Search results for: multiple distribution supply chain network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16191

Search results for: multiple distribution supply chain network

13821 C-eXpress: A Web-Based Analysis Platform for Comparative Functional Genomics and Proteomics in Human Cancer Cell Line, NCI-60 as an Example

Authors: Chi-Ching Lee, Po-Jung Huang, Kuo-Yang Huang, Petrus Tang

Abstract:

Background: Recent advances in high-throughput research technologies such as new-generation sequencing and multi-dimensional liquid chromatography makes it possible to dissect the complete transcriptome and proteome in a single run for the first time. However, it is almost impossible for many laboratories to handle and analysis these “BIG” data without the support from a bioinformatics team. We aimed to provide a web-based analysis platform for users with only limited knowledge on bio-computing to study the functional genomics and proteomics. Method: We use NCI-60 as an example dataset to demonstrate the power of the web-based analysis platform and data delivering system: C-eXpress takes a simple text file that contain the standard NCBI gene or protein ID and expression levels (rpkm or fold) as input file to generate a distribution map of gene/protein expression levels in a heatmap diagram organized by color gradients. The diagram is hyper-linked to a dynamic html table that allows the users to filter the datasets based on various gene features. A dynamic summary chart is generated automatically after each filtering process. Results: We implemented an integrated database that contain pre-defined annotations such as gene/protein properties (ID, name, length, MW, pI); pathways based on KEGG and GO biological process; subcellular localization based on GO cellular component; functional classification based on GO molecular function, kinase, peptidase and transporter. Multiple ways of sorting of column and rows is also provided for comparative analysis and visualization of multiple samples.

Keywords: cancer, visualization, database, functional annotation

Procedia PDF Downloads 618
13820 Introduction of Integrated Image Deep Learning Solution and How It Brought Laboratorial Level Heart Rate and Blood Oxygen Results to Everyone

Authors: Zhuang Hou, Xiaolei Cao

Abstract:

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

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

Procedia PDF Downloads 135
13819 The Tadpole-Shaped Polypeptides with Two Regulable (Alkyl Chain) Tails

Authors: Hua Jin, Il Kim

Abstract:

The biocompatible tadpole-shaped polypeptides with one cyclic polypeptides ring and two alkyl chain tails were synthesized by N-heterocyclic carbine (NHC)-mediated ring-opening polymerization (ROP) of α-amino acid N-carboxyanhydrides (NCAs). First, the NHC precursor, denoted as [NHC(H)][HCO₃], with two alkyl chains at the nitrogen was prepared by a simple anion metathesis of imidazole(in)ium chlorides with KHCO₃. Then NHC releasing from the [NHC(H)][HCO₃] directly initiated the ROP of NCA to produce the cyclic polypeptides. Finally, the tadpole-shaped polypeptides with two regulable tails were obtained. The target polypeptides were characterized by nuclear magnetic resonance spectrum (1H NMR), Fourier transform infrared spectroscopy (FT-IR), gel permeation chromatography (GPC) and matrix-assisted laser desorption ionization-time of flight mass spectra (MALDI-TOF MS). This pioneering approach simplifies the synthesis procedures of tadpole-shaped polypeptides compared to other methods, which usually requires specific intramolecular ring-closure reaction.

Keywords: cyclic polypeptides, α-amino acid N-carboxyanhydrides, N-heterocyclic carbene, ring-opening polymerization, tadpole-shaped

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13818 Numerical and Experimental Studies on the Characteristic of the Air Distribution in the Wind-Box of a Circulating Fluidized Bed Boiler

Authors: Xiaozhou Liu, Guangyu Zhu, Yu Zhang, Hongwei Wu

Abstract:

The wind-box is one of the important components of a Circulating Fluidized Bed (CFB) boiler. The uniformity of air flow in the wind-box of is very important for highly efficient operation of the CFB boiler. Non-uniform air flow distribution within the wind-box can reduce the boiler's thermal efficiency, leading to higher energy consumptions. An effective measure to solve this problem is to install an air flow distributing device in the wind-box. In order to validate the effectiveness of the air flow distributing device, visual and velocity distribution uniformity experiments have been carried out under five different test conditions by using a 1:64 scale model of a 220t/hr CFB boiler. It has been shown that the z component of flow velocity remains almost the same at control cross-sections of the wind-box, with a maximum variation of less than 10%. Moreover, the same methodology has been carried out to a full-scale 220t/hr CFB boiler. The hot test results depict that the thermal efficiency of the boiler has increased from 85.71% to 88.34% when tested with an air flow distributing device in place, which is equivalent to a saving of 5,000 tons of coal per year. The economic benefits of this energy-saving technology have been shown to be very significant, which clearly demonstrates that the technology is worth applying and popularizing.

Keywords: circulating fluidized bed, CFB, wind-box, air flow distributing device, visual experiment, velocity distribution uniformity experiment, hot test

Procedia PDF Downloads 176
13817 Modbus Gateway Design Using Arm Microprocessor

Authors: Semanur Savruk, Onur Akbatı

Abstract:

Integration of various communication protocols into an automation system causes a rise in setup and maintenance cost and make to control network devices in difficulty. The gateway becomes necessary for reducing complexity in network topology. In this study, Modbus RTU/Modbus TCP industrial ethernet gateway design and implementation are presented with ARM embedded system and FreeRTOS real-time operating system. The Modbus gateway can perform communication with Modbus RTU and Modbus TCP devices over itself. Moreover, the gateway can be adjustable with the user-interface application or messaging interface. Conducted experiments and the results are presented in the paper. Eventually, the proposed system is a complete, low-cost, real-time, and user-friendly design for monitoring and setting devices and useful for meeting remote control purposes.

Keywords: gateway, industrial communication, modbus, network

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13816 Valorisation of Food Waste Residue into Sustainable Bioproducts

Authors: Krishmali N. Ekanayake, Brendan J. Holland, Colin J. Barrow, Rick Wood

Abstract:

Globally, more than one-third of all food produced is lost or wasted, equating to 1.3 billion tonnes per year. Around 31.2 million tonnes of food waste are generated across the production, supply, and consumption chain in Australia. Generally, the food waste management processes adopt environmental-friendly and more sustainable approaches such as composting, anerobic digestion and energy implemented technologies. However, unavoidable, and non-recyclable food waste ends up as landfilling and incineration that involve many undesirable impacts and challenges on the environment. A biorefinery approach contributes to a waste-minimising circular economy by converting food and other organic biomass waste into valuable outputs, including feeds, nutrition, fertilisers, and biomaterials. As a solution, Green Eco Technologies has developed a food waste treatment process using WasteMaster system. The system uses charged oxygen and moderate temperatures to convert food waste, without bacteria, additives, or water, into a virtually odour-free, much reduced quantity of reusable residual material. In the context of a biorefinery, the WasteMaster dries and mills food waste into a form suitable for storage or downstream extraction/separation/concentration to create products. The focus of the study is to determine the nutritional composition of WasteMaster processed residue to potential develop aquafeed ingredients. The global aquafeed industry is projected to reach a high value market in future, which has shown high demand for the aquafeed products. Therefore, food waste can be utilized for aquaculture feed development by reducing landfill. This framework will lessen the requirement of raw crops cultivation for aquafeed development and reduce the aquaculture footprint. In the present study, the nutritional elements of processed residue are consistent with the input food waste type, which has shown that the WasteMaster is not affecting the expected nutritional distribution. The macronutrient retention values of protein, lipid, and nitrogen free extract (NFE) are detected >85%, >80%, and >95% respectively. The sensitive food components including omega 3 and omega 6 fatty acids, amino acids, and phenolic compounds have been found intact in each residue material. Preliminary analysis suggests a price comparability with current aquafeed ingredient cost making the economic feasibility. The results suggest high potentiality of aquafeed development as 5 to 10% of the ingredients to replace/partially substitute other less sustainable ingredients across biorefinery setting. Our aim is to improve the sustainability of aquaculture and reduce the environmental impacts of food waste.

Keywords: biorefinery, ffood waste residue, input, wasteMaster

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13815 Reactive Power Control Strategy for Z-Source Inverter Based Reconfigurable Photovoltaic Microgrid Architectures

Authors: Reshan Perera, Sarith Munasinghe, Himali Lakshika, Yasith Perera, Hasitha Walakadawattage, Udayanga Hemapala

Abstract:

This research presents a reconfigurable architecture for residential microgrid systems utilizing Z-Source Inverter (ZSI) to optimize solar photovoltaic (SPV) system utilization and enhance grid resilience. The proposed system addresses challenges associated with high solar power penetration through various modes, including current control, voltage-frequency control, and reactive power control. It ensures uninterrupted power supply during grid faults, providing flexibility and reliability for grid-connected SPV customers. Challenges and opportunities in reactive power control for microgrids are explored, with simulation results and case studies validating proposed strategies. From a control and power perspective, the ZSI-based inverter enhances safety, reduces failures, and improves power quality compared to traditional inverters. Operating seamlessly in grid-connected and islanded modes guarantees continuous power supply during grid disturbances. Moreover, the research addresses power quality issues in long distribution feeders during off-peak and night-peak hours or fault conditions. Using the Distributed Static Synchronous Compensator (DSTATCOM) for voltage stability, the control objective is nighttime voltage regulation at the Point of Common Coupling (PCC). In this mode, disconnection of PV panels, batteries, and the battery controller allows the ZSI to operate in voltage-regulating mode, with critical loads remaining connected. The study introduces a structured controller for Reactive Power Controlling mode, contributing to a comprehensive and adaptable solution for residential microgrid systems. Mathematical modeling and simulations confirm successful maximum power extraction, controlled voltage, and smooth voltage-frequency regulation.

Keywords: reconfigurable architecture, solar photovoltaic, microgrids, z-source inverter, STATCOM, power quality, battery storage system

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13814 Transformation of Positron Emission Tomography Raw Data into Images for Classification Using Convolutional Neural Network

Authors: Paweł Konieczka, Lech Raczyński, Wojciech Wiślicki, Oleksandr Fedoruk, Konrad Klimaszewski, Przemysław Kopka, Wojciech Krzemień, Roman Shopa, Jakub Baran, Aurélien Coussat, Neha Chug, Catalina Curceanu, Eryk Czerwiński, Meysam Dadgar, Kamil Dulski, Aleksander Gajos, Beatrix C. Hiesmayr, Krzysztof Kacprzak, łukasz Kapłon, Grzegorz Korcyl, Tomasz Kozik, Deepak Kumar, Szymon Niedźwiecki, Dominik Panek, Szymon Parzych, Elena Pérez Del Río, Sushil Sharma, Shivani Shivani, Magdalena Skurzok, Ewa łucja Stępień, Faranak Tayefi, Paweł Moskal

Abstract:

This paper develops the transformation of non-image data into 2-dimensional matrices, as a preparation stage for classification based on convolutional neural networks (CNNs). In positron emission tomography (PET) studies, CNN may be applied directly to the reconstructed distribution of radioactive tracers injected into the patient's body, as a pattern recognition tool. Nonetheless, much PET data still exists in non-image format and this fact opens a question on whether they can be used for training CNN. In this contribution, the main focus of this paper is the problem of processing vectors with a small number of features in comparison to the number of pixels in the output images. The proposed methodology was applied to the classification of PET coincidence events.

Keywords: convolutional neural network, kernel principal component analysis, medical imaging, positron emission tomography

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13813 Kinetics of Growth Rate of Microalga: The Effect of Carbon Dioxide Concentration

Authors: Retno Ambarwati Sigit Lestari

Abstract:

Microalga is one of the organisms that can be considered ideal and potential for raw material of bioenergy production, because the content of lipids in microalga is relatively high. Microalga is an aquatic organism that produces complex organic compounds from inorganic molecules using carbon dioxide as a carbon source, and sunlight for energy supply. Microalga-CO₂ fixation has potential advantages over other carbon captures and storage approaches, such as wide distribution, high photosynthetic rate, good environmental adaptability, and ease of operation. The rates of growth and CO₂ capture of microalga are influenced by CO₂ concentration and light intensity. This study quantitatively investigates the effects of CO₂ concentration on the rates of growth and CO₂ capture of a type of microalga, cultivated in bioreactors. The works include laboratory experiments as well as mathematical modelling. The mathematical models were solved numerically and the accuracy of the model was tested by the experimental data. It turned out that the mathematical model proposed can well quantitatively describe the growth and CO₂ capture of microalga, in which the effects of CO₂ concentration can be observed.

Keywords: Microalga, CO2 concentration, photobioreactor, mathematical model

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13812 Establishing Forecasts Pointing Towards the Hungarian Energy Change Based on the Results of Local Municipal Renewable Energy Production and Energy Export

Authors: Balazs Kulcsar

Abstract:

Professional energy organizations perform analyses mainly on the global and national levels about the expected development of the share of renewables in electric power generation, heating, and cooling, as well as the transport sectors. There are just a few publications, research institutions, non-profit organizations, and national initiatives with a focus on studies in the individual towns, settlements. Issues concerning the self-supply of energy on the settlement level have not become too wide-spread. The goal of our energy geographic studies is to determine the share of local renewable energy sources in the settlement-based electricity supply across Hungary. The Hungarian energy supply system defines four categories based on the installed capacities of electric power generating units. From these categories, the theoretical annual electricity production of small-sized household power plants (SSHPP) featuring installed capacities under 50 kW and small power plants with under 0.5 MW capacities have been taken into consideration. In the above-mentioned power plant categories, the Hungarian Electricity Act has allowed the establishment of power plants primarily for the utilization of renewable energy sources since 2008. Though with certain restrictions, these small power plants utilizing renewable energies have the closest links to individual settlements and can be regarded as the achievements of the host settlements in the shift of energy use. Based on the 2017 data, we have ranked settlements to reflect the level of self-sufficiency in electricity production from renewable energy sources. The results show that the supply of all the energy demanded by settlements from local renewables is within reach now in small settlements, e.g., in the form of the small power plant categories discussed in the study, and is not at all impossible even in small towns and cities. In Hungary, 30 settlements produce more renewable electricity than their own annual electricity consumption. If these overproductive settlements export their excess electricity towards neighboring settlements, then full electricity supply can be realized on further 29 settlements from renewable sources by local small power plants. These results provide an opportunity for governmental planning of the realization of energy shift (legislative background, support system, environmental education), as well as framing developmental forecasts and scenarios until 2030.

Keywords: energy geography, Hungary, local small power plants, renewable energy sources, self-sufficiency settlements

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13811 A Fuzzy Hybrıd Decısıon Support System for Naval Base Place Selectıon in a Foreıgn Country

Authors: Latif Yanar, Muharrem Kaçan

Abstract:

In this study, an Analytic Hierarchy Process and Analytic Network Process Decision Support System (DSS) model for determination of a navy base place in another country is proposed together with a decision support software (DESTEC 1.0) developed using C Sharp programming language. The proposed software also has the ability of performing the fuzzy models (Fuzzy AHP and Fuzzy ANP) of the proposed DSS to cope with the ambiguous and linguistic nature of the model. The AHP and ANP model, for a decision support for selecting the best place among the alternatives, including the criteria and alternatives, is developed and solved by the experts from Turkish Navy and Turkish academicians related to international relations branches of the universities in Turkey. Also, the questionnaires used for weighting of the criteria and the alternatives are filled by these experts.Some of our alternatives are: economic and political stability of the third country, the effect of another super power in that country, historical relations, security in that country, social facilities in the city in which the base will be built, the transportation security and difficulty from a main city that have an airport to the city will have the base etc. Over 20 criteria like these are determined which are categorized in social, political, economic and military aspects. As a result all the criteria and three alternatives are evaluated by different people who have background and experience to weight the criteria and alternatives as it must be in AHP and ANP evaluation system. The alternatives got their degrees all between 0 – 1 and the total is 1. At the end the DSS advices one of the alternatives as the best one to the decision maker according to the developed model and the evaluations of the experts.

Keywords: analytic hierarchical process, analytic network process, fuzzy logic, naval base place selection, multiple criteria decision making

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13810 The Effect of Electric Field Distributions on Grains and Insect for Dielectric Heating Applications

Authors: S. Santalunai, T. Thosdeekoraphat, C. Thongsopa

Abstract:

This paper presents the effect of electric field distribution which is an electric field intensity analysis. Consideration of the dielectric heating of grains and insects, the rice and rice weevils are utilized for dielectric heating analysis. Furthermore, this analysis compares the effect of electric field distribution in rice and rice weevil. In this simulation, two copper plates are used to generate the electric field for dielectric heating system and put the rice materials between the copper plates. The simulation is classified in two cases, which are case I one rice weevil is placed in the rice and case II two rice weevils are placed at different position in the rice. Moreover, the probes are located in various different positions on plate. The power feeding on this plate is optimized by using CST EM studio program of 1000 watt electrical power at 39 MHz resonance frequency. The results of two cases are indicated that the most electric field distribution and intensity are occurred on the rice and rice weevils at the near point of the probes. Moreover, the heat is directed to the rice weevils more than the rice. When the temperature of rice and rice weevils are calculated and compared, the rice weevils has the temperature more than rice is about 41.62 Celsius degrees. These results can be applied for the dielectric heating applications to eliminate insect.

Keywords: capacitor copper plates, electric field distribution, dielectric heating, grains

Procedia PDF Downloads 408
13809 Investigation of Droplet Size Produced in Two-Phase Gravity Separators

Authors: Kul Pun, F. A. Hamad, T. Ahmed, J. O. Ugwu, J. Eyers, G. Lawson, P. A. Russell

Abstract:

Determining droplet size and distribution is essential when determining the separation efficiency of a two/three-phase separator. This paper investigates the effect of liquid flow and oil pad thickness on the droplet size at the lab scale. The findings show that increasing the inlet flow rates of the oil and water results in size reduction of the droplets and increasing the thickness of the oil pad increases the size of the droplets. The data were fitted with a simple Gaussian model, and the parameters of mean, standard deviation, and amplitude were determined. Trends have been obtained for the fitted parameters as a function of the Reynolds number, which suggest a way forward to better predict the starting parameters for population models when simulating separation using CFD packages. The key parameter to predict to fix the position of the Gaussian distribution was found to be the mean droplet size.

Keywords: two-phase separator, average bubble droplet, bubble size distribution, liquid-liquid phase

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13808 Human Action Recognition Using Variational Bayesian HMM with Dirichlet Process Mixture of Gaussian Wishart Emission Model

Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

Abstract:

In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.

Keywords: human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, prior distribution and approximate posterior distribution, KTH dataset

Procedia PDF Downloads 353
13807 Multi Criteria Authentication Method in Cognitive Radio Networks

Authors: Shokoufeh Monjezi Kouchak

Abstract:

Cognitive radio network (CRN) is future network .Without this network wireless devices can’t work appropriately in the next decades. Today, wireless devices use static spectrum access methods and these methods don’t use spectrums optimum so we need use dynamic spectrum access methods to solve shortage spectrum challenge and CR is a great device for DSA but first of all its challenges should be solved .security is one of these challenges .In this paper we provided a survey about CR security. You can see this survey in tables 1 to 7 .After that we proposed a multi criteria authentication method in CRN. Our criteria in this method are: sensing results, following sending data rules, position of secondary users and no talk zone. Finally we compared our method with other authentication methods.

Keywords: authentication, cognitive radio, security, radio networks

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13806 Latitudinal Impact on Spatial and Temporal Variability of 7Be Activity Concentrations in Surface Air along Europe

Authors: M. A. Hernández-Ceballos, M. Marín-Ferrer, G. Cinelli, L. De Felice, T. Tollefsen, E. Nweke, P. V. Tognoli, S. Vanzo, M. De Cort

Abstract:

This study analyses the latitudinal impact of the spatial and temporal distribution on the cosmogenic isotope 7Be in surface air along Europe. The long-term database of the 6 sampling sites (Ivalo, Helsinki, Berlin, Freiburg, Sevilla and La Laguna), that regularly provide data to the Radioactivity Environmental Monitoring (REM) network managed by the Joint Research Centre (JRC) in Ispra, were used. The selection of the stations was performed attending to different factors, such as 1) heterogeneity in terms of latitude and altitude, and 2) long database coverage. The combination of these two parameters ensures a high degree of representativeness of the results. In the later, the temporal coverage varies between stations, being used in the present study sampling stations with a database more or less continuously from 1984 to 2011. The mean values of 7Be activity concentration presented a spatial distribution value ranging from 2.0 ± 0.9 mBq/m3 (Ivalo, north) to 4.8 ± 1.5 mBq/m3 (La Laguna, south). An increasing gradient with latitude was observed from the north to the south, 0.06 mBq/m3. However, there was no correlation with altitude, since all stations are sited within the atmospheric boundary layer. The analyses of the data indicated a dynamic range of 7Be activity for solar cycle and phase (maximum or minimum), having been observed different impact on stations according to their location. The results indicated a significant seasonal behavior, with the maximum concentrations occurring in the summer and minimum in the winter, although with differences in the values reached and in the month registered. Due to the large heterogeneity in the temporal pattern with which the individual radionuclide analyses were performed in each station, the 7Be monthly index was calculated to normalize the measurements and perform the direct comparison of monthly evolution among stations. Different intensity and evolution of the mean monthly index were observed. The knowledge of the spatial and temporal distribution of this natural radionuclide in the atmosphere is a key parameter for modeling studies of atmospheric processes, which are important phenomena to be taken into account in the case of a nuclear accident.

Keywords: Berilium-7, latitudinal impact in Europe, seasonal and monthly variability, solar cycle

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13805 Reliability and Probability Weighted Moment Estimation for Three Parameter Mukherjee-Islam Failure Model

Authors: Ariful Islam, Showkat Ahmad Lone

Abstract:

The Mukherjee-Islam Model is commonly used as a simple life time distribution to assess system reliability. The model exhibits a better fit for failure information and provides more appropriate information about hazard rate and other reliability measures as shown by various authors. It is possible to introduce a location parameter at a time (i.e., a time before which failure cannot occur) which makes it a more useful failure distribution than the existing ones. Even after shifting the location of the distribution, it represents a decreasing, constant and increasing failure rate. It has been shown to represent the appropriate lower tail of the distribution of random variables having fixed lower bound. This study presents the reliability computations and probability weighted moment estimation of three parameter model. A comparative analysis is carried out between three parameters finite range model and some existing bathtub shaped curve fitting models. Since probability weighted moment method is used, the results obtained can also be applied on small sample cases. Maximum likelihood estimation method is also applied in this study.

Keywords: comparative analysis, maximum likelihood estimation, Mukherjee-Islam failure model, probability weighted moment estimation, reliability

Procedia PDF Downloads 274
13804 Machine Learning Methods for Network Intrusion Detection

Authors: Mouhammad Alkasassbeh, Mohammad Almseidin

Abstract:

Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE.

Keywords: IDS, DDoS, MLP, KDD

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13803 Grain Size Characteristics and Sediments Distribution in the Eastern Part of Lekki Lagoon

Authors: Mayowa Philips Ibitola, Abe Oluwaseun Banji, Olorunfemi Akinade-Solomon

Abstract:

A total of 20 bottom sediment samples were collected from the Lekki Lagoon during the wet and dry season. The study was carried out to determine the textural characteristics, sediment distribution pattern and energy of transportation within the lagoon system. The sediment grain sizes and depth profiling was analyzed using dry sieving method and MATLAB algorithm for processing. The granulometric reveals fine grained sand both for the wet and dry season with an average mean value of 2.03 ϕ and -2.88 ϕ, respectively. Sediments were moderately sorted with an average inclusive standard deviation of 0.77 ϕ and -0.82 ϕ. Skewness varied from strongly coarse and near symmetrical 0.34- ϕ and 0.09 ϕ. The kurtosis average value was 0.87 ϕ and -1.4 ϕ (platykurtic and leptokurtic). Entirely, the bathymetry shows an average depth of 4.0 m. The deepest and shallowest area has a depth of 11.2 m and 0.5 m, respectively. High concentration of fine sand was observed at deep areas compared to the shallow areas during wet and dry season. Statistical parameter results show that the overall sediments are sorted, and deposited under low energy condition over a long distance. However, sediment distribution and sediment transport pattern of Lekki Lagoon is controlled by a low energy current and the down slope configuration of the bathymetry enhances the sorting and the deposition rate in the Lekki Lagoon.

Keywords: Lekki Lagoon, Marine sediment, bathymetry, grain size distribution

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13802 Evaluation of the Enablers of Industry 4.0 in the Ready-Made Garments Sector of Bangladesh: A Fuzzy Analytical Hierarchy Process Approach

Authors: Shihab-Uz-Zaman Shah, Sanjeeb Roy, Habiba Akter

Abstract:

Keeping the high impact of the Ready-Made Garments (RMG) on the country’s economic growth in mind, this research paves a way for the implementation of Industry 4.0 in the garments industry of Bangladesh. At present, Industry 4.0 is a common buzzword representing the adoption of digital technologies in the production process to transform the existing industries into smart factories and create a great change in the global value chain. The RMG industry is the largest industrial sector of Bangladesh which provides 12.26% to its National GDP (Gross Domestic Product). The work starts with identifying possible enablers of Industry 4.0. To evaluate the enablers, a Multiple-Criteria Decision-Making (MCDM) procedure named Fuzzy Analytical Hierarchy Process (FAHP) was used. A questionnaire was developed as a part of a survey for collecting and analyzing expert opinions from relevant academicians and industrialists. The responses were eventually used as the input for the FAHP which helped to assign weight matrices to the enablers. This weight matrix indicated the level of importance of these enablers. The full paper will discuss the way of a successful evaluation of the enablers and implementation of Industry 4.0 by using these enablers.

Keywords: enablers, fuzzy AHP, industry 4.0, RMG sector

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13801 A Case Study on the Seismic Performance Assessment of the High-Rise Setback Tower Under Multiple Support Excitations on the Basis of TBI Guidelines

Authors: Kamyar Kildashti, Rasoul Mirghaderi

Abstract:

This paper describes the three-dimensional seismic performance assessment of a high-rise steel moment-frame setback tower, designed and detailed per the 2010 ASCE7, under multiple support excitations. The vulnerability analyses are conducted based on nonlinear history analyses under a set of multi-directional strong ground motion records which are scaled to design-based site-specific spectrum in accordance with ASCE41-13. Spatial variation of input motions between far distant supports of each part of the tower is considered by defining time lag. Plastic hinge monotonic and cyclic behavior for prequalified steel connections, panel zones, as well as steel columns is obtained from predefined values presented in TBI Guidelines, PEER/ATC72 and FEMA P440A to include stiffness and strength degradation. Inter-story drift ratios, residual drift ratios, as well as plastic hinge rotation demands under multiple support excitations, are compared to those obtained from uniform support excitations. Performance objectives based on acceptance criteria declared by TBI Guidelines are compared between uniform and multiple support excitations. The results demonstrate that input motion discrepancy results in detrimental effects on the local and global response of the tower.

Keywords: high-rise building, nonlinear time history analysis, multiple support excitation, performance-based design

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13800 Detection of Autistic Children's Voice Based on Artificial Neural Network

Authors: Royan Dawud Aldian, Endah Purwanti, Soegianto Soelistiono

Abstract:

In this research we have been developed an automatic investigation to classify normal children voice or autistic by using modern computation technology that is computation based on artificial neural network. The superiority of this computation technology is its capability on processing and saving data. In this research, digital voice features are gotten from the coefficient of linear-predictive coding with auto-correlation method and have been transformed in frequency domain using fast fourier transform, which used as input of artificial neural network in back-propagation method so that will make the difference between normal children and autistic automatically. The result of back-propagation method shows that successful classification capability for normal children voice experiment data is 100% whereas, for autistic children voice experiment data is 100%. The success rate using back-propagation classification system for the entire test data is 100%.

Keywords: autism, artificial neural network, backpropagation, linier predictive coding, fast fourier transform

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13799 Protecting the Privacy and Trust of VIP Users on Social Network Sites

Authors: Nidal F. Shilbayeh, Sameh T. Khuffash, Mohammad H. Allymoun, Reem Al-Saidi

Abstract:

There is a real threat on the VIPs personal pages on the Social Network Sites (SNS). The real threats to these pages is violation of privacy and theft of identity through creating fake pages that exploit their names and pictures to attract the victims and spread of lies. In this paper, we propose a new secure architecture that improves the trusting and finds an effective solution to reduce fake pages and possibility of recognizing VIP pages on SNS. The proposed architecture works as a third party that is added to Facebook to provide the trust service to personal pages for VIPs. Through this mechanism, it works to ensure the real identity of the applicant through the electronic authentication of personal information by storing this information within content of their website. As a result, the significance of the proposed architecture is that it secures and provides trust to the VIPs personal pages. Furthermore, it can help to discover fake page, protect the privacy, reduce crimes of personality-theft, and increase the sense of trust and satisfaction by friends and admirers in interacting with SNS.

Keywords: social network sites, online social network, privacy, trust, security and authentication

Procedia PDF Downloads 381
13798 Mixtures of Length-Biased Weibull Distributions for Loss Severity Modelling

Authors: Taehan Bae

Abstract:

In this paper, a class of length-biased Weibull mixtures is presented to model loss severity data. The proposed model generalizes the Erlang mixtures with the common scale parameter, and it shares many important modelling features, such as flexibility to fit various data distribution shapes and weak-denseness in the class of positive continuous distributions, with the Erlang mixtures. We show that the asymptotic tail estimate of the length-biased Weibull mixture is Weibull-type, which makes the model effective to fit loss severity data with heavy-tailed observations. A method of statistical estimation is discussed with applications on real catastrophic loss data sets.

Keywords: Erlang mixture, length-biased distribution, transformed gamma distribution, asymptotic tail estimate, EM algorithm, expectation-maximization algorithm

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13797 Comparative Performance Analysis of Fiber Delay Line Based Buffer Architectures for Contention Resolution in Optical WDM Networks

Authors: Manoj Kumar Dutta

Abstract:

Wavelength division multiplexing (WDM) technology is the most promising technology for the proper utilization of huge raw bandwidth provided by an optical fiber. One of the key problems in implementing the all-optical WDM network is the packet contention. This problem can be solved by several different techniques. In time domain approach the packet contention can be reduced by incorporating fiber delay lines (FDLs) as optical buffer in the switch architecture. Different types of buffering architectures are reported in literatures. In the present paper a comparative performance analysis of three most popular FDL architectures are presented in order to obtain the best contention resolution performance. The analysis is further extended to consider the effect of different fiber non-linearities on the network performance.

Keywords: WDM network, contention resolution, optical buffering, non-linearity, throughput

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13796 Linking Sustainable Public Procurement and the Sustainable Development Goals Targets in Zambia: A Preliminary Investigation

Authors: Charles P. Mukumba, Kahilu K. Shakantu

Abstract:

Achieving the Sustainable Development Goals [SDGs] is a key to achieving transformational results that support Zambia’s development. Public procurement is an integral to the government’s mission to deliver goods and services, in a timely and economic manner beyond the value of money spent. This study explores the link between sustainable public procurement and the SDG targets in Zambia. And to validate the established links with the public sector procurement in Zambia. The study employed qualitative research using semi-structured interviews with 18 public procurement officials. The collected data was analysed using thematic analysis. The findings indicate that public procurement plays a fundamental role in achieving the sustainable development goals [SDGs] by helping to deliver core public services that support SDGs and also by systematising and co-delivering added value along the way. The study further established the importance of sustainable public procurement within the context of development. The interviews were limited to mainstream public sector procurement entities in Lusaka, Zambia. Sustainable public procurement actions have the potential to impact SDG goals. Promoting sustainable public procurement will enhance sustainable development and significantly improve supply chain that would benefit the economy, society and environment. Findings will inform policy-makers how to strategically design sustainable public procurement policy by attuning it to procuring entities objectives and priorities in order to contribute to the attainment of SDGs.

Keywords: sustainable public procurement, sustainable development goals, target, Zambia

Procedia PDF Downloads 149
13795 Combination of Unmanned Aerial Vehicle and Terrestrial Laser Scanner Data for Citrus Yield Estimation

Authors: Mohammed Hmimou, Khalid Amediaz, Imane Sebari, Nabil Bounajma

Abstract:

Annual crop production is one of the most important macroeconomic indicators for the majority of countries around the world. This information is valuable, especially for exporting countries which need a yield estimation before harvest in order to correctly plan the supply chain. When it comes to estimating agricultural yield, especially for arboriculture, conventional methods are mostly applied. In the case of the citrus industry, the sale before harvest is largely practiced, which requires an estimation of the production when the fruit is on the tree. However, conventional method based on the sampling surveys of some trees within the field is always used to perform yield estimation, and the success of this process mainly depends on the expertise of the ‘estimator agent’. The present study aims to propose a methodology based on the combination of unmanned aerial vehicle (UAV) images and terrestrial laser scanner (TLS) point cloud to estimate citrus production. During data acquisition, a fixed wing and rotatory drones, as well as a terrestrial laser scanner, were tested. After that, a pre-processing step was performed in order to generate point cloud and digital surface model. At the processing stage, a machine vision workflow was implemented to extract points corresponding to fruits from the whole tree point cloud, cluster them into fruits, and model them geometrically in a 3D space. By linking the resulting geometric properties to the fruit weight, the yield can be estimated, and the statistical distribution of fruits size can be generated. This later property, which is information required by importing countries of citrus, cannot be estimated before harvest using the conventional method. Since terrestrial laser scanner is static, data gathering using this technology can be performed over only some trees. So, integration of drone data was thought in order to estimate the yield over a whole orchard. To achieve that, features derived from drone digital surface model were linked to yield estimation by laser scanner of some trees to build a regression model that predicts the yield of a tree given its features. Several missions were carried out to collect drone and laser scanner data within citrus orchards of different varieties by testing several data acquisition parameters (fly height, images overlap, fly mission plan). The accuracy of the obtained results by the proposed methodology in comparison to the yield estimation results by the conventional method varies from 65% to 94% depending mainly on the phenological stage of the studied citrus variety during the data acquisition mission. The proposed approach demonstrates its strong potential for early estimation of citrus production and the possibility of its extension to other fruit trees.

Keywords: citrus, digital surface model, point cloud, terrestrial laser scanner, UAV, yield estimation, 3D modeling

Procedia PDF Downloads 142
13794 A Remote Sensing Approach to Calculate Population Using Roads Network Data in Lebanon

Authors: Kamel Allaw, Jocelyne Adjizian Gerard, Makram Chehayeb, Nada Badaro Saliba

Abstract:

In developing countries, such as Lebanon, the demographic data are hardly available due to the absence of the mechanization of population system. The aim of this study is to evaluate, using only remote sensing data, the correlations between the number of population and the characteristics of roads network (length of primary roads, length of secondary roads, total length of roads, density and percentage of roads and the number of intersections). In order to find the influence of the different factors on the demographic data, we studied the degree of correlation between each factor and the number of population. The results of this study have shown a strong correlation between the number of population and the density of roads and the number of intersections.

Keywords: population, road network, statistical correlations, remote sensing

Procedia PDF Downloads 162
13793 Reliability of Movement Assessment Battery for Children-2 Age Band 3 Using Multiple Testers

Authors: Jernice S. Y. Tan

Abstract:

Introduction: Reliability within and between testers is vital to ensure the accuracy of any motor assessment instrument. However, reliability checks of the Movement Assessment Battery for Children-2 (MABC-2) age band 3 using multiple testers assigned to different MABC-2 tasks for the same group of participants are uncommon. Multiple testers were not stated as a choice in the MABC-2 manual. Therefore, the purpose of this study was to determine the inter- and intra-tester reliability for using multiple testers to administer the test protocols of MABC-2 age band 3. Methods: Thirty volunteered adolescents (n = 30; 15 males, 15 females; age range: 13 – 16 years) performed the eight tasks in a randomised sequence at three different test stations for the MABC-2 task components (Manual Dexterity, Aiming and Catching, Balance). Ethics approval and parental consent were obtained. The participants were videotaped while performing the test protocols of MABC-2 age band 3. Five testers were involved in the data collection process. They were Sports Science graduating students doing their final year project and were supervised by experienced motor assessor. Inter- and intra-tester reliability checks using intra-class coefficient (ICC) were carried out using the videotaped data. Results: The inter-tester reliability between the five testers for the eight tasks ranged from rᵢcc = 0.705 to rᵢcc = 0.995. This suggests that the average agreement between them was considered good to excellent. With the exception of one tester who had rᵢcc = 0.687 for one of the eight tasks (i.e. zip-zap hopping), the intra-tester reliability within each tester ranged from rᵢcc = 0.728 to rᵢcc = 1.000, and this also suggested good to excellent consistency within testers. Discussion: The use of multiple testers with good intra-tester reliability for different test stations is feasible. This method allows several participants to be assessed concurrently at different test stations and saves overall data collection time. Therefore, it is recommended that the administering of MABC-2 with multiple testers should be extended to other age bands ensuring the feasibility of such method for other age bands.

Keywords: adolescents, MABC, motor assessment, motor skills, reliability

Procedia PDF Downloads 323
13792 Cooperative Cross Layer Topology for Concurrent Transmission Scheduling Scheme in Broadband Wireless Networks

Authors: Gunasekaran Raja, Ramkumar Jayaraman

Abstract:

In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.

Keywords: cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing

Procedia PDF Downloads 265