Search results for: latent profile analysis

Authors: Bagher Rahimpour Cami, Hamid Hassanpour, Hoda Mashayekhi

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Nowadays websites provide a vast number of resources for users. Recommender systems have been developed as an essential element of these websites to provide a personalized environment for users. They help users to retrieve interested resources from large sets of available resources. Due to the dynamic feature of user preference, constructing an appropriate model to estimate the user preference is the major task of recommender systems. Profile matching and latent factors are two main approaches to identify user preference. In this paper, we employed the latent factor and profile matching to cluster the user profile and identify user preference, respectively. The method uses the Distance Dependent Chines Restaurant Process as a Bayesian nonparametric framework to extract the latent factors from the user profile. These latent factors are mapped to user interests and a weighted distribution is used to identify user preferences. We evaluate the proposed method using a real-world data-set that contains news tweets of a news agency (BBC). The experimental results and comparisons show the superior recommendation accuracy of the proposed approach related to existing methods, and its ability to effectively evolve over time.

Keywords: Content-based recommender systems, dynamic user modeling, extracting user interests, predicting user preference.

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Authors: Tomoya Okubo, Kuninori Nakamura, Shin-ichi Mayekawa

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In this research, a latent class vector model for pairwise data is formulated. As compared to the basic vector model, this model yields consistent estimates of the parameters since the number of parameters to be estimated does not increase with the number of subjects. The result of the analysis reveals that the model was stable and could classify each subject to the latent classes representing the typical scales used by these subjects.

Keywords: finite mixture models, latent class analysis, Thrustone's paired comparison method, vector model

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Authors: Malika Yaici, Kamel Hariche, Tim Clarke

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The relationship between eigenstructure (eigenvalues and eigenvectors) and latent structure (latent roots and latent vectors) is established. In control theory eigenstructure is associated with the state space description of a dynamic multi-variable system and a latent structure is associated with its matrix fraction description. Beginning with block controller and block observer state space forms and moving on to any general state space form, we develop the identities that relate eigenvectors and latent vectors in either direction. Numerical examples illustrate this result. A brief discussion of the potential of these identities in linear control system design follows. Additionally, we present a consequent result: a quick and easy method to solve the polynomial eigenvalue problem for regular matrix polynomials.

Keywords: Eigenvalues/Eigenvectors, Latent values/vectors, Matrix fraction description, State space description.

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Authors: Jian-hua Yeh, Shi-yi Kuo

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This paper discusses the classification process for medical data. In this paper, we use the data from ACM KDDCup 2008 to demonstrate our classification process based on latent topic discovery. In this data set, the target set and outliers are quite different in their nature: target set is only 0.6% size in total, while the outliers consist of 99.4% of the data set. We use this data set as an example to show how we dealt with this extremely biased data set with latent topic discovery and noise reduction techniques. Our experiment faces two major challenge: (1) extremely distributed outliers, and (2) positive samples are far smaller than negative ones. We try to propose a suitable process flow to deal with these issues and get a best AUC result of 0.98.

Keywords: classification, latent topics, outlier adjustment, feature scaling

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Authors: Phumelele P. Kubheka, Pius A. Owolawi, Gbolahan Aiyetoro

Abstract:

Twitter is one of the most popular social media platforms where users share their opinions on different subjects. Twitter can be considered a great source for mining text due to the high volumes of data generated through the platform daily. Many industries such as telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model in this experiment. A higher topic coherence score indicates better performance of the model.

Keywords: Big data, latent Dirichlet allocation, latent semantic indexing, Telco, topic modeling, Twitter.

