Rana Nauman Shabbir

Abstract:

New strategies aimed at increasing the resilience of crop plants to the negative effects of climate change represent important research priorities of plant scientists. The use of soil microorganisms to alleviate abiotic stresses like drought has gained particular importance in recent past. A field experiment was planned to investigate the effect of phosphorous solubilizing bacteria on yield and seed quality of Camelina (Camelina sativa L.) under water deficit conditions. The study was conducted at Agronomic Research Farm, University College of Agriculture and Environmental Sciences, The Islamia University Bahawalpur, during 4th week of November, 2013. The available seeds of Camelina sativa were inoculated with two bacterial strains (pseudomonas and Bacillus spp.) and grown under various water stress levels i.e. D0, (four irrigations), D3 (three irrigation), D2 (two irrigations), and D1 (one irrigation). The results revealed that drought stress significantly reduced the plant growth and yield, consequently reducing protein contents and oil concentration in camelina. The exposure to drought stress decreased plant height (16%), plant population (27%), number of fertile branches (41-59%), number of pods per plant (35%) and seed per pod (33%). Drought stress also exerted a negative impact on yield characteristics by reducing the 1000-seed weight (65%), final seed yield (52%), biological yield (22%) and harvest index (39%) of camelina. However, the inoculation of seeds with Pseudomonas and Bacillus spp. promoted the plant growth characterized by increased plant height and enhanced plant population. It was noted that inoculation of seeds with Pseudomonas resulted in the maximum plant population (113.4 cm), primary branches (19 plant-1), and number of pods (664 plant-1), whereas Bacillus inoculation resulted in maximum plant height (113.4 cm), seeds per pod (15.9), 1000-seed weight (1.85 g), and seed yield (3378.8 kg ha-1). Moreover, the inoculation with Bacillus also significantly improved the quality attributes of camelina and gave 3.5% and 2.1% higher oil contents than Pseudomonas and control (no-inoculation), respectively. Similarly, the same strain also resulted in maximum protein contents (33.3%). Our results confirmed the hypothesis that inoculation of seeds with phosphorous solubilizing bacterial strains is an effective, viable and environment-friendly approach to improve yield and quality of camelina under water deficit conditions. However, further studies are suggested to investigate the physiological and molecular processes, stimulated by bacterial strains, for increasing drought tolerance in food crops.

Keywords: Camelina, drought stress, phosphate solubilizing bacteria, seed quality

Procedia PDF Downloads 257

Authors: J. BalaRaju, M. Govinda Raj, C. S. N. Murthy

Abstract:

Every organization in the competitive world tends to improve its economy by increasing their production and productivity rates. Unequivocally, the production in Indian underground mines over the years is not satisfactory, due to a variety of reasons. There are manifold of avenues for the betterment of production, and one such approach is through enhanced utilization of mechanized equipment such as Load Haul Dumper (LHD). This is used as loading and hauling purpose in underground mines. In view of the aforementioned facts, this paper delves into identification of the key influencing factors such as LHDs maintenance effectiveness, vehicle condition, operator skill and utilization of the machines on performance of LHDs. An attempt has been made for improvement of performance of the equipment through evaluation of Overall Equipment Effectiveness (OEE). Two different approaches for evaluation of OEE have been adopted and compared under various operating conditions. The use of OEE calculation in terms of percentage availability, performance and quality and the hitherto existing situation of the underground mine production is evaluated. Necessary recommendations are suggested to mining industry on the basis of OEE.

Keywords: utilization, maintenance, availability, performance and quality

Procedia PDF Downloads 217

Authors: Abdur Rosyid, Mohamed El-Madany, Mohanad Alata

Abstract:

Due to simplicity and low cost, rotordynamic system is often modeled by using lumped parameters. Recently, finite elements have been used to model rotordynamic system as it offers higher accuracy. However, it involves high degrees of freedom. In some applications such as control design, this requires higher cost. For this reason, various model reduction methods have been proposed. This work demonstrates the quality of model reduction of rotor-bearing-support system through substructuring. The quality of the model reduction is evaluated by comparing some first natural frequencies, modal damping ratio, critical speeds and response of both the full system and the reduced system. The simulation shows that the substructuring is proven adequate to reduce finite element rotor model in the frequency range of interest as long as the numbers and the locations of master nodes are determined appropriately. However, the reduction is less accurate in an unstable or nearly-unstable system.

Keywords: rotordynamic, finite element model, timoshenko beam, 3D solid elements, Guyan reduction method

Procedia PDF Downloads 269

Authors: Ananta Kumar Das, Sujit Kumar Chakrabarti

Abstract:

Architectural tactics such as heartbeat, ping-echo, encapsulate, encrypt data are techniques that are used to achieve quality attributes of a system. Detecting architectural tactics has several benefits: it can aid system comprehension (e.g., legacy systems) and in the estimation of quality attributes such as safety, security, maintainability, etc. Architectural tactics are typically spread over the source code and are implicit. For large codebases, manual detection is often not feasible. Therefore, there is a need for automated methods of detection of architectural tactics. This paper presents a formalization of the heartbeat architectural tactic and a program analytic approach to detect this tactic in source code. The experiment of the proposed method is done on a set of Java applications. The outcome of the experiment strongly suggests that the method compares well with a manual approach in terms of its sensitivity and specificity, and far supersedes a manual exercise in terms of its scalability.

Keywords: software architecture, architectural tactics, detecting architectural tactics, program analysis, AST, alias analysis

Procedia PDF Downloads 151

Authors: Chiung-Ju Huang, Yuan-Hong Ho

Abstract:

This study utilizes the International Monetary Fund (IMF) Fiscal Rules Dataset focusing on four specific fiscal rules such as expenditure rule, revenue rule, budget balance rule, and debt rule and five main characteristics of each fiscal rule those are monitoring, enforcement, coverage, legal basis, and escape clause to construct the Fiscal Rule Index for nine countries in the Asia-Pacific region from 1996 to 2015. After constructing the fiscal rule index for each country, we utilize the Panel Generalized Method of Moments (Panel GMM) by using the constructed fiscal rule index to examine the effectiveness of fiscal rules in reducing procyclicality. Empirical results show that national fiscal rules have a significantly negative impact on procyclicality of government expenditure. Additionally, stricter fiscal rules combined with high government effectiveness are effective in reducing procyclicality of government expenditure. Results of this study indicate that for nine Asia-Pacific countries, policymakers’ use of fiscal rules and government effectiveness to reducing procyclicality of fiscal policy are effective.

Keywords: counter-cyclical policy, fiscal rules, government efficiency, procyclical policy

Procedia PDF Downloads 268

Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

Abstract:

The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

Procedia PDF Downloads 176

Authors: Lakmali Anthony, Madeline Gillies

Abstract:

Background Breast cancer (BC) is usually managed with surgical resection. Many outcomes traditionally used to define successful operative management, such as resection margin, do not adequately reflect patients’ experience. Patient-reported outcomes (PRO) such as Health-Related Quality of life (HRQoL) provide a means by which the impact of surgery for cancer can be reported in a patient-centered way. This exploratory cross-sectional study aims to; (1) describe postoperative HRQoL in patients who underwent primary resection in a regional Australian hospital; (2) describe the prevalence of anxiety, depression and clinically significant fear of cancer recurrence (FCR) in this population; and (3) identify demographic, psychosocial, disease and treatment factors associated with poorer self-reported HRQoL. Methods Patients who had resection of BC in a regional Australian hospital between 2015 and 2022 were eligible. Participants were asked to complete a survey designed to assess HRQoL, as well as validated instruments that assess several other psychosocial PROs hypothesized to be associated with HRQoL; emotional distress, fear of cancer recurrence, social support, dispositional optimism, body image and spirituality. Results Forty-six patients completed the survey. Clinically significant levels of FCR and emotional distress were present in this group. Many domains of HRQoL were significantly worse than an Australian reference population for BC. Demographic and disease factors associated with poor HRQoL included smoking and ongoing adjuvant systemic therapy. The primary operation was not associated with HRQoL for breast cancer. All psychosocial factors measured were associated with HRQoL. Conclusion HRQoL is an important outcome in surgery for both research and clinical practice. This study provides an overview of the quality of life in a regional Australian population of postoperative breast cancer patients and the factors that affect it. Understanding HRQoL and awareness of patients particularly vulnerable to poor outcomes should be used to aid the informed consent and shared decision-making process between surgeon and patient.

Keywords: breast cancer, surgery, quality of life, regional population

Procedia PDF Downloads 63

Authors: Hyunbin Choi, Jihyeon Noh, Changwon Lim

Abstract:

In this paper, we propose SiamMask++, an architecture that performs layer-wise aggregation and depth-wise cross-correlation and introduce multi-RPN module and multi-MASK module to improve EAO (Expected Average Overlap), a representative performance evaluation metric for Visual Object Tracking (VOT) challenge. The proposed architecture, SiamMask++, has two versions, namely, bi_SiamMask++, which satisfies the real time (56fps) on systems equipped with GPUs (Titan XP), and rf_SiamMask++, which combines mask refinement modules for EAO improvements. Tests are performed on VOT2016, VOT2018 and VOT2019, the representative datasets of Visual Object Tracking tasks labeled as rotated bounding boxes. SiamMask++ perform better than SiamMask on all the three datasets tested. SiamMask++ is achieved performance of 62.6% accuracy, 26.2% robustness and 39.8% EAO, especially on the VOT2018 dataset. Compared to SiamMask, this is an improvement of 4.18%, 37.17%, 23.99%, respectively. In addition, we do an experimental in-depth analysis of how much the introduction of features and multi modules extracted from the backbone affects the performance of our model in the VOT task.

Keywords: visual object tracking, video, deep learning, layer wise aggregation, Siamese network

Procedia PDF Downloads 148

Authors: Pranvera Shehaj

Abstract:

Unlike any prior analysis on the withholding tax rates negotiated in tax treaties, this study looks at the treaty heterogeneity content, by investigating the impact of the residence country’s double tax relief method and of tax-sparing agreements, on the difference between developing countries’ domestic withholding taxes on dividends on one side, and treaty negotiated withholding taxes at source on portfolio dividends on the other side. Using a dyadic panel dataset of asymmetric double tax treaties between 2005 and 2019, this study suggests first that the difference between domestic and negotiated WHTs on portfolio dividends is higher when the OECD member uses the credit method, as compared to when it uses the exemption method. Second, results suggest that the inclusion of tax-sparing provisions vanishes the positive effect of the credit method at home on the difference between domestic and negotiated WHTs on portfolio dividends, incentivizing developing countries to negotiate higher withholding taxes.

Keywords: double tax treaties, asymmetric investments, withholding tax, dividends, double tax relief method, tax sparing

Procedia PDF Downloads 60

Authors: Pedro Esteban

Abstract:

Most installations nowadays are exposed to many power quality problems, and they also face numerous challenges to comply with grid code and energy efficiency requirements. The reason behind this is that they are not designed to support nonlinear, non-balanced, and variable loads and generators that make up a large percentage of modern electric power systems. These problems and challenges become especially critical when designing green buildings and smart cities. These problems and challenges are caused by equipment that can be typically found in these installations like variable speed drives (VSD), transformers, lighting, battery chargers, double-conversion UPS (uninterruptible power supply) systems, highly dynamic loads, single-phase loads, fossil fuel generators and renewable generation sources, to name a few. Moreover, events like capacitor switching (from existing capacitor banks or passive harmonic filters), auto-reclose operations of transmission and distribution lines, or the starting of large motors also contribute to these problems and challenges. Active power filters (APF) are one of the fastest-growing power electronics technologies for solving power quality problems and meeting grid code and energy efficiency requirements for a wide range of segments and applications. They are a high performance, flexible, compact, modular, and cost-effective type of power electronics solutions that provide an instantaneous and effective response in low or high voltage electric power systems. They enable longer equipment lifetime, higher process reliability, improved power system capacity and stability, and reduced energy losses, complying with most demanding power quality and energy efficiency standards and grid codes. There can be found several types of active power filters, including active harmonic filters (AHF), static var generators (SVG), active load balancers (ALB), hybrid var compensators (HVC), and low harmonic drives (LHD) nowadays. All these devices can be used in applications in Smart Cities bringing several technical and economic benefits.

Keywords: power quality improvement, energy efficiency, grid code compliance, green buildings, smart cities

Procedia PDF Downloads 109

Authors: Hongyu Chen, Li Jiang

Abstract:

Ubiquitous anomalies endanger the security of our system con- stantly. They may bring irreversible damages to the system and cause leakage of privacy. Thus, it is of vital importance to promptly detect these anomalies. Traditional supervised methods such as Decision Trees and Support Vector Machine (SVM) are used to classify normality and abnormality. However, in some case, the abnormal status are largely rarer than normal status, which leads to decision bias of these methods. Generative adversarial network (GAN) has been proposed to handle the case. With its strong generative ability, it only needs to learn the distribution of normal status, and identify the abnormal status through the gap between it and the learned distribution. Nevertheless, existing GAN-based models are not suitable to process data with discrete values, leading to immense degradation of detection performance. To cope with the discrete features, in this paper, we propose an efficient GAN-based model with specifically-designed loss function. Experiment results show that our model outperforms state-of-the-art models on discrete dataset and remarkably reduce the overhead.

Keywords: GAN, discrete feature, Wasserstein distance, multiple intermediate layers

Procedia PDF Downloads 124

Authors: Kaycee Bills

Abstract:

This study will determine if students with disabilities have higher student loan debt payments than other student populations. The hypothesis was that students with disabilities would have significantly higher student loan debt payments than other students due to the length of time they spend in school. Using the Bachelorette and Beyond Study Wave 2015/017 dataset, quantitative methods were employed. These data analysis methods included linear regression and a correlation matrix. Due to the exploratory nature of the study, the significance levels for the overall model and each variable were set at .05. The correlation matrix demonstrated that students with certain types of disabilities are more likely to fall under higher student loan payment brackets than students without disabilities. These results also varied among the different types of disabilities. The result of the overall linear regression model was statistically significant (p = .04). Despite the overall model being statistically significant, the majority of the significance values for the different types of disabilities were null. However, several other variables had statistically significant results, such as veterans, people of minority races, and people who attended private schools. Implications for how this impacts the economy, capitalism, and financial wellbeing of various students are discussed.

Keywords: disability, student loan debt, higher education, social work

Procedia PDF Downloads 163

Authors: Lundqvist M., Alwin J., Levin L-A.

Abstract:

Background: Assistance dogs are dogs trained to assist persons with functional impairment or chronic diseases. The assistance dog concept includes different types: guide dogs, hearing dogs, and service dogs. The service dog can further be divided into subgroups of physical services dogs, diabetes alert dogs, and seizure alert dogs. To examine the long-term effects of health care interventions, both in terms of resource use and health outcomes, cost-effectiveness analyses can be conducted. This analysis can provide important input to decision-makers when setting priorities. Little is known when it comes to the cost-effectiveness of assistance dogs. The study aimed to assess the cost-effectiveness of certified service or hearing dogs in comparison to regular companion dogs. Methods: The main data source for the analysis was the “service and hearing dog project”. It was a longitudinal interventional study with a pre-post design that incorporated fifty-five owners and their dogs. Data on all relevant costs affected by the use of a service dog such as; municipal services, health care costs, costs of sick leave, and costs of informal care were collected. Health-related quality of life was measured with the standardized instrument EQ-5D-3L. A decision-analytic Markov model was constructed to conduct the cost-effectiveness analysis. Outcomes were estimated over a 10-year time horizon. The incremental cost-effectiveness ratio expressed as cost per gained quality-adjusted life year was the primary outcome. The analysis employed a societal perspective. Results: The result of the cost-effectiveness analysis showed that compared to a regular companion dog, a certified dog is cost-effective with both lower total costs [-32,000 USD] and more quality-adjusted life-years [0.17]. Also, we will present subgroup results analyzing the cost-effectiveness of physicals service dogs and diabetes alert dogs. Conclusions: The study shows that a certified dog is cost-effective in comparison with a regular companion dog for individuals with functional impairments or chronic diseases. Analyses of uncertainty imply that further studies are needed.

Keywords: service dogs, hearing dogs, health economics, Markov model, quality-adjusted, life years

Procedia PDF Downloads 145

Authors: Xavier Bertrand, Alexandre Cayrel

Abstract:

The early phase of an aircraft development is instrumental as it really drives the potential of a new concept. Any weakness in the high-level design (wing planform, moveable surfaces layout etc.) will be extremely difficult and expensive to recover later in the aircraft development process. Aerodynamic evaluation in this very early development phase is driven by two main criteria: a short lead-time to allow quick iterations of the geometrical design, and a high quality of the calculations to get an accurate & reliable assessment of the current status. These two criteria are usually quite contradictory. Actually, short lead time of a couple of hours from end-to-end can be obtained with very simple tools (semi-empirical methods for instance) although their accuracy is limited, whereas higher quality calculations require heavier/more complex tools, which obviously need more complex inputs as well, and a significantly longer lead time. At this point, the choice has to be done between accuracy and lead-time. A brand new approach has been developed within Airbus, aiming at obtaining quickly high quality evaluations of the aerodynamic of an aircraft. This methodology is based on a joint use of Surrogate Modelling and a lifting line code. The Surrogate Modelling is used to get the wing sections characteristics (e.g. lift coefficient vs. angle of attack), whatever the airfoil geometry, the status of the moveable surfaces (aileron/spoilers) or the high-lift devices deployment. From these characteristics, the lifting line code is used to get the 3D effects on the wing whatever the flow conditions (low/high Mach numbers etc.). This methodology has been applied successfully to a concept of medium range aircraft.

Keywords: aerodynamics, lifting line, surrogate model, CFD

Procedia PDF Downloads 352

Authors: Naser Valipour Motlagh, Majid Aliabadi, Elnaz Rahmani, Samira Ghorbanpour

Abstract:

Strawberry is one of the most favored fruits all along the world. But due to its vulnerability to microbial contamination and short life storage, there are lots of problems in industrial production and transportation of this fruit. Therefore, lots of ideas have tried to increase the storage life of strawberries especially through proper packaging. This paper works on efficient packaging as well. The primary material used is produced through simple mixing of low-density polyethylene (LDPE) and silver nanoparticles in different weight fractions of 0.5 and 1% in presence of dicumyl peroxide as a cross-linking agent. Final packages were made in a twin-screw extruder. Then, their effect on the quality maintenance of strawberry is evaluated. The SEM images of nano-silver packages show the distribution of silver nanoparticles in the packages. Total bacteria count, mold, yeast and E. coli are measured for microbial evaluation of all samples. Texture, color, appearance, odor, taste and total acceptance of various samples are evaluated by trained panelists and based on 9-point hedonic scale method. The results show a decrease in total bacteria count and mold in nano-silver packages compared to the samples packed in polyethylene packages for the same storage time. The optimum concentration of silver nanoparticles for the lowest bacteria count and mold is predicted to be around 0.5% which has attained the most acceptance from the panelist as well. Moreover, organoleptic properties of strawberry are preserved for a longer period in nano-silver packages. It can be concluded that using nano-silver particles in strawberry packages has improved the storage life and quality maintenance of the fruit.

Keywords: antimicrobial properties, polyethylene, silver nanoparticles, strawberry

Procedia PDF Downloads 151

Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

Abstract:

The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

Procedia PDF Downloads 234