Search results for: time delayed SVIRS epidemic model

Authors: Muhammad A. Khan, Waseem Shahzad

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Analysis of protein sequences is carried out for the purpose to discover their structural and ancestry relationship. Sequence similarity determines similar protein structures, similar function, and homology detection. Biological sequences composed of amino acid residues or nucleotides provide significant information through sequence alignment. In this paper, we present a new similarity/dissimilarity measure to sequence alignment based on the primary structure of a protein. The approach finds the distance between the two given sequences using the novel sequence alignment algorithm and a mathematical model. The algorithm runs at a time complexity of O(n²). A distance matrix is generated to construct a phylogenetic tree of different species. The new similarity/dissimilarity measure outperforms other existing methods.

Keywords: alignment, distance, homology, mathematical model, phylogenetic tree

Procedia PDF Downloads 176

Authors: Sheraz Ahmad Choudhary

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Health plays a vital role in the growth. The study examined the effect of health indicator on the growth of Pakistan. ARDL model is used to check the growth rate which is affected by the health by using the time series date of Pakistan from 1990 to 2017. Health indicator, fertility rate, life expectancy, foreign direct investment, and infant mortality rate are variables Where the unit root is applied to check the stationarity of the model. consequences find a significant relationship between GDP, foreign direct investment, fertility rate, and life expectancy in the short run, whereas mortality rate effected negatively to economic growth but have significant values. In the long run, foreign direct investment (FDI) and fertility rate(FR) have significantly influenced the GDP. The results show thateconomic growth is positively stimulated by most of the health indicators. The study accomplishes that nations can achieve a high level of economic growth by increasing wellbeing human capital.

Keywords: economic growth, health expenditures, fertility rate, human capital, life expectancy, foreign direct investment, and infant mortality rate

Procedia PDF Downloads 128

Authors: Kehinde Peter Oyeduntan, Kayode Oshinubi

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The west African ports have been experiencing large inflow and outflow of containerized cargo in the last decades, and this has created a quest amongst the countries to attain the status of hub port for the sub-region. This study analyzed the relationship between the container throughput and Gross Domestic Products (GDP) of nine west African countries, using Simple Linear Regression (SLR), Polynomial Regression Model (PRM) and Support Vector Machines (SVM) with a time series of 20 years. The results showed that there exists a high correlation between the GDP and container throughput. The model also predicted the container throughput in west Africa for the next 20 years. The findings and recommendations presented in this research will guide policy makers and help improve the management of container ports and terminals in west Africa, thereby boosting the economy.

Keywords: container, ports, terminals, throughput

Procedia PDF Downloads 212

Authors: Ming-Yue Zhai

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Due to the multipath and pulse noise nature, power line communications(PLC) channel can be modelled as a memory one with the finite states Markov model(FSMC). As the most important parameter modelling a Markov channel,the memory order in an FSMC is not solved in PLC systems yet. In the paper, the mutual information is used as a measure of the dependence between the different symbols, treated as the received SNA or amplitude of the current channel symbol or that of previous symbols. The joint distribution probabilities of the envelopes in PLC systems are computed based on the multi-path channel model, which is commonly used in PLC. we confirm that given the information of the symbol immediately preceding the current one, any other previous symbol is independent of the current one in PLC systems, which means the PLC channels is a Markov chain with the first-order. The field test is also performed to model the received OFDM signals with the help of AR model. The results show that the first-order AR model is enough to model the fading channel in PLC systems, which means the amount of uncertainty remaining in the current symbol should be negligible, given the information corresponding to the immediately preceding one.

Keywords: power line communication, channel model, markovian, information theory, first-order

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Authors: Shinji Ukita, Naohiro Nakamura, Yuji Miyazu

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In considering the dynamic characteristics of structure, natural frequency and damping ratio are useful indicator. When performing dynamic design, it's necessary to select an appropriate initial damping model and hysteretic model. In the linear region, the setting of initial damping model influences the response, and in the nonlinear region, the combination of initial damping model and hysteretic model influences the response. However, the dynamic characteristics of structure in the nonlinear region remain unclear. In this paper, we studied the effect of setting of initial damping model and hysteretic model on the dynamic characteristics of structure. On initial damping model setting, Initial stiffness proportional, Tangent stiffness proportional, and Rayleigh-type were used. On hysteretic model setting, TAKEDA model and Normal-trilinear model were used. As a study method, dynamic analysis was performed using a lumped mass model of base-fixed. During analysis, the maximum acceleration of input earthquake motion was gradually increased from 1 to 600 gal. The dynamic characteristics were calculated using the ARX model. Then, the characteristics of 1st and 2nd natural frequency and 1st damping ratio were evaluated. Input earthquake motion was simulated wave that the Building Center of Japan has published. On the building model, an RC building with 30×30m planes on each floor was assumed. The story height was 3m and the maximum height was 18m. Unit weight for each floor was 1.0t/m2. The building natural period was set to 0.36sec, and the initial stiffness of each floor was calculated by assuming the 1st mode to be an inverted triangle. First, we investigated the difference of the dynamic characteristics depending on the difference of initial damping model setting. With the increase in the maximum acceleration of the input earthquake motions, the 1st and 2nd natural frequency decreased, and the 1st damping ratio increased. Then, in the natural frequency, the difference due to initial damping model setting was small, but in the damping ratio, a significant difference was observed (Initial stiffness proportional≒Rayleigh type>Tangent stiffness proportional). The acceleration and the displacement of the earthquake response were largest in the tangent stiffness proportional. In the range where the acceleration response increased, the damping ratio was constant. In the range where the acceleration response was constant, the damping ratio increased. Next, we investigated the difference of the dynamic characteristics depending on the difference of hysteretic model setting. With the increase in the maximum acceleration of the input earthquake motions, the natural frequency decreased in TAKEDA model, but in Normal-trilinear model, the natural frequency didn’t change. The damping ratio in TAKEDA model was higher than that in Normal-trilinear model, although, both in TAKEDA model and Normal-trilinear model, the damping ratio increased. In conclusion, in initial damping model setting, the tangent stiffness proportional was evaluated the most. In the hysteretic model setting, TAKEDA model was more appreciated than the Normal-trilinear model in the nonlinear region. Our results would provide useful indicator on dynamic design.

Keywords: initial damping model, damping ratio, dynamic analysis, hysteretic model, natural frequency

Procedia PDF Downloads 174

Authors: Liang Wang, Beste F. Yuksel, David Guy Brizan

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A computational model of affect that can distinguish between spontaneous and posed smiles with no errors on a large, popular data set using deep learning techniques is presented in this paper. A Long Short-Term Memory (LSTM) classifier, a type of Recurrent Neural Network, is utilized and compared to human classification. Results showed that while human classification (mean of 0.7133) was above chance, the LSTM model was more accurate than human classification and other comparable state-of-the-art systems. Additionally, a high accuracy rate was maintained with small amounts of training videos (70 instances). The derivation of important features to further understand the success of our computational model were analyzed, and it was inferred that thousands of pairs of points within the eyes and mouth are important throughout all time segments in a smile. This suggests that distinguishing between a posed and spontaneous smile is a complex task, one which may account for the difficulty and lower accuracy of human classification compared to machine learning models.

Keywords: affective computing, affect detection, computer vision, deep learning, human-computer interaction, machine learning, posed smile detection, spontaneous smile detection

Procedia PDF Downloads 124

Authors: Fatima Zahra Falah, Touria El. Ghailassi, Samia Yousfi, Ahmed Moussaif, Hasna Hamdane, Mouna Latifa Bouamrani

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The management and treatment of radioactive wastewater pose significant challenges to environmental safety and public health. This study presents an innovative approach to optimizing radioactive wastewater treatment using a novel biosorbent: chitosan-argan nutshell beads. By employing Response Surface Methodology (RSM), we aimed to determine the optimal conditions for maximum removal efficiency of radioactive contaminants. Chitosan, a biodegradable and non-toxic biopolymer, was combined with argan nutshell powder to create composite beads. The argan nutshell, a waste product from argan oil production, provides additional adsorption sites and mechanical stability to the biosorbent. The beads were characterized using Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), and X-ray Diffraction (XRD) to confirm their structure and composition. A three-factor, three-level Box-Behnken design was utilized to investigate the effects of pH (3-9), contact time (30-150 minutes), and adsorbent dosage (0.5-2.5 g/L) on the removal efficiency of radioactive isotopes, primarily focusing on cesium-137. Batch adsorption experiments were conducted using synthetic radioactive wastewater with known concentrations of these isotopes. The RSM analysis revealed that all three factors significantly influenced the adsorption process. A quadratic model was developed to describe the relationship between the factors and the removal efficiency. The model's adequacy was confirmed through analysis of variance (ANOVA) and various diagnostic plots. Optimal conditions for maximum removal efficiency were pH 6.8, a contact time of 120 minutes, and an adsorbent dosage of 0.8 g/L. Under these conditions, the experimental removal efficiency for cesium-137 was 94.7%, closely matching the model's predictions. Adsorption isotherms and kinetics were also investigated to elucidate the mechanism of the process. The Langmuir isotherm and pseudo-second-order kinetic model best described the adsorption behavior, indicating a monolayer adsorption process on a homogeneous surface. This study demonstrates the potential of chitosan-argan nutshell beads as an effective and sustainable biosorbent for radioactive wastewater treatment. The use of RSM allowed for the efficient optimization of the process parameters, potentially reducing the time and resources required for large-scale implementation. Future work will focus on testing the biosorbent's performance with real radioactive wastewater samples and investigating its regeneration and reusability for long-term applications.

Keywords: adsorption, argan nutshell, beads, chitosan, mechanism, optimization, radioactive wastewater, response surface methodology

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Authors: Marwa Hussien Mohamed, Mohamed Helmy Khafagy

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Map-Reduce is a programming model which is widely used to extract valuable information from enormous volumes of data. Map-reduce designed to support heterogeneous datasets. Apache Hadoop map-reduce used extensively to uncover hidden pattern like data mining, SQL, etc. The most important operation for data analysis is joining operation. But, map-reduce framework does not directly support join algorithm. This paper explains and compares two-way and multi-way map-reduce join algorithms for map reduce also we implement MR join Algorithms and show the performance of each phase in MR join algorithms. Our experimental results show that map side join and map merge join in two-way join algorithms has the longest time according to preprocessing step sorting data and reduce side cascade join has the longest time at Multi-Way join algorithms.

Keywords: Hadoop, MapReduce, multi-way join, two-way join, Ubuntu

Procedia PDF Downloads 485

Authors: Tea Poklepović, Zdravka Aljinović, Branka Marasović

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Due to the importance of yield curve and its estimation it is inevitable to have valid methods for yield curve forecasting in cases when there are scarce issues of securities and/or week trade on a secondary market. Therefore in this paper, after the estimation of weekly yield curves on Croatian financial market from October 2011 to August 2012 using Nelson-Siegel and Svensson models, yield curves are forecasted using Vector auto-regressive model and Neural networks. In general, it can be concluded that both forecasting methods have good prediction abilities where forecasting of yield curves based on Nelson Siegel estimation model give better results in sense of lower Mean Squared Error than forecasting based on Svensson model Also, in this case Neural networks provide slightly better results. Finally, it can be concluded that most appropriate way of yield curve prediction is neural networks using Nelson-Siegel estimation of yield curves.

Keywords: Nelson-Siegel Model, neural networks, Svensson Model, vector autoregressive model, yield curve

Procedia PDF Downloads 330

Authors: A. S. Grewal, R. S. Sangwan, Dharambir, Vikas Dhanda

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The purpose of this paper is to develop and analyze two reliability models for a system of non-identical firearms – one is standard firearm (called as original unit) and the other is a country-made firearm (called as duplicate /substandard unit). There is a single server who comes immediately to do inspection and repair whenever needed. On the failure of standard firearm, the server inspects the operative country-made firearm to see whether the unit is capable of performing the desired function well or not. If country-made firearm is not capable to do so, the operation of the system is stopped and server starts repair of the standard firearms immediately. However, no inspection is done at the failure of the country-made firearm as the country-made firearm alone is capable of performing the given task well. In model I, priority to repair the standard firearm is given in case system fails completely and country-made firearm is already under repair, whereas in model II there is no such priority. The failure and repair times of each unit are assumed to be independent and uncorrelated random variables. The distributions of failure time of the units are taken as negative exponential while that of repair and inspection times are general. By using semi-Markov process and regenerative point technique some econo-reliability measures are obtained. Graphs are plotted to compare the MTSF (mean time to system failure), availability and profit of the models for a particular case.

Keywords: non-identical firearms, inspection, priority to repair, semi-Markov process, regenerative point

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Authors: Michelle Roesler, Ian Glendon, Francis O'Callaghan

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This study expands on recent findings and offers a new perspective on recovery from injury and return to work (RTW) after an acute traumatic occupational hand injury. Recovery is a complex medical and psychosocial process. A number of predictor variables were studied simultaneously to identify the bio-psychosocial variables that impede recovery. An unexpected phenomenon to emerge from this study was the high incidence of complications within the hand-injured patient sample. Twenty six percent (n = 71) of the total sample (N = 263) required a second operation due to complications. This warranted further investigation. Results confirmed that complications not only significantly delayed the RTW outcome but also had a profound psychological impact on the individuals affected. Research has found that surgical complications are usually the result of incorrect early assessment and management. A strategic plan needs to be implemented to ensure the optimal level of surgical care is provided for managing acute traumatic hand injuries to avoid such complications.

Keywords: occupational hand trauma, psychological recovery, return to work, psychology

Procedia PDF Downloads 508

Authors: Cristina da Silva Torres, José Luis Duarte Ribeiro, Maria Auxiliadora Cannarozzo Tinoco

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As a result of the rapid growth of the Brazilian Air Transport, many airports are at the limit of their capacities and have a reduction in the quality of services provided. Thus, there is a need of models for assessing the quality of airport services. Because of this, the main objective of this work is to propose a model for the evaluation of quality attributes in airport services. To this end, we used the method composed by literature review and interview. Structured a working method composed by 5 steps, which resulted in a model to evaluate the quality of airport services, consisting of 8 dimensions and 45 attributes. Was used as base for model definition the process mapping of boarding and landing processes of passengers and luggage. As a contribution of this work is the integration of management process with structuring models to assess the quality of services in airport environments.

Keywords: quality airport services, model for identification of attributes quality, air transport, passenger

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Authors: Demet Ozgur-Unluakin, Busenur Turkali, S. Caglar Aksezer

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Since the age of industrialization, maintenance has always been a very crucial element for all kinds of factories and plants. With today’s increasingly developing technology, the system structure of such facilities has become more complicated, and even a small operational disruption may return huge losses in profits for the companies. In order to reduce these costs, effective maintenance planning is crucial, but at the same time, it is a difficult task because of the complexity of systems. The most important aspect of correct maintenance planning is to understand the structure of the system, not to ignore the dependencies among the components and as a result, to model the system correctly. In this way, it will be better to understand which component improves the system more when it is maintained. Undoubtedly, proactive maintenance at a scheduled time reduces costs because the scheduled maintenance prohibits high losses in profits. But the necessity of corrective maintenance, which directly affects the situation of the system and provides direct intervention when the system fails, should not be ignored. When a fault occurs in the system, if the problem is not solved immediately and proactive maintenance time is awaited, this may result in increased costs. This study proposes various maintenance methods with different efficiency measures under corrective maintenance strategy on a subsystem of a thermal power plant. To model the dependencies between the components, dynamic Bayesian Network approach is employed. The proposed maintenance methods aim to minimize the total maintenance cost in a planning horizon, as well as to find the most appropriate component to be attacked on, which improves the system reliability utmost. Performances of the methods are compared under corrective maintenance strategy. Furthermore, sensitivity analysis is also applied under different cost values. Results show that all fault effect methods perform better than the replacement effect methods and this conclusion is also valid under different downtime cost values.

Keywords: dynamic Bayesian networks, maintenance, multi-component systems, reliability

Procedia PDF Downloads 128

Authors: Tae Bo Jeon

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Korean air force is undertaking a big project to replace prevailing hundreds of old air fighters such as F-4, F-5, KF-16 etc. The task is to develop and produce domestic fighters equipped with 2 complete-type engines each. A large number of engines, however, will be purchased as products from a foreign engine maker. In addition to the fighters themselves, secure the proper number of spare engines serves a significant role in maintaining combat readiness and effectively managing the national defense budget due to high cost. In this paper, we presented a model dynamically updating spare engine requirements. Currently, the military administration purchases all the fighters, engines, and spare engines at acquisition stage and does not have additional procurement processes during the life cycle, 30-40 years. With the assumption that procurement procedure during the operational stage is established, our model starts from the initial estimate of spare engine requirements based on limited information. The model then performs military missions and repair/maintenance works when necessary. During operation, detailed field information - aircraft repair and test, engine repair, planned maintenance, administration time, transportation pipeline between base, field, and depot etc., - should be considered for actual engine requirements. At the end of each year, the performance measure is recorded and proceeds to next year when it shows higher the threshold set. Otherwise, additional engine(s) will be bought and added to the current system. We repeat the process for the life cycle period and compare the results. The proposed model is seen to generate far better results appropriately adding spare engines thus avoiding possible undesirable situations. Our model may well be applied to future air force military operations.

Keywords: DMSMS, operational availability, METRIC, PRS

Procedia PDF Downloads 169

Authors: Zhenjie Liu

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This paper investigates the existence and uniqueness of solutions for singular higher order boundary value problems on time scales by using mixed monotone method. The theorems obtained are very general. For the different time scale, the problem may be the corresponding continuous or discrete boundary value problem.

Keywords: mixed monotone operator, boundary value problem, time scale, green's function, positive solution, singularity

Procedia PDF Downloads 255

Authors: Motonobu Hattori

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In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudo patterns. Because, temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.

Keywords: catastrophic forgetting, dual-network, temporal sequences, hippocampal

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Authors: C. C. Kruger, P. Van Tonder

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Concrete deteriorates over time and the deterioration can be escalated due to multiple factors. When deteriorations are beneath the concrete’s surface, they could be unknown, even more so when they are located at high elevations. Establishing the severity of such defects could prove difficult and therefore the need to find efficient, safe and economical methods to find these defects becomes ever more important. Current methods using thermography to find defects require equipment such as scaffolding to reach these higher elevations. This could become time- consuming and costly. The risks involved with personnel scaffold or abseil to such heights are high. Accordingly, by combining the technologies of a thermal camera and a Remotely Piloted Aerial System it could be used to find better diagnostic methods. The data could then be constructed into a 3D thermal model to easy representation of the results

Keywords: concrete, infrared thermography, 3D thermal models, diagnostic

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Authors: Peter J. Riley

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Introductory courses in High Energy Physics (HEP) can be extended with the Tri-Preon (TP) model to both supplements and challenge the Standard Model (SM) theory. TP supplements by simplifying the tracking of Conserved Quantum Numbers at an interaction vertex, e.g., the lepton number can be seen as a di-preon current. TP challenges by proposing extended particle families to three generations of particle triplets for leptons, quarks, and weak bosons. There are extensive examples discussed at an introductory level in six arXiv publications, including supersymmetry, hyper color, and the Higgs. Interesting exercises include pion decay, kaon-antikaon mixing, neutrino oscillations, and K+ decay to muons. It is a revealing exercise for students to weigh the pros and cons of parallel theories at an early stage in their HEP journey.

Keywords: HEP, particle physics, standard model, Tri-Preon model

Procedia PDF Downloads 71

Authors: Shan Li, Qiuwen Ma

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Integrated project delivery (IPD) is a project delivery method distinguished by a shared risk/rewards mechanism and multiparty agreement. IPD has drawn increasingly attention from construction industry because of its efficiency of solving adversarial problems and reliability to deliver high-performing buildings. However, some evidence showed that some project participants obtained less profit from IPD projects than the typical projects. They attributed it to the unfair IPD sharing mechanism, which resulted in additional time and cost of negotiation on the sharing fractions among project participants. The study is aimed to investigate the reward distribution by constructing a principal-agent model. Based on cooperative game theory, it is examined how to distribute the shared project rewards between client and non-client parties, and identify the sharing fractions among non-client parties. It is found that at least half of the project savings should be allocated to the non-client parties to motivate them to create more project value. Second, the client should raise his sharing fractions when the integration among project participants is efficient. In addition, the client should allocate higher sharing fractions to the non-client party who is more able. This study can help the IPD project participants make fair and motivated sharing mechanisms.

Keywords: cooperative game theory, IPD, principal agent model, sharing mechanism

Procedia PDF Downloads 290

Authors: Yang Jian-Hong, Zhang Ren-Cheng, Huang Li

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Arc fault is one of the main inducements of electric fires. Arc Fault Detection Device (AFDD) can detect arc fault effectively. Arc fault detections and unhooking standards are the keys to AFDD practical application. First, an arc fault continuous production system was developed, which could count the arc half wave number. Then, Combining with the UL1699 standard, ignition probability curve of cotton and unhooking time of various currents intensity were obtained by experiments. The combustion degree of arc fault could be expressed effectively by arc area. Experiments proved that electric fires would be misjudged or missed only using arc half wave number as AFDD unhooking basis. At last, Practical tests were carried out on the self-developed AFDD system. The result showed that actual AFDD unhooking time was the sum of arc half wave cycling number, Arc wave identification time and unhooking mechanical operation time And the first two shared shorter time. Unhooking time standard depended on the shortest mechanical operation time.

Keywords: arc fault detection device, arc area, arc half wave, unhooking time, arc fault

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Authors: Mousouris Spiridon, Kavakli Evangelia

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This paper focuses on Digital Libraries (DLs) that contain and geovisualise cultural data, highlighting the need to define them as a separate category termed Cultural Mapping Libraries, based on their inherent connection of culture with geographic location and their design requirements in support of visual representation of cultural data on the map. An exploratory analysis of DLs that conform to the above definition brought forward the observation that existing Cultural Mapping Libraries fail to geovisualise the entirety of cultural data per point of interest thus resulting in a Cultural Snapshot phenomenon. The existence of this phenomenon was reinforced by the results of a systematic bibliographic research. In order to address the Cultural Snapshot, this paper proposes the use of the Semantic Web principles to efficiently interconnect spatial cultural data through time, per geographic location. In this way points of interest are transformed into scenery where culture evolves over time. This evolution is expressed as occurrences taking place chronologically, in an event oriented approach, a conceptualization also endorsed by the CIDOC Conceptual Reference Model (CIDOC CRM). In particular, we posit the use of CIDOC CRM as the baseline for defining the logic of Cultural Mapping Libraries as part of the Culture Domain in accordance with the Digital Library Reference Model, in order to define the rules of cultural data management by the system. Our future goal is to transform this conceptual definition in to inferencing rules that resolve the Cultural Snapshot and lead to a more complete geovisualisation of cultural data.

Keywords: digital libraries, semantic web, geovisualization, CIDOC-CRM

Procedia PDF Downloads 107

Authors: N. Agon, T. Kavka, J. Vierendeels, M. Hrabovský, G. Van Oost

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A plasma jet model was developed with a rigorous method for calculating the thermophysical properties of the gas mixture without mixing rules. A simplified model approach to account for the anode effects was incorporated in this model to allow the valorization of the simulations with experimental results. The radial heat transfer was under-predicted by the model because of the limitations of the radiation model, but the calculated evolution of centerline temperature, velocity and gas composition downstream of the torch exit corresponded well with the measured values. The CFD modeling of thermal plasmas is either focused on development of the plasma arc or the flow of the plasma jet outside of the plasma torch. In the former case, the Maxwell equations are coupled with the Navier-Stokes equations to account for electromagnetic effects which control the movements of the anode arc attachment. In plasma jet simulations, however, the computational domain starts from the exit nozzle of the plasma torch and the influence of the arc attachment fluctuations on the plasma jet flow field is not included in the calculations. In that case, the thermal plasma flow is described by temperature, velocity and concentration profiles at the torch exit nozzle and no electromagnetic effects are taken into account. This simplified approach is widely used in literature and generally acceptable for plasma torches with a circular anode inside the torch chamber. The unique DC hybrid water/gas-stabilized plasma torch developed at the Institute of Plasma Physics of the Czech Academy of Sciences on the other hand, consists of a rotating anode disk, located outside of the torch chamber. Neglecting the effects of the anode arc attachment downstream of the torch exit nozzle leads to erroneous predictions of the flow field. With the simplified approach introduced in this model, the Joule heating between the exit nozzle and the anode attachment position of the plasma arc is modeled by a volume heat source and the jet deflection caused by the anode processes by a momentum source at the anode surface. Furthermore, radiation effects are included by the net emission coefficient (NEC) method and diffusion is modeled with the combined diffusion coefficient method. The time-averaged simulation results are compared with numerous experimental measurements. The radial temperature profiles were obtained by spectroscopic measurements at different axial positions downstream of the exit nozzle. The velocity profiles were evaluated from the time-dependent evolution of flow structures, recorded by photodiode arrays. The shape of the plasma jet was compared with charge-coupled device (CCD) camera pictures. In the cooler regions, the temperature was measured by enthalpy probe downstream of the exit nozzle and by thermocouples in radial direction around the torch nozzle. The model results correspond well with the experimental measurements. The decrease in centerline temperature and velocity is predicted within an acceptable range and the shape of the jet closely resembles the jet structure in the recorded images. The temperatures at the edge of the jet are underestimated due to the absence of radial radiative heat transfer in the model.

Keywords: anode arc attachment, CFD modeling, experimental comparison, thermal plasma jet

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Authors: Anna Lower, Michal Lower, Robert Masztalski, Agnieszka Szumilas

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Contemporary cities are facing serious congestion and parking problems. In urban transport policy the introduction of the park and ride system (P&R) is an increasingly popular way of limiting vehicular traffic. The determining of P&R facilities location is a key aspect of the system. Criteria for assessing the quality of the selected location are formulated generally and descriptively. The research outsourced to specialists are expensive and time consuming. The most focus is on the examination of a few selected places. The practice has shown that the choice of the location of these sites in a intuitive way without a detailed analysis of all the circumstances, often gives negative results. Then the existing facilities are not used as expected. Methods of location as a research topic are also widely taken in the scientific literature. Built mathematical models often do not bring the problem comprehensively, e.g. assuming that the city is linear, developed along one important communications corridor. The paper presents a new method where the expert knowledge is applied to fuzzy inference model. With such a built system even a less experienced person could benefit from it, e.g. urban planners, officials. The analysis result is obtained in a very short time, so a large number of the proposed location can also be verified in a short time. The proposed method is intended for testing of car parks location in a city. The paper will show selected examples of locations of the P&R facilities in cities planning to introduce the P&R. The analysis of existing objects will also be shown in the paper and they will be confronted with the opinions of the system users, with particular emphasis on unpopular locations. The research are executed using the fuzzy inference model which was built and described in more detail in the earlier paper of the authors. The results of analyzes are compared to documents of P&R facilities location outsourced by the city and opinions of existing facilities users expressed on social networking sites. The research of existing facilities were conducted by means of the fuzzy model. The results are consistent with actual users feedback. The proposed method proves to be good, but does not require the involvement of a large experts team and large financial contributions for complicated research. The method also provides an opportunity to show the alternative location of P&R facilities. The performed studies show that the method has been confirmed. The method can be applied in urban planning of the P&R facilities location in relation to the accompanying functions. Although the results of the method are approximate, they are not worse than results of analysis of employed experts. The advantage of this method is ease of use, which simplifies the professional expert analysis. The ability of analyzing a large number of alternative locations gives a broader view on the problem. It is valuable that the arduous analysis of the team of people can be replaced by the model's calculation. According to the authors, the proposed method is also suitable for implementation on a GIS platform.

Keywords: fuzzy logic inference, park and ride system, P&R facilities, P&R location

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Authors: Vinod Kumar Jaysaval, Prateek Agarwal

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Performance prediction of airborne radar is a challenging and cumbersome task in clutter scenario for different types of targets. A generalized model requires to predict the performance of Radar for air targets as well as ground moving targets. In this paper, we propose a generalized model to bring out the performance of airborne radar for different Pulsed Repetition Frequency (PRF) as well as different type of targets. The model provides a platform to bring out different subsystem parameters for different applications and performance requirements under different types of clutter terrain.

Keywords: airborne radar, blind zone, clutter, probability of detection

Procedia PDF Downloads 469

Authors: Sai-Kit Choi

Abstract:

While traditional social services heavily depended on Government funding and support, there were always time lag, and resources mismatch with the fast growing and changing social needs. This study aims at investigating the effectiveness of implementing Circular Economy concept in a social service setting with comparison to Government Policy in response to social needs in 3 areas: response time, suitability, and community participation. To investigate the effectiveness of implementing Circular Economy concept in a social service setting, a real service model, a community resources sharing platform, was set up and statistics of the first 6 months’ operation data were used as comparison with traditional social services. Literature review was conducted as a reference basis of traditional social services under Government Policy. Case studies were conducted to provide the qualitative perspectives of the innovative approach. The results suggest that the Circular Economy model showed extraordinarily high level of community participation. In addition, it could utilize community resources in response precisely to the burning social needs. On the other hand, the available resources were unstable when comparing to those services supported by Government funding. The research team concluded that Circular Economy has high potential in applications in social service, especially in certain areas, such as resources sharing platform. Notwithstanding, it should be aware of the stability of resources when the services targeted to support some crucial needs.

Keywords: circular economy, social innovation, community participation, sharing economy, social response

Procedia PDF Downloads 111

Authors: Marton Gergely

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Digital experience goods, such as music and video, are readily available and easily accessible through a sundry of illegal mediums. Furthermore, the rate of music theft has been increasing at a seemingly unstoppable rate. Instead of studying the effect of copyright infringement on affected shareholders, this paper aims to examine the overall impact that digital music piracy has on society as a whole. Through a systems dynamics approach, an archetype is built to model the behavior of both legal and illegal music users. Additionally, the effects over time are considered. The conceptual model suggests that if piracy continues to grow at the current pace, industry shareholders will eventually lose the motivation to supply new music. In turn, this tragedy would affect not only the illegal players, but legal consumers as well, by means of a decrease in overall quality of life.

Keywords: music piracy, illegal downloading, tragedy of the commons, system archetypes

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Authors: Wei Li, Tuo Yang

Abstract:

In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.

Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction

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Authors: Zhang Shuqi, Liu Dan

Abstract:

For the problems in intelligent network anomaly traffic detection models, such as low detection accuracy caused by the lack of training samples, poor effect with small sample attack detection, a classification model enhancement method, F-ACGAN(Flow Auxiliary Classifier Generative Adversarial Network) which introduces generative adversarial network and adversarial training, is proposed to solve these problems. Generating adversarial data with category labels could enhance the training effect and improve classification accuracy and model robustness. FACGAN consists of three steps: feature preprocess, which includes data type conversion, dimensionality reduction and normalization, etc.; A generative adversarial network model with feature learning ability is designed, and the sample generation effect of the model is improved through adversarial iterations between generator and discriminator. The adversarial disturbance factor of the gradient direction of the classification model is added to improve the diversity and antagonism of generated data and to promote the model to learn from adversarial classification features. The experiment of constructing a classification model with the UNSW-NB15 dataset shows that with the enhancement of FACGAN on the basic model, the classification accuracy has improved by 8.09%, and the score of F1 has improved by 6.94%.

Keywords: data imbalance, GAN, ACGAN, anomaly detection, adversarial training, data augmentation

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Authors: Ghofrane Rehaiem, Hamza Gharsellaoui, Samir Benahmed

Abstract:

In this study, Artificial Neural Networks (ANNs) were used for modeling the parameters that allow the real-time scheduling of embedded systems under resources constraints designed for real-time applications running. The objective of this work is to implement a neural networks based approach for real-time scheduling of embedded systems in order to handle real-time constraints in execution scenarios. In our proposed approach, many techniques have been proposed for both the planning of tasks and reducing energy consumption. In fact, a combination of Dynamic Voltage Scaling (DVS) and time feedback can be used to scale the frequency dynamically adjusting the operating voltage. Indeed, we present in this paper a hybrid contribution that handles the real-time scheduling of embedded systems, low power consumption depending on the combination of DVS and Neural Feedback Scheduling (NFS) with the energy Priority Earlier Deadline First (PEDF) algorithm. Experimental results illustrate the efficiency of our original proposed approach.

Keywords: optimization, neural networks, real-time scheduling, low-power consumption

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Authors: Ehsan Mehryaar, Seyed Armin Motahari Tabari

Abstract:

Without a doubt, soil shear strength is the most important property of the soil. The majority of fatal and catastrophic geological accidents are related to shear strength failure of the soil. Therefore, its prediction is a matter of high importance. However, acquiring the shear strength is usually a cumbersome task that might need complicated laboratory testing. Therefore, prediction of it based on common and easy to get soil properties can simplify the projects substantially. In this paper, A hybrid model based on the classification and regression tree algorithm and logistic regression is proposed where each leaf of the tree is an independent regression model. A database of 189 points for clay soil, including Moisture content, liquid limit, plastic limit, clay content, and shear strength, is collected. The performance of the developed model compared to the existing models and equations using root mean squared error and coefficient of correlation.

Keywords: model tree, CART, logistic regression, soil shear strength

Procedia PDF Downloads 194