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Authors: Narong Kulnides

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This research involved fingerprints on ballistics after shooting. Two objectives of research were as follow; (1) to study the duration of the existence of latent fingerprints on .38, .45, 9 mm and .223 cartridge case after shooting, and (2) to compare the effectiveness of the detection of latent fingerprints by Black Powder, Super Glue, Perma Blue and Gun Bluing. The latent fingerprint appearance were studied on .38, .45, 9 mm. and .223 cartridge cases before and after shooting with Black Powder, Super Glue, Perma Blue and Gun Bluing. The detection times were 3 minute, 6, 12, 18, 24, 30, 36, 42, 48, 54, 60, 66, 72, 78 and 84 hours respectively. As a result of the study, it can be conclude that

1. Before shooting, the detection of latent fingerprints on 38, .45, and 9 mm. and .223 cartridge cases with Black Powder, Super Glue, Perma Blue and Gun Bluing can detect the fingerprints at all detection times.
2. After shooting, the detection of latent fingerprints on .38, .45, 9 mm. and .223 cartridge cases with Black Powder, Super Glue did not appear. The detection of latent fingerprints on .38, .45, 9 mm. cartridge cases with Perma Blue and Gun Bluing were found 100% of the time and the detection of latent fingerprints on .223 cartridge cases with Perma Blue and Gun Bluing were found 40% and 46.67% of the time, respectively.

Keywords: Ballistic, Fingerprint, Shooting.

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Authors: Xiaochun Huang, Xuejun Zhao, Yun Zou, Feiyu Yang, Wenbin Liu, Nan Deng, Ming Zhang, Nengbin Cai

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A simple device termed infrared radiation (IR) was developed for rapid visualization of sweat fingerprints deposit on paper with blue light (450 nm, 11 W). In this approach, IR serves as the pretreatment device before the sweat fingerprints was illuminated by blue light. An annular blue light source was adopted for visualizing latent sweat fingerprints. Sample fingerprints were examined under various conditions after deposition, and experimental results indicate that the recovery rate of the latent sweat fingerprints is in the range of 50%-100% without chemical treatments. A mechanism for the observed visibility is proposed based on transportation and re-impregnation of fluorescer in paper at the region of water. And further exploratory experimental results gave the full support to the visible mechanism. Therefore, such a method as IR-pretreated in detecting latent fingerprints may be better for examination in the case where biological information of samples is needed for consequent testing.

Keywords: Forensic science, visualization, infrared radiation, blue light, latent sweat fingerprints, detection.

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Authors: Emmanuel U. Ohaegbulem, Felix N. Nwobi

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Alternative and simple computational arrangements in carrying out multivariate profile analysis when more than two groups (populations) are involved are presented. These arrangements have been demonstrated to not only yield equivalent results for the test statistics (the Wilks lambdas), but they have less computational efforts relative to other arrangements so far presented in the literature; in addition to being quite simple and easy to apply.

Keywords: Coincident profiles, g-group profile analysis, level profiles, parallel profiles, repeated measures MANOVA.

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Authors: Pamela-Zoe Topalli, Niina Junttila, Päivi M. Niemi, Klaus Ranta

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Adolescents’ biased perceptions about their social competence (SC), whether negatively or positively, serve to influence their socioemotional adjustment such as early feelings of social phobia (nowadays referred to as Social Anxiety Disorder-SAD). Despite the importance of biased self-perceptions in adolescents’ psychosocial adjustment, the extent to which discrepancies between self- and others’ evaluations of one’s SC are linked to social phobic symptoms remains unclear in the literature. This study examined the perceptual discrepancy profiles between self- and peers’ as well as between self- and teachers’ evaluations of adolescents’ SC and the interrelations of these profiles with self-reported social phobic symptoms. The participants were 390 3^rd graders (15 years old) of Finnish lower secondary school (50.8% boys, 49.2% girls). In contrast with variable-centered approaches that have mainly been used by previous studies when focusing on this subject, this study used latent profile analysis (LPA), a person-centered approach which can provide information regarding risk profiles by capturing the heterogeneity within a population and classifying individuals into groups. LPA revealed the following five classes of discrepancy profiles: i) extremely negatively biased perceptions of SC, ii) negatively biased perceptions of SC, iii) quite realistic perceptions of SC, iv) positively biased perceptions of SC, and v) extremely positively biased perceptions of SC. Adolescents with extremely negatively biased perceptions and negatively biased perceptions of their own SC reported the highest number of social phobic symptoms. Adolescents with quite realistic, positively biased and extremely positively biased perceptions reported the lowest number of socio-phobic symptoms. The results point out the negatively and the extremely negatively biased perceptions as possible contributors to social phobic symptoms. Moreover, the association of quite realistic perceptions with low number of social phobic symptoms indicates its potential protective power against social phobia. Finally, positively and extremely positively biased perceptions of SC are negatively associated with social phobic symptoms in this study. However, the profile of extremely positively biased perceptions might be linked as well with the existence of externalizing problems such as antisocial behavior (e.g. disruptive impulsivity). The current findings highlight the importance of considering discrepancies between self- and others’ perceptions of one’s SC in clinical and research efforts. Interventions designed to prevent or moderate social phobic symptoms need to take into account individual needs rather than aiming for uniform treatment. Implications and future directions are discussed.

Keywords: Adolescence, latent profile analysis, perceptual discrepancies, social competence, social phobia.

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Authors: Manish K Rathod, Jyotirmay Banerjee

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The storage of thermal energy as a latent heat of phase change material (PCM) has created considerable interest among researchers in recent times. Here, an attempt is made to carry out numerical investigations to analyze the performance of latent heat storage units (LHSU) employing phase change material. The mathematical model developed is based on an enthalpy formulation. Freezing time of PCM packed in three different shaped containers viz. rectangular, cylindrical and cylindrical shell is compared. The model is validated with the results available in the literature. Results show that for the same mass of PCM and surface area of heat transfer, cylindrical shell container takes the least time for freezing the PCM and this geometric effect is more pronounced with an increase in the thickness of the shell than that of length of the shell.

Keywords: Enthalpy Formulation, Latent heat storage unit(LHSU), Numerical Model, Phase change material (PCM)

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Authors: Radouane Elbahjaoui, Hamid El Qarnia

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Melting of Paraffin Wax (P116) dispersed with Al₂O₃ nanoparticles in a rectangular latent heat storage unit (LHSU) is numerically investigated. The storage unit consists of a number of vertical and identical plates of nano-enhanced phase change material (NEPCM) separated by rectangular channels in which heat transfer fluid flows (HTF: Water). A two dimensional mathematical model is considered to investigate numerically the heat and flow characteristics of the LHSU. The melting problem was formulated using the enthalpy porosity method. The finite volume approach was used for solving equations. The effects of nanoparticles’ volumetric fraction and the Reynolds number on the thermal performance of the storage unit were investigated.

Keywords: Nano-enhanced phase change material, phase change material, nanoparticles, latent heat storage unit, melting.

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Authors: YongXian, JIN

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Introducing survivability into embedded real-time system (ERTS) can improve the survivability power of the system. This paper mainly discusses about the survivability of ERTS. The first is the survivability origin of ERTS. The second is survivability analysis. According to the definition of survivability based on survivability specification and division of the entire survivability analysis process for ERTS, a survivability analysis profile is presented. The quantitative analysis model of this profile is emphasized and illuminated in detail, the quantifying analysis of system was showed helpful to evaluate system survivability more accurate. The third is platform design of survivability analysis. In terms of the profile, the analysis process is encapsulated and assembled into one platform, on which quantification, standardization and simplification of survivability analysis are all achieved. The fourth is survivability design. According to character of ERTS, strengthened design method is selected to realize system survivability design. Through the analysis of embedded mobile video-on-demand system, intrusion tolerant technology is introduced in whole survivability design.

Keywords: ERTS (embedded real-time system), survivability, quantitative analysis, survivability specification, intrusion tolerant

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Authors: Sidi Yang, Haiyi Zhang

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Twitter is a microblogging platform, where millions of users daily share their attitudes, views, and opinions. Using a probabilistic Latent Dirichlet Allocation (LDA) topic model to discern the most popular topics in the Twitter data is an effective way to analyze a large set of tweets to find a set of topics in a computationally efficient manner. Sentiment analysis provides an effective method to show the emotions and sentiments found in each tweet and an efficient way to summarize the results in a manner that is clearly understood. The primary goal of this paper is to explore text mining, extract and analyze useful information from unstructured text using two approaches: LDA topic modelling and sentiment analysis by examining Twitter plain text data in English. These two methods allow people to dig data more effectively and efficiently. LDA topic model and sentiment analysis can also be applied to provide insight views in business and scientific fields.

Keywords: Text mining, Twitter, topic model, sentiment analysis.

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Authors: V. Lukášová, P. Peukert, V. Votrubec

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Thermal conductivity in the x, y and z-directions was measured on a pultruded profile that was manufactured by the technology of pulling from glass fibers and a polyester matrix. The results of measurements of thermal conductivity showed considerable variability in different directions. The caused variability in thermal conductivity was expected due fraction variations. The cross-section of the pultruded profile was scanned. An image analysis illustrated an uneven distribution of the fibers and the matrix in the cross-section. The distribution of these inequalities was processed into a Voronoi diagram in the observed area of the pultruded profile cross-section. In order to verify whether the variation of the fiber volume fraction in the pultruded profile can affect its thermal conductivity, the numerical simulations in the ANSYS Fluent were performed. The simulation was based on the geometry reconstructed from image analysis. The aim is to quantify thermal conductivity numerically. Above all, images with different volume fractions were chosen. The results of the measured thermal conductivity were compared with the calculated thermal conductivity. The evaluated data proved a strong correlation between volume fraction and thermal conductivity of the pultruded profile. Based on presented results, a modification of production technology may be proposed.

Keywords: Numerical simulation, pultruded profile, volume fraction, thermal conductivity.

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Authors: Rishindra M. Sarviya, Ashish Agrawal

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Solar energy is available abundantly in the world, but it is not continuous and its intensity also varies with time. Due to above reason the acceptability and reliability of solar based thermal system is lower than conventional systems. A properly designed heat storage system increases the reliability of solar thermal systems by bridging the gap between the energy demand and availability. In the present work, two dimensional numerical simulation of the melting of heat storage material is presented in the horizontal annulus of double pipe latent heat storage system. Longitudinal fins were used as a thermal conductivity enhancement. Paraffin wax was used as a heat-storage or phase change material (PCM). Constant wall temperature is applied to heat transfer tube. Presented two-dimensional numerical analysis shows the movement of melting front in the finned cylindrical annulus for analyzing the thermal behavior of the system during melting.

Keywords: Latent heat, numerical study, phase change material, solar energy.

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Authors: Young-Su Ryu, Won-Gi Jeon, Byoung-Chul Song, Jae-Hong Park, Ki-Won Kwon

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In this paper, an open framework based smart energy storage system (ESS) profile for photovoltaic (PV)-ESS and uninterruptible power supply (UPS)-ESS is proposed and designed. An open framework based smart ESS is designed and developed for unifying the different interfaces among manufacturers. The smart ESS operates under the profile which provides the specifications of peripheral devices such as different interfaces and to the open framework. The profile requires well systemicity and expandability for addible peripheral devices. Especially, the smart ESS should provide the expansion with existing systems such as UPS and the linkage with new renewable energy technology such as PV. This paper proposes and designs an open framework based smart ESS profile for PV-ESS and UPS-ESS. The designed profile provides the existing smart ESS and also the expandability of additional peripheral devices on smart ESS such as PV and UPS.

Keywords: ESS, open framework, profile, PV, UPS.

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Authors: Shin-Hyung Cho, Dong-Kyu Kim, Seung-Young Kho

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Truck-involved crashes have higher crash severity than non-truck-involved crashes. There have been many studies about the frequency of crashes and the development of severity models, but those studies only analyzed the relationship between observed variables. To identify why more people are injured or killed when trucks are involved in the crash, we must examine to quantify the complex causal relationship between severity of the crash and risk factors by adopting the latent factors of crashes. The aim of this study was to develop a structural equation or model based on truck-involved and non-truck-involved crashes, including five latent variables, i.e. a crash factor, environmental factor, road factor, driver’s factor, and severity factor. To clarify the unique characteristics of truck-involved crashes compared to non-truck-involved crashes, a confirmatory analysis method was used. To develop the model, we extracted crash data from 10,083 crashes on Korean freeways from 2008 through 2014. The results showed that the most significant variable affecting the severity of a crash is the crash factor, which can be expressed by the location, cause, and type of the crash. For non-truck-involved crashes, the crash and environment factors increase severity of the crash; conversely, the road and driver factors tend to reduce severity of the crash. For truck-involved crashes, the driver factor has a significant effect on severity of the crash although its effect is slightly less than the crash factor. The multiple group analysis employed to analyze the differences between the heterogeneous groups of drivers.

Keywords: Crash severity, structural equation modeling, truck-involved crashes, multiple group analysis, crash on freeway.

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Authors: Pattamad Panedpojaman

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For fire safety purposes, the fire resistance and the structural behavior of reinforced concrete members are assessed to satisfy specific fire performance criteria. The available prescribed provisions are based on standard fire load. Under various fire scenarios, engineers are in need of both heat transfer analysis and structural analysis. For heat transfer analysis, the study proposed a modified finite difference method to evaluate the temperature profile within a cross section. The research conducted is limited to concrete sections exposed to a fire on their one side. The method is based on the energy conservation principle and a pre-determined power function of the temperature profile. The power value of 2.7 is found to be a suitable value for concrete sections. The temperature profiles of the proposed method are only slightly deviate from those of the experiment, the FEM and the FDM for various fire loads such as ASTM E 119, ASTM 1529, BS EN 1991-1-2 and 550 oC. The proposed method is useful to avoid incontinence of the large matrix system of the typical finite difference method to solve the temperature profile. Furthermore, design engineers can simply apply the proposed method in regular spreadsheet software.

Keywords: temperature profile, finite difference method, concrete section, one-side fire exposed, energy conservation

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Authors: Byung-Soo Shin, Nam-Seok Kim, Sang-Kyu Lee, O-Hyun Keum

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This analysis investigates the distortion of flow measurement and the increase of cavitation along orifice flowmeter. The analysis using the numerical method (CFD) validated the distortion of flow measurement through the inlet velocity profile considering the convergence and grid dependency. Realizable k-e model was selected and y+ was about 50 in this numerical analysis. This analysis also estimated the vulnerability of cavitation effect due to inlet velocity profile. The investigation concludes that inclined inlet velocity profile could vary the pressure which was measured at pressure tab near pipe wall and it led to distort the pressure values ranged from -3.8% to 5.3% near the orifice plate and to make the increase of cavitation. The investigation recommends that the fully developed inlet velocity flow is beneficial to accurate flow measurement in orifice flowmeter.

Keywords: Orifice, k-e model, CFD

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Authors: Zhen Cheng, Xinyu Dai, Shujian Huang, Jiajun Chen

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Recently, explanatory natural language inference has attracted much attention for the interpretability of logic relationship prediction, which is also known as explanation generation for Natural Language Inference (NLI). Existing explanation generators based on discriminative Encoder-Decoder architecture have achieved noticeable results. However, we find that these discriminative generators usually generate explanations with correct evidence but incorrect logic semantic. It is due to that logic information is implicitly encoded in the premise-hypothesis pairs and difficult to model. Actually, logic information identically exists between premise-hypothesis pair and explanation. And it is easy to extract logic information that is explicitly contained in the target explanation. Hence we assume that there exists a latent space of logic information while generating explanations. Specifically, we propose a generative model called Variational Explanation Generator (VariationalEG) with a latent variable to model this space. Training with the guide of explicit logic information in target explanations, latent variable in VariationalEG could capture the implicit logic information in premise-hypothesis pairs effectively. Additionally, to tackle the problem of posterior collapse while training VariaztionalEG, we propose a simple yet effective approach called Logic Supervision on the latent variable to force it to encode logic information. Experiments on explanation generation benchmark—explanation-Stanford Natural Language Inference (e-SNLI) demonstrate that the proposed VariationalEG achieves significant improvement compared to previous studies and yields a state-of-the-art result. Furthermore, we perform the analysis of generated explanations to demonstrate the effect of the latent variable.

Keywords: Natural Language Inference, explanation generation, variational auto-encoder, generative model.

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Authors: L. Hammadi, D. Boukhaloua

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In this study, a numerical model was developed to predict cavitation phenomena around a NACA0009 profile. The equations of the Rayleigh-Plesset and modified Rayleigh-Plesset are used to modeling the cavitation by bubble around a NACA0009 profile. The study shows that the distributions of pressures around extrados and intrados of profile for angle of incidence equal zero are the same. The study also shows that the increase in the angle of incidence makes it possible to differentiate the pressures on the intrados and the extrados.

Keywords: Cavitation, NACA0009 profile, flow, pressure coefficient.

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Authors: Said M. Easa, Shinya Kikuchi

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When the profile information of an existing road is missing or not up-to-date and the parameters of the vertical alignment are needed for engineering analysis, the engineer has to recreate the geometric design features of the road alignment using collected profile data. The profile data may be collected using traditional surveying methods, global positioning systems, or digital imagery. This paper develops a method that estimates the parameters of the geometric features that best characterize the existing vertical alignments in terms of tangents and the expressions of the curve, that may be symmetrical, asymmetrical, reverse, and complex vertical curves. The method is implemented using an Excel-based optimization method that minimizes the differences between the observed profile and the profiles estimated from the equations of the vertical curve. The method uses a 'wireframe' representation of the profile that makes the proposed method applicable to all types of vertical curves. A secondary contribution of this paper is to introduce the properties of the equal-arc asymmetrical curve that has been recently developed in the highway geometric design field.

Keywords: Optimization, parameters, data, reverse, spreadsheet, vertical curves

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Authors: A. Al-Sayyad, P. Lama, J. Bardon, P. Hirchenhahn, L. Houssiau, P. Plapper

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Composite metal–polymer materials, in particular titanium alloy (Ti-6Al-4V) to polyamide (PA6.6), fabricated by laser joining, have gained cogent interest among industries and researchers concerned with aerospace and biomedical applications. This work adopts infrared (IR) thermography technique to investigate effects of laser parameters used in the welding process on the three-dimensional temperature profile at the rear-side of titanium, at the region to be welded with polyamide. Cross sectional analysis of welded joints showed correlations between the morphology of titanium and polyamide at the weld zone with the corresponding temperature profile. In particular, spatial temperature profile was found to be correlated with the laser beam energy density, titanium molten pool width and depth, and polyamide heat affected zone depth.

Keywords: Laser welding, metals to polymers joining, process monitoring, temperature profile, thermography.

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Authors: Lippong Tan, Yuenting Kwok, Ahbijit Date, Aliakbar Akbarzadeh

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A numerical investigation has carried out to understand the melting characteristics of phase change material (PCM) in a fin type latent heat storage with the addition of embedded aluminum spiral fillers. It is known that melting performance of PCM can be significantly improved by increasing the number of embedded metallic fins in the latent heat storage system but to certain values where only lead to small improvement in heat transfer rate. Hence, adding aluminum spiral fillers within the fin gap can be an option to improve heat transfer internally. This paper presents extensive computational visualizations on the PCM melting patterns of the proposed fin-spiral fillers configuration. The aim of this investigation is to understand the PCM-s melting behaviors by observing the natural convection currents movement and melting fronts formation. Fluent 6.3 simulation software was utilized in producing twodimensional visualizations of melting fractions, temperature distributions and flow fields to illustrate the melting process internally. The results show that adding aluminum spiral fillers in Fin type latent heat storage can promoted small but more active natural convection currents and improve melting of PCM.

Keywords: Phase change material, thermal enhancement, aluminum spiral fillers, fins

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Authors: Praveen Kumar, Satish Kumar, Jashanpreet Singh

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Transportation of unrefined crude oil from the production unit to a refinery or large storage area by a pipeline is difficult due to the different properties of crude in various areas. Thus, the design of a crude oil pipeline is a very complex and time consuming process, when considering all the various parameters. There were three very important parameters that play a significant role in the transportation and processing pipeline design; these are: viscosity profile, temperature profile and the velocity profile of waxy crude oil through the crude oil pipeline. Knowledge of the Rheological computational technique is required for better understanding the flow behavior and predicting the flow profile in a crude oil pipeline. From these profile parameters, the material and the emulsion that is best suited for crude oil transportation can be predicted. Rheological computational fluid dynamic technique is a fast method used for designing flow profile in a crude oil pipeline with the help of computational fluid dynamics and rheological modeling. With this technique, the effect of fluid properties including shear rate range with temperature variation, degree of viscosity, elastic modulus and viscous modulus was evaluated under different conditions in a transport pipeline. In this paper, two crude oil samples was used, as well as a prepared emulsion with natural and synthetic additives, at different concentrations ranging from 1,000 ppm to 3,000 ppm. The rheological properties was then evaluated at a temperature range of 25 to 60 °C and which additive was best suited for transportation of crude oil is determined. Commercial computational fluid dynamics (CFD) has been used to generate the flow, velocity and viscosity profile of the emulsions for flow behavior analysis in crude oil transportation pipeline. This rheological CFD design can be further applied in developing designs of pipeline in the future.

Keywords: Natural surfactant, crude oil, rheology, CFD, viscosity.

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Authors: Chien-Chun Hung, Yao-Jen Teng, Yung-Sheng Tien, Yu-Tsung Tsai

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Microstrip antennas are conformable to planar and nonplanar surfaces, simple and inexpensive to fabricate using modern printed-circuit technology. Circular polarization of low-profile microstrip patch with high bandwidth is achieved in this research through the use of a three-cross-arms branch-line coupler with sequential rotated arrays, another low-profile antenna of hollow cylinder is also proposed and the function of reconnaissance with microstrip antenna on Mini UAV (unmanned aerial vehicle) are evaluated in practical flight test.

Keywords: low-profile antenna, Mini UAV, reconnaissance

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Authors: Veruska C. Dutra, Mary L. G. S. Senna, Felipe S. Spindler

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The State Park Jalapão - PEJ proved to be one of the protected areas that has attracted tourists from all over the world with its unique scenic landscapes. Although the region already has a considerable tourist flow, to our knowledge there is a lack of continuity of studies in the region capable of drawing a plan of activities, such as the profile of the tourist and analysis of their experiences in the region, carried out from 2006-2007. Therefore, this study was proposed to know the profile and experiences of tourists visiting the park today, making a connection with the earlier study, in order to generate subsidies to trace improvement actions. We conducted interviews with tourists in the main tourism season 2015. The results show that after eight years of carrying out the first study, there were no changes, highlighting the lack of a tourism plan for the park.

Keywords: Jalapão, profile tourist, level of satisfaction.

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods.

Keywords: Multinomial dirichlet classification model, Gaussian process priors, variational Bayesian approximation, Importance sampling, approximate posterior distribution, Marginal likelihood evidence.

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Authors: Jaime R. S. Fonseca

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Nevertheless the widespread application of finite mixture models in segmentation, finite mixture model selection is still an important issue. In fact, the selection of an adequate number of segments is a key issue in deriving latent segments structures and it is desirable that the selection criteria used for this end are effective. In order to select among several information criteria, which may support the selection of the correct number of segments we conduct a simulation study. In particular, this study is intended to determine which information criteria are more appropriate for mixture model selection when considering data sets with only categorical segmentation base variables. The generation of mixtures of multinomial data supports the proposed analysis. As a result, we establish a relationship between the level of measurement of segmentation variables and some (eleven) information criteria-s performance. The criterion AIC3 shows better performance (it indicates the correct number of the simulated segments- structure more often) when referring to mixtures of multinomial segmentation base variables.

Keywords: Quantitative Methods, Multivariate Data Analysis, Clustering, Finite Mixture Models, Information Theoretical Criteria, Simulation experiments.

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

Abstract:

In this paper, we propose the variational EM inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multiclass. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: Bayesian rule, Gaussian process classification model with multiclass, Gaussian process prior, human action classification, laplace approximation, variational EM algorithm.

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