Search results for: data mining technique
28562 Design of Multi-Loop Controller for Minimization of Energy Consumption in the Distillation Column
Authors: Vinayambika S. Bhat, S. Shanmuga Priya, I. Thirunavukkarasu, Shreeranga Bhat
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An attempt has been made to design a decoupling controller for systems with more inputs more outputs with dead time in it. The de-coupler is designed for the chemical process industry 3×3 plant transfer function with dead time. The Quantitative Feedback Theory (QFT) based controller has also been designed here for the 2×2 distillation column transfer function. The developed control techniques were simulated using the MATLAB/Simulink. Also, the stability of the process was analyzed, together with the presence of various perturbations in it. Time domain specifications like setting time along with overshoot and oscillations were analyzed to prove the efficiency of the de-coupler method. The load disturbance rejection was tested along with its performance. The QFT control technique was synthesized based on the stability and performance specifications in the presence of uncertainty in time constant of the plant transfer function through sequential loop shaping technique. Further, the energy efficiency of the distillation column was improved by proper tuning of the controller. A distillation column consumes 3% of the total energy consumption of the world. A suitable control technique is very important from an economic point of view. The real time implementation of the process is under process in our laboratory.Keywords: distillation, energy, MIMO process, time delay, robust stability
Procedia PDF Downloads 41528561 Introduction of the Fluid-Structure Coupling into the Force Analysis Technique
Authors: Océane Grosset, Charles Pézerat, Jean-Hugh Thomas, Frédéric Ablitzer
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This paper presents a method to take into account the fluid-structure coupling into an inverse method, the Force Analysis Technique (FAT). The FAT method, also called RIFF method (Filtered Windowed Inverse Resolution), allows to identify the force distribution from local vibration field. In order to only identify the external force applied on a structure, it is necessary to quantify the fluid-structure coupling, especially in naval application, where the fluid is heavy. This method can be decomposed in two parts, the first one consists in identifying the fluid-structure coupling and the second one to introduced it in the FAT method to reconstruct the external force. Results of simulations on a plate coupled with a cavity filled with water are presented.Keywords: aeroacoustics, fluid-structure coupling, inverse methods, naval, turbulent flow
Procedia PDF Downloads 52028560 Big Data and Analytics in Higher Education: An Assessment of Its Status, Relevance and Future in the Republic of the Philippines
Authors: Byron Joseph A. Hallar, Annjeannette Alain D. Galang, Maria Visitacion N. Gumabay
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One of the unique challenges provided by the twenty-first century to Philippine higher education is the utilization of Big Data. The higher education system in the Philippines is generating burgeoning amounts of data that contains relevant data that can be used to generate the information and knowledge needed for accurate data-driven decision making. This study examines the status, relevance and future of Big Data and Analytics in Philippine higher education. The insights gained from the study may be relevant to other developing nations similarly situated as the Philippines.Keywords: big data, data analytics, higher education, republic of the philippines, assessment
Procedia PDF Downloads 35028559 The application of Gel Dosimeters and Comparison with other Dosimeters in Radiotherapy: A Literature Review
Authors: Sujan Mahamud
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Purpose: A major challenge in radiotherapy treatment is to deliver precise dose of radiation to the tumor with minimum dose to the healthy normal tissues. Recently, gel dosimetry has emerged as a powerful tool to measure three-dimensional (3D) dose distribution for complex delivery verification and quality assurance. These dosimeters act both as a phantom and detector, thus confirming the versatility of dosimetry technique. The aim of the study is to know the application of Gel Dosimeters in Radiotherapy and find out the comparison with 1D and 2D dimensional dosimeters. Methods and Materials: The study is carried out from Gel Dosimeter literatures. Secondary data and images have been collected from different sources such as different guidelines, books, and internet, etc. Result: Analyzing, verifying, and comparing data from treatment planning system (TPS) is determined that gel dosimeter is a very excellent powerful tool to measure three-dimensional (3D) dose distribution. The TPS calculated data were in very good agreement with the dose distribution measured by the ferrous gel. The overall uncertainty in the ferrous-gel dose determination was considerably reduced using an optimized MRI acquisition protocol and a new MRI scanner. The method developed for comparing measuring gel data with calculated treatment plans, the gel dosimetry method, was proven to be a useful for radiation treatment planning verification. In 1D and 2D Film, the depth dose and lateral for RMSD are 1.8% and 2%, and max (Di-Dj) are 2.5% and 8%. Other side 2D+ ( 3D) Film Gel and Plan Gel for RMSDstruct and RMSDstoch are 2.3% & 3.6% and 1% & 1% and system deviation are -0.6% and 2.5%. The study is investigated that the result fined 2D+ (3D) Film Dosimeter is better than the 1D and 2D Dosimeter. Discussion: Gel Dosimeters is quality control and quality assurance tool which will used the future clinical application.Keywords: gel dosimeters, phantom, rmsd, QC, detector
Procedia PDF Downloads 15228558 Speeding-up Gray-Scale FIC by Moments
Authors: Eman A. Al-Hilo, Hawraa H. Al-Waelly
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In this work, fractal compression (FIC) technique is introduced based on using moment features to block indexing the zero-mean range-domain blocks. The moment features have been used to speed up the IFS-matching stage. Its moments ratio descriptor is used to filter the domain blocks and keep only the blocks that are suitable to be IFS matched with tested range block. The results of tests conducted on Lena picture and Cat picture (256 pixels, resolution 24 bits/pixel) image showed a minimum encoding time (0.89 sec for Lena image and 0.78 of Cat image) with appropriate PSNR (30.01dB for Lena image and 29.8 of Cat image). The reduction in ET is about 12% for Lena and 67% for Cat image.Keywords: fractal gray level image, fractal compression technique, iterated function system, moments feature, zero-mean range-domain block
Procedia PDF Downloads 49728557 Novel Numerical Technique for Dusty Plasma Dynamics (Yukawa Liquids): Microfluidic and Role of Heat Transport
Authors: Aamir Shahzad, Mao-Gang He
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Currently, dusty plasmas motivated the researchers' widespread interest. Since the last two decades, substantial efforts have been made by the scientific and technological community to investigate the transport properties and their nonlinear behavior of three-dimensional and two-dimensional nonideal complex (dusty plasma) liquids (NICDPLs). Different calculations have been made to sustain and utilize strongly coupled NICDPLs because of their remarkable scientific and industrial applications. Understanding of the thermophysical properties of complex liquids under various conditions is of practical interest in the field of science and technology. The determination of thermal conductivity is also a demanding question for thermophysical researchers, due to some reasons; very few results are offered for this significant property. Lack of information of the thermal conductivity of dense and complex liquids at different parameters related to the industrial developments is a major barrier to quantitative knowledge of the heat flux flow from one medium to another medium or surface. The exact numerical investigation of transport properties of complex liquids is a fundamental research task in the field of thermophysics, as various transport data are closely related with the setup and confirmation of equations of state. A reliable knowledge of transport data is also important for an optimized design of processes and apparatus in various engineering and science fields (thermoelectric devices), and, in particular, the provision of precise data for the parameters of heat, mass, and momentum transport is required. One of the promising computational techniques, the homogenous nonequilibrium molecular dynamics (HNEMD) simulation, is over viewed with a special importance on the application to transport problems of complex liquids. This proposed work is particularly motivated by the FIRST TIME to modify the problem of heat conduction equations leads to polynomial velocity and temperature profiles algorithm for the investigation of transport properties with their nonlinear behaviors in the NICDPLs. The aim of proposed work is to implement a NEMDS algorithm (Poiseuille flow) and to delve the understanding of thermal conductivity behaviors in Yukawa liquids. The Yukawa system is equilibrated through the Gaussian thermostat in order to maintain the constant system temperature (canonical ensemble ≡ NVT)). The output steps will be developed between 3.0×105/ωp and 1.5×105/ωp simulation time steps for the computation of λ data. The HNEMD algorithm shows that the thermal conductivity is dependent on plasma parameters and the minimum value of lmin shifts toward higher G with an increase in k, as expected. New investigations give more reliable simulated data for the plasma conductivity than earlier known simulation data and generally the plasma λ0 by 2%-20%, depending on Γ and κ. It has been shown that the obtained results at normalized force field are in satisfactory agreement with various earlier simulation results. This algorithm shows that the new technique provides more accurate results with fast convergence and small size effects over a wide range of plasma states.Keywords: molecular dynamics simulation, thermal conductivity, nonideal complex plasma, Poiseuille flow
Procedia PDF Downloads 27428556 The Barriers in the Adoption of E-readiness and Affective E-Business of Developing Countries: From the Prospective of Pakistani Organizations
Authors: Asma Moomal, Maslin Masrom
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The literature has identified that the competition among the business firms has been intensified due to the change in operating environment such as; knowledge diffusion, amount of R&D investments, and the adoption of technological innovation. Correspondingly, the E-business has potential to add a higher value to business and consumers in developed countries than in developing countries. However, the technological innovation (such as e-readiness) also considered as the major influential element on the firms competitiveness and development, Yet most of the developing countries including Pakistan failed to reap the benefits offered by modern information and communication technologies adoption (e-readiness), e-business and other innovative technologies. Thus, this paper reviewed the relevant literature in order to examine the barriers to the adoption of e-readiness and e-business in the organizations of Pakistan. The data collection technique used in this study was done through the secondary data resources (i.e. the existing literature analysis). The result of the study reveals that the most of the organizations of Pakistan like other developing countries are lagging behind in terms of adoption of e-readiness and e-business as compared to the developed countries of the world.Keywords: e-readiness, e-business, potential, technological innovation
Procedia PDF Downloads 52328555 Basal Cell Carcinoma Excision Intraoperative Frozen Section for Tumor Clearance and Reconstructive Surgery: A Prospective Open Label Interventional Study
Authors: Moizza Tahir, Uzma Bashir, Aisha Akhtar, Zainab Ansari, Sameen Ansari, Muhammad Ali Tahir
