Search results for: moving average model

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 333

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: Amer Momani, Tarek Al-Hawari, Abdallah Alakayleh

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This study explains how to construct an actionable activity-based costing and management system to accurately track and account the total costs of architectural aluminum projects. Two ABC models were proposed to accomplish this purpose. First, the learning and development model was introduced to examine how to apply an ABC model in an architectural aluminum firm for the first time and to be familiar with ABC concepts. Second, an actual ABC model was built on the basis of the results of the previous model to accurately trace the actual costs incurred on each project in a year, and to be able to provide a quote with the best trade-off between competitiveness and profitability. The validity of the proposed model was verified on a local architectural aluminum company.

Keywords: activity-based costing, activity-based management, construction, architectural aluminum

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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: Mahshid Arabi

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With the rapid expansion of digital technologies and the internet, information security has become a critical priority for organizations and individuals. The widespread use of digital tools such as smartphones and internet networks facilitates the storage of vast amounts of data, but simultaneously, vulnerabilities and security threats have significantly increased. The aim of this study is to examine and analyze modern methods of information security management and to develop a comprehensive model to counteract threats and information misuse. This study employs a mixed-methods approach, including both qualitative and quantitative analyses. Initially, a systematic review of previous articles and research in the field of information security was conducted. Then, using the Delphi method, interviews with 30 information security experts were conducted to gather their insights on security challenges and solutions. Based on the results of these interviews, a comprehensive model for information security management was developed. The proposed model includes advanced encryption techniques, machine learning-based intrusion detection systems, and network security protocols. AES and RSA encryption algorithms were used for data protection, and machine learning models such as Random Forest and Neural Networks were utilized for intrusion detection. Statistical analyses were performed using SPSS software. To evaluate the effectiveness of the proposed model, T-Test and ANOVA statistical tests were employed, and results were measured using accuracy, sensitivity, and specificity indicators of the models. Additionally, multiple regression analysis was conducted to examine the impact of various variables on information security. The findings of this study indicate that the comprehensive proposed model reduced cyber-attacks by an average of 85%. Statistical analysis showed that the combined use of encryption techniques and intrusion detection systems significantly improves information security. Based on the obtained results, it is recommended that organizations continuously update their information security systems and use a combination of multiple security methods to protect their data. Additionally, educating employees and raising public awareness about information security can serve as an effective tool in reducing security risks. This research demonstrates that effective and up-to-date information security management requires a comprehensive and coordinated approach, including the development and implementation of advanced techniques and continuous training of human resources.

Keywords: data protection, digital technologies, information security, modern management

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Authors: Yu-Ting Tsai, Chiun-Chieh Hsu, Yu-Chun Chu

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In recent years, due to the development of wireless network technology, many researchers have devoted to the study of wireless sensor networks. The applications of wireless sensor network mainly use the sensor nodes to collect the required information, and send the information back to the users. Since the sensed area is difficult to reach, there are many restrictions on the design of the sensor nodes, where the most important restriction is the limited energy of sensor nodes. Because of the limited energy, researchers proposed a number of ways to reduce energy consumption and balance the load of sensor nodes in order to increase the network lifetime. In this paper, we proposed the Energy-Balanced Clustering method with Auxiliary Members on Wireless Sensor Networks（EBCAM）based on the cluster routing. The main purpose is to balance the energy consumption on the sensed area and average the distribution of dead nodes in order to avoid excessive energy consumption because of the increasing in transmission distance. In addition, we use the residual energy and average energy consumption of the nodes within the cluster to choose the cluster heads, use the multi hop transmission method to deliver the data, and dynamically adjust the transmission radius according to the load conditions. Finally, we use the auxiliary cluster members to change the delivering path according to the residual energy of the cluster head in order to its load. Finally, we compare the proposed method with the related algorithms via simulated experiments and then analyze the results. It reveals that the proposed method outperforms other algorithms in the numbers of used rounds and the average energy consumption.

Keywords: auxiliary nodes, cluster, load balance, routing algorithm, wireless sensor network

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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

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Authors: Jaechun No

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This paper focuses on I/O optimizations of N-hybrid (New-Form of hybrid), which provides a hybrid file system space constructed on SSD and HDD. Although the promising potentials of SSD, such as the absence of mechanical moving overhead and high random I/O throughput, have drawn a lot of attentions from IT enterprises, its high ratio of cost/capacity makes it less desirable to build a large-scale data storage subsystem composed of only SSDs. In this paper, we present N-hybrid that attempts to integrate the strengths of SSD and HDD, to offer a single, large hybrid file system space. Several experiments were conducted to verify the performance of N-hybrid.

Keywords: SSD, data section, I/O optimizations, hybrid system

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Authors: Zhang Shuqi, Liu Dan

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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: Ehsan Mehryaar, Seyed Armin Motahari Tabari

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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

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Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Anamarija Mandic, Katarina Penov Gasi, Marija Sakac, Aleksandar Okljesa, Andrea Nikolic

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The present paper deals with chromatographic lipophilicity prediction of newly synthesized steroid derivatives. The prediction was achieved using in silico generated molecular descriptors and quantitative structure-retention relationship (QSRR) methodology with the artificial neural networks (ANN) approach. Chromatographic lipophilicity of the investigated compounds was expressed as retention factor value logk. For QSRR modeling, a feedforward back-propagation ANN with gradient descent learning algorithm was applied. Using the novel sum of ranking differences (SRD) method generated ANN models were ranked. The aim was to distinguish the most consistent QSRR model that can be found, and similarity or dissimilarity between the models that could be noticed. In this study, SRD was performed with average values of retention factor value logk as reference values. An excellent correlation between experimentally observed retention factor value logk and values predicted by the ANN was obtained with a correlation coefficient higher than 0.9890. Statistical results show that the established ANN models can be applied for required purpose. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation in Science and Technology).

Keywords: artificial neural networks, liquid chromatography, molecular descriptors, steroids, sum of ranking differences

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Authors: Muhammad Naziru Yahaya, Mustapha Bashir Ayinde

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Noise has been recognized as a major source of pollution in many urban and semi-urban settlements. Noise pollution causes by vehicular movement in urban cities has reaches an alarming proportion due to continuous increases in vehicles and industrialization. This research aim to determine the geo-physical characteristics of the study area and to determine the level of noise generation and volume intensity in areas where noise levels are high within the metropolis and compare with NESREA and WHO standards. This study identified the various sources of noise, compared noise levels in various parts of the study area with recommended standards and determined the geo-physical characteristic of noise generated. A sound level meter Gm 1352, was used for the noise measurements. The study showed that the noise pollution levels measured in minimum noise level of 63.75 dBA and average maximum of 95.175 dBA, at some locations in Birnin Kebbi metropolis the noise level have exceeded the standard limits set by the World Health Organization (WHO), Federal Environment Protection Agency (FEPA). Results revealed that there was a considerable increase in noise pollution in First Bank roundabout and Haliru Abdu roundabout, attribute to high numbers of vehicular movement and road congestion within Birnin Kebbi. The study therefore concluded that there should be an enforcement and adherence to the regulation regarding noise pollution limit. The minimum average day noise level recorded was 67.225 dBA, and average maximum of 96.6 dBA is an indication that the noise level of Birnin Kebbi metropolis was highly unsatisfactory. Based on this, it is suggested that taking adequate measures and following the laid-down recommendations will reduce traffic noise to the barest minimum.

Keywords: decibel, noise level, pollution, sound level, traffic, highway

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Authors: Rodríguez Sánchez Carla, Sancho-Esper Franco, Guillen-Davo Marina

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Tourism is one of the most important sectors worldwide since it is an important economic engine for today's society. It is also one of the sectors that most negatively affect the environment in terms of CO₂ emissions due to this expansion. In light of this, airlines are developing Voluntary Carbon Offset (VCO). There is important evidence focused on analyzing the features of these VCO programs and their efficacy in reducing CO₂ emissions, and findings are mixed without a clear consensus. Different research approaches have centered on analyzing factors and consequences of VCO programs, such as economic modelling based on panel data, survey research based on traveler responses or experimental research analyzing customer decisions in a simulated context. This study belongs to the latter group because it tries to understand how different characteristics of an online ticket purchase website affect the willingness of a traveler to choose a sustainable one. The proposed behavioral model is based on several theories, such as the nudge theory, the dual processing ELM and the cognitive dissonance theory. This randomized experiment aims at overcoming previous studies based on self-reported measures that mainly study sustainable behavioral intention rather than actual decision-making. It also complements traditional self-reported independent variables by gathering objective information from an eye-tracking device. This experiment analyzes the influence of two characteristics of the online purchase website: i) the type of information regarding flight CO₂ emissions (quantitative vs. qualitative) and the comparison framework related to the sustainable purchase decision (negative: alternative with more emissions than the average flight of the route vs. positive: alternative with less emissions than the average flight of the route), therefore it is a 2x2 experiment with four alternative scenarios. A pretest was run before the actual experiment to refine the experiment features and to check the manipulations. Afterward, a different sample of students answered the pre-test questionnaire aimed at recruiting the cases and measuring several pre-stimulus measures. One week later, students came to the neurolab at the University setting to be part of the experiment, made their decision regarding online purchases and answered the post-test survey. A final sample of 21 students was gathered. The committee of ethics of the institution approved the experiment. The results show that qualitative information generates more sustainable decisions (less contaminant alternative) than quantitative information. Moreover, evidence shows that subjects are more willing to choose the sustainable decision to be more ecological (comparison of the average with the less contaminant alternative) rather than to be less contaminant (comparison of the average with the more contaminant alternative). There are also interesting differences in the information processing variables from the eye tracker. Both the total time to make the choice and the specific times by area of interest (AOI) differ depending on the assigned scenario. These results allow for a better understanding of the factors that condition the decision of a traveler to be part of a VCO program and provide useful information for airline managers to promote these programs to reduce environmental impact.

Keywords: voluntary carbon offset, airline, online purchase, carbon emission, sustainability, randomized experiment

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Authors: Yung C. Lin, Kung D. Wu, Wei C. Shih, Jui P. Hung

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High speed and high precision machining have become the most important technology in manufacturing industry. The surface roughness of high precision components is regarded as the important characteristics of the product quality. However, machining chatter could damage the machined surface and restricts the process efficiency. Therefore, selection of the appropriate cutting conditions is of importance to prevent the occurrence of chatter. In addition, vibration of the spindle tool also affects the surface quality, which implies the surface precision can be controlled by monitoring the vibration of the spindle tool. Based on this concept, this study was aimed to investigate the influence of the machining conditions on the surface roughness and the vibration of the spindle tool. To this end, a series of machining tests were conducted on aluminum alloy. In tests, the vibration of the spindle tool was measured by using the acceleration sensors. The surface roughness of the machined parts was examined using white light interferometer. The response surface methodology (RSM) was employed to establish the mathematical models for predicting surface finish and tool vibration, respectively. The correlation between the surface roughness and spindle tool vibration was also analyzed by ANOVA analysis. According to the machining tests, machined surface with or without chattering was marked on the lobes diagram as the verification of the machining conditions. Using multivariable regression analysis, the mathematical models for predicting the surface roughness and tool vibrations were developed based on the machining parameters, cutting depth (a), feed rate (f) and spindle speed (s). The predicted roughness is shown to agree well with the measured roughness, an average percentage of errors of 10%. The average percentage of errors of the tool vibrations between the measurements and the predictions of mathematical model is about 7.39%. In addition, the tool vibration under various machining conditions has been found to have a positive influence on the surface roughness (r=0.78). As a conclusion from current results, the mathematical models were successfully developed for the predictions of the surface roughness and vibration level of the spindle tool under different cutting condition, which can help to select appropriate cutting parameters and to monitor the machining conditions to achieve high surface quality in milling operation.

Keywords: machining parameters, machining stability, regression analysis, surface roughness

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Authors: Hadia Abdel Aziz, Raghda El Ebrashi

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Business models are shaped by their design space or the environment they are designed to be implemented in. The rapidly changing economic, technological, political, regulatory and market external environment severely affects business logic. This is particularly true for social enterprises whose core mission is to transform their environments, and thus, their whole business logic revolves around the interchange between the enterprise and the environment. The context in which social business operates imposes different business design constraints while at the same time, open up new design opportunities. It is also affected to a great extent by the impact that successful enterprises generate; a continuous loop of interaction that needs to be managed through a dynamic capability in order to generate a lasting powerful impact. This conceptual research synthesizes and analyzes literature on social enterprise, social enterprise business models, business model innovation, business model design, and the open system view theory to propose a new business model design process for social enterprises that takes into account the critical role of environmental factors. This process would help the social enterprise develop a dynamic capability that ensures the alignment of its business model to its environmental context, thus, maximizing its probability of success.

Keywords: social enterprise, business model, business model design, business model environment

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Authors: Anik Sarminingsih, Krishna V. Pradana

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The failure of flood control system can be caused by various factors, such as not considering the uncertainty of designed flood causing the capacity of the flood control system is exceeded. The presence of the uncertainty factor is recognized as a serious issue in hydrological studies. Uncertainty in hydrological analysis is influenced by many factors, starting from reading water elevation data, rainfall data, selection of method of analysis, etc. In hydrological modeling selection of models and parameters corresponding to the watershed conditions should be evaluated by the hydraulic model in the river as a drainage channel. River cross-section capacity is the first defense in knowing the reliability of the flood control system. Reliability of river capacity describes the potential magnitude of flood risk. Case study in this research is Wulan River in Central Java. This river occurring flood almost every year despite some efforts to control floods such as levee, floodway and diversion. The flood-affected areas include several sub-districts, mainly in Kabupaten Kudus and Kabupaten Demak. First step is analyze the frequency of discharge observation from Klambu weir which have time series data from 1951-2013. Frequency analysis is performed using several distribution frequency models such as Gumbel distribution, Normal, Normal Log, Pearson Type III and Log Pearson. The result of the model based on standard deviation overlaps, so the maximum flood discharge from the lower return periods may be worth more than the average discharge for larger return periods. The next step is to perform a hydraulic analysis to evaluate the reliability of river capacity based on the flood discharge resulted from several methods. The selection of the design flood discharge of flood control system is the result of the method closest to bankfull capacity of the river.

Keywords: design flood, hydrological model, reliability, uncertainty, Wulan river

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Authors: Abdel Hadi Ebraheim

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This paper introduces a new extension of the Inverse Pareto distribution in the framework of Marshal-Olkin (1997) family of distributions. This model is capable of modeling various shapes of aging and failure data. The statistical properties of the new model are discussed. Several methods are used to estimate the parameters involved. Explicit expressions are derived for different types of moments of value in reliability analysis are obtained. Besides, the order statistics of samples from the new proposed model have been studied. Finally, the usefulness of the new model for modeling reliability data is illustrated using two real data sets with simulation study.

Keywords: pareto distribution, marshal-Olkin, reliability, hazard functions, moments, estimation

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Authors: Dua K. S. Y. Klaas, Monzur A. Imteaz, Ika Sudiayem, Elkan M. E. Klaas, Eldav C. M. Klaas

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Due to its porous nature, karst terrains – geomorphologically developed from dissolved formations, is vulnerable to water shortage and deteriorated water quality. Therefore, a solid comprehension on sub-surface flow of karst landscape is essential to assess the long-term availability of groundwater resources. In this paper, a single-continuum model using a finite difference model, MODLFOW, was constructed to represent an unconfined carbonate aquifer in a tropical karst island of Rote in Indonesia. The model, spatially discretized in 20 x 20 m grid cells, was calibrated and validated using available groundwater level and atmospheric variables. In the calibration and validation steps, Parameter Estimation (PEST) and geostatistical pilot point methods were employed to estimate hydraulic conductivity and specific yield values. The results show that the model is able to represent the sub-surface flow indicated by good model performances both in calibration and validation steps. The final model can be used as a robust representation of the system for future study on climate and land use scenarios.

Keywords: carbonate aquifer, karst, sub-surface flow, groundwater model

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Authors: Vigen Barkhudaryan

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The influence of external effects (γ-, UV–radiations, high temperature) in presence of air oxygen on structural transformations of low-density polyethylene (LDPE) have been investigated dependent on the polymers’ thickness, the intensity and the dose of external actions. The methods of viscosimetry, light scattering, turbidimetry and gelation measuring were used for this purpose. The comparison of influence of external effects on LDPE shows, that the destruction and cross-linking processes of macromolecules proceed simultaneously with all kinds of external effects. A remarkable growth of average molecular mass of LDPE along with the irradiation doses and heat treatment exposure growth was established. It was linear for the mass average molecular mass and at the initial doses is mainly the result of the increase of the macromolecular branching. As a result, the macromolecular hydrodynamic volumes have been changed, and therefore the dependence of viscosity average molecular mass on the doses was going through the minimum at initial doses. A significant change of molecular mass, sizes and shape of macromolecules of LDPE occurs under the influence of external effects. The influence is limited only by diffusion of oxygen during -irradiation and heat treatment. At UV–irradiation the influence is limited both by diffusion of oxygen and penetration of radiation. Consequently, the molecular transformations are deeper and evident in case of -irradiation, as soon as the polymer is transformed in a whole volume. It was also established, that the mechanism of molecular transformations in polymers from the surface layer distinctly differs from those of the sample deeper layer. A comparison of the results of these investigations allows us to conclude, that the mechanisms of influence of investigated external effects on polyethylene are similar.

Keywords: cross-linking, destruction, high temperature, LDPE, γ-radiations, UV-radiations

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Authors: Julianne Cai, Weili Xue, Yibin Wu

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Social media retailing (SMR) platforms have become popular nowadays. It is characterized by a creative combination of content creation and product selling, which differs from traditional e-tailing (TE) with product selling alone. Motivated by real-world practices like social media platforms “TikTok” and douyin.com, we endeavor to study if the SMR model performs better than the TE model in a monopoly setting. By building a stylized economic model, we find that the SMR model does not always outperform the TE model. Specifically, when the SMR platform collects less commission from the seller than the TE platform, the seller, consumers, and social welfare all benefit more from the SMR model. In contrast, the platform benefits more from the SMR model if and only if the creator’s social influence is high enough or the cost of content creation is small enough. For the incentive structure of the content rewards in the SMR model, we found that a strong incentive mechanism (e.g., the quadratic form) is more powerful than a weak one (e.g., the linear form). The previous one will encourage the creator to choose a much higher quality level of content creation and meanwhile allowing the platform, consumers, and social welfare to become better off. Counterintuitively, providing more generous content rewards is not always helpful for the creator (seller), and it may reduce her profit. Our findings will guide the platform to effectively design incentive mechanisms to boost the content creation and retailing in the SMR model and help the influencers efficiently create content, engage their followers (fans), and price their products sold on the SMR platform.

Keywords: content creation, creator economy, incentive strategy, platform retailing

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Authors: Saad M. Darwish

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Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However, these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: software quality, quality assurance, software certification model, software assessment

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Authors: Ochuko K. Overen, Edson L. Meyer

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Uncontrolled heat transfer between the inner and outer space of low-cost housings through the thermal envelope result in indoor thermal discomfort. As a result, an excessive amount of energy is consumed for space heating and cooling. Thermo-optical properties are the ability of paints to reduce the rate of heat transfer through the thermal envelope. The aim of this study is to analyze the thermal performance of a low-cost house with its walls inner surface coated with transparent infrared reflective paint. The thermo-optical properties of the paint were analyzed using Scanning Electron Microscopy/ Energy Dispersive X-ray spectroscopy (SEM/EDX), Fourier Transform Infra-Red (FTIR) and thermal photographic technique. Meteorological indoor and ambient parameters such as; air temperature, relative humidity, solar radiation, wind speed and direction of a low-cost house in Golf-course settlement, South Africa were monitored. The monitoring period covers both winter and summer period before and after coating. The thermal performance of the coated walls was evaluated using time lag and decrement factor. The SEM image shows that the coat is transparent to light. The presence of Al as Al2O and other elements were revealed by the EDX spectrum. Before coating, the average decrement factor of the walls in summer was found to be 0.773 with a corresponding time lag of 1.3 hours. In winter, the average decrement factor and corresponding time lag were 0.467 and 1.6 hours, respectively. After coating, the average decrement factor and corresponding time lag were 0.533 and 2.3 hour, respectively in summer. In winter, an average decrement factor of 1.120 and corresponding time lag of 3 hours was observed. The findings show that the performance of the coats is influenced by the seasons. With a 74% reduction in decrement factor and 1.4 time lag increase in winter, it implies that the coatings have more ability to retain heat within the inner space of the house than preventing heat flow into the house. In conclusion, the results have shown that transparent infrared reflective paint has the ability to reduce the propagation of heat flux through building walls. Hence, it can serve as a remedy to the poor thermal performance of low-cost housings in South Africa.

Keywords: energy efficiency, decrement factor, low-cost housing, paints, rural development, thermal comfort, time lag

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Authors: Hui Wei, Zheng Dong

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Object recognition has long been a challenging task in computer vision. Yet the human brain, with the ability to rapidly and accurately recognize visual stimuli, manages this task effortlessly. In the past decades, advances in neuroscience have revealed some neural mechanisms underlying visual processing. In this paper, we present a novel model inspired by the visual pathway in primate brains. This multi-layer neural network model imitates the hierarchical convergent processing mechanism in the visual pathway. We show that local image features generated by this model exhibit robust discrimination and even better generalization ability compared with some existing image descriptors. We also demonstrate the application of this model in an object recognition task on image data sets. The result provides strong support for the potential of this model.

Keywords: biological model, feature extraction, multi-layer neural network, object recognition

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Authors: Jérémy Philippe, Lucien Baldas, Batoul Attar, Jean-Charles Mare

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The proposed communication deals with the research and development of a rotary direct-drive servo valve for aerospace applications. A key challenge of the project is to downsize the electromagnetic torque motor by reducing the torque required to drive the rotary spool. It is intended to optimize the spool and the sleeve geometries by combining a Computational Fluid Dynamics (CFD) approach with commercial optimization software. The present communication addresses an important phase of the project, which consists firstly of gaining confidence in the simulation results. It is well known that the force needed to pilot a sliding spool valve comes from several physical effects: hydraulic forces, friction and inertia/mass of the moving assembly. Among them, the flow force is usually a major contributor to the steady-state (or Root Mean Square) driving torque. In recent decades, CFD has gradually become a standard simulation tool for studying fluid-structure interactions. However, in the particular case of high-pressure valve design, the authors have experienced that the calculated overall hydraulic force depends on the parameterization and options used to build and run the CFD model. To solve this issue, the authors have selected the standard case of the linear spool valve, which is addressed in detail in numerous scientific references (analytical models, experiments, CFD simulations). The first CFD simulations run by the authors have shown that the evolution of the equivalent discharge coefficient vs. Reynolds number at the metering orifice corresponds well to the values that can be predicted by the classical analytical models. Oppositely, the simulated flow force was found to be quite different from the value calculated analytically. This drove the authors to investigate minutely the influence of the studied domain and the setting of the CFD simulation. It was firstly shown that the flow recirculates in the inlet and outlet channels if their length is not sufficient regarding their hydraulic diameter. The dead volume on the uncontrolled orifice side also plays a significant role. These examples highlight the influence of the geometry of the fluid domain considered. The second action was to investigate the influence of the type of mesh, the turbulence models and near-wall approaches, and the numerical solver and discretization scheme order. Two approaches were used to determine the overall hydraulic force acting on the moving spool. First, the force was deduced from the momentum balance on a control domain delimited by the valve inlet and outlet and the spool walls. Second, the overall hydraulic force was calculated from the integral of pressure and shear forces acting at the boundaries of the fluid domain. This underlined the significant contribution of the viscous forces acting on the spool between the inlet and outlet orifices, which are generally not considered in the literature. This also emphasized the influence of the choices made for the implementation of CFD calculation and results analysis. With the step-by-step process adopted to increase confidence in the CFD simulations, the authors propose a set of best practices and recommendations for the efficient use of CFD to design high-pressure spool valves.

Keywords: computational fluid dynamics, hydraulic forces, servovalve, rotary servovalve

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Authors: Alastair Hales, Xi Jiang, Siming Zhang

Abstract:

Numerical methods are used to generate vortices in a domain. Through considered design, two counter-rotating vortices may interact and effectively drive one another downstream. This phenomenon is comparable to the vortex interaction that occurs in a region immediately downstream from two counter-oscillating piezoelectric (PE) fan blades. PE fans are small blades clamped at one end and driven to oscillate at their first natural frequency by an extremely low powered actuator. In operation, the high oscillation amplitude and frequency generate sufficient blade tip speed through the surrounding air to create downstream air flow. PE fans are considered an ideal solution for low power hot spot cooling in a range of small electronic devices, but a single blade does not typically induce enough air flow to be considered a direct alternative to conventional air movers, such as axial fans. The development of face-to-face PE fan arrays containing multiple blades oscillating in counter-phase to one another is essential for expanding the range of potential PE fan applications regarding the cooling of power electronics. Even in an unoptimised state, these arrays are capable of moving air volumes comparable to axial fans with less than 50% of the power demand. Replicating the airflow generated by face-to-face PE fan arrays without including the actual blades in the model reduces the process’s computational demands and enhances the rate of innovation and development in the field. Vortices are generated at a defined inlet using a time-dependent velocity profile function, which pulsates the inlet air velocity magnitude. This induces vortex generation in the considered domain, and these vortices are shown to separate and propagate downstream in a regular manner. The generation and propagation of a single vortex are compared to an equivalent vortex generated from a PE fan blade in a previous experimental investigation. Vortex separation is found to be accurately replicated in the present numerical model. Additionally, the downstream trajectory of the vortices’ centres vary by just 10.5%, and size and strength of the vortices differ by a maximum of 10.6%. Through non-dimensionalisation, the numerical method is shown to be valid for PE fan blades with differing parameters to the specific case investigated. The thorough validation methods presented verify that the numerical model may be used to replicate vortex formation from an oscillating PE fans blade. An investigation is carried out to evaluate the effects of varying the distance between two PE fan blade, pitch. At small pitch, the vorticity in the domain is maximised, along with turbulence in the near vicinity of the inlet zones. It is proposed that face-to-face PE fan arrays, oscillating in counter-phase, should have a minimal pitch to optimally cool nearby heat sources. On the other hand, downstream airflow is maximised at a larger pitch, where the vortices can fully form and effectively drive one another downstream. As such, this should be implemented when bulk airflow generation is the desired result.

Keywords: piezoelectric fans, low energy cooling, vortex formation, computational fluid dynamics

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Authors: Ross Guest, Bjarne Jensen

Abstract:

This paper analyses a potentially new consumption dividend from lower fertility arising from imperfect labour substitution by age. A smaller proportion of young workers relative to older workers raises relative youth wages given imperfect labour substitution by age. Discounted lifetime labour income rises which provides a consumption dividend. Simulation results are reported for the four Scandinavian countries, adopting a simple overlapping generations model. Imperfect labour substitution is modelled using a CRESH functional form of an aggregate labour index. The magnitudes of this new consumption dividend from a Low fertility projection compared with a high fertility projection are found to be approximately 4 percent annually, on average over the Scandinavian countries in the very long run, but somewhat lower in the short term. There is some sensitivity to the interest rate and the degree of consumption smoothing.

Keywords: fertility, consumption, productivity, labour substitution

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Authors: Sachin Jain, Daniel Perez-Astudillo, Dunia A. Bachour, Antonio P. Sanfilippo

Abstract:

The future of solar energy in Qatar is evolving steadily. Hence, high-quality spatial solar radiation data is of the uttermost requirement for any planning and commissioning of solar technology. Generally, two types of solar radiation data are available: satellite data and ground observations. Satellite solar radiation data is developed by the physical and statistical model. Ground data is collected by solar radiation measurement stations. The ground data is of high quality. However, they are limited to distributed point locations with the high cost of installation and maintenance for the ground stations. On the other hand, satellite solar radiation data is continuous and available throughout geographical locations, but they are relatively less accurate than ground data. To utilize the advantage of both data, a product has been developed here which provides spatial continuity and higher accuracy than any of the data alone. The popular satellite databases: National Solar radiation Data Base, NSRDB (PSM V3 model, spatial resolution: 4 km) is chosen here for merging with ground-measured solar radiation measurement in Qatar. The spatial distribution of ground solar radiation measurement stations is comprehensive in Qatar, with a network of 13 ground stations. The monthly average of the daily total Global Horizontal Irradiation (GHI) component from ground and satellite data is used for error analysis. The normalized root means square error (NRMSE) values of 3.31%, 6.53%, and 6.63% for October, November, and December 2019 were observed respectively when comparing in-situ and NSRDB data. The method is based on the Empirical Bayesian Kriging Regression Prediction model available in ArcGIS, ESRI. The workflow of the algorithm is based on the combination of regression and kriging methods. A regression model (OLS, ordinary least square) is fitted between the ground and NSBRD data points. A semi-variogram is fitted into the experimental semi-variogram obtained from the residuals. The kriging residuals obtained after fitting the semi-variogram model were added to NSRBD data predicted values obtained from the regression model to obtain the final predicted values. The NRMSE values obtained after merging are respectively 1.84%, 1.28%, and 1.81% for October, November, and December 2019. One more explanatory variable, that is the ground elevation, has been incorporated in the regression and kriging methods to reduce the error and to provide higher spatial resolution (30 m). The final GHI maps have been created after merging, and NRMSE values of 1.24%, 1.28%, and 1.28% have been observed for October, November, and December 2019, respectively. The proposed merging method has proven as a highly accurate method. An additional method is also proposed here to generate calibrated maps by using regression and kriging model and further to use the calibrated model to generate solar radiation maps from the explanatory variable only when not enough historical ground data is available for long-term analysis. The NRMSE values obtained after the comparison of the calibrated maps with ground data are 5.60% and 5.31% for November and December 2019 month respectively.

Keywords: global horizontal irradiation, GIS, empirical bayesian kriging regression prediction, NSRDB

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Authors: Idrissa Kayijuka

Abstract:

The logistic regression and Cox regression models (proportional hazard model) at present are being employed in the analysis of prospective epidemiologic research looking into risk factors in their application on chronic diseases. However, a theoretical relationship between the two models has been studied. By definition, Cox regression model also called Cox proportional hazard model is a procedure that is used in modeling data regarding time leading up to an event where censored cases exist. Whereas the Logistic regression model is mostly applicable in cases where the independent variables consist of numerical as well as nominal values while the resultant variable is binary (dichotomous). Arguments and findings of many researchers focused on the overview of Cox and Logistic regression models and their different applications in different areas. In this work, the analysis is done on secondary data whose source is SPSS exercise data on BREAST CANCER with a sample size of 1121 women where the main objective is to show the application difference between Cox regression model and logistic regression model based on factors that cause women to die due to breast cancer. Thus we did some analysis manually i.e. on lymph nodes status, and SPSS software helped to analyze the mentioned data. This study found out that there is an application difference between Cox and Logistic regression models which is Cox regression model is used if one wishes to analyze data which also include the follow-up time whereas Logistic regression model analyzes data without follow-up-time. Also, they have measurements of association which is different: hazard ratio and odds ratio for Cox and logistic regression models respectively. A similarity between the two models is that they are both applicable in the prediction of the upshot of a categorical variable i.e. a variable that can accommodate only a restricted number of categories. In conclusion, Cox regression model differs from logistic regression by assessing a rate instead of proportion. The two models can be applied in many other researches since they are suitable methods for analyzing data but the more recommended is the Cox, regression model.

Keywords: logistic regression model, Cox regression model, survival analysis, hazard ratio

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Authors: Saba Rahman, Arvind K. Jain, S. D. Bharti, T. K. Datta

Abstract:

The present study compares the semi-empirical wake-oscillator models that are used to predict vortex-induced vibration of structures. These models include those proposed by Facchinetti, Farshidian, and Dolatabadi, and Skop and Griffin. These models combine a wake oscillator model resembling the Van der Pol oscillator model and a single degree of freedom oscillation model. In order to use these models for estimating the top displacement of chimneys, the first mode vibration of the chimneys is only considered. The modal equation of the chimney constitutes the single degree of freedom model (SDOF). The equations of the wake oscillator model and the SDOF are simultaneously solved using an iterative procedure. The empirical parameters used in the wake-oscillator models are estimated using a newly developed approach, and response is compared with experimental data, which appeared comparable. For carrying out the iterative solution, the ode solver of MATLAB is used. To carry out the comparative study, a tall concrete chimney of height 210m has been chosen with the base diameter as 28m, top diameter as 20m, and thickness as 0.3m. The responses of the chimney are also determined using the linear model proposed by E. Simiu and the deterministic model given in Eurocode. It is observed from the comparative study that the responses predicted by the Facchinetti model and the model proposed by Skop and Griffin are nearly the same, while the model proposed by Fashidian and Dolatabadi predicts a higher response. The linear model without considering the aero-elastic phenomenon provides a less response as compared to the non-linear models. Further, for large damping, the prediction of the response by the Euro code is relatively well compared to those of non-linear models.

Keywords: chimney, deterministic model, van der pol, vortex-induced vibration

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Authors: Ahmad Idris, Armaya`u Suleiman Labo, Ado Yusuf Abdulfatah, Murtala Umar

Abstract:

Super pave is the short form of Superior Performing Asphalt Pavement and represents a basis for specifying component materials, asphalt mixture design and analysis, and pavement performance prediction. This new technology is the result of long research projects conducted by the strategic Highway Research program (SHRP) of the Federal Highway Administration. This research was aimed at examining the suitability of Aggregates found in Kano for used in super pave design method. Aggregates samples were collected from different sources in Kano Nigeria and their Engineering properties, as they relate to the SUPERPAVE design requirements were determined. The average result of Coarse Aggregate Angularity in Kano was found to be 87% and 86% of one fractured face and two or more fractured faces respectively with a standard of 80% and 85% respectively. Fine Aggregate Angularity average result was found to be 47% with a requirement of 45% minimum. A flat and elongated particle which was found to be 10% has a maximum criterion of 10%. Sand equivalent was found to be 51% with the criteria of 45% minimum. Strength tests were also carried out, and the results reflect the requirements of the standards. The tests include Impact value test, Aggregate crushing value and Aggregate Abrasion tests and the results are 27.5%, 26.7% and 13% respectively with a maximum criteria of 30%. Specific gravity was also carried out and the result was found to have an average value of 2.52 with a criterion of 2.6 to 2.9 and Water absorption was found to be 1.41% with maximum criteria of 0.6%. From the study, the result of the tests indicated that the aggregates properties have met the requirements of Super pave design method based on the specifications of ASTMD 5821, ASTM D 4791, AASHTO T176, AASHTO T33 and BS815.

Keywords: aggregates, construction, road design, super pave

Procedia PDF Downloads 238