Search results for: robust ranking technique
7500 Softener Washes Affecting the Shrinkage and Appearance of Knitted Garments
Authors: Ezza Nasir, Babar Ramzan
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Silicon washes on altered knitted fabrics will provide diverse shrinkage trends. The expectation on shrinkage for various apparel products are also changed. However, the effect of shrinkage in garment is still ambiguous. As a result, analysis of shrinkage after different concentrations of silicon washes can provide a more realistic study. The purpose of this study is to analyze the shrinkage with commercial sewing threads in knitted fabric. Study focuses on the effect of different washes on garment measurement and to study the effect of washes on fabric shrinkage. Four different types of knitted fabric were sewn with same length and width measurements. To study the effect of softener washes on shrinkage of garment through subjective ranking, there were critical dimensions for measurements done on body length and width garment appearance and shrinkage.Keywords: shrinkage, dimensions, knitted fabric, silicon
Procedia PDF Downloads 4747499 Outline of a Technique for the Recommendation of Tourism Products in Cuba Using GIS
Authors: Jesse D. Cano, Marlon J. Remedios
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Cuban tourism has developed so much in the last 30 years to the point of becoming one of the engines of the Cuban economy. With such a development, Cuban companies opting for e-tourism as a way to publicize their products and attract customers has also grown. Despite this fact, the majority of Cuban tourism-themed websites simply provide information on the different products and services they offer which results in many cases, in the user getting overwhelmed with the amount of information available which results in the user abandoning the search before he can find a product that fits his needs. Customization has been recognized as a critical factor for successful electronic tourism business and the use of recommender systems is the best approach to address the problem of personalization. This paper aims to outline a preliminary technique to obtain predictions about which products a particular user would give a better evaluation; these products would be those which the website would show in the first place. To achieve this, the theoretical elements of the Cuban tourism environment are discussed; recommendation systems and geographic information systems as tools for information representation are also discussed. Finally, for each structural component identified, we define a set of rules that allows obtaining an electronic tourism system that handles the personalization of the service provided effectively.Keywords: geographic information system, technique, tourism products, recommendation
Procedia PDF Downloads 5037498 The Effect of Using Augmented Reality Technique in a Computer Course Unit on the Academic Achievement and Attitudes of High School Female Students
Authors: Maha A. Al-Hsayni
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Title of the Study: The Effect of Using Augmented Reality Technique in a Computer Course Unit on the Academic Achievement and Attitudes of High School Female Students. This study aimed at identifying the effect of using the Augmented Reality technique on the academic achievement of computer course at the cognitive domains (Knowledge, comprehension and analysis) with third high school female students in Holy Makkah. The researcher used: The quasi-experimental approach. The sample of the study was comprised of (55) female students in the third high school level in Holy Makkah in the second semester of the academic year 1434/1435 H. These students were assigned to two groups: The experimental group of (28) students who were taught by using the Augmented Reality technology, and the control group of (27) students, who were taught by using the traditional method. The researcher prepared a set of tools and materials, which are represented in achievement test consisted of (30) clauses, direction instrument consisted of (25) clauses and the design of augmented reality for computer study unit. The study used the following statistical methods for data analysis: Cronbach's alpha coefficient, Pearson correlation coefficient, means, standard deviations, t-test and analysis of covariance test ANCOVA. The study reached the following results: 1- There are statistically significance difference at ( 0.05) among the adjusted means of the experimental and control groups in the posttest at the domains of (Knowledge, comprehension and analysis) of third high school graders after adjusting the pretest 2- There are statistically significance difference at ( 0.05) among the means of pre and post-test for female students of the experimental group in the scale of attitude towards using Augmented Reality Technique. In the light of the study results, the researcher recommends the followings: The necessity of using Augmented Reality Technique in teaching computer courses for high school students. Furthermore, emphasizing the need to provide schools with educational halls equipped with instruments and screens that enable teachers to use the Augmented Reality in teaching the other courses. Also, the researcher suggested conducting more studies in order to improve the process of teaching and learning.Keywords: augmented reality technique, computer course unit, academic achievement, attitudes, high school female students
Procedia PDF Downloads 4117497 Police and Crime Scene Management Model
Authors: Najaf Hamadzadeh Arbabi
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Crime scene management is the first and most critical step in criminal investigations and all the criminal investigations are based on the ability of the crime scene investigation officers for diagnosing the importance and the role of physical evidence at the crime scene. According to the role of available physical evidence at the scene to prove the crime and identify the perpetrator and prove the innocence of those accused have been unduly and also impossible due to the rejection of these reasons, the maintenance and investigation of crime scene and collect evidence are very important in the crime scene. This research, by identifying the factors affecting the management of the crime scene, looking for presenting the effective and efficient indigenous pattern for managing of the crime scene in Iran. Method: This study is an applied and development research. Wilcoxon signed-rank test and the Friedman test for ranking, were used for analyzing the data and all hypotheses were tested at 95% confidence level. The target population is 50 judges and experts in Tehran.Keywords: crime scene, identification, designation, individualization, reconstruction
Procedia PDF Downloads 2777496 The Simultaneous Application of Chemical and Biological Markers to Identify Reliable Indicators of Untreated Human Waste and Fecal Pollution in Urban Philadelphia Source Waters
Authors: Stafford Stewart, Hui Yu, Rominder Suri
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This paper publishes the results of the first known study conducted in urban Philadelphia waterways that simultaneously utilized anthropogenic chemical and biological markers to identify suitable indicators of untreated human waste and fecal pollution. A total of 13 outfall samples, 30 surface water samples, and 2 groundwater samples were analyzed for fecal contamination and untreated human waste using a suite of 25 chemical markers and 5 bio-markers. Pearson rank correlation tests were conducted to establish associations between the abundances of bio-markers and the concentrations of chemical markers. Results show that 16S rRNA gene of human-associated Bacteroidales (BacH) was very strongly correlated (0.76 – 0.97, p < 0.05) with labile chemical markers acetaminophen, cotinine, estriol, and urobilin. Likewise, human-specific F- RNA coliphages (F-RNA-II) and labile chemical markers, urobilin, ibuprofen, cotinine and estriol, were significantly correlated (0.77 – 0.95, p < 0.05). Similarly, a strong positive correlation (0.67 – 0.91, p < 0.05) was evident between the abundances of bio-markers BacH and F-RNA-II, and the concentrations of the conservative markers, trimethoprim, meprobamate, diltiazem, triclocarban, metformin, sucralose, gemfibrozil, sulfamethoxazole, and carbamazepine. Human mitochondrial DNA (MitoH) correlated moderately with labile markers nicotine and salicylic acid as well as with conservative markers metformin and triclocarban (0.31 – 0.47, p<0.05). This study showed that by associating chemical and biological markers, a robust technique was developed for fingerprinting source-specific untreated waste and fecal contamination in source waters.Keywords: anthropogenic markers, bacteroidales, fecal pollution, source waters, wastewater
Procedia PDF Downloads 167495 Luminescent Enhancement with Morphology Controlled Gd2O3:Eu Phosphors
Authors: Ruby Priya, Om Parkash Pandey
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Eu doped Gd₂O₃ phosphors are synthesized via co-precipitation method using ammonia as a precipitating agent. The concentration of the Eu was set as 4 mol% for all the samples. The effect of the surfactants (CTAB, PEG, and SDS) on the structural, morphological and luminescent properties has been studied in details. The as-synthesized phosphors were characterized by X-ray diffraction technique, Field emission scanning electron microscopy, Fourier transformed infrared spectroscopy and photoluminescence technique. It was observed that the surfactants have not changed the crystal structure, but influenced the morphology of as-synthesized phosphors to a great extent. The as-synthesized phosphors are expected to be promising candidates for optoelectronic devices, biosensors, MRI contrast agents and various biomedical applications.Keywords: co-precipitation, Europium, photoluminescence, surfactants
Procedia PDF Downloads 1857494 Development of an Interactive and Robust Image Analysis and Diagnostic Tool in R for Early Detection of Cervical Cancer
Authors: Kumar Dron Shrivastav, Ankan Mukherjee Das, Arti Taneja, Harpreet Singh, Priya Ranjan, Rajiv Janardhanan
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Cervical cancer is one of the most common cancer among women worldwide which can be cured if detected early. Manual pathology which is typically utilized at present has many limitations. The current gold standard for cervical cancer diagnosis is exhaustive and time-consuming because it relies heavily on the subjective knowledge of the oncopathologists which leads to mis-diagnosis and missed diagnosis resulting false negative and false positive. To reduce time and complexities associated with early diagnosis, we require an interactive diagnostic tool for early detection particularly in developing countries where cervical cancer incidence and related mortality is high. Incorporation of digital pathology in place of manual pathology for cervical cancer screening and diagnosis can increase the precision and strongly reduce the chances of error in a time-specific manner. Thus, we propose a robust and interactive cervical cancer image analysis and diagnostic tool, which can categorically process both histopatholgical and cytopathological images to identify abnormal cells in the least amount of time and settings with minimum resources. Furthermore, incorporation of a set of specific parameters that are typically referred to for identification of abnormal cells with the help of open source software -’R’ is one of the major highlights of the tool. The software has the ability to automatically identify and quantify the morphological features, color intensity, sensitivity and other parameters digitally to differentiate abnormal from normal cells, which may improve and accelerate screening and early diagnosis, ultimately leading to timely treatment of cervical cancer.Keywords: cervical cancer, early detection, digital Pathology, screening
Procedia PDF Downloads 1787493 Comparing the Apparent Error Rate of Gender Specifying from Human Skeletal Remains by Using Classification and Cluster Methods
Authors: Jularat Chumnaul
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In forensic science, corpses from various homicides are different; there are both complete and incomplete, depending on causes of death or forms of homicide. For example, some corpses are cut into pieces, some are camouflaged by dumping into the river, some are buried, some are burned to destroy the evidence, and others. If the corpses are incomplete, it can lead to the difficulty of personally identifying because some tissues and bones are destroyed. To specify gender of the corpses from skeletal remains, the most precise method is DNA identification. However, this method is costly and takes longer so that other identification techniques are used instead. The first technique that is widely used is considering the features of bones. In general, an evidence from the corpses such as some pieces of bones, especially the skull and pelvis can be used to identify their gender. To use this technique, forensic scientists are required observation skills in order to classify the difference between male and female bones. Although this technique is uncomplicated, saving time and cost, and the forensic scientists can fairly accurately determine gender by using this technique (apparently an accuracy rate of 90% or more), the crucial disadvantage is there are only some positions of skeleton that can be used to specify gender such as supraorbital ridge, nuchal crest, temporal lobe, mandible, and chin. Therefore, the skeletal remains that will be used have to be complete. The other technique that is widely used for gender specifying in forensic science and archeology is skeletal measurements. The advantage of this method is it can be used in several positions in one piece of bones, and it can be used even if the bones are not complete. In this study, the classification and cluster analysis are applied to this technique, including the Kth Nearest Neighbor Classification, Classification Tree, Ward Linkage Cluster, K-mean Cluster, and Two Step Cluster. The data contains 507 particular individuals and 9 skeletal measurements (diameter measurements), and the performance of five methods are investigated by considering the apparent error rate (APER). The results from this study indicate that the Two Step Cluster and Kth Nearest Neighbor method seem to be suitable to specify gender from human skeletal remains because both yield small apparent error rate of 0.20% and 4.14%, respectively. On the other hand, the Classification Tree, Ward Linkage Cluster, and K-mean Cluster method are not appropriate since they yield large apparent error rate of 10.65%, 10.65%, and 16.37%, respectively. However, there are other ways to evaluate the performance of classification such as an estimate of the error rate using the holdout procedure or misclassification costs, and the difference methods can make the different conclusions.Keywords: skeletal measurements, classification, cluster, apparent error rate
Procedia PDF Downloads 2527492 Intuitive Decision Making When Facing Risks
Authors: Katharina Fellnhofer
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The more information and knowledge that technology provides, the more important are profoundly human skills like intuition, the skill of using nonconscious information. As our world becomes more complex, shaken by crises, and characterized by uncertainty, time pressure, ambiguity, and rapidly changing conditions, intuition is increasingly recognized as a key human asset. However, due to methodological limitations of sample size or time frame or a lack of real-world or cross-cultural scope, precisely how to measure intuition when facing risks on a nonconscious level remains unclear. In light of the measurement challenge related to intuition’s nonconscious nature, a technique is introduced to measure intuition via hidden images as nonconscious additional information to trigger intuition. This technique has been tested in a within-subject fully online design with 62,721 real-world investment decisions made by 657 subjects in Europe and the United States. Bayesian models highlight the technique’s potential to measure skill at using nonconscious information for conscious decision making. Over the long term, solving the mysteries of intuition and mastering its use could be of immense value in personal and organizational decision-making contexts.Keywords: cognition, intuition, investment decisions, methodology
Procedia PDF Downloads 867491 Design and Performance Improvement of Three-Dimensional Optical Code Division Multiple Access Networks with NAND Detection Technique
Authors: Satyasen Panda, Urmila Bhanja
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In this paper, we have presented and analyzed three-dimensional (3-D) matrices of wavelength/time/space code for optical code division multiple access (OCDMA) networks with NAND subtraction detection technique. The 3-D codes are constructed by integrating a two-dimensional modified quadratic congruence (MQC) code with one-dimensional modified prime (MP) code. The respective encoders and decoders were designed using fiber Bragg gratings and optical delay lines to minimize the bit error rate (BER). The performance analysis of the 3D-OCDMA system is based on measurement of signal to noise ratio (SNR), BER and eye diagram for a different number of simultaneous users. Also, in the analysis, various types of noises and multiple access interference (MAI) effects were considered. The results obtained with NAND detection technique were compared with those obtained with OR and AND subtraction techniques. The comparison results proved that the NAND detection technique with 3-D MQC\MP code can accommodate more number of simultaneous users for longer distances of fiber with minimum BER as compared to OR and AND subtraction techniques. The received optical power is also measured at various levels of BER to analyze the effect of attenuation.Keywords: Cross Correlation (CC), Three dimensional Optical Code Division Multiple Access (3-D OCDMA), Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA), Multiple Access Interference (MAI), Phase Induced Intensity Noise (PIIN), Three Dimensional Modified Quadratic Congruence/Modified Prime (3-D MQC/MP) code
Procedia PDF Downloads 4127490 A Miniaturized Circular Patch Antenna Based on Metamaterial for WI-FI Applications
Authors: Fatima Zahra Moussa, Yamina Belhadef, Souheyla Ferouani
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In this work, we present a new form of miniature circular patch antenna based on CSRR metamaterials with an extended bandwidth proposed for 5 GHz Wi-Fiapplications. A reflection coefficient of -35 dB and a radiation pattern of 7.47 dB are obtained when simulating the initial proposed antenna with the CST microwave studio simulation software. The notch insertion technique in the radiating element was used for matching the antenna to the desired frequency in the frequency band [5150-5875] MHz.An extension of the bandwidth from 332 MHz to 1423 MHz was done by the DGS (defected ground structure) technique to meet the user's requirement in the 5 GHz Wi-Fi frequency band.Keywords: patch antenna, miniaturisation, CSRR, notches, wifi, DGS
Procedia PDF Downloads 1227489 Electrocardiogram Signal Denoising Using a Hybrid Technique
Authors: R. Latif, W. Jenkal, A. Toumanari, A. Hatim
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This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid approach. Two techniques are brought together to create an efficient denoising process. The first is an Adaptive Dual Threshold Filter (ADTF) and the second is the Discrete Wavelet Transform (DWT). The presented approach is based on three steps of denoising, the DWT decomposition, the ADTF step and the highest peaks correction step. This paper presents some application of the approach on some electrocardiogram signals of the MIT-BIH database. The results of these applications are promising compared to other recently published techniques.Keywords: hybrid technique, ADTF, DWT, thresholding, ECG signal
Procedia PDF Downloads 3227488 Novel Framework for MIMO-Enhanced Robust Selection of Critical Control Factors in Auto Plastic Injection Moulding Quality Optimization
Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari
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Apparent quality defects such as warpage, shrinkage, weld line, etc. are such an irresistible phenomenon in mass production of auto plastic appearance parts. These frequently occurred manufacturing defects should be satisfied concurrently so as to achieve a final product with acceptable quality standards. Determining the significant control factors that simultaneously affect multiple quality characteristics can significantly improve the optimization results by eliminating the deviating effect of the so-called ineffective outliers. Hence, a robust quantitative approach needs to be developed upon which major control factors and their level can be effectively determined to help improve the reliability of the optimal processing parameter design. Hence, the primary objective of current study was to develop a systematic methodology for selection of significant control factors (SCF) relevant to multiple quality optimization of auto plastic appearance part. Auto bumper was used as a specimen with the most identical quality and production characteristics to APAP group. A preliminary failure modes and effect analysis (FMEA) was conducted to nominate a database of pseudo significant significant control factors prior to the optimization phase. Later, CAE simulation Moldflow analysis was implemented to manipulate four rampant plastic injection quality defects concerned with APAP group including warpage deflection, volumetric shrinkage, sink mark and weld line. Furthermore, a step-backward elimination searching method (SESME) has been developed for systematic pre-optimization selection of SCF based on hierarchical orthogonal array design and priority-based one-way analysis of variance (ANOVA). The development of robust parameter design in the second phase was based on DOE module powered by Minitab v.16 statistical software. Based on the F-test (F 0.05, 2, 14) one-way ANOVA results, it was concluded that for warpage deflection, material mixture percentage was the most significant control factor yielding a 58.34% of contribution while for the other three quality defects, melt temperature was the most significant control factor with a 25.32%, 84.25%, and 34.57% contribution for sin mark, shrinkage and weld line strength control. Also, the results on the he least significant control factors meaningfully revealed injection fill time as the least significant factor for both warpage and sink mark with respective 1.69% and 6.12% contribution. On the other hand, for shrinkage and weld line defects, the least significant control factors were holding pressure and mold temperature with a 0.23% and 4.05% overall contribution accordingly.Keywords: plastic injection moulding, quality optimization, FMEA, ANOVA, SESME, APAP
Procedia PDF Downloads 3497487 Enhancing Protein Incorporation in Calcium Phosphate Coating on Titanium by Rapid Biomimetic Co-Precipitation Technique
Authors: J. Suwanprateeb, F. Thammarakcharoen
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Calcium phosphate coating (CaP) has been employed for protein delivery, but the typical direct protein adsorption on the coating led to low incorporation content and fast release of the protein from the coating. By using bovine serum albumin (BSA) as a model protein, rapid biomimetic co-precipitation between calcium phosphate and BSA was employed to control the distribution of BSA within calcium phosphate coating during biomimetic formation on titanium surface for only 6 h at 50 oC in an accelerated calcium phosphate solution. As a result, the amount of BSA incorporation and release duration could be increased by using a rapid biomimetic co-precipitation technique. Up to 43 fold increases in the BSA incorporation content and the increase from 6 h to more than 360 h in release duration compared to typical direct adsorption technique were observed depending on the initial BSA concentration used during co-precipitation (1, 10, and 100 microgram/ml). From X-ray diffraction and Fourier transform infrared spectroscopy studies, the coating composition was not altered with the incorporation of BSA by this rapid biomimetic co-precipitation and mainly comprised octacalcium phosphate and hydroxyapatite. However, the microstructure of calcium phosphate crystals changed from straight, plate-like units to curved, plate-like units with increasing BSA content.Keywords: biomimetic, Calcium Phosphate Coating, protein, titanium
Procedia PDF Downloads 3857486 Optimization of Cloud Classification Using Particle Swarm Algorithm
Authors: Riffi Mohammed Amine
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A cloud is made up of small particles of liquid water or ice suspended in the atmosphere, which generally do not reach the ground. Various methods are used to classify clouds. This article focuses specifically on a technique known as particle swarm optimization (PSO), an AI approach inspired by the collective behaviors of animals living in groups, such as schools of fish and flocks of birds, and a method used to solve complex classification and optimization problems with approximate solutions. The proposed technique was evaluated using a series of second-generation METOSAT images taken by the MSG satellite. The acquired results indicate that the proposed method gave acceptable results.Keywords: remote sensing, particle swarm optimization, clouds, meteorological image
Procedia PDF Downloads 187485 Numerical Buckling of Composite Cylindrical Shells under Axial Compression Using Asymmetric Meshing Technique (AMT)
Authors: Zia R. Tahir, P. Mandal
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This paper presents the details of a numerical study of buckling and post buckling behaviour of laminated carbon fiber reinforced plastic (CFRP) thin-walled cylindrical shell under axial compression using asymmetric meshing technique (AMT) by ABAQUS. AMT is considered to be a new perturbation method to introduce disturbance without changing geometry, boundary conditions or loading conditions. Asymmetric meshing affects both predicted buckling load and buckling mode shapes. Cylindrical shell having lay-up orientation [0°/+45°/-45°/0°] with radius to thickness ratio (R/t) equal to 265 and length to radius ratio (L/R) equal to 1.5 is analysed numerically. A series of numerical simulations (experiments) are carried out with symmetric and asymmetric meshing to study the effect of asymmetric meshing on predicted buckling behaviour. Asymmetric meshing technique is employed in both axial direction and circumferential direction separately using two different methods, first by changing the shell element size and varying the total number elements, and second by varying the shell element size and keeping total number of elements constant. The results of linear analysis (Eigenvalue analysis) and non-linear analysis (Riks analysis) using symmetric meshing agree well with analytical results. The results of numerical analysis are presented in form of non-dimensional load factor, which is the ratio of buckling load using asymmetric meshing technique to buckling load using symmetric meshing technique. Using AMT, load factor has about 2% variation for linear eigenvalue analysis and about 2% variation for non-linear Riks analysis. The behaviour of load end-shortening curve for pre-buckling is same for both symmetric and asymmetric meshing but for asymmetric meshing curve behaviour in post-buckling becomes extraordinarily complex. The major conclusions are: different methods of AMT have small influence on predicted buckling load and significant influence on load displacement curve behaviour in post buckling; AMT in axial direction and AMT in circumferential direction have different influence on buckling load and load displacement curve in post-buckling.Keywords: CFRP composite cylindrical shell, asymmetric meshing technique, primary buckling, secondary buckling, linear eigenvalue analysis, non-linear riks analysis
Procedia PDF Downloads 3537484 Coating of Polyelectrolyte Multilayer Thin Films on Poly(S/EGDMA) HIPE Loaded with Hydroxyapatite as a Scaffold for Tissue Engineering Application
Authors: Kornkanok Noulta, Pornsri Pakeyangkoon, Stephen T. Dubas, Pomthong Malakul, Manit Nithithanakul
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In recent years, interest in the development of material for tissue engineering application has increased considerably. Poly(High Internal Phase Emulsion) (PolyHIPE) foam is a material that is good candidate for used in tissue engineering application due to its 3D structure and highly porous with interconnected pore. The PolyHIPE was prepared from poly (styrene/ethylene glycol dimethacrylate) through high internal phase emulsion polymerization technique and loaded with hydroxyapatite (HA) to improve biocompatibility. To further increase hydrophilicity of the obtained polyHIPE, layer-by-layer polyelectrolyte multilayers (PEM) technique was used. A surface property of polyHIPE was characterized by contact angle measurement. Morphology and pore size was observed by scanning electron microscope (SEM). The cell viability was revealed by the 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay technique.Keywords: polyelectrolyte multilayer thin film, high internal phase emulsion, polyhipe foam, scaffold, tissue engineering
Procedia PDF Downloads 3527483 The Excess Loop Delay Calibration in a Bandpass Continuous-Time Delta Sigma Modulators Based on Q-Enhanced LC Filter
Authors: Sorore Benabid
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The Q-enhanced LC filters are the most used architecture in the Bandpass (BP) Continuous-Time (CT) Delta-Sigma (ΣΔ) modulators, due to their: high frequencies operation, high linearity than the active filters and a high quality factor obtained by Q-enhanced technique. This technique consists of the use of a negative resistance that compensate the ohmic losses in the on-chip inductor. However, this technique introduces a zero in the filter transfer function which will affect the modulator performances in term of Dynamic Range (DR), stability and in-band noise (Signal-to-Noise Ratio (SNR)). In this paper, we study the effect of this zero and we demonstrate that a calibration of the excess loop delay (ELD) is required to ensure the best performances of the modulator. System level simulations are done for a 2ndorder BP CT (ΣΔ) modulator at a center frequency of 300MHz. Simulation results indicate that the optimal ELD should be reduced by 13% to achieve the maximum SNR and DR compared to the ideal LC-based ΣΔ modulator.Keywords: continuous-time bandpass delta-sigma modulators, excess loop delay, on-chip inductor, Q-enhanced LC filter
Procedia PDF Downloads 3297482 Optimal Allocation of Distributed Generation Sources for Loss Reduction and Voltage Profile Improvement by Using Particle Swarm Optimization
Authors: Muhammad Zaheer Babar, Amer Kashif, Muhammad Rizwan Javed
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Nowadays distributed generation integration is best way to overcome the increasing load demand. Optimal allocation of distributed generation plays a vital role in reducing system losses and improves voltage profile. In this paper, a Meta heuristic technique is proposed for allocation of DG in order to reduce power losses and improve voltage profile. The proposed technique is based on Multi Objective Particle Swarm optimization. Fewer control parameters are needed in this algorithm. Modification is made in search space of PSO. The effectiveness of proposed technique is tested on IEEE 33 bus test system. Single DG as well as multiple DG scenario is adopted for proposed method. Proposed method is more effective as compared to other Meta heuristic techniques and gives better results regarding system losses and voltage profile.Keywords: Distributed generation (DG), Multi Objective Particle Swarm Optimization (MOPSO), particle swarm optimization (PSO), IEEE standard Test System
Procedia PDF Downloads 4557481 A Fermatean Fuzzy MAIRCA Approach for Maintenance Strategy Selection of Process Plant Gearbox Using Sustainability Criteria
Authors: Soumava Boral, Sanjay K. Chaturvedi, Ian Howard, Kristoffer McKee, V. N. A. Naikan
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Due to strict regulations from government to enhance the possibilities of sustainability practices in industries, and noting the advances in sustainable manufacturing practices, it is necessary that the associated processes are also sustainable. Maintenance of large scale and complex machines is a pivotal task to maintain the uninterrupted flow of manufacturing processes. Appropriate maintenance practices can prolong the lifetime of machines, and prevent associated breakdowns, which subsequently reduces different cost heads. Selection of the best maintenance strategies for such machines are considered as a burdensome task, as they require the consideration of multiple technical criteria, complex mathematical calculations, previous fault data, maintenance records, etc. In the era of the fourth industrial revolution, organizations are rapidly changing their way of business, and they are giving their utmost importance to sensor technologies, artificial intelligence, data analytics, automations, etc. In this work, the effectiveness of several maintenance strategies (e.g., preventive, failure-based, reliability centered, condition based, total productive maintenance, etc.) related to a large scale and complex gearbox, operating in a steel processing plant is evaluated in terms of economic, social, environmental and technical criteria. As it is not possible to obtain/describe some criteria by exact numerical values, these criteria are evaluated linguistically by cross-functional experts. Fuzzy sets are potential soft-computing technique, which has been useful to deal with linguistic data and to provide inferences in many complex situations. To prioritize different maintenance practices based on the identified sustainable criteria, multi-criteria decision making (MCDM) approaches can be considered as potential tools. Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) is a recent addition in the MCDM family and has proven its superiority over some well-known MCDM approaches, like TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and ELECTRE (ELimination Et Choix Traduisant la REalité). It has a simple but robust mathematical approach, which is easy to comprehend. On the other side, due to some inherent drawbacks of Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS), recently, the use of Fermatean Fuzzy Sets (FFSs) has been proposed. In this work, we propose the novel concept of FF-MAIRCA. We obtain the weights of the criteria by experts’ evaluation and use them to prioritize the different maintenance practices according to their suitability by FF-MAIRCA approach. Finally, a sensitivity analysis is carried out to highlight the robustness of the approach.Keywords: Fermatean fuzzy sets, Fermatean fuzzy MAIRCA, maintenance strategy selection, sustainable manufacturing, MCDM
Procedia PDF Downloads 1387480 Research on Carbon Fiber Tow Spreading Technique with Multi-Rolls
Authors: Soon Ok Jo, Han Kyu Jeung, Si Woo Park
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With the process of consistent expansion of carbon fiber in width (Carbon Fiber Tow Spreading Technique), it can be expected that such process can enhance the production of carbon fiber reinforced composite material and quality of the product. In this research, the method of mechanically expanding carbon fiber and increasing its width was investigated by using various geometric rolls. In addition, experimental type of carbon fiber expansion device was developed and tested using 12K carbon fiber. As a result, the effects of expansion of such fiber under optimized operating conditions and geometric structure of an elliptical roll, were analyzed.Keywords: carbon fiber, tow spreading fiber, pre-preg, roll structure
Procedia PDF Downloads 3497479 Factors Influencing the Decision of International Tourists to Revisit Bangkok,Thailand
Authors: Taksina Bunbut, Kevin Wongleedee
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The purposes of this research were to study factors influencing the decision of international tourists to revisit Bangkok, Thailand. A random 200 samples was collected. Half the sample group was male and the other half was female. A questionnaire was used to collect data and small in-depth interviews were also used to get their opinions about importance of tourist decision making factors. The findings revealed that the majority of respondents rated these factors at medium level of importance. The ranking showed that the first three important factors were a safe place to stay, friendly people, and clean food. The three least important factors were a convenience transportation, clean country, and child friendly. In addition there was no significance difference between male and female in their ratings of the factors of influencing the decision of international tourists to revisit Bangkok, Thailand.Keywords: factors, international tourists, revisit, Thailand
Procedia PDF Downloads 3277478 Regulating Green Roofs: A Review of the Relation between Current International Regulations and Economic, Environmental and Social Effects
Authors: Marianna Nigra, Maicol Negrello
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Efficiency, productivity, and sustainability are important factors for structure and the application of processes in green building. Various previous studies have addressed efficiency, productivity, and sustainability separately. This research study aims to investigate the implications of these three factors taking together. Frequency analysis and the ranking techniques are carried out to explore the connection between these factors. The interconnection matrix has been developed and functional grouping is made based upon data from expert opinion and field professionals. The existence of a relationship, the type of relationship and the scaled impact have been drawn. Additionally, a system diagram has been developed to show the variable correlation. The results of expert opinion show that efficiency, productivity, and sustainability have a stronger impact on green buildings.Keywords: green roof regulation, architecture, climate adaptation, resilience, innovation management
Procedia PDF Downloads 1047477 A Novel Method for Face Detection
Authors: H. Abas Nejad, A. R. Teymoori
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Facial expression recognition is one of the open problems in computer vision. Robust neutral face recognition in real time is a major challenge for various supervised learning based facial expression recognition methods. This is due to the fact that supervised methods cannot accommodate all appearance variability across the faces with respect to race, pose, lighting, facial biases, etc. in the limited amount of training data. Moreover, processing each and every frame to classify emotions is not required, as the user stays neutral for the majority of the time in usual applications like video chat or photo album/web browsing. Detecting neutral state at an early stage, thereby bypassing those frames from emotion classification would save the computational power. In this work, we propose a light-weight neutral vs. emotion classification engine, which acts as a preprocessor to the traditional supervised emotion classification approaches. It dynamically learns neutral appearance at Key Emotion (KE) points using a textural statistical model, constructed by a set of reference neutral frames for each user. The proposed method is made robust to various types of user head motions by accounting for affine distortions based on a textural statistical model. Robustness to dynamic shift of KE points is achieved by evaluating the similarities on a subset of neighborhood patches around each KE point using the prior information regarding the directionality of specific facial action units acting on the respective KE point. The proposed method, as a result, improves ER accuracy and simultaneously reduces the computational complexity of ER system, as validated on multiple databases.Keywords: neutral vs. emotion classification, Constrained Local Model, procrustes analysis, Local Binary Pattern Histogram, statistical model
Procedia PDF Downloads 3397476 Numerical Study of Fatigue Crack Growth at a Web Stiffener of Ship Structural Details
Authors: Wentao He, Jingxi Liu, De Xie
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It is necessary to manage the fatigue crack growth (FCG) once those cracks are detected during in-service inspections. In this paper, a simulation program (FCG-System) is developed utilizing the commercial software ABAQUS with its object-oriented programming interface to simulate the fatigue crack path and to compute the corresponding fatigue life. In order to apply FCG-System in large-scale marine structures, the substructure modeling technique is integrated in the system under the consideration of structural details and load shedding during crack growth. Based on the nodal forces and nodal displacements obtained from finite element analysis, a formula for shell elements to compute stress intensity factors is proposed in the view of virtual crack closure technique. The cracks initiating from the intersection of flange and the end of the web-stiffener are investigated for fatigue crack paths and growth lives under water pressure loading and axial force loading, separately. It is found that the FCG-System developed by authors could be an efficient tool to perform fatigue crack growth analysis on marine structures.Keywords: crack path, fatigue crack, fatigue live, FCG-system, virtual crack closure technique
Procedia PDF Downloads 5687475 Efficient Modeling Technique for Microstrip Discontinuities
Authors: Nassim Ourabia, Malika Ourabia
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A new and efficient method is presented for the analysis of arbitrarily shaped discontinuities. The technique obtains closed form expressions for the equivalent circuits which are used to model these discontinuities. Then it would be easy to handle and to characterize complicated structures like T and Y junctions, truncated junctions, arbitrarily shaped junctions, cascading junctions, and more generally planar multiport junctions. Another advantage of this method is that the edge line concept for arbitrary shape junctions operates with real parameters circuits. The validity of the method was further confirmed by comparing our results for various discontinuities (bend, filters) with those from HFSS as well as from other published sources.Keywords: CAD analysis, contour integral approach, microwave circuits, s-parameters
Procedia PDF Downloads 5167474 A Data Mining Approach for Analysing and Predicting the Bank's Asset Liability Management Based on Basel III Norms
Authors: Nidhin Dani Abraham, T. K. Sri Shilpa
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Asset liability management is an important aspect in banking business. Moreover, the today’s banking is based on BASEL III which strictly regulates on the counterparty default. This paper focuses on prediction and analysis of counter party default risk, which is a type of risk occurs when the customers fail to repay the amount back to the lender (bank or any financial institutions). This paper proposes an approach to reduce the counterparty risk occurring in the financial institutions using an appropriate data mining technique and thus predicts the occurrence of NPA. It also helps in asset building and restructuring quality. Liability management is very important to carry out banking business. To know and analyze the depth of liability of bank, a suitable technique is required. For that a data mining technique is being used to predict the dormant behaviour of various deposit bank customers. Various models are implemented and the results are analyzed of saving bank deposit customers. All these data are cleaned using data cleansing approach from the bank data warehouse.Keywords: data mining, asset liability management, BASEL III, banking
Procedia PDF Downloads 5537473 Factors Contributing to Building Construction Project’s Cost Overrun in Jordan
Authors: Ghaleb Y. Abbasi, Sufyan Al-Mrayat
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This study examined the contribution of thirty-six factors to building construction project’s cost overrun in Jordan. A questionnaire was distributed to a random sample of 350 stakeholders comprised of owners, consultants, and contractors, of which 285 responded. SPSS analysis was conducted to identify the top five causes of cost overrun, which were a large number of variation orders, inadequate quantities provided in the contract, misunderstanding of the project plan, incomplete bid documents, and choosing the lowest price in the contract bidding. There was an agreement among the study participants in ranking the factors contributing to cost overrun, which indicated that these factors were very commonly encountered in most construction projects in Jordan. Thus, it is crucial to enhance the collaboration among the different project stakeholders to understand the project’s objectives and set a realistic plan that takes into consideration all the factors that might influence the project cost, which might eventually prevent cost overrun.Keywords: cost, overrun, building construction projects, Jordan
Procedia PDF Downloads 1087472 Analysis of Real Time Seismic Signal Dataset Using Machine Learning
Authors: Sujata Kulkarni, Udhav Bhosle, Vijaykumar T.
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Due to the closeness between seismic signals and non-seismic signals, it is vital to detect earthquakes using conventional methods. In order to distinguish between seismic events and non-seismic events depending on their amplitude, our study processes the data that come from seismic sensors. The authors suggest a robust noise suppression technique that makes use of a bandpass filter, an IIR Wiener filter, recursive short-term average/long-term average (STA/LTA), and Carl short-term average (STA)/long-term average for event identification (LTA). The trigger ratio used in the proposed study to differentiate between seismic and non-seismic activity is determined. The proposed work focuses on significant feature extraction for machine learning-based seismic event detection. This serves as motivation for compiling a dataset of all features for the identification and forecasting of seismic signals. We place a focus on feature vector dimension reduction techniques due to the temporal complexity. The proposed notable features were experimentally tested using a machine learning model, and the results on unseen data are optimal. Finally, a presentation using a hybrid dataset (captured by different sensors) demonstrates how this model may also be employed in a real-time setting while lowering false alarm rates. The planned study is based on the examination of seismic signals obtained from both individual sensors and sensor networks (SN). A wideband seismic signal from BSVK and CUKG station sensors, respectively located near Basavakalyan, Karnataka, and the Central University of Karnataka, makes up the experimental dataset.Keywords: Carl STA/LTA, features extraction, real time, dataset, machine learning, seismic detection
Procedia PDF Downloads 1247471 Imputation Technique for Feature Selection in Microarray Data Set
Authors: Younies Saeed Hassan Mahmoud, Mai Mabrouk, Elsayed Sallam
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Analysing DNA microarray data sets is a great challenge, which faces the bioinformaticians due to the complication of using statistical and machine learning techniques. The challenge will be doubled if the microarray data sets contain missing data, which happens regularly because these techniques cannot deal with missing data. One of the most important data analysis process on the microarray data set is feature selection. This process finds the most important genes that affect certain disease. In this paper, we introduce a technique for imputing the missing data in microarray data sets while performing feature selection.Keywords: DNA microarray, feature selection, missing data, bioinformatics
Procedia PDF Downloads 574