Search results for: cointegration approach in panel data

Authors: Melisa Mete, Gary Davies, Susan Whelan

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Maintaining a good employer brand image is crucial for companies since it has numerous advantages such as better recruitment, retention and employee engagement, and commitment. This study aims to understand the relationship between employer brand image and employee satisfaction and engagement in the British context. A panel survey data (N=228) is tested via the regression models from the Hayes (2012) PROCESS macro, in IBM SPSS 23.0. The results are statistically significant and proves that the more positive employer brand image, the greater employee’ engagement and satisfaction, and the greater is employee satisfaction, the greater their engagement.

Keywords: employer brand, employer brand image, employee engagement, employee satisfaction

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Authors: Meng Su

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High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

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Authors: Loong Qing Zhe, Foo Jing Heng

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A variety of data files are now available on the internet due to the advancement of technology across the globe today. As more and more data are being uploaded on the internet, people are becoming more concerned that their private data, particularly medical health records, are being compromised and sold to others for money. Hence, the accessibility and confidentiality of patients' medical records have to be protected through electronic means. Blockchain technology is introduced to offer patients security against adversaries or unauthorised parties. In the blockchain network, only authorised personnel or organisations that have been validated as nodes may share information and data. For any change within the network, including adding a new block or modifying existing information about the block, a majority of two-thirds of the vote is required to confirm its legitimacy. Additionally, a consortium permission blockchain will connect all the entities within the same community. Consequently, all medical data in the network can be safely shared with all authorised entities. Also, synchronization can be performed within the cloud since the data is real-time. This paper discusses an efficient method for storing and sharing electronic health records (EHRs). It also examines the framework of roles within the blockchain and proposes a new approach to maintain EHRs with keyword indexes to search for patients' medical records while ensuring data privacy.

Keywords: healthcare sectors, distributed system, blockchain, electronic health records (EHR)

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Authors: Meshari Aljohani, Stephan Olariu, Ravi Mukkamala

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Data is essential for enhancing the quality of life. Its value creates chances for users to profit from data sales and purchases. Users in data marketplaces, however, must share and trade data in a secure and trusted environment while maintaining their privacy. The first main contribution of this paper is to identify enabling technologies and challenges facing the development of decentralized data marketplaces. The second main contribution is to propose a decentralized data marketplace framework based on blockchain technology. The proposed framework enables sellers and buyers to transact with more confidence. Using a security deposit, the system implements a unique approach for enforcing honesty in data exchange among anonymous individuals. Before the transaction is considered complete, the system has a time frame. As a result, users can submit disputes to the arbitrators which will review them and respond with their decision. Use cases are presented to demonstrate how these technologies help data marketplaces handle issues and challenges.

Keywords: blockchain, data, data marketplace, smart contract, reputation system

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Authors: Halison da Silva Pereira, Ciro Sobrinho Campolina Martins, Vitor Mainenti Leal Lopes

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Long range performance is a goal for aircraft configuration optimization. Blended Wing Body (BWB) is presented in many works of literature as the most aerodynamically efficient design for a fixed-wing aircraft. Because of its high weight to thrust ratio, BWB is the ideal configuration for many Unmanned Aerial Vehicle (UAV) missions on geomatics applications. In this work, a BWB aerodynamic design for typical light geomatics payload is presented. Aerodynamic non-dimensional coefficients are predicted using low Reynolds number computational techniques (3D Panel Method) and wing parameters like aspect ratio, taper ratio, wing twist and sweep are optimized for high cruise performance and flight quality. The methodology of this work is a summary of tailless aircraft wing design and its application, with appropriate computational schemes, to light UAV subjected to low Reynolds number flows leads to conclusions like the higher performance and flight quality of thicker airfoils in the airframe body and the benefits of using aerodynamic twist rather than just geometric.

Keywords: blended wing body, low Reynolds number, panel method, UAV

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Authors: Assaad Ghazouani, Hedia Teraoui

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The purpose of this article is to try to see if the FDI actually contributes to technology transfer in Tunisia or are there other sources that can guarantee this transfer? The answer to this problem was gradual as we followed an approach using economic theory, the reality of Tunisia and econometric and statistical tools. We examined the relationship between technology transfer and FDI in Tunisia over a period of 40 years from 1970 to 2010. We estimated in two stages: first, a growth equation, then we have learned from this regression residue (proxy technology), secondly, we regressed on European FDI, exports of manufactures, imports of goods from the European Union in addition to other variables to test the robustness of the results and describing the level of infrastructure in the country. It follows from our study that technology transfer does not originate primarily and exclusively in the FDI and the latter is econometrically weakly with technology transfer and spill over effect of FDI does not seem to occur according to our results. However, the relationship between technology transfer and imports is negative and significant. Although this result is cons-intuitive, is recurrent in the literature of panel data. It has also given rise to intense debate on the microeconomic modelling as well as on the empirical applications. Technology transfer through trade or foreign investment has become a catalyst for growth recognized by numerous empirical studies in particular. However, the relationship technology transfer FDI is more complex than it appears. This complexity is due, primarily, but not exclusively to the close link between FDI and the characteristics of the host country. This is essentially the host's responsibility to establish general conditions, transparent and conducive to investment, and to strengthen human and institutional capacity necessary for foreign capital flows that can have real effects on growth.