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Cancer burden has globally increased. Among cutaneous cancers basal cell carcinoma constitute vast majority of skin cancer. There is need for appropriate diagnostic, therapeutic and prognostic significance evaluation for skin cancers Present study report intraoperative frozen section (FS) histopathological clearance for excision of BCC in a tertiary care center and find the frequency of involvement of surgical margin with reference to anatomical site, with size and surgical technique. It was prospective open label interventional study conducted at Dermatology department of tertiary care hospital Rawalpindi Pakistan in lais on with histopathology department from January 2023 to April 2024. Total of thirty-six (n = 36) patients between age 45-80 years with basal cell carcinoma of 10-20mm on face were included following inclusion exclusion criteria by purposive sampling technique. Informed consent was taken. Surgical excision was performed and intraoperative frozen section histopathology clearance of tumor margin was taken from histopathologist on telephone. Surgical reconstruction was done. Final Histopathology report was reexamined on day 10th for margin and depth clearance. Descriptive statistics were calculated for age, gender, sun exposure, reconstructive technique, anatomical site, and tumor free margin report on frozen section analysis. Chi square test was employed for statistical significance of involvement of surgical margin with reference to anatomical site, size and decision on reconstructive surgical technique, p value of <0.05 was considered significant. Total of 36 patients of BCC were enrolled, males 12 (33.3%) and females were 24 (66.6%). Age ranged from 45 year to 80 year mean of 58.36 ±SD7.8. Size of BCC ranged from 10mm to 35mm mean of 25mm ±SD 0.63. Morphology was nodular 18 (50%), superficial spreading 11(30.6%), morphoeic 1 (2.8%) and ulcerative in 6(16.7%) cases. Intraoperative frozen section for histopathological margin clearance with 2-3 mm safety margin and surgical technique has p-value0.51, for anatomical site p value 0.24 and size p-0.84. Intraoperative frozen section (FS) histopathological clearance for BCC face with 2-3mm safety margin with reference to reconstructive technique, anatomical site and size of BCC were insignificant.Keywords: basal cell carcinoma, tumor free amrgin, basal cell carcinoma and frozen section, safety margin
Procedia PDF Downloads 5728554 Study of Natural Patterns on Digital Image Correlation Using Simulation Method
Authors: Gang Li, Ghulam Mubashar Hassan, Arcady Dyskin, Cara MacNish
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Digital image correlation (DIC) is a contactless full-field displacement and strain reconstruction technique commonly used in the field of experimental mechanics. Comparing with physical measuring devices, such as strain gauges, which only provide very restricted coverage and are expensive to deploy widely, the DIC technique provides the result with full-field coverage and relative high accuracy using an inexpensive and simple experimental setup. It is very important to study the natural patterns effect on the DIC technique because the preparation of the artificial patterns is time consuming and hectic process. The objective of this research is to study the effect of using images having natural pattern on the performance of DIC. A systematical simulation method is used to build simulated deformed images used in DIC. A parameter (subset size) used in DIC can have an effect on the processing and accuracy of DIC and even cause DIC to failure. Regarding to the picture parameters (correlation coefficient), the higher similarity of two subset can lead the DIC process to fail and make the result more inaccurate. The pictures with good and bad quality for DIC methods have been presented and more importantly, it is a systematic way to evaluate the quality of the picture with natural patterns before they install the measurement devices.Keywords: Digital Image Correlation (DIC), deformation simulation, natural pattern, subset size
Procedia PDF Downloads 42128553 Development and Validation of First Derivative Method and Artificial Neural Network for Simultaneous Spectrophotometric Determination of Two Closely Related Antioxidant Nutraceuticals in Their Binary Mixture”
Authors: Mohamed Korany, Azza Gazy, Essam Khamis, Marwa Adel, Miranda Fawzy
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Background: Two new, simple and specific methods; First, a Zero-crossing first-derivative technique and second, a chemometric-assisted spectrophotometric artificial neural network (ANN) were developed and validated in accordance with ICH guidelines. Both methods were used for the simultaneous estimation of the two closely related antioxidant nutraceuticals ; Coenzyme Q10 (Q) ; also known as Ubidecarenone or Ubiquinone-10, and Vitamin E (E); alpha-tocopherol acetate, in their pharmaceutical binary mixture. Results: For first method: By applying the first derivative, both Q and E were alternatively determined; each at the zero-crossing of the other. The D1 amplitudes of Q and E, at 285 nm and 235 nm respectively, were recorded and correlated to their concentrations. The calibration curve is linear over the concentration range of 10-60 and 5.6-70 μg mL-1 for Q and E, respectively. For second method: ANN (as a multivariate calibration method) was developed and applied for the simultaneous determination of both analytes. A training set (or a concentration set) of 90 different synthetic mixtures containing Q and E, in wide concentration ranges between 0-100 µg/mL and 0-556 µg/mL respectively, were prepared in ethanol. The absorption spectra of the training sets were recorded in the spectral region of 230–300 nm. A Gradient Descend Back Propagation ANN chemometric calibration was computed by relating the concentration sets (x-block) to their corresponding absorption data (y-block). Another set of 45 synthetic mixtures of the two drugs, in defined range, was used to validate the proposed network. Neither chemical separation, preparation stage nor mathematical graphical treatment were required. Conclusions: The proposed methods were successfully applied for the assay of Q and E in laboratory prepared mixtures and combined pharmaceutical tablet with excellent recoveries. The ANN method was superior over the derivative technique as the former determined both drugs in the non-linear experimental conditions. It also offers rapidity, high accuracy, effort and money saving. Moreover, no need for an analyst for its application. Although the ANN technique needed a large training set, it is the method of choice in the routine analysis of Q and E tablet. No interference was observed from common pharmaceutical additives. The results of the two methods were compared togetherKeywords: coenzyme Q10, vitamin E, chemometry, quantitative analysis, first derivative spectrophotometry, artificial neural network
Procedia PDF Downloads 44728552 Data Management and Analytics for Intelligent Grid
Authors: G. Julius P. Roy, Prateek Saxena, Sanjeev Singh
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Power distribution utilities two decades ago would collect data from its customers not later than a period of at least one month. The origin of SmartGrid and AMI has subsequently increased the sampling frequency leading to 1000 to 10000 fold increase in data quantity. This increase is notable and this steered to coin the tern Big Data in utilities. Power distribution industry is one of the largest to handle huge and complex data for keeping history and also to turn the data in to significance. Majority of the utilities around the globe are adopting SmartGrid technologies as a mass implementation and are primarily focusing on strategic interdependence and synergies of the big data coming from new information sources like AMI and intelligent SCADA, there is a rising need for new models of data management and resurrected focus on analytics to dissect data into descriptive, predictive and dictatorial subsets. The goal of this paper is to is to bring load disaggregation into smart energy toolkit for commercial usage.Keywords: data management, analytics, energy data analytics, smart grid, smart utilities
Procedia PDF Downloads 78128551 Identification of Flooding Attack (Zero Day Attack) at Application Layer Using Mathematical Model and Detection Using Correlations
Authors: Hamsini Pulugurtha, V.S. Lakshmi Jagadmaba Paluri
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Distributed denial of service attack (DDoS) is one altogether the top-rated cyber threats presently. It runs down the victim server resources like a system of measurement and buffer size by obstructing the server to supply resources to legitimate shoppers. Throughout this text, we tend to tend to propose a mathematical model of DDoS attack; we discuss its relevancy to the choices like inter-arrival time or rate of arrival of the assault customers accessing the server. We tend to tend to further analyze the attack model in context to the exhausting system of measurement and buffer size of the victim server. The projected technique uses an associate in nursing unattended learning technique, self-organizing map, to make the clusters of identical choices. Lastly, the abstract applies mathematical correlation and so the standard likelihood distribution on the clusters and analyses their behaviors to look at a DDoS attack. These systems not exclusively interconnect very little devices exchanging personal data, but to boot essential infrastructures news standing of nuclear facilities. Although this interconnection brings many edges and blessings, it to boot creates new vulnerabilities and threats which might be conversant in mount attacks. In such sophisticated interconnected systems, the power to look at attacks as early as accomplishable is of paramount importance.Keywords: application attack, bandwidth, buffer correlation, DDoS distribution flooding intrusion layer, normal prevention probability size
Procedia PDF Downloads 22628550 Intrusion Detection Based on Graph Oriented Big Data Analytics
Authors: Ahlem Abid, Farah Jemili
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Intrusion detection has been the subject of numerous studies in industry and academia, but cyber security analysts always want greater precision and global threat analysis to secure their systems in cyberspace. To improve intrusion detection system, the visualisation of the security events in form of graphs and diagrams is important to improve the accuracy of alerts. In this paper, we propose an approach of an IDS based on cloud computing, big data technique and using a machine learning graph algorithm which can detect in real time different attacks as early as possible. We use the MAWILab intrusion detection dataset . We choose Microsoft Azure as a unified cloud environment to load our dataset on. We implement the k2 algorithm which is a graphical machine learning algorithm to classify attacks. Our system showed a good performance due to the graphical machine learning algorithm and spark structured streaming engine.Keywords: Apache Spark Streaming, Graph, Intrusion detection, k2 algorithm, Machine Learning, MAWILab, Microsoft Azure Cloud
Procedia PDF Downloads 14928549 Career Development for Benjarong Porcelain Handicraft Communities in Central Thailand
Authors: Chutikarn Sriwiboon, Suwaree Yordchim
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Benjarong handicraft product is one of the most important handicraft products from Thailand. It involves the management of traditional wisdom of arts and Thai culture. This paper drew upon data collection from local communities by using an in-depth interview technique which was conducted in Thailand during summer of 2014. The survey was structured primarily to obtain local wisdom and concerns toward their career development. This research paper was a qualitative research conducted by focus groups with a total of 51 cooperative women and occupational groups around Thailand which produced the Benjarong products. The data were significantly collected from many sources and many communities, which totaled 24,430 handicraft products, in which the 668 different patterns of Benjarong products were produced by 51 local community network groups in Thailand. The findings revealed that after applying the Philosophy of Sufficiency Economy, there was a significantly positive change in their career development and the process of knowledge management enables local community to enhance their personal development and career.Keywords: Benjarong, career development, community, handicraft
Procedia PDF Downloads 38428548 Comparative Assessment of ISSR and RAPD Markers among Egyptian Jojoba Shrubs
Authors: Abdelsabour G. A. Khaled, Galal A.R. El-Sherbeny, Ahmed M. Hassanein, Gameel M. G. Aly
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Classical methods of identification, based on agronomical characterization, are not always the most accurate way due to the instability of these characteristics under the influence of the different environments. In order to estimate the genetic diversity, molecular markers provided excellent tools. In this study, Genetic variation of nine Egyptian jojoba shrubs was tested using ISSR (inter simple sequences repeats), RAPD (random amplified polymorphic DNA) markers and based on the morphological characterization. The average of the percentage of polymorphism (%P) ranged between 58.17% and 74.07% for ISSR and RAPD markers, respectively. The range of genetic similarity percents among shrubs based on ISSR and RAPD markers were from 82.9 to 97.9% and from 85.5 to 97.8%, respectively. The average of PIC (polymorphism information content) values were 0.19 (ISSR) and 0.24 (RAPD). In the present study, RAPD markers were more efficient than the ISSR markers. Where the RAPD technique exhibited higher marker index (MI) average (1.26) compared to ISSR one (1.11). There was an insignificant correlation between the ISSR and RAPD data (0.076, P > 0.05). The dendrogram constructed by the combined RAPD and ISSR data gave a relatively different clustering pattern.Keywords: correlation, molecular markers, polymorphism, marker index
Procedia PDF Downloads 48028547 Beating Heart Coronary Artery Bypass Grafting on Intermittent Pump Support
Authors: Sushil Kumar Singh, Vivek Tewarson, Sarvesh Kumar, Shobhit Kumar
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Objective: ‘Beating Heart coronary artery bypass grafting on Intermittent Pump Support’ is a more reliable method of coronary revascularization that takes advantage of off and on-pump CABG while eliminating the disadvantage of both techniques. Methods: From January 2015 to December 2021, a new technique, “Intermittent On pump beating heart CABG” using a suction stabilizer was used by putting aortic and venous cannulas electively in all the patients. Patients were supported by a pump intermittently, as and when required (Group 1, n=254). Retrospective data were collected from our record of the patients who underwent off-pump CABG electively by the same surgeon and team (Group 2, n=254). Results: Significant advantage was noted in Group 1 patients in terms of the number of grafts (3.31 ± 1.16 vs. 2.30 ±0.66), grafting of lateral vessels (316 vs.202), mean operating time (1.37 ± 0.23 hrs vs. 2.22 ± 0.45 hrs) and postoperative blood loss (406.30 ± 257.90 ml vs. 567.41 ± 265.20 ml).CPB support time was less than 15 minutes in the majority of patients (n=179, 70.37 %), with a mean of 16.81 minutes. It was required, particularly during the grafting of lateral vessels. A rise in enzymes level (CRP, CKMB, Trop I, and NTPro BNP) was noted in Group 1 patients. But, these did not affect the postoperative course in patients. There was no mortality in Group 1 patients, while four patients in Group 2 died. Coclusions: Intermittent on-pump CABG technique is a promising method of surgical revascularization for all patients requiring CABG. It has shown its superiority in terms of safety, the number of grafts, operating time, and better perioperative course.Keywords: cardiopulmonary bypass, CABG, beating heart CABG, on-pump CABG
Procedia PDF Downloads 12128546 The Clash between Environmental and Heritage Laws: An Australian Case Study
Authors: Andrew R. Beatty
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The exploitation of Australia’s vast mineral wealth is regulated by a matrix of planning, environment and heritage legislation, and despite the desire for a ‘balance’ between economic, environmental and heritage values, Aboriginal objects and places are often detrimentally impacted by mining approvals. The Australian experience is not novel. There are other cases of clashes between the rights of traditional landowners and businesses seeking to exploit mineral or other resources on or beneath those lands, including in the United States, Canada, and Brazil. How one reconciles the rights of traditional owners with those of resource companies is an ongoing legal problem of general interest. In Australia, planning and environmental approvals for resource projects are ordinarily issued by State or Territory governments. Federal legislation such as the Aboriginal and Torres Strait Islander Heritage Protection Act 1984 (Cth) is intended to act as a safety net when State or Territory legislation is incapable of protecting Indigenous objects or places in the context of approvals for resource projects. This paper will analyse the context and effectiveness of legislation enacted to protect Indigenous heritage in the planning process. In particular, the paper will analyse how the statutory objects of such legislation need to be weighed against the statutory objects of competing legislation designed to facilitate and control resource exploitation. Using a current claim in the Federal Court of Australia for the protection of a culturally significant landscape as a case study, this paper will examine the challenges faced in ascribing value to cultural heritage within the wider context of environmental and planning laws. Our findings will reveal that there is an inherent difficulty in defining and weighing competing economic, environmental and heritage considerations. An alternative framework will be proposed to guide regulators towards making decisions that result in better protection of Indigenous heritage in the context of resource management.Keywords: environmental law, heritage law, indigenous rights, mining
Procedia PDF Downloads 9628545 Vibration Measurements of Single-Lap Cantilevered SPR Beams
Authors: Xiaocong He
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Self-pierce riveting (SPR) is a new high-speed mechanical fastening technique which is suitable for point joining dissimilar sheet materials, as well as coated and pre-painted sheet materials. Mechanical structures assembled by SPR are expected to possess a high damping capacity. In this study, experimental measurement techniques were proposed for the prediction of vibration behavior of single-lap cantilevered SPR beams. The dynamic test software and the data acquisition hardware were used in the experimental measurement of the dynamic response of the single-lap cantilevered SPR beams. Free and forced vibration behavior of the single-lap cantilevered SPR beams was measured using the LMS CADA-X experimental modal analysis software and the LMS-DIFA Scadas II data acquisition hardware. The frequency response functions of the SPR beams of different rivet number were compared. The main goal of the paper is to provide a basic measuring method for further research on vibration based non-destructive damage detection in single-lap cantilevered SPR beams.Keywords: self-piercing riveting, dynamic response, experimental measurement, frequency response functions
Procedia PDF Downloads 42928544 Application of Groundwater Level Data Mining in Aquifer Identification
Authors: Liang Cheng Chang, Wei Ju Huang, You Cheng Chen
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Investigation and research are keys for conjunctive use of surface and groundwater resources. The hydrogeological structure is an important base for groundwater analysis and simulation. Traditionally, the hydrogeological structure is artificially determined based on geological drill logs, the structure of wells, groundwater levels, and so on. In Taiwan, groundwater observation network has been built and a large amount of groundwater-level observation data are available. The groundwater level is the state variable of the groundwater system, which reflects the system response combining hydrogeological structure, groundwater injection, and extraction. This study applies analytical tools to the observation database to develop a methodology for the identification of confined and unconfined aquifers. These tools include frequency analysis, cross-correlation analysis between rainfall and groundwater level, groundwater regression curve analysis, and decision tree. The developed methodology is then applied to groundwater layer identification of two groundwater systems: Zhuoshui River alluvial fan and Pingtung Plain. The abovementioned frequency analysis uses Fourier Transform processing time-series groundwater level observation data and analyzing daily frequency amplitude of groundwater level caused by artificial groundwater extraction. The cross-correlation analysis between rainfall and groundwater level is used to obtain the groundwater replenishment time between infiltration and the peak groundwater level during wet seasons. The groundwater regression curve, the average rate of groundwater regression, is used to analyze the internal flux in the groundwater system and the flux caused by artificial behaviors. The decision tree uses the information obtained from the above mentioned analytical tools and optimizes the best estimation of the hydrogeological structure. The developed method reaches training accuracy of 92.31% and verification accuracy 93.75% on Zhuoshui River alluvial fan and training accuracy 95.55%, and verification accuracy 100% on Pingtung Plain. This extraordinary accuracy indicates that the developed methodology is a great tool for identifying hydrogeological structures.Keywords: aquifer identification, decision tree, groundwater, Fourier transform
Procedia PDF Downloads 15728543 Privacy Preserving Data Publishing Based on Sensitivity in Context of Big Data Using Hive
Authors: P. Srinivasa Rao, K. Venkatesh Sharma, G. Sadhya Devi, V. Nagesh
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Privacy Preserving Data Publication is the main concern in present days because the data being published through the internet has been increasing day by day. This huge amount of data was named as Big Data by its size. This project deals the privacy preservation in the context of Big Data using a data warehousing solution called hive. We implemented Nearest Similarity Based Clustering (NSB) with Bottom-up generalization to achieve (v,l)-anonymity. (v,l)-Anonymity deals with the sensitivity vulnerabilities and ensures the individual privacy. We also calculate the sensitivity levels by simple comparison method using the index values, by classifying the different levels of sensitivity. The experiments were carried out on the hive environment to verify the efficiency of algorithms with Big Data. This framework also supports the execution of existing algorithms without any changes. The model in the paper outperforms than existing models.Keywords: sensitivity, sensitive level, clustering, Privacy Preserving Data Publication (PPDP), bottom-up generalization, Big Data
Procedia PDF Downloads 29828542 Kinetic Monte Carlo Simulation of ZnSe Homoepitaxial Growth and Characterization
Authors: Hamid Khachab, Yamani Abdelkafi, Mouna Barhmi
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The epitaxial growth has great important in the fabricate of the new semi-conductors devices and upgrading many factors, such as the quality of crystallization and efficiency with their deferent types and the most effective epitaxial technique is the molecular beam epitaxial. The MBE growth modeling allows to confirm the experiments results out by atomic beam and to analyze the microscopic phenomena. In of our work, we determined the growth processes specially the ZnSe epitaxial technique by Kinetic Monte Carlo method and we also give observations that are made in real time at the growth temperature using reflection high energy electron diffraction (RHEED) and photoemission current.Keywords: molecular beam epitaxy, II-VI, morpholy, photoemission, RHEED, simulation, kinetic Monte Carlo, ZnSe
Procedia PDF Downloads 49028541 Grain and Grain Boundary Behavior of Sm Substituted Barium Titanate Based Ceramics
Authors: Parveen Kumar, J. K. Juneja, Chandra Prakash, K. K. Raina
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A series of polycrystalline ferroelectric ceramics with compositional formula Ba0.80-xSmxPb0.20Ti0.90Zr0.10O3 with x varying from 0 to 0.01 in the steps of 0.0025 has been prepared by solid state reaction method. The dielectric constant and tangent loss was measured as a function of frequency from 100Hz to 1MHz at different temperatures (200-500oC). The electrical behavior was then investigated using complex impedance spectroscopy (CIS) technique. From the CIS study, it has been found that there is a contribution of both grain and grain boundary in the electrical behavior of such ceramics. Grain and grain boundary resistivity and capacitance were calculated at different temperature using CIS technique. The present paper is about the discussion of grain and grain boundary contribution towards the electrical properties of Sm modified BaTiO3 based ceramics at high temperature.Keywords: grain, grain boundary, impedance, dielectric
Procedia PDF Downloads 39928540 Parental Bonding and Cognitive Emotion Regulation
Authors: Fariea Bakul, Chhanda Karmaker
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The present study was designed to investigate the effects of parental bonding on adult’s cognitive emotion regulation and also to investigate gender differences in parental bonding and cognitive emotion regulation. Data were collected by using convenience sampling technique from 100 adult students (50 males and 50 females) of different universities of Dhaka city, ages between 20 to 25 years, using Bengali version of Parental Bonding Inventory and Bengali version of Cognitive Emotion Regulation Questionnaire. The obtained data were analyzed by using multiple regression analysis and independent samples t-test. The results revealed that fathers care (β =0.317, p < 0.05) was only significantly positively associated with adult’s cognitive emotion regulation. Adjusted R² indicated that the model explained 30% of the variance in adult’s adaptive cognitive emotion regulation. No significant association was found between parental bonding and less adaptive cognitive emotion regulations. Results from independent samples t-test also revealed that there was no significant gender difference in both parental bonding and cognitive emotion regulations.Keywords: cognitive emotion regulation, parental bonding, parental care, parental over-protection
Procedia PDF Downloads 37328539 Destination Decision Model for Cruising Taxis Based on Embedding Model
Authors: Kazuki Kamada, Haruka Yamashita
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In Japan, taxi is one of the popular transportations and taxi industry is one of the big businesses. However, in recent years, there has been a difficult problem of reducing the number of taxi drivers. In the taxi business, mainly three passenger catching methods are applied. One style is "cruising" that drivers catches passengers while driving on a road. Second is "waiting" that waits passengers near by the places with many requirements for taxies such as entrances of hospitals, train stations. The third one is "dispatching" that is allocated based on the contact from the taxi company. Above all, the cruising taxi drivers need the experience and intuition for finding passengers, and it is difficult to decide "the destination for cruising". The strong recommendation system for the cruising taxies supports the new drivers to find passengers, and it can be the solution for the decreasing the number of drivers in the taxi industry. In this research, we propose a method of recommending a destination for cruising taxi drivers. On the other hand, as a machine learning technique, the embedding models that embed the high dimensional data to a low dimensional space is widely used for the data analysis, in order to represent the relationship of the meaning between the data clearly. Taxi drivers have their favorite courses based on their experiences, and the courses are different for each driver. We assume that the course of cruising taxies has meaning such as the course for finding business man passengers (go around the business area of the city of go to main stations) and course for finding traveler passengers (go around the sightseeing places or big hotels), and extract the meaning of their destinations. We analyze the cruising history data of taxis based on the embedding model and propose the recommendation system for passengers. Finally, we demonstrate the recommendation of destinations for cruising taxi drivers based on the real-world data analysis using proposing method.Keywords: taxi industry, decision making, recommendation system, embedding model
Procedia PDF Downloads 13828538 Destination Management Organization in the Digital Era: A Data Framework to Leverage Collective Intelligence
Authors: Alfredo Fortunato, Carmelofrancesco Origlia, Sara Laurita, Rossella Nicoletti
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In the post-pandemic recovery phase of tourism, the role of a Destination Management Organization (DMO) as a coordinated management system of all the elements that make up a destination (attractions, access, marketing, human resources, brand, pricing, etc.) is also becoming relevant for local territories. The objective of a DMO is to maximize the visitor's perception of value and quality while ensuring the competitiveness and sustainability of the destination, as well as the long-term preservation of its natural and cultural assets, and to catalyze benefits for the local economy and residents. In carrying out the multiple functions to which it is called, the DMO can leverage a collective intelligence that comes from the ability to pool information, explicit and tacit knowledge, and relationships of the various stakeholders: policymakers, public managers and officials, entrepreneurs in the tourism supply chain, researchers, data journalists, schools, associations and committees, citizens, etc. The DMO potentially has at its disposal large volumes of data and many of them at low cost, that need to be properly processed to produce value. Based on these assumptions, the paper presents a conceptual framework for building an information system to support the DMO in the intelligent management of a tourist destination tested in an area of southern Italy. The approach adopted is data-informed and consists of four phases: (1) formulation of the knowledge problem (analysis of policy documents and industry reports; focus groups and co-design with stakeholders; definition of information needs and key questions); (2) research and metadatation of relevant sources (reconnaissance of official sources, administrative archives and internal DMO sources); (3) gap analysis and identification of unconventional information sources (evaluation of traditional sources with respect to the level of consistency with information needs, the freshness of information and granularity of data; enrichment of the information base by identifying and studying web sources such as Wikipedia, Google Trends, Booking.com, Tripadvisor, websites of accommodation facilities and online newspapers); (4) definition of the set of indicators and construction of the information base (specific definition of indicators and procedures for data acquisition, transformation, and analysis). The framework derived consists of 6 thematic areas (accommodation supply, cultural heritage, flows, value, sustainability, and enabling factors), each of which is divided into three domains that gather a specific information need to be represented by a scheme of questions to be answered through the analysis of available indicators. The framework is characterized by a high degree of flexibility in the European context, given that it can be customized for each destination by adapting the part related to internal sources. Application to the case study led to the creation of a decision support system that allows: •integration of data from heterogeneous sources, including through the execution of automated web crawling procedures for data ingestion of social and web information; •reading and interpretation of data and metadata through guided navigation paths in the key of digital story-telling; •implementation of complex analysis capabilities through the use of data mining algorithms such as for the prediction of tourist flows.Keywords: collective intelligence, data framework, destination management, smart tourism
Procedia PDF Downloads 12228537 Democracy Bytes: Interrogating the Exploitation of Data Democracy by Radical Terrorist Organizations
Authors: Nirmala Gopal, Sheetal Bhoola, Audecious Mugwagwa
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This paper discusses the continued infringement and exploitation of data by non-state actors for destructive purposes, emphasizing radical terrorist organizations. It will discuss how terrorist organizations access and use data to foster their nefarious agendas. It further examines how cybersecurity, designed as a tool to curb data exploitation, is ineffective in raising global citizens' concerns about how their data can be kept safe and used for its acquired purpose. The study interrogates several policies and data protection instruments, such as the Data Protection Act, Cyber Security Policies, Protection of Personal Information(PPI) and General Data Protection Regulations (GDPR), to understand data use and storage in democratic states. The study outcomes point to the fact that international cybersecurity and cybercrime legislation, policies, and conventions have not curbed violations of data access and use by radical terrorist groups. The study recommends ways to enhance cybersecurity and reduce cyber risks using democratic principles.Keywords: cybersecurity, data exploitation, terrorist organizations, data democracy
Procedia PDF Downloads 20528536 Web Data Scraping Technology Using Term Frequency Inverse Document Frequency to Enhance the Big Data Quality on Sentiment Analysis
Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan
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Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis
Procedia PDF Downloads 8828535 Characteization and Optimization of S-Parameters of Microwave Circuits
Authors: N. Ourabia, M. Boubaker Ourabia
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An approach for modeling and numerical simulation of passive planar structures using the edge line concept is developed. With this method, we develop an efficient modeling technique for microstrip 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: optimization, CAD analysis, microwave circuits, S-parameters
Procedia PDF Downloads 45428534 Numerical Modelling of 3-D Fracture Propagation and Damage Evolution of an Isotropic Heterogeneous Rock with a Pre-Existing Surface Flaw under Uniaxial Compression
Authors: S. Mondal, L. M. Olsen-Kettle, L. Gross
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Fracture propagation and damage evolution are extremely important for many industrial applications including mining industry, composite materials, earthquake simulations, hydraulic fracturing. The influence of pre-existing flaws and rock heterogeneity on the processes and mechanisms of rock fracture has important ramifications in many mining and reservoir engineering applications. We simulate the damage evolution and fracture propagation in an isotropic sandstone specimen containing a pre-existing 3-D surface flaw in different configurations under uniaxial compression. We apply a damage model based on the unified strength theory and solve the solid deformation and damage evolution equations using the Finite Element Method (FEM) with tetrahedron elements on unstructured meshes through the simulation software, eScript. Unstructured meshes provide higher geometrical flexibility and allow a more accurate way to model the varying flaw depth, angle, and length through locally adapted FEM meshes. The heterogeneity of rock is considered by initializing material properties using a Weibull distribution sampled over a cubic grid. In our model, we introduce a length scale related to the rock heterogeneity which is independent of the mesh size. We investigate the effect of parameters including the heterogeneity of the elastic moduli and geometry of the single flaw in the stress strain response. The generation of three typical surface cracking patterns, called wing cracks, anti-wing cracks and far-field cracks were identified, and these depend on the geometry of the pre-existing surface flaw. This model results help to advance our understanding of fracture and damage growth in heterogeneous rock with the aim to develop fracture simulators for different industry applications.Keywords: finite element method, heterogeneity, isotropic damage, uniaxial compression
Procedia PDF Downloads 21928533 Drone On-Time Obstacle Avoidance for Static and Dynamic Obstacles
Authors: Herath M. P. C. Jayaweera, Samer Hanoun
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Path planning for on-time obstacle avoidance is an essential and challenging task that enables drones to achieve safe operation in any application domain. The level of challenge increases significantly on the obstacle avoidance technique when the drone is following a ground mobile entity (GME). This is mainly due to the change in direction and magnitude of the GME′s velocity in dynamic and unstructured environments. Force field techniques are the most widely used obstacle avoidance methods due to their simplicity, ease of use, and potential to be adopted for three-dimensional dynamic environments. However, the existing force field obstacle avoidance techniques suffer many drawbacks, including their tendency to generate longer routes when the obstacles are sideways of the drone′s route, poor ability to find the shortest flyable path, propensity to fall into local minima, producing a non-smooth path, and high failure rate in the presence of symmetrical obstacles. To overcome these shortcomings, this paper proposes an on-time three-dimensional obstacle avoidance method for drones to effectively and efficiently avoid dynamic and static obstacles in unknown environments while pursuing a GME. This on-time obstacle avoidance technique generates velocity waypoints for its obstacle-free and efficient path based on the shape of the encountered obstacles. This method can be utilized on most types of drones that have basic distance measurement sensors and autopilot-supported flight controllers. The proposed obstacle avoidance technique is validated and evaluated against existing force field methods for different simulation scenarios in Gazebo and ROS-supported PX4-SITL. The simulation results show that the proposed obstacle avoidance technique outperforms the existing force field techniques and is better suited for real-world applications.Keywords: drones, force field methods, obstacle avoidance, path planning
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