Search results for: scanning time
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19307

Search results for: scanning time

16127 Single Carrier Frequency Domain Equalization Design to Cope with Narrow Band Jammer

Authors: So-Young Ju, Sung-Mi Jo, Eui-Rim Jeong

Abstract:

In this paper, based on the conventional single carrier frequency domain equalization (SC-FDE) structure, we propose a new SC-FDE structure to cope with narrowband jammer. In the conventional SC-FDE structure, channel estimation is performed in the time domain. When a narrowband jammer exists, time-domain channel estimation is very difficult due to high power jamming interference, which degrades receiver performance. To relieve from this problem, a new SC-FDE frame is proposed to enable channel estimation under narrow band jamming environments. In this paper, we proposed a modified SC-FDE structure that can perform channel estimation in the frequency domain and verified the performance via computer simulation.

Keywords: channel estimation, jammer, pilot, SC-FDE

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16126 Phosphate Bonded Hemp (Cannabis sativa) Fibre Composites

Authors: Stephen O. Amiandamhen, Martina Meinken, Luvuyo Tyhoda

Abstract:

The properties of Hemp (Cannabis sativa) in phosphate bonded composites were investigated in this research. Hemp hurds were collected from the Hemporium institute for research, South Africa. The hurds were air-dried and shredded using a hammer mill. The shives were screened into different particle sizes and were treated separately with 5% solution of acetic anhydride and sodium hydroxide. The binding matrix was prepared using a reactive magnesia, phosphoric acid, class S fly ash and unslaked lime. The treated and untreated hemp fibers were mixed thoroughly in different ratios with the inorganic matrix. Boric acid and excess water were used to retard and control the rate of the reaction and the setting of the binder. The Hemp composite was formed in a rectangular mold and compressed at room temperature at a pressure of 100KPa. After de-molding the composites, they were cured in a conditioning room for 96 h. Physical and mechanical tests were conducted to evaluate the properties of the composites. A central composite design (CCD) was used to determine the best conditions to optimize the performance of the composites. Thereafter, these combinations were applied in the production of the composites, and the properties were evaluated. Scanning electron microscopy (SEM) was used to carry out the advance examination of the behavior of the composites while X-ray diffractometry (XRD) was used to analyze the reaction pathway in the composites. The results revealed that all properties of phosphate bonded Hemp composites exceeded the LD-1 grade classification of particle boards. The proposed product can be used for ceiling, partitioning, wall claddings and underlayment.

Keywords: CCD, fly ash, magnesia, phosphate bonded hemp composites, phosphoric acid, unslaked lime

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16125 SciPaaS: a Scientific Execution Platform for the Cloud

Authors: Wesley H. Brewer, John C. Sanford

Abstract:

SciPaaS is a prototype development of an execution platform/middleware designed to make it easy for scientists to rapidly deploy their scientific applications (apps) to the cloud. It provides all the necessary infrastructure for running typical IXP (Input-eXecute-Plot) style apps, including: a web interface, post-processing and plotting capabilities, job scheduling, real-time monitoring of running jobs, and even a file/case manager. In this paper, first the system architecture is described and then is demonstrated for a two scientific applications: (1) a simple finite-difference solver of the inviscid Burger’s equation, and (2) Mendel’s Accountant—a forward-time population genetics simulation model. The implications of the prototype are discussed in terms of ease-of-use and deployment options, especially in cloud environments.

Keywords: web-based simulation, cloud computing, Platform-as-a-Service (PaaS), rapid application development (RAD), population genetics

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16124 Obtaining Bioactive Mg-hydroxyapatite Composite Ceramics From Phosphate Rock For Medical Applications

Authors: Sara Mercedes Barroso Pinzón, Antonio Javier Sanchéz Herencia, Begoña Ferrari, Álvaro Jesús Castro

Abstract:

The current need for durable implants and bone substitutes characterised by biocompatibility, bioactivity and mechanical properties, without immunological rejection, is a major challenge for scientists. Hydroxyapatite (HAp) has been considered for decades as an ideal biomaterial for bone regeneration due to its chemical and crystallographic similarity to the mineral structure bioapatites. However, the lack of trace elements in the hydroxyapatite structure gives it very low mechanical and biological properties. In this sense, the objective of the research is to address the synthesis of hydroxyapatite with Mg from phosphate rock from sedimentary deposits in the central-eastern region of Colombia, taking advantage of the release of the species contained as natural precursors of Ca, P and Mg. The minerals present were studied, fluorapatite as the mineral of interest associated with mineralogical species of magnesium carbonates and quartz. The chemical and mineralogical composition was determined by X-ray fluorescence (XRF) and X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX); as well as the evaluation of the surface physicochemical properties of zeta potential (PZC), with the aim of studying the surface behaviour of the microconstituents present in the phosphate rock and to elucidate the synergistic mechanism between the minerals and establish the optimum conditions for the wet concentration process. From the products obtained and characterised by XRD, XRF, SEM, FTIR, RAMAN, HAp-Mg biocomposite scaffolds are fabricated and the influence of Mg on the morphometric parameters, mechanical and biological properties of the designed materials is evaluated.

Keywords: phosphate rock, hydroxyapatite, magnesium, biomaterials

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16123 Performance of BLDC Motor under Kalman Filter Sensorless Drive

Authors: Yuri Boiko, Ci Lin, Iluju Kiringa, Tet Yeap

Abstract:

The performance of a BLDC motor controlled by the Kalman filter-based position-sensorless drive is studied in terms of its dependence on the system’s parameters' variations. The effects of system’s parameters changes on the dynamic behavior of state variables are verified. Simulated is a closed-loop control scheme with a Kalman filter in the feedback line. Distinguished are two separate data sampling modes in analyzing feedback output from the BLDC motor: (1) equal angular separation and (2) equal time intervals. In case (1), the data are collected via equal intervals Δθ of rotor’s angular position θᵢ, i.e., keeping Δθ=const. In case (2), the data collection time points tᵢ are separated by equal sampling time intervals Δt=const. Demonstrated are the effects of the parameters changes on the sensorless control flow, in particular, reduction of the torque ripples, switching spikes, torque load balancing. It is specifically shown that an efficient suppression of commutation induced torque ripples is achievable selection of the sampling rate in the Kalman filter settings above certain critical value. The computational cost of such suppression is shown to be higher for the motors with lower induction values of the windings.

Keywords: BLDC motor, Kalman filter, sensorless drive, state variables, torque ripples reduction, sampling rate

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16122 Waste-Based Surface Modification to Enhance Corrosion Resistance of Aluminium Bronze Alloy

Authors: Wilson Handoko, Farshid Pahlevani, Isha Singla, Himanish Kumar, Veena Sahajwalla

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Aluminium bronze alloys are well known for their superior abrasion, tensile strength and non-magnetic properties, due to the co-presence of iron (Fe) and aluminium (Al) as alloying elements and have been commonly used in many industrial applications. However, continuous exposure to the marine environment will accelerate the risk of a tendency to Al bronze alloys parts failures. Although a higher level of corrosion resistance properties can be achieved by modifying its elemental composition, it will come at a price through the complex manufacturing process and increases the risk of reducing the ductility of Al bronze alloy. In this research, the use of ironmaking slag and waste plastic as the input source for surface modification of Al bronze alloy was implemented. Microstructural analysis conducted using polarised light microscopy and scanning electron microscopy (SEM) that is equipped with energy dispersive spectroscopy (EDS). An electrochemical corrosion test was carried out through Tafel polarisation method and calculation of protection efficiency against the base-material was determined. Results have indicated that uniform modified surface which is as the result of selective diffusion process, has enhanced corrosion resistance properties up to 12.67%. This approach has opened a new opportunity to access various industrial utilisations in commercial scale through minimising the dependency on natural resources by transforming waste sources into the protective coating in environmentally friendly and cost-effective ways.

Keywords: aluminium bronze, waste-based surface modification, tafel polarisation, corrosion resistance

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16121 Microstructure and Mechanical Properties of Boron-Containing AZ91D Mg Alloys

Authors: Ji Chan Kim, Seok Hong Min, Tae Kwon Ha

Abstract:

Effect of boron addition on the microstructure and mechanical properties of AZ91D Mg alloy was investigated in this study. Through calculation of phase equilibria, carried out by using FactSage® and FTLite database, solution treatment temperature was decided as 420 °C where supersaturated solid solution can be obtained. Solid solution treatment was conducted at 420 °C for 24 hrs followed by hot rolling at 420 °C and the total reduction was about 60%. Recrystallization heat treatment was followed at 420 °C for 6 hrs to obtain equiaxed microstructure. After recrystallization treatment, aging heat treatment was conducted at temperature of 200 °C for time intervals from 1 min to 200 hrs and hardness of each condition was measured by micro-Vickers method. Peak hardness was observed after 20 hrs. Tensile tests were also conducted on the specimens aged for various time intervals and the results were compared with hardness.

Keywords: AZ91D Mg alloy, boron, heat treatment, microstructure, mechanical properties, hardness

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16120 Influence of the Substitution of C for Mg and Ni on the Microstructure and Hydrogen Storage Characteristics of Mg2Ni Alloys

Authors: Sajad Haghanifar, Seyed-Farshid Kashani Bozorg

Abstract:

Nano-crystalline Mg2Ni-based powder was produced by mechanical alloying technique using binary and ternary powder mixtures with stoichiometric compositions of Mg2Ni, Mg1.9C0.1Ni and Mg2C0.1Ni0.9. The structures and morphologies of the milled products were studied by XRD, SEM and HRTEM. Their electrochemical hydrogen storage characteristics were investigated in 6 M KOH solution. X-Ray diffraction, scanning and transmission electron microscopy of the milled products showed the formation of Mg2Ni-based nano-crystallites after 5, 15 and 30 h of milling using the initial powder mixtures of Mg1.9C0.1Ni, Mg2Ni and Mg2C0.1Ni0.9, respectively. It was found that partial substitution of C for Mg has beneficial effect on the formation kinetic of nano-crystalline Mg2Ni. Contrary to this, partial substitution of C for Ni was resulted in retardation of formation kinetic of nano-crystalline Mg2Ni. In addition, the negative electrode made from Mg1.9C0.1Ni ternary milled product after 30 hour of milling exhibited the highest initial discharge capacity and longest discharge life. Thus, partial substitution of C for Mg is beneficial to electrode properties of the Mg2Ni-based crystallites. The relation between the discharge capacity and cycling number of mechanically alloyed products was proposed on the basis of the fact that the degradation of discharge capacity was mainly caused by the oxidation of magnesium and nickel. The experimental data fitted the deduced equation well.

Keywords: Mg2Ni, hydrogen absorbing materials, electrochemical properties, nano-crystalline, amorphous, mechanical alloying, carbon

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16119 Study of the Effect of the Continuous Electric Field on the Rd Cancer Cell Line by Response Surface Methodology

Authors: Radia Chemlal, Salim Mehenni, Dahbia Leila Anes-boulahbal, Mohamed Kherat, Nabil Mameri

Abstract:

The application of the electric field is considered to be a very promising method in cancer therapy. Indeed, cancer cells are very sensitive to the electric field, although the cellular response is not entirely clear. The tests carried out consisted in subjecting the RD cell line under the effect of the continuous electric field while varying certain parameters (voltage, exposure time, and cell concentration). The response surface methodology (RSM) was used to assess the effect of the chosen parameters, as well as the existence of interactions between them. The results obtained showed that the voltage, the cell concentration as well as the interaction between voltage and exposure time have an influence on the mortality rate of the RD cell line.

Keywords: continuous electric field, RD cancer cell line, RSM, voltage

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16118 An Experimental Study of Automotive Drum Brake Vibrations

Authors: Nouby Ghazaly

Abstract:

The present paper investigates experimentally the effect coefficient of friction at different operation conditions on the variation of the brake temperature, brake force, and brake vibration with the braking time. All the experimental tests were carried out using brake dynamometer which designed and constructed in Vehicle Dynamic Laboratory. The results indicate that the brake temperature increases with the increase of the normal force and sliding speed especially with the increase of the braking time. The normal force has the effect on increasing the brake force. On the contrary, the vehicle speed has the effect on decreasing the brake force. Both the normal force and sliding speed affect the brake vibration according to the friction behavior.

Keywords: brake dynamometer, coefficient of friction, drum brake vibrations, friction behavior

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16117 Scalable Learning of Tree-Based Models on Sparsely Representable Data

Authors: Fares Hedayatit, Arnauld Joly, Panagiotis Papadimitriou

Abstract:

Many machine learning tasks such as text annotation usually require training over very big datasets, e.g., millions of web documents, that can be represented in a sparse input space. State-of the-art tree-based ensemble algorithms cannot scale to such datasets, since they include operations whose running time is a function of the input space size rather than a function of the non-zero input elements. In this paper, we propose an efficient splitting algorithm to leverage input sparsity within decision tree methods. Our algorithm improves training time over sparse datasets by more than two orders of magnitude and it has been incorporated in the current version of scikit-learn.org, the most popular open source Python machine learning library.

Keywords: big data, sparsely representable data, tree-based models, scalable learning

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16116 Adsorption and Selective Determination Ametryne in Food Sample Using of Magnetically Separable Molecular Imprinted Polymers

Authors: Sajjad Hussain, Sabir Khan, Maria Del Pilar Taboada Sotomayor

Abstract:

This work demonstrates the synthesis of magnetic molecularly imprinted polymers (MMIPs) for determination of a selected pesticide (ametryne) using high performance liquid chromatography (HPLC). Computational simulation can assist the choice of the most suitable monomer for the synthesis of polymers. The (MMIPs) were polymerized at the surface of Fe3O4@SiO2 magnetic nanoparticles (MNPs) using 2-vinylpyradine as functional monomer, ethylene-glycol-dimethacrylate (EGDMA) is a cross-linking agent and 2,2-Azobisisobutyronitrile (AIBN) used as radical initiator. Magnetic non-molecularly imprinted polymer (MNIPs) was also prepared under the same conditions without analyte. The MMIPs were characterized by scanning electron microscopy (SEM), Brunauer, Emmett and Teller (BET) and Fourier transform infrared spectroscopy (FTIR). Pseudo first order and pseudo second order model were applied to study kinetics of adsorption and it was found that adsorption process followed the pseudo first order kinetic model. Adsorption equilibrium data was fitted to Freundlich and Langmuir isotherms and the sorption equilibrium process was well described by Langmuir isotherm mode. The selectivity coefficients (α) of MMIPs for ametryne with respect to atrazine, ciprofloxacin and folic acid were 4.28, 12.32, and 14.53 respectively. The spiked recoveries ranged between 91.33 and 106.80% were obtained. The results showed high affinity and selectivity of MMIPs for pesticide ametryne in the food samples.

Keywords: molecularly imprinted polymer, pesticides, magnetic nanoparticles, adsorption

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16115 Intrarenal Injection of Pentobarbital Sodium for Euthanasia in Cats: 131 Cases, 2010-2011

Authors: Kathleen Cooney, Jennifer Coates, Lesley Leach, Kristin Hrenchir

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The objective of this retrospective study was to determine whether intrarenal injection of pentobarbital sodium is a practicable method of euthanasia in client-owned cats. 131 Cats were anesthetized using a combination of tiletamine, zolazepam, and acepromazine given by of subcutaneous or intramuscular injection. Once an appropriate plane of anesthesia was reached, 6 ml of pentobarbital sodium was injected into either the left or right kidney. The patient’s age, sex, estimated weight, presenting condition, estimated dehydration level, palpable characteristics of the kidney pre and post injection, physical response of the cat, and time to cardiopulmonary arrest were recorded. Analysis of 131 records revealed that cats receiving an intrarenal injection of pentobarbital sodium had an average time to cardiopulmonary arrest of 1 minute. The great majority (79%) experienced cardiopulmonary arrest in less than one minute with the remainder experiencing cardiopulmonary arrest between 1 and 8 minutes of the injection. 95% of cats had no observable reaction to intrarenal injection other than cardiopulmonary arrest. In the 19% of cases where kidney swelling was not palpable upon injection, average time to cardiopulmonary arrest increased from 0.9 to 1.6 min. Conclusions and Clinical Relevance: Intrarenal injections of pentobarbital sodium are similar in effect to intravenous methods of euthanasia. Veterinarians who elect to use intrarenal injections can expect cardiopulmonary arrest to occur quickly in the majority of patients with few agonal reactions. Intrarenal injection of pentobarbital sodium in anesthetized cats has ideally suited for cases of owner observed euthanasia when obtaining intravenous access would difficult or disruptive.

Keywords: euthanasia, injection, intrarenal, pentobarbital sodium

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16114 Cubic Trigonometric B-Spline Approach to Numerical Solution of Wave Equation

Authors: Shazalina Mat Zin, Ahmad Abd. Majid, Ahmad Izani Md. Ismail, Muhammad Abbas

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The generalized wave equation models various problems in sciences and engineering. In this paper, a new three-time level implicit approach based on cubic trigonometric B-spline for the approximate solution of wave equation is developed. The usual finite difference approach is used to discretize the time derivative while cubic trigonometric B-spline is applied as an interpolating function in the space dimension. Von Neumann stability analysis is used to analyze the proposed method. Two problems are discussed to exhibit the feasibility and capability of the method. The absolute errors and maximum error are computed to assess the performance of the proposed method. The results were found to be in good agreement with known solutions and with existing schemes in literature.

Keywords: collocation method, cubic trigonometric B-spline, finite difference, wave equation

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16113 The Effects of Distribution Channels on the Selling Prices of Hotels in Time of Crisis

Authors: Y. Yılmaz, C. Ünal, A. Dursun

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Distribution channels play significant role for hotels. Direct and indirect selling options of hotel rooms have been increased especially with the help of new technologies, i.e. hotel’s own web sites and online booking sites. Although these options emerged as tools for diversifying the distribution channels, vast number of hotels -mostly resort hotels- is still heavily dependent upon international tour operators when selling their products. On the other hand, hotel sector is so vulnerable against crises. Economic, political or any other crisis can affect hotels very badly and so it is critical to have the right balance of distribution channel to avoid the adverse impacts of a crisis. In this study, it is aimed to search the impacts of a general crisis on the selling prices of hotels which have different weights of distribution channels. The study was done in Turkey where various crises occurred in 2015 and 2016 which had great negative impacts on Turkish tourism and led enormous occupancy rate and selling price reductions. 112 upscale resort hotel in Antalya, which is the most popular tourism destination of Turkey, joined to the research. According to the results, hotels with high dependency to international tour operators are more forced to reduce their room prices in crisis time compared to the ones which use their own web sites more. It was also found that the decline in room prices is limited for hotels which are working with national tour operators and travel agencies in crisis time.

Keywords: marketing channels, crisis, hotel, international tour operators, online travel agencies

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16112 Doxorubicin and Cyclosporine Loaded PLGA Nanoparticles to Combat Multidrug Resistance

Authors: Senthil Rajan Dharmalingam, Shamala Nadaraju, Srinivasan Ramamurthy

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Doxorubicin is the most widely used anticancer drugs in chemotherapy treatment. However, problems related to the development of multidrug resistance (MDR) and acute cardiotoxicity have led researchers to investigate alternative forms of administering doxorubicin for cancer therapy. Several methods have been attempted to overcome MDR, including the co-administration of a chemosensitizer inhibiting the efflux caused by ATP binding cassette transporters with anticancer drugs, and the bypass of the efflux mechanism. Co encapsulation of doxorubicin (Dox) and cyclosporine A (CSA) into poly (DL-lactide-co-glycolide) nanoparticles was emulsification-solvent evaporation method using polyvinyl alcohol as emulsion stabilizers. The Dox-CSA loaded nanoparticles were evaluated for particle size, zeta potential and PDI by light scattering analysis and thermal characterizations by differential scanning calorimetry (DSC). Loading efficiency (LE %) and in-vitro dissolution samples were evaluated by developed and validated HPLC method. The optimum particle size obtained is 298.6.8±39.4 nm and polydispersity index (PDI) is 0.098±0.092. Zeta potential is found to be -29.9±4.23. Optimum pH to increase Dox LE% was found 7.1 which gave 42.5% and 58.9% increase of LE% for pH 6.6 and pH 8.6 compared respectively. LE% achieved for Dox is 0.07±0.01 % and CSA is 0.09±0.03%. Increased volume of PVA and weight of PLGA shows increase in size of nanoparticles. DSC thermograms showed shift in the melting peak for the nanoparticles compared to Dox and CSA indicating encapsulation of drugs. In conclusion, these preliminary studies showed the feasibility of PLGA nanoparticles to entrap Dox and CSA and require future in-vivo studies to be performed to establish its potential.

Keywords: doxorubicin, cyclosporine, PLGA, nanoparticles

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16111 Post-Disaster Recovery and Impacts on Construction Resources: Case Studies of Queensland Catastrophic Events

Authors: Scott A. Abbott

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This paper examines the increase in the occurrence of natural disasters worldwide and the need to support vulnerable communities in post-disaster recovery. Preparation and implementation of post-disaster recovery projects need to be improved to allow communities to recover infrastructure, housing, economically and socially following a catastrophe. With the continual rise in catastrophic events worldwide due to climate change, impacts on construction resources affect the ability for post-disaster recovery to be undertaken. This research focuses on case studies of catastrophic events in Queensland, Australia, to contribute to the body of knowledge and gain valuable insights on lessons learned from past events and how they have been managed. The aim of this research is to adopt qualitative data using semi-structured interviews from participants predominantly from the insurance sector to understand barriers that have previously and currently exist in post-disaster recovery. Existing literature was reviewed to reveal gaps in knowledge that needed to be tested. Qualitative data was collected and summarised from field research with the results analysed and discussed. Barriers that impacted post-disaster recovery included time, cost, and resource capability and capacity. Causal themes that impacted time and cost were identified as decision making, pre-planning, and preparedness, as well as effective communication across stakeholders. The research study applied a qualitative approach to the existing literature and case studies across Queensland, Australia, to identify existing and new barriers that impact post-disaster recovery. It was recommended to implement effective procurement strategies to assist in cost control; implement pre-planning and preparedness strategies across funder, contractor, and local governments; more effective and timely decision making to reduce time and cost impacts.

Keywords: construction recovery, cost, disaster recovery, resources, time

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16110 Recent Development of Materials for Proton Exchange Membrane Fuel Cell (PEMFC)

Authors: Mohammed Jourdani, Hamid Mounir, Abdellatif El Marjani

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Proton exchange membrane fuel cells (PEMFCs) have been developed as a promising power source for transportation and stationary applications, and power devices for computers and mobile telephones. This paper discusses and summarizes the latest developments of materials and remaining challenges of PEMFC. The different contributions to the material of all components and the efficiencies are analyzed. Many technical advances are introduced to increase the PEMFC fuel cell efficiency and life time for transportation, stationary and portable utilization. By the last years the total cost of this system is decreasing. However, the remaining challenges that need to be overcome mean that it will be several years before full commercialization can take place.

Keywords: PEMFC fuel cell, materials, recent development, efficiency, life time, commercialization possibility

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16109 Predicting Provider Service Time in Outpatient Clinics Using Artificial Intelligence-Based Models

Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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16108 A Real-Time Snore Detector Using Neural Networks and Selected Sound Features

Authors: Stelios A. Mitilineos, Nicolas-Alexander Tatlas, Georgia Korompili, Lampros Kokkalas, Stelios M. Potirakis

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Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a widespread chronic disease that mostly remains undetected, mainly due to the fact that it is diagnosed via polysomnography which is a time and resource-intensive procedure. Screening the disease’s symptoms at home could be used as an alternative approach in order to alert individuals that potentially suffer from OSAHS without compromising their everyday routine. Since snoring is usually linked to OSAHS, developing a snore detector is appealing as an enabling technology for screening OSAHS at home using ubiquitous equipment like commodity microphones (included in, e.g., smartphones). In this context, this study developed a snore detection tool and herein present the approach and selection of specific sound features that discriminate snoring vs. environmental sounds, as well as the performance of the proposed tool. Furthermore, a Real-Time Snore Detector (RTSD) is built upon the snore detection tool and employed in whole-night sleep sound recordings resulting to a large dataset of snoring sound excerpts that are made freely available to the public. The RTSD may be used either as a stand-alone tool that offers insight to an individual’s sleep quality or as an independent component of OSAHS screening applications in future developments.

Keywords: obstructive sleep apnea hypopnea syndrome, apnea screening, snoring detection, machine learning, neural networks

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16107 Forecasting Issues in Energy Markets within a Reg-ARIMA Framework

Authors: Ilaria Lucrezia Amerise

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Electricity markets throughout the world have undergone substantial changes. Accurate, reliable, clear and comprehensible modeling and forecasting of different variables (loads and prices in the first instance) have achieved increasing importance. In this paper, we describe the actual state of the art focusing on reg-SARMA methods, which have proven to be flexible enough to accommodate the electricity price/load behavior satisfactory. More specifically, we will discuss: 1) The dichotomy between point and interval forecasts; 2) The difficult choice between stochastic (e.g. climatic variation) and non-deterministic predictors (e.g. calendar variables); 3) The confrontation between modelling a single aggregate time series or creating separated and potentially different models of sub-series. The noteworthy point that we would like to make it emerge is that prices and loads require different approaches that appear irreconcilable even though must be made reconcilable for the interests and activities of energy companies.

Keywords: interval forecasts, time series, electricity prices, reg-SARIMA methods

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16106 Particle Size Dependent Enhancement of Compressive Strength and Carbonation Efficiency in Steel Slag Cementitious Composites

Authors: Jason Ting Jing Cheng, Lee Foo Wei, Yew Ming Kun, Chin Ren Jie, Yip Chun Chieh

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The utilization of industrial by-products, such as steel slag in cementitious materials, not only mitigates environmental impact but also enhances material properties. This study investigates the dual influence of steel slag particle size on the compressive strength and carbonation efficiency of cementitious composites. Through a systematic experimental approach, steel slag particles were incorporated into cement at varying sizes, and the resulting composites were subjected to mechanical and carbonation tests. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) are conducted in this paper. The findings reveal a positive correlation between increased particle size and compressive strength, attributed to the improved interfacial transition zone and packing density. Conversely, smaller particle sizes exhibited enhanced carbonation efficiency, likely due to the increased surface area facilitating the carbonation reaction. The presence of higher silica and calcium content in finer particles was confirmed by EDX, which contributed to the accelerated carbonation process. This study underscores the importance of particle size optimization in designing sustainable cementitious materials with balanced mechanical performance and carbon sequestration potential. The insights gained from the advanced analytical techniques offer a comprehensive understanding of the mechanisms at play, paving the way for the strategic use of steel slag in eco-friendly construction practices.

Keywords: steel slag, carbonation efficiency, particle size enhancement, compressive strength

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16105 Combined Effect of Heat Stimulation and Delay Addition of Superplasticizer with Slag on Fresh and Hardened Property of Mortar

Authors: Antoni Wibowo, Harry Pujianto, Dewi Retno Sari Saputro

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The stock market can provide huge profits in a relatively short time in financial sector; however, it also has a high risk for investors and traders if they are not careful to look the factors that affect the stock market. Therefore, they should give attention to the dynamic fluctuations and movements of the stock market to optimize profits from their investment. In this paper, we present a nonlinear autoregressive exogenous model (NARX) to predict the movements of stock market; especially, the movements of the closing price index. As case study, we consider to predict the movement of the closing price in Indonesia composite index (IHSG) and choose the best structures of NARX for IHSG’s prediction.

Keywords: NARX (Nonlinear Autoregressive Exogenous Model), prediction, stock market, time series

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16104 Athlete Coping: Personality Dimensions of Recovery from Injury

Authors: Randall E. Osborne, Seth A. Doty

Abstract:

As participation in organized sports increases, so does the risk of sustaining an athletic injury. These unfortunate injuries result in missed time from practice and, inevitably, the field of competition. Recovery time plays a pivotal role in the overall rehabilitation of the athlete. With time and rehabilitation, an athlete’s physical injury can be properly treated. However, there seem to be few measures assessing psychological recovery from injury. Although an athlete has been cleared to return to play, there may still be lingering doubt about their injury. Overall, there is a vast difference between being physically cleared to play and being psychologically ready to return to play. Certain personality traits might serve as predictors of an individual’s rate of psychological recovery from an injury. The purpose of this research study is to explore the correlations between athletes’ personality and their recovery from an athletic injury, specifically, examining how locus of control has been utilized through other studies and can be beneficial to the current study. Additionally, this section will examine the link between hardiness and coping strategies. In the current study, mental toughness is being tested, but it is important to determine the link between these two concepts. Hardiness and coping strategies are closely related and can play a major role in an athlete’s mental toughness. It is important to examine competitive trait anxiety to illustrate perceived anxiety during athletic competition. The Big 5 and Social Support will also be examined in conjunction with recovery from athletic injury. Athletic injury is a devastating and common occurrence that can happen in any sport. Injured athletes often require resources and treatment to be able to return to the field of play. Athletes become more involved with physical and mental treatment as the length of recovery time increases. It is very reasonable to assume that personality traits would be predictive of athlete recovery from injury. The current study investigated the potential relationship between personality traits and recovery time; more specifically, the personality traits of locus of control, hardiness, social support, competitive trait anxiety, and the “Big 5” personality traits. Results indicated that athletes with a higher internal locus of control tend to report being physically ready to return to play and “ready” to return to play faster than those with an external locus of control. Additionally, Openness to Experience (among the Big 5 personality dimensions) was also related to the speed of return to play.

Keywords: athlete, injury, personality, readiness to play, recovery

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16103 Theoretical Research for Influence of Irradiation on Transient Creep of Metals

Authors: Pavlo Selyshchev, Tetiana Didenko

Abstract:

Via formalism of the Complex systems and in the framework of the climb - glide model a theoretical approach to describe the influence of irradiation on transient creep of metals. We consider metal under such stress and conditions of irradiation at which creep is determined by dislocation motion that consists in climb and glide. It is shown that there are qualitatively different regimes of a creep as a result of irradiation. Simulation and analysis of this phenomenon are performed. The time dependence of creep rate of metal under an irradiation is theoretically obtained. The conditions of zero minimums of the creep-rate existence as well as the times of their appearance are determined. The changing of the position of creep-rate dips in the conditions of the temperature exposure change is investigated. The obtained results are compared with the experimentally observed dependence of the creep rate on time.

Keywords: creep, climb and glide of dislocations, irradiation, non-linear feed-back, point defects

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16102 Triplex Detection of Pistacia vera, Arachis hypogaea and Pisum sativum in Processed Food Products Using Probe Based PCR

Authors: Ergün Şakalar, Şeyma Özçirak Ergün, Emrah Yalazi̇, Emine Altinkaya, Cengiz Ataşoğlu

Abstract:

In recent years, food allergies which cause serious health problems affect to public health around the world. Foodstuffs which contain allergens are either intentionally used as ingredients or are encased as contaminant in food products. The prevalence of clinical allergy to peanuts and nuts is estimated at about 0.4%-1.1% of the adult population, representing the allergy to pistachio the 7% of the cases of tree nut causing allergic reactions. In order to protect public health and enforce the legislation, methods for sensitive analysis of pistachio and peanut contents in food are required. Pea, pistachio and peanut are used together, to reduce the cost in food production such as baklava, snack foods.DNA technology-based methods in food analysis are well-established and well-roundedtools for species differentiation, allergen detection. Especially, the probe-based TaqMan real-time PCR assay can amplify target DNA with efficiency, specificity, and sensitivity.In this study, pistachio, peanut and pea were finely ground and three separate series of triplet mixtures containing 0.1, 1, 10, 100, 1000, 10,000 and 100,000 mg kg-1 of each sample were prepared for each series, to a final weight of 100 g. DNA from reference samples and industrial products was successfully extracted with the GIDAGEN® Multi-Fast DNA Isolation Kit. TaqMan probes were designed for triplex determination of ITS, Ara h 3 and pea lectin genes which are specific regions for identification pistachio, peanut and pea, respectively.The real-time PCR as quantitative detected pistachio, peanut and pea in these mixtures down to the lowest investigated level of 0.1, 0.1 and 1 mg kg-1, respectively. Also, the methods reported here are capable of detecting of as little as 0.001% level of peanut DNA, 0,000001% level of pistachio DNA and 0.000001% level of pea DNA. We accomplish that the quantitative triplex real-time PCR method developed in this study canbe applied to detect pistachio, peanut and peatraces for three allergens at once in commercial food products.

Keywords: allergens, DNA, real-time PCR, TaqMan probe

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16101 Anaerobic Digestion Batch Study of Taxonomic Variations in Microbial Communities during Adaptation of Consortium to Different Lignocellulosic Substrates Using Targeted Sequencing

Authors: Priyanka Dargode, Suhas Gore, Manju Sharma, Arvind Lali

Abstract:

Anaerobic digestion has been widely used for production of methane from different biowastes. However, the complexity of microbial communities involved in the process is poorly understood. The performance of biogas production process concerning the process productivity is closely coupled to its microbial community structure and syntrophic interactions amongst the community members. The present study aims at understanding taxonomic variations occurring in any starter inoculum when acclimatised to different lignocellulosic biomass (LBM) feedstocks relating to time of digestion. The work underlines use of high throughput Next Generation Sequencing (NGS) for validating the changes in taxonomic patterns of microbial communities. Biomethane Potential (BMP) batches were set up with different pretreated and non-pretreated LBM residues using the same microbial consortium and samples were withdrawn for studying the changes in microbial community in terms of its structure and predominance with respect to changes in metabolic profile of the process. DNA of samples withdrawn at different time intervals with reference to performance changes of the digestion process, was extracted followed by its 16S rRNA amplicon sequencing analysis using Illumina Platform. Biomethane potential and substrate consumption was monitored using Gas Chromatography(GC) and reduction in COD (Chemical Oxygen Demand) respectively. Taxonomic analysis by QIIME server data revealed that microbial community structure changes with different substrates as well as at different time intervals. It was observed that biomethane potential of each substrate was relatively similar but, the time required for substrate utilization and its conversion to biomethane was different for different substrates. This could be attributed to the nature of substrate and consequently the discrepancy between the dominance of microbial communities with regards to different substrate and at different phases of anaerobic digestion process. Knowledge of microbial communities involved would allow a rational substrate specific consortium design which will help to reduce consortium adaptation period and enhance the substrate utilisation resulting in improved efficacy of biogas process.

Keywords: amplicon sequencing, biomethane potential, community predominance, taxonomic analysis

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16100 Financial and Human Resources of Terrorism

Authors: Abdurrahman Karacabey

Abstract:

Threat paradigm has shifted throughout the history. Considering conjuncture of our time, a major threat for humanity is terrorism. Although variety of reasons are influential, financial, and human resources are the vital needs for terrorist groups. It is known that terrorism is a significant term while taking decisions in diplomatic, politic, and military issues. Even though the methods to provide resources for terrorism are quite similar, there are still some differences for deterrent terrorist groups being active in various regions of the globe. Due to social and psychological reasons activists have generally similar excuses to join terrorist groups.At the same time, terrorists’ fiscal activities to secure permanence of terrorism, occupy the politics of the countries. Besides, preventive actions are expensive creating huge burdens in host nation’s economy. This paper elaborates on how ISIS is providing human and economic resources, course of actions to overcome ISIS is on the agenda of all countries.

Keywords: financial resources, human resources, isis, terrorism

Procedia PDF Downloads 389
16099 Deep Learning-Based Object Detection on Low Quality Images: A Case Study of Real-Time Traffic Monitoring

Authors: Jean-Francois Rajotte, Martin Sotir, Frank Gouineau

Abstract:

The installation and management of traffic monitoring devices can be costly from both a financial and resource point of view. It is therefore important to take advantage of in-place infrastructures to extract the most information. Here we show how low-quality urban road traffic images from cameras already available in many cities (such as Montreal, Vancouver, and Toronto) can be used to estimate traffic flow. To this end, we use a pre-trained neural network, developed for object detection, to count vehicles within images. We then compare the results with human annotations gathered through crowdsourcing campaigns. We use this comparison to assess performance and calibrate the neural network annotations. As a use case, we consider six months of continuous monitoring over hundreds of cameras installed in the city of Montreal. We compare the results with city-provided manual traffic counting performed in similar conditions at the same location. The good performance of our system allows us to consider applications which can monitor the traffic conditions in near real-time, making the counting usable for traffic-related services. Furthermore, the resulting annotations pave the way for building a historical vehicle counting dataset to be used for analysing the impact of road traffic on many city-related issues, such as urban planning, security, and pollution.

Keywords: traffic monitoring, deep learning, image annotation, vehicles, roads, artificial intelligence, real-time systems

Procedia PDF Downloads 178
16098 Greening of Supply Chains: Benefits and Challenges Faced

Authors: Anurag Reddy Ramireddy, Abrar Ahmed, G. Sourya Sri Harsha, Pushkala Muralidharan

Abstract:

Supply chains have been developing over time since the inception of commercial trade and barter. The Green Supply Chain Management (GSCM) is a powerful way to differentiate a company from its competitors and it can greatly influence the plan success. With increased awareness to corporate responsibility and the requirement to meet the terms with environmental policy, GSCM is becoming increasingly important for companies. This paper explains the concept of green supply chain management, the difference between conventional supply chain management and green supply management and how GSCM benefits organizations while at the same time supporting a sustainable environment system. An effort has also been made to analyse research already done in this field while exploring the challenges and barriers that organizations face in implementing GSCM practices in their existing systems.

Keywords: corporate social responsibility, green supply chain management, sustainability

Procedia PDF Downloads 357