Keywords: technology transfer, foreign direct investment, economics, finance

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Authors: Paul Gurr, Maik Moser

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In Europe, some countries recently abolished air passenger taxes (APT), while others issued or consider issuing an APT. From a fiscal perspective, APT can benefit the environment, while generating a vast amount of tax revenue with relatively low administration costs. However, they may have significant negative effects on the economy. Focusing on the German air passenger tax issued 2011, this work estimates the elasticity of tourism outflows using data on passenger departures from German airports between 2010 and 2016 aggregated by destination country. The results are obtained by estimating a model of the demand for outbound tourism. In line with theory, the regression results indicate a negative relationship between taxes and departures from Germany. Furthermore, on average, an increase of the air passenger tax rate results in a relatively higher decrease of passenger departures. The elasticity of tourism outflows can be used to estimate tax revenue changes and hence evaluate possible policy actions. Neglecting environmental reasons, the results suggest that tax revenue might be maximized by reducing the air passenger tax rate. Besides Germany, this work is also important for countries which have or consider implementing APT.

Keywords: air passenger tax, Germany, Outbound tourism, panel data

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Authors: Tetsuji Tanaka, Jin Guo

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The extant literature has not succeeded in uncovering the common determinants of price volatility transmissions of agricultural commodities from international to local markets, and further, has rarely investigated the role of self-sufficiency measures in the context of national food security. We analyzed various factors to determine the degree of price volatility transmissions of wheat, rice, and maize between world and domestic markets using GARCH models with dynamic conditional correlation (DCC) specifications and panel-feasible generalized least square models. We found that the grain autarky system has the potential to diminish volatility pass-throughs for three grain commodities. Furthermore, it was discovered that the substitutive commodity consumption behavior between maize and wheat buffers the volatility transmissions of both, but rice does not function as a transmission-relieving element, either for the volatilities of wheat or maize. The effectiveness of grain consumption substitution to insulate the pass-throughs from global markets is greater than that of cereal self-sufficiency. These implications are extremely beneficial for developing governments to protect their domestic food markets from uncertainty in foreign countries and as such, improves food security.

Keywords: food security, GARCH, grain self-sufficiency, volatility transmission

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Authors: Tijjani Bashir Musa

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The recent global crisis which suddenly results to Nigerian stock market crash revealed some peculiarities of Nigerian firms. Some firms in Nigeria are performing but their stock prices are not increasing while some firms are at the brink of collapse but their stock prices are increasing. Thus, this study examines the relationship between firm performance and stock price in Nigeria. The study covered the period of 2005 to 2009. This period is the period of stock boom and also marked the period of stock market crash as a result of global financial meltdown. The study is a panel study. A total of 140 firms were sampled from 216 firms listed on the Nigerian Stock Exchange (NSE). Data were collected from secondary source. These data were divided into four strata comprising the most performing stock, the least performing stock, most performing firms and the least performing firms. Each stratum contains 35 firms with characteristic of most performing stock, most performing firms, least performing stock and least performing firms. Multiple linear regression models were used to analyse the data while statistical/econometrics package of Stata 11.0 version was used to run the data. The study found that, relationship exists between selected firm performance parameters (operating efficiency, firm profit, earning per share and working capital) and stock price. As such firm performance gave sufficient information or has predictive power on stock prices movements in Nigeria for all the years under study.. The study recommends among others that Managers of firms in Nigeria should formulate policies and exert effort geared towards improving firm performance that will enhance stock prices movements.

Keywords: firm, Nigeria, performance, stock price

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Authors: Abhijith Asok

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This paper presents a generalized approach for the simple linear data transformation, Y=bX, through an integration of multidimensional coordinate geometry, vector space theory and polygonal geometry. The scaling is performed by adding an additional ’Dummy Dimension’ to the n-dimensional data, which helps plot two dimensional component-wise straight lines on pairs of dimensions. The end result is a set of scaled extensions of observations in any of the 2n spatial divisions, where n is the total number of applicable dimensions/dataset variables, created by shifting the n-dimensional plane along the ’Dummy Axis’. The derived scaling factor was found to be dependent on the coordinates of the common point of origin for diverging straight lines and the plane of extension, chosen on and perpendicular to the ’Dummy Axis’, respectively. This result indicates the geometrical interpretation of a linear data transformation and hence, opportunities for a more informed choice of the factor ’b’, based on a better choice of these coordinate values. The paper follows on to identify the effect of this transformation on certain popular distance metrics, wherein for many, the distance metric retained the same scaling factor as that of the features.

Keywords: data transformation, dummy dimension, linear transformation, scaling

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Authors: Nileshkumar Vaishnav, Aditya Tatu

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An algebraic framework for processing graph signals axiomatically designates the graph adjacency matrix as the shift operator. In this setup, we often encounter a problem wherein we know the filtered output and the filter coefficients, and need to find out the input graph signal. Solution to this problem using direct approach requires O(N3) operations, where N is the number of vertices in graph. In this paper, we adapt the spectral graph partitioning method for partitioning of graphs and use it to reduce the computational cost of the filtering problem. We use the example of denoising of the temperature data to illustrate the efficacy of the approach.

Keywords: graph signal processing, graph partitioning, inverse filtering on graphs, algebraic signal processing

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Authors: W. Badla

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A significant portion of the buildings constructed in Algeria is structural frames with infill panels which are usually considered as non structural components and are neglected in the analysis. However, these masonry panels tend to influence the structural response. Thus, these structures can be regarded as seismic risk buildings, although in the Algerian seismic code there is little guidance on the seismic evaluation of infilled frame buildings. In this study, three RC frames with 2, 4, and 8 story and subjected to three recorded Algerian accelerograms are studied. The diagonal strut approach is adopted for modeling the infill panels and a fiber model is used to model RC members. This paper reports on the seismic evaluation of RC frames with brick infill panels. The results obtained show that the masonry panels enhance the load lateral capacity of the buildings and the infill panel configuration influences the response of the structures.

Keywords: seismic design, RC frames, infill panels, non linear dynamic analysis

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Authors: Zhichao Jiao, Craig Farnham, Jihui Yuan, Kazuo Emura

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It is common to use the outdoor design weather data to select the air-conditioning capacity in the building design stage. The outdoor design weather data are usually comprised of multiple meteorological elements for a 24-hour period separately, but the dependency between the elements is not well considered, which may cause an overestimation of selecting air-conditioning capacity. Considering the dependency between the air temperature and global solar radiation, we used the copula approach to model the joint distributions of those two weather elements and suggest a new method of selecting more credible outdoor design conditions based on the specific simultaneous occurrence probability of air temperature and global solar radiation. In this paper, the 10-year period hourly weather data from 2001 to 2010 in Osaka, Japan, was used to analyze the dependency structure and joint distribution, the result shows that the Joe-Frank copula fit for almost all hourly data. According to calculating the simultaneous occurrence probability and the common exceeding probability of air temperature and global solar radiation, the results have shown that the maximum difference in design air temperature and global solar radiation of the day is about 2 degrees Celsius and 30W/m2, respectively.

Keywords: energy conservation, design weather database, HVAC, copula approach

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Authors: Masese Chuma Benard, Martin Onsiro Ronald

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Businesses have been using cloud computing more frequently recently because they wish to take advantage of its advantages. However, employing cloud computing also introduces new security concerns, particularly with regard to data security, potential risks and weaknesses that could be exploited by attackers, and various tactics and strategies that could be used to lessen these risks. This study examines data security issues on cloud computing amongst sme’s in Nairobi county, Kenya. The study used the sample size of 48, the research approach was mixed methods, The findings show that data owner has no control over the cloud merchant's data management procedures, there is no way to ensure that data is handled legally. This implies that you will lose control over the data stored in the cloud. Data and information stored in the cloud may face a range of availability issues due to internet outages; this can represent a significant risk to data kept in shared clouds. Integrity, availability, and secrecy are all mentioned.

Keywords: data security, cloud computing, information, information security, small and medium-sized firms (SMEs)

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Authors: John Monro, Suman Mishra

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Choosing foods for health benefits requires information that accurately represents the relative effectiveness of foods with respect to specific health end points, or with respect to responses leading to health outcomes. At present consumers must rely on nutrient composition data, and on health claims to guide them to healthy food choices. Nutrient information may be of limited usefulness because it does not reflect the effect of food structure and food component interactions – that is, whole food effects. Health claims demand stringent criteria that exclude most foods, even though most foods have properties through which they may contribute to positive health outcomes in a diet. In this presentation, we show how the functional efficacy of foods may be expressed in the same format as nutrients, with weight units, as virtual food components that allow a nutrition information panel to show not only what a food is, but also what it does. In the presentation, two body responses linked to well-being are considered – glycaemic response and colonic bulk – in order to illustrate the concept. We show how the nutrient information on available carbohydrates and dietary fibre values obtained by food analysis methods fail to provide information of the glycaemic potency or the colonic bulking potential of foods, because of failings in the methods and approach taken to food analysis. It is concluded that a category of food values that represent the functional efficacy of foods is required to accurately guide food choices for health.

Keywords: dietary fibre, glycaemic response, food values, food effects, health

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Authors: Saad Odeh

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Thermal performance is considered to be a key measure in building sustainability. One of the technologies used in the current building sustainable design is the rooftop solar PV power generators. The application of this type of technology has expanded vastly during the last five years in many countries. This paper studies the effect of roof shading developed by the solar PV panels on dwellings’ thermal performance. The analysis in this work is performed by using two types of packages: “AccuRate Sustainability” for rating the energy efficiency of residential building design, and “PVSYST” for the solar PV power system design. The former package is used to calculate the annual heating and cooling load, and the later package is used to evaluate the power production from the roof top PV system. The analysis correlates the electrical energy generated from the PV panels to the change in the heating and cooling load due to roof shading. Different roof orientation, roof inclination, roof insulation, as well as PV panