Search results for: measurement accuracy

Authors: Syazreen N. Shair, Saiful A. Ishak, Aida Y. Yusof, Azizah Murad

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In this paper, we forecast age-specific Malaysian mortality rates and life expectancy at births by gender and ethnic groups including Malay, Chinese and Indian. Two mortality forecasting models are adopted the original Lee-Carter model and its recent modified version, the product ratio coherent model. While the first forecasts the mortality rates for each subpopulation independently, the latter accounts for the relationship between sub-populations. The evaluation of both models is performed using the out-of-sample forecast errors which are mean absolute percentage errors (MAPE) for mortality rates and mean forecast errors (MFE) for life expectancy at births. The best model is then used to perform the long-term forecasts up to the year 2030, the year when Malaysia is expected to become an aged nation. Results suggest that in terms of overall accuracy, the product ratio model performs better than the original Lee-Carter model. The association of lower mortality group (Chinese) in the subpopulation model can improve the forecasts of high mortality groups (Malay and Indian).

Keywords: coherent forecasts, life expectancy at births, Lee-Carter model, product-ratio model, mortality rates

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Authors: Solomon Tilahun Desisa, Muktar Seid Hussen

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Hibiscus macranthus is one of family Malvaceae and genus Hibiscus plant which grows mainly in western part of Ethiopia. Hibiscus macranthus is the most adaptable and abundant plant in the nation, which are used as an ornamental plant often a hedge or fence plant, and used as a firewood after harvesting the stem together with the bark, and used also as a fiber for trying different kinds of things by forming the rope. However, Hibiscus macranthus plant fibre has not been commercially exploited and extracted properly. This study of work describes the possibility of mechanical and retting methods of Hibiscus macranthus fibre extraction and characterization. Hibiscus macranthus fibre is a bast fibre which obtained naturally from the stem or stalks of the dicotyledonous plant since it is a natural cellulose plant fiber. And the fibre characterized by studying its physical and chemical properties. The physical characteristics were investigated as follows, including the length of 100-190mm, fineness of 1.0-1.2Tex, diameter under X100 microscopic view 16-21 microns, the moisture content of 12.46% and dry tenacity of 48-57cN/Tex along with breaking extension of 0.9-1.6%. Hibiscus macranthus fiber productivity was observed that 12-18% of the stem out of which more than 65% is primary long fibers. The fiber separation methods prove to decrease of non-cellulose ingredients in the order of mechanical, water and chemical methods. The color measurement also shows the raw Hibiscus macranthus fiber has a natural golden color according to YID1925 and paler look under both retting methods than mechanical separation. Finally, it is suggested that Hibiscus macranthus fibre can be used for manufacturing of natural and organic crop and coffee packages as well as super absorbent, fine and high tenacity textile products.

Keywords: Hibiscus macranthus, bast fiber, extraction, characterization

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Authors: Diana López-Soto, Soumaya Yacout, Francisco Ángel-Bello

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Although inventories are considered as stocks of money sitting on shelve, they are needed in order to secure a constant and continuous production. Therefore, companies need to have control over the amount of inventory in order to find the balance between excessive and shortage of inventory. The classification of items according to certain criteria such as the price, the usage rate and the lead time before arrival allows any company to concentrate its investment in inventory according to certain ranking or priority of items. This makes the decision making process for inventory management easier and more justifiable. The purpose of this paper is to present a new approach for the classification of new items based on the already existing criteria. This approach is called the Logical Analysis of Data (LAD). It is used in this paper to assist the process of ABC items classification based on multiple criteria. LAD is a data mining technique based on Boolean theory that is used for pattern recognition. This technique has been tested in medicine, industry, credit risk analysis, and engineering with remarkable results. An application on ABC inventory classification is presented for the first time, and the results are compared with those obtained when using the well-known AHP technique and the ANN technique. The results show that LAD presented very good classification accuracy.

Keywords: ABC multi-criteria inventory classification, inventory management, multi-class LAD model, multi-criteria classification

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Authors: Jamaiah H. Yahaya, Aziz Deraman, Abdul Razak Hamdan, Yusmadi Yah Jusoh

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One of the most essential issues in software products is to maintain it relevancy to the dynamics of the user’s requirements and expectation. Many studies have been carried out in quality aspect of software products to overcome these problems. Previous software quality assessment models and metrics have been introduced with strengths and limitations. In order to enhance the assurance and buoyancy of the software products, certification models have been introduced and developed. From our previous experiences in certification exercises and case studies collaborating with several agencies in Malaysia, the requirements for user based software certification approach is identified and demanded. The emergence of social network applications, the new development approach such as agile method and other varieties of software in the market have led to the domination of users over the software. As software become more accessible to the public through internet applications, users are becoming more critical in the quality of the services provided by the software. There are several categories of users in web-based systems with different interests and perspectives. The classifications and metrics are identified through brain storming approach with includes researchers, users and experts in this area. The new paradigm in software quality assessment is the main focus in our research. This paper discusses the classifications of users in web-based software system assessment and their associated factors and metrics for quality measurement. The quality model is derived based on IEEE structure and FCM model. The developments are beneficial and valuable to overcome the constraints and improve the application of software certification model in future.

Keywords: software certification model, user centric approach, software quality factors, metrics and measurements, web-based system

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Authors: Salah Hadjout, Mohamed Zouidi

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In Algeria, several works carried out in recent years have shown the importance of fusarium head blight in durum wheat. Indeed, this disease is caused by a complex of Fusarium genus pathogens. The research carried out reports that F. culmorum is the main species infecting cereals. These informations motivated our interest in the field evaluation of the behavior of some durum wheat genotypes (parental varieties and lines) with regard to fusarium head blight, mainly caused by four F. culmorum isolates. Our research work focused on following the evolution of symptom development throughout the grain filling, after artificial inoculation of ears by Fusarium isolates in order to establish a first image on the differences in genotype behavior to fusarium haed blight. Field disease assessment criteria are: disease assessment using a grading scale, thousand grain weight measurement and AUDPC. The results obtained revealed that the varieties and lines resulting from crosses had a quite different level of sensitivity to F. culmorum species and no genotype showed complete resistance in our culture conditions. Among the material tested, some lines showed higher resistance than their parents. The results also show a slight behavioral variability also linked to the aggressiveness of the Fusarium species studied in this work. Our results open very important research perspectives on fusarium head blight, in particular the search for toxins produced by Fusarium species.

Keywords: fusarium head blight, durum wheat, Fusarium culmorum, field disease assessment criteria, Algeria

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Authors: Wahiba Boudraa, Khalil Draidi, Badis Bakhouch, Farah Chettibi, Meriem Aberkane, Zihad Bouslama, Moussa Houhamdi

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The Gulf of Annaba, located at the extreme north eastern Algerian; our site of study is a marsh administratively it is part of the wilaya of Annaba, municipality of El-Bouni; extends on a surface from 55 hectare, the maximum depth is of less 2m. A scheme of work was adopted for an evaluation and characterization of the reproduction of the water nicheurs birds in the marsh of Boussedra. Some important parameters described by the scientific literature; According to standardized methods, variables were the object of a regular follow-up during the period of reproduction. These parameters were taken into account: the installation date of the nests, the vegetable support; blossoming of eggs, causes of the failure of the blossomings (predation or abandonment), characteristics of the nests (composition, internal diameter, external diameter, depth and heightening), measurements of the distances nest-nest nearest, Depth of water, the measurement of eggs, size of laying, size of laying. The follow-up in the marsh was carried out between March 2013 until the month of July 2014 at a rate of two outputs per weeks, one located and noted the nests to control them each week. The study on the reproduction of the water birds enables us to note that this site plays a very important part in the wintering and the reproduction of certain species important. This study opens broad prospects for study of several phenomena related to the ecology of the water birds, and the conservation of the wetlands.

Keywords: Algeria, Boussedra, nests, reproduction, water birds

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Authors: Amir Andria Gad Shehata

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

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Authors: Tasneem Halawani, Yamen Khateeb

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With customers’ ever-increasing expectations for fast services provisioning for all their business needs, information technology (IT) organizations, as business partners, have to cope with this demanding environment and deliver their services in the most effective and efficient way. The purpose of this paper is to identify optimization and automation opportunities for the top requested IT services in a heterogenic digital environment and widely spread customer base. In collaboration with systems, processes, and subject matter experts (SMEs), the processes in scope were approached by analyzing four-year related historical data, identifying and surveying stakeholders, modeling the as-is processes, and studying systems integration/automation capabilities. This effort resulted in identifying several pain areas, including standardization, unnecessary customer and IT involvement, manual steps, systems integration, and performance measurement. These pain areas were addressed by standardizing the top five requested IT services, eliminating/automating 43 steps, and utilizing a single platform for end-to-end process execution. In conclusion, the optimization of IT service request processes in a heterogenic digital environment and widely spread customer base is challenging, yet achievable without compromising the service quality and customers’ added value. Further studies can focus on measuring the value of the eliminated/automated process steps to quantify the enhancement impact. Moreover, a similar approach can be utilized to optimize other IT service requests, with a focus on business criticality.

Keywords: automation, customer value, heterogenic, integration, IT services, optimization, processes

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Authors: Shaolin Allen Liao, Hual-Te Chien

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Various THz phase extraction algorithms have been developed for a novel THz Modulating Interferometric Doppler Radar (THz-MIDR) developed recently by the author. The THz-MIDR differs from the well-known FTIR technique in that it introduces a continuously modulating reference branch, compared to the time-consuming discrete FTIR stepping reference branch. Such change allows real-time tracking of a moving object and capturing of its Doppler signature. The working principle of the THz-MIDR is similar to the FTIR technique: the incoming THz emission from the scene is split by a beam splitter/combiner; one of the beams is continuously modulated by a vibrating mirror or phase modulator and the other split beam is reflected by a reflection mirror; finally both the modulated reference beam and reflected beam are combined by the same beam splitter/combiner and detected by a THz intensity detector (for example, a pyroelectric detector). In order to extract THz phase from the single intensity measurement signal, we have derived rigorous mathematical formulas for 3 Frequency Banded (FB) signals: 1) DC Low-Frequency Banded (LFB) signal; 2) Fundamental Frequency Banded (FFB) signal; and 3) Harmonic Frequency Banded (HFB) signal. The THz phase extraction algorithms are then developed based combinations of 2 or all of these 3 FB signals with efficient algorithms such as Levenberg-Marquardt nonlinear fitting algorithm. Numerical simulation has also been performed in Matlab with simulated THz-MIDR interferometric signal of various Signal to Noise Ratio (SNR) to verify the algorithms.

Keywords: algorithm, modulation, THz phase, THz interferometry doppler radar

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Authors: N. Adjlane, N. Haddad

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The American foulbrood is one of the most serious diseases that may affect brood of larvae and pupae stages. The causative organism is a gram positive bacterium Paaenibacillus larvae. American foulbrood infected apiaries suffer from severe economic losses, resulting from significant decreases in honeybee populations and honey production. The aim of this study was to detect Paenibacillus larvae in the remains collected at the bottom of the hive from the suspected hives by direct PCR and culture growth. A total of 56 suspected beehive wax debris samples collected in 40 different apiaries located in the central region of Algeria. MYPGP the culture medium is used during all the identifications of the bacterium. After positive results on samples, biochemical confirmation tests (test of catalase, presence hydrolysis of casein) and microscopic (gram stain) are used in order to verify the accuracy of the initial results. The QIAamp DNA Mini Kit is used to identify the DNA of Paaenibacillus larvae. Paaenibacillus larvae were identified in 14 samples out of 16 by the PCR. A suspected culture-negative sample was found positive through evaluation with PCR. This research is for the bacterium Paaenibacillus larvae in the debris of the colony is an effective method for diagnosis of the pathology of American foulbrood.

Keywords: Paenibacillus larvae, honeybee, PCR, microbiological method

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Authors: Joao Garretto, R. J. Yarwood, Vamsi Borra, Frank Li

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Bluetooth Low Energy (BLE) has emerged as one of the main wireless communication technologies used in low-power electronics, such as wearables, beacons, and Internet of Things (IoT) devices. BLE’s energy efficiency characteristic, smart mobiles interoperability, and Over the Air (OTA) capabilities are essential features for ultralow-power devices, which are usually designed with size and cost constraints. Most current research regarding the power analysis of BLE devices focuses on the theoretical aspects of the advertising and scanning cycles, with most results being presented in the form of mathematical models and computer software simulations. Such computer modeling and simulations are important for the comprehension of the technology, but hardware measurement is essential for the understanding of how BLE devices behave in real operation. In addition, recent literature focuses mostly on the BLE technology, leaving possible applications and its analysis out of scope. In this paper, a coin cell battery-powered BLE Data Acquisition Device, with a 4-in-1 sensor and one accelerometer, is proposed and evaluated with respect to its Power Consumption. First, evaluations of the device in advertising mode with the sensors turned off completely, followed by the power analysis when each of the sensors is individually turned on and data is being transmitted, and concluding with the power consumption evaluation when both sensors are on and respectively broadcasting the data to a mobile phone. The results presented in this paper are real-time measurements of the electrical current consumption of the BLE device, where the energy levels that are demonstrated are matched to the BLE behavior and sensor activity.

Keywords: bluetooth low energy, power analysis, BLE advertising cycle, wireless sensor node

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Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

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This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: G. Gokceli, O. Eksik, E. Ozkan Zayim, N. Karatepe

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Alternative electrode materials for optoelectronic devices have been widely investigated in recent years. Since indium tin oxide (ITO) is the most preferred transparent conductive electrode, producing ITO films by simple and cost-effective solution-based techniques with enhanced optical and electrical properties has great importance. In this study, single- and multi-walled carbon nanotubes (SWCNT and MWCNT) incorporated into the ITO structure to increase electrical conductivity, mechanical strength, and chemical stability. Carbon nanotubes (CNTs) were firstly functionalized by acid treatment (HNO₃:H₂SO₄), and the thermal resistance of CNTs after functionalization was determined by thermogravimetric analysis (TGA). Thin films were then prepared by spin coating technique and characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), four-point probe measurement system and UV-Vis spectrophotometer. The effects of process parameters were compared for ITO, MWCNT-ITO, and SWCNT-ITO films. Two factors including CNT concentration and annealing temperature were considered. The UV-Vis measurements demonstrated that the transmittance of ITO films was 83.58% at 550 nm, which was decreased depending on the concentration of CNT dopant. On the other hand, both CNT dopants provided an enhancement in the crystalline structure and electrical conductivity. Due to compatible diameter and better dispersibility of SWCNTs in the ITO solution, the best result in terms of electrical conductivity was obtained by SWCNT-ITO films with the 0.1 g/L SWCNT dopant concentration and heat-treatment at 550 °C for 1 hour.

Keywords: CNT incorporation, ITO electrode, spin coating, thin film

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Authors: Huda S. Al-Azmi

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There is a growing consensus that adoption of teachers’ self-efficacy measurement tools help to assess teachers’ abilities in specific areas in order to improve their skills. As a result, different instruments to assess teachers’ ability were developed by academics and practitioners. However, many of these instruments focused either on general teaching skills, or on the other hand, were very specific to one subject. As such, these instruments do not offer a tool to measure the ability of teachers in teaching 21^st century skills such as innovation skills. Teaching innovation skills helps to prepare students for lives and careers in the 21^st century. The purpose of this study is to develop an instrument measuring teachers’ self-efficacy of teaching innovation skills related to the classroom context and evaluating the teachers’ beliefs regarding their ability in teaching innovation skills. To reach this goal, the 16-item instrument measures four dimensions of innovation skills: creativity, critical thinking, communication, and collaboration. 211 secondary-school teachers filled out the survey to quantitatively analyze the quality of the instrument. The instrument’s reliability and item analysis were measured by using jMetrik. The results concluded that the mean of self-efficacy ranged from 3 to 3.6 without extreme high or low self-efficacy scores. The discrimination analysis revealed that one item recorded a negative correlation with the total, and three items recorded low correlation with the total. The reliabilities of items ranged from 0.64 to 0.69 and the instrument needed a couple of revisions before practical use. The study concluded the need to discard one item and revise five items to increase the quality of the instrument for future work.

Keywords: critical thinking, collaboration, innovation skills, self-efficacy

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Authors: Muhammad Qadir, Yuncang Li, Cuie Wen

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Surface properties such as topography and physicochemistry of metallic implants determine the cell behavior. The surface of titanium (Ti)-based implant can be modified to enhance the bioactivity and biocompatibility. In this study, a self-organized titania–niobium pentoxide–zirconia (TiO₂–Nb₂O₅–ZrO₂) nanotubular layer on β phase Ti35Zr28Nb alloy was fabricated via electrochemical anodization. Energy-dispersive X-ray spectroscopy (EDX), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS) and water contact angle measurement techniques were used to investigate the nanotubes dimensions (i.e., the inner and outer diameters, and wall thicknesses), microstructural features and evolution of the hydrophilic properties. The in vitro biocompatibility of the TiO₂–Nb₂O₅–ZrO₂ nanotubes (NTs) was assessed by using osteoblast cells (SaOS2). Influence of anodization parameters on the morphology of TiO₂–Nb₂O₅–ZrO₂ NTs has been studied. The results indicated that the average inner diameter, outer diameter and the wall thickness of the TiO₂–Nb₂O₅–ZrO₂ NTs were ranged from 25–70 nm, 45–90 nm and 5–13 nm, respectively, and were directly influenced by the applied voltage during anodization. The average inner and outer diameters of NTs increased with increasing applied voltage, and the length of NTs increased with increasing anodization time and water content of the electrolyte. In addition, the size distribution of the NTs noticeably affected the hydrophilic properties and enhanced the biocompatibility as compared with the uncoated substrate. The results of this study could be considered for developing nano-scale coatings for a wide range of biomedical applications.

Keywords: Titanium alloy, TiO₂–Nb₂O₅–ZrO₂ nanotubes, anodization, surface wettability, biocompatibility

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Authors: Salizar Mohamed Ludin, Mohd Khairul Hasyimi Firdaus, Paul Arbon

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Purpose: This paper aims to develop Malaysian Government and community-level critical thinking, planning and action for improving community disaster resilience by reporting Phase 1, Part 1 of a larger community disaster resilience measurement study about adapting the Torrens Resilience Institute Australian Community Disaster Resilience Scorecard to the Malaysian context. Methodology: Pparticipatory action research encouraged key people involved in managing the six most affected areas in the 2014 flooding of Kelantan in Malaysia’s north-east to participate in discussions about adapting and self-testing the Australian Community Disaster Resilience Scorecard to measure and improve their communities’ disaster resilience. Findings: Communities need to strengthen their disaster resilience through better communication, cross-community cooperation, maximizing opportunities to compare their plans, actions and reactions with those reported in research publications, and aligning their community disaster management with reported best practice internationally while acknowledging the need to adapt such practice to local contexts. Research implications: There is a need for a Malaysia-wide, simple-to-use, standardized disaster resilience scorecard to improve the quality, quantity and capability of healthcare and emergency services’ preparedness, and to facilitate urgent reallocation of aid. Value: This study is the first of its kind in Malaysia. The resulting community disaster resilience guideline based on participants’ feedback about the Kelantan floods and scorecard self-testing has the potential for further adaptation to suit contexts across Malaysia, as well as demonstrating how the scorecard can be adapted for international use.

Keywords: community disaster resilience, CDR Scorecard, participatory action research, flooding, Malaysia

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Authors: Zuoji Huang, Haiming Qian, Chunlin Wang, Jinyan Sun, Nan Xu

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In this paper, the strategy to extract double road edge lines from acquired road stripe image was explored. The workflow is as follows: the road stripes are acquired by probabilistic boosting tree algorithm and morphological algorithm immediately, and road centerlines are detected by thinning algorithm, so the initial road edge lines can be acquired along the road centerlines. Then we refine the results with big variation of local curvature of centerlines. Specifically, the energy function of edge line is constructed by gradient feature and spectral information, and Dijkstra algorithm is used to optimize the initial road edge lines. The Snake model is constructed to solve the fracture problem of intersection, and the discrete dynamic programming algorithm is used to solve the model. After that, we could get the final road network. Experiment results show that the strategy proposed in this paper can be used to extract the continuous and smooth road edge lines from high-resolution remote sensing images with an accuracy of 88% in our study area.

Keywords: road edge lines extraction, energy function, intersection fracture, Snake model

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Authors: Shrey Sharma, Gunjan Kumar Verma

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High density electrical prospecting has been widely used in groundwater investigation, civil engineering and environmental survey. For efficient inversion, the forward modeling routine, sensitivity calculation, and inversion algorithm must be efficient. This paper attempts to provide a brief summary of the past and ongoing developments of the method. It includes reviews of the procedures used for data acquisition, processing and inversion of electrical resistivity data based on compilation of academic literature. In recent times there had been a significant evolution in field survey designs and data inversion techniques for the resistivity method. In general 2-D inversion for resistivity data is carried out using the linearized least-square method with the local optimization technique .Multi-electrode and multi-channel systems have made it possible to conduct large 2-D, 3-D and even 4-D surveys efficiently to resolve complex geological structures that were not possible with traditional 1-D surveys. 3-D surveys play an increasingly important role in very complex areas where 2-D models suffer from artifacts due to off-line structures. Continued developments in computation technology, as well as fast data inversion techniques and software, have made it possible to use optimization techniques to obtain model parameters to a higher accuracy. A brief discussion on the limitations of the electrical resistivity method has also been presented.

Keywords: inversion, limitations, optimization, resistivity

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Authors: Fatma El-Zahraa El-Taher, Ayman Taha, Jane Courtney, Susan Mckeever

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Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions, is critical to decisions such as crossing roads or selecting the safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer the state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset is examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of the detection of intersections in satellite images is evaluated.

Keywords: satellite images, remote sensing images, data acquisition, autonomous vehicles

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

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Model updating method has received increasing attention in damage detection structures based on measured modal parameters. Therefore, a probability-based damage detection (PBDD) procedure based on a model updating procedure is presented in this paper, in which a one-stage model-based damage identification technique based on the dynamic features of a structure is investigated. The presented framework uses a finite element updating method with a Monte Carlo simulation that considers the uncertainty caused by measurement noise. Enhanced ideal gas molecular movement (EIGMM) is used as the main algorithm for model updating. Ideal gas molecular movement (IGMM) is a multiagent algorithm based on the ideal gas molecular movement. Ideal gas molecules disperse rapidly in different directions and cover all the space inside. This is embedded in the high speed of molecules, collisions between them and with the surrounding barriers. In IGMM algorithm to accomplish the optimal solutions, the initial population of gas molecules is randomly generated and the governing equations related to the velocity of gas molecules and collisions between those are utilized. In this paper, an enhanced version of IGMM, which removes unchanged variables after specified iterations, is developed. The proposed method is implemented on two numerical examples in the field of structural damage detection. The results show that the proposed method can perform well and competitive in PBDD of structures.

Keywords: enhanced ideal gas molecular movement (EIGMM), ideal gas molecular movement (IGMM), model updating method, probability-based damage detection (PBDD), uncertainty quantification

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Authors: E. Grochowska-Niedworok, K. Brukało, M. Hadasik, M. Kardas

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Consumption of vegetables by school children and adolescents is essential for their normal growth, development and health, but a significant minority of the world's population consumes the right amount of these products. The aim of the study was to evaluate the preferences and frequency of consumption of vegetables by school children and adolescents. It has been assumed that effectively implemented nutrition education programs should have an impact on increasing the frequency of vegetable consumption among the recipients. The study covered 514 students of five schools in the Opole Voivodeship aged 9 years to 22 years. The research tool was an author's questionnaire, which consisted of closed questions on the frequency of vegetable consumption and the use of 10 ways to treat them. Preferences and frequencies are shown in percentages, while correlations were estimated on the basis of Cramer`s V and gamma coefficients. In each of the examined age groups, the relationship between sex and vegetable consumption (the Cramer`s V coefficient value was 0.06 to 0.38) was determined and the various methods of culinary processing were used (V Craméra was 0.08 to 0.34). For both sexes, the relationship between age and frequency of vegetable consumption was shown (gamma values ranged from ~ 0.00 to 0.39) and different cooking methods (gamma values were 0.01 to 0.22). The most important determinant of nutritional choices is the taste and availability of products. The fact that they have a positive effect on their health is only in third position. As has been shown, obesity prevention programs can not only address nutrition education but also teach about new flavors and increase the availability of healthy foods. In addition, the frequency of vegetable consumption can be a good indicator reflecting the healthy behaviors of children and adolescents.

Keywords: children and adolescents, frequency, welfare rate, vegetables

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Authors: Chia-Chen Wei, Pack Hsieh, Jeffrey Chen

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Surface Mount Technology (SMT) is widely used in the area of the electronic assembly in which the electronic components are mounted to the surface of the printed circuit board (PCB). Most of the defects in the SMT process are mainly related to the quality of solder paste printing. These defects lead to considerable manufacturing costs in the electronics assembly industry. Therefore, the solder paste inspection (SPI) machine for controlling and monitoring the amount of solder paste printing has become an important part of the production process. So far, the setting of the SPI threshold is based on statistical analysis and experts’ experiences to determine the appropriate threshold settings. Because the production data are not normal distribution and there are various variations in the production processes, defects related to solder paste printing still occur. In order to solve this problem, this paper proposes an online machine learning algorithm, called the automatic threshold adjustment (ATA) algorithm, and closed-loop architecture in the SMT process to determine the best threshold settings. Simulation experiments prove that our proposed threshold settings improve the accuracy from 99.85% to 100%.

Keywords: big data analytics, Industry 4.0, SPI threshold setting, surface mount technology

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Authors: Fatemeh Kourkinejad Gharaei, Tahereh Safari, Zahra Saebinasab

Abstract:

Metabolic syndrome (MetS) is a set of risk factors associated with cardiovascular diseases, atherosclerosis, and type 2 diabetes. Nonalcoholic fatty liver disease (NAFLD) is the most important liver disorder in metabolic syndrome. High fructose consumption increases the risk of NAFLD. Eugenol shows anti-thrombotic, insulin-sensitive, fat-reducing effects. This study was designed to investigate the protective role of eugenol in NAFLD caused by metabolic syndrome. Methods: Thirty male Wistar rats were randomly divided into five groups; group 1, drinking water intake animals; group 2, fructose, group 3, fructose+eugenol solvent; group 4, fructose+ eugenol 50mg/kg and group 5, fructose+ eugenol 100mg/kg. At the end of the experiment, after 12 hours of fasting and under anesthesia, blood samples were taken for measurement of fast blood glucose (FBS), SGOT, AGPT, LDL, HDL, cholesterol, triglyceride. Results: FBG significantly increased in group 2 compared to group 1 (p < 0.001); however, it significantly decreased in groups 4 and 5 compared to group 2 (p < 0.05). SGOT and SGPT levels significantly increased in group 2 compared to drinking water alone (p < 0.001). However, SGOT and SGPT levels significantly decreased in groups 4 and 5. MDA and LTDS significantly increased in group 2 compared with drinking water alone (p < 0.01), while MDA and LTDS decreased in 4 and 5 groups compared to group 2 (p < 0.05), which confirms the pathology results related to the liver damage. Conclusion: Eugenol has protective effects on the liver and fat accumulation in liver cells.

Keywords: eugenol, fructose, metabolic syndrome, nonalcoholic fatty liver disease

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Authors: Yong Zhao, Jian He, Cheng Zhang

Abstract:

Cardiovascular diseases caused by hypertension are extremely threatening to human health, and early diagnosis of hypertension can save a large number of lives. Traditional hypertension detection methods require special equipment and are difficult to detect continuous blood pressure changes. In this regard, this paper first analyzes the principle of heart rate variability (HRV) and introduces sliding window and power spectral density (PSD) to analyze the time domain features and frequency domain features of HRV, and secondly, designs an HRV-based hypertension prediction network by combining Resnet, attention mechanism, and multilayer perceptron, which extracts the frequency domain through the improved ResNet18 features through a modified ResNet18, its fusion with time-domain features through an attention mechanism, and the auxiliary prediction of hypertension through a multilayer perceptron. Finally, the network was trained and tested using the publicly available SHAREE dataset on PhysioNet, and the test results showed that this network achieved 92.06% prediction accuracy for hypertension and outperformed K Near Neighbor(KNN), Bayes, Logistic, and traditional Convolutional Neural Network(CNN) models in prediction performance.

Keywords: feature extraction, heart rate variability, hypertension, residual networks

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Authors: Balogun R. Ayodeji, Adefisan E. Adesanya, Adeyewa Z. Debo, E. C. Okogbue

Abstract:

Deep convective systems during active periods of the West African monsoon season have not been properly investigated over better temporal and spatial resolution in West Africa. Deep convective systems are investigated over seven climatic zones of the West African sub-region, which are; west-coast rainforest, dry rainforest, Nigeria-Cameroon rainforest, Nigeria savannah, Central African and South Sudan (CASS) Savannah, Sudano-Sahel, and Sahel, using data from Tropical Rainfall Measurement Mission (TRMM) Precipitation Feature (PF) database. The vertical structure of the convective systems indicated by the presence of at least one 40 dBZ and reaching (attaining) at least 1km in the atmosphere showed strong core (highest frequency (%)) of reflectivity values around 2 km which is below the freezing level (4-5km) for all the zones. Echoes are detected above the 15km altitude much more frequently in the rainforest and Savannah zones than the Sudano and Sahel zones during active periods in March-May (MAM), whereas during active periods in June-September (JJAS) the savannahs, Sudano and Sahel zones convections tend to reach higher altitude more frequently than the rainforest zones. The percentage frequencies of deep convection indicated that the occurrences of the systems are within the range of 2.3-2.8% during both March-May (MAM) and June-September (JJAS) active periods in the rainforest and savannah zones. On the contrary, the percentage frequencies were found to be less than 2% in the Sudano and Sahel zones, except during the active-JJAS period in the Sudano zone.

Keywords: active periods, convective system, frequency, reflectivity

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Authors: Alireza Yavar, Sukiman Sarmani, Khoo Kok Siong

Abstract:

The residents of villages in Kandal province of Cambodia, because of dietary habits, lifestyle and ecological conditions, are exposed to toxic elements like arsenic (As) and mercury (Hg). For comparison purpose, scalp hair samples of 12-17 school children from three villages of Anglong Romiot (AR), Svay Romiot (SR) and Kampong Kong (KK) in Kandal province of Cambodia were considered using k0- instrumental neutron activation method (k0-INAA). The samples irradiated 6 hours with 750 kW power in Malaysian nuclear agency (MNA) research reactor and subsequently found gamma peaks of radionuclides in samples using HPGe detector. The average values of arsenic and mercury were 0.0 and 3.52 (mg/kg) in AR; 1.88 and 4.26 (mg/kg) in SR; 2.81 and 3.37 (mg/kg) in KK, respectively. The results indicate KK, SR, and AR villages were in high, medium and control level of arsenic pollution, respectively. However, Hg concentration were highest in SR, then KK and AR villages, respectively. The accuracy of the method was assessed by analyzing ERM-DB001-human hair as certified reference materials (CRMs), which experimental result of ERM-DB001 was consistent with certified values. In addition, correlation between As and Hg levels was found by Pearson’s correlation test.

Keywords: Kandal province of Cambodia, k0- instrumental neutron activation method., scalp human hair, arsenic and mercury

Procedia PDF Downloads 100

Authors: Mahsa Habibzadeh

Abstract:

The function is defined as the process of systematic and systematic measurement of the components of how each task is performed and determining their potential for improvement in accordance with the specific standards of each component. Hence, evaluation is the basis for the improvement of organizations' functional excellence and the move towards performance excellence depends on performance improvement planning. Because of the past two decades, the public sector system has undergone dramatic changes. The purpose of such developments is often to overcome the barriers of the bureaucratic system, which impedes the efficient use of limited resources. Implementing widespread changes in the public sector of developed and even developing countries has led the process of developments to be addressed by many researchers. In this regard, the present paper has been carried out with the approach of analyzing the components that affect the performance of the public sector in Iran. To achieve this goal, indicators that affect the performance of the public sector and the factors affecting the improvement of its accountability have been identified. The research method in this research is descriptive and analytical. A statistical population of 120 people consists of managers and employees of the public sector in Iran. The questionnaires were distributed among them and analyzed using SPSS and LISREL software. The obtained results indicate that the results of the research findings show that between responsibilities there is a significant relationship between participation of managers and employees, legality, justice and transparency of specialty and competency, participation in public sector functions. Also, the significant coefficient for the liability variable is 3.31 for justice 2.89 for transparency 1.40 for legality of 2.27 for specialty and competence 2.13 and 5.17 for participation 5.17. Implementing indicators that affect the performance of the public sector can lead to satisfaction of the audience.

Keywords: performance, accountability system, public sector, components

Procedia PDF Downloads 229

Authors: Christopher Giehl, Anja Allabar, Daniela Ehgartner

Abstract:

Rotational rheometry is standard practice for the viscosity measurement of molten glass, neglecting the viscoelastic properties of this material, especially at temperatures approaching the glass transition. Oscillatory rheometry serves as a powerful toolbox for glass melt characterization beyond viscosity measurements. Heating and cooling rates and the time-dependent visco-elastic behavior influence the temperature where materials undergo the glass transition. This study presents quantitative thermo-mechanical visco-elasticity measurements on three samples in the Na-K-Al-Si-O system. The measurements were performed with a Furnace Rheometer System combined with an air-bearing DSR 502 measuring head (Anton Paar) and a Pt90Rh10 measuring geometry. Temperature ramps were conducted in rotation and oscillation, and the (complex) viscosity values were compared to calculated viscosity values based on sample composition. Furthermore, temperature ramps with different frequencies were conducted, also revealing the frequency-dependence of the shear loss modulus G’’ and the shear storage modulus G’. Here, lower oscillatory frequency results in lower glass transition temperature, as defined by the G’-G’’ crossover point. This contribution demonstrates that oscillatory rheometry serves as a powerful toolbox beyond viscosity measurements, as it considers the visco-elasticity of glass melts quantifying viscous and elastic moduli. Further, it offers a strong definition of Tg beyond the 10^12 Pas concept, which cannot be utilized with rotational viscometry data.

Keywords: frequency dependent glass transition, Na-K-Al-Si-O glass melts, oscillatory rheometry, visco-elasticity

Procedia PDF Downloads 108

Authors: Santosh Tummidi, Pragati Sathe, Kanchan Kothari, Prachi Gholap, Mona Agnihotri, Gwendolyn Fernandes, Leena Naik, Rachana Chaturvedi

Abstract:

Introduction: EUS-Guided Fine Needle Aspiration/Brush (EUS-FNA/Brush) has become increasingly popular for the diagnosis and staging of gastrointestinal and peri-gastrointestinal lesions. Objective: To evaluate the diagnostic accuracy and spectrum of lesions in gastrointestinal EUS-FNA. Material and Methods: A total of 124 EUS-FNA during the period from Aug 2015-Nov 2016 were studied. Results: Age ranged from 13-80 years with a slight female predominance. CBD was the most common site with 47 cases amongst which were 9 adenocarcinoma, and 7 cases were suspicious for malignancy. Pancreatic EUS-FNA showed 5 adenocarcinoma, 2 SPEN, 1 case each of neuroendocrine tumor, anaplastic carcinoma and NHL. Amongst oesophageal lesions, 3 cases were suspicious for malignancy, and 4 were inflammatory, 4 showed SCC, 1case each adenocarcinoma and leiomyoma. Stomach- 1 case each of adenocarcinoma, granulomatous inflammation, and GIST. Periportal lymph nodes were the commonest nodes, and there were 11 necrotising granulomatous inflammations, 3 metastatic adenocarcinoma, 2 cases of atypical cells and 1 case of NHL. 17 cases were unsatisfactory, 41 cases had histopathology follow up with 85% cases being concordant. Conclusion: EUS-FNA is reliable, sensitive and specific. It can be utilized for better management of intra-abdominal lesions.

Keywords: EUS-FNA, brush, cytology, histopathology

Procedia PDF Downloads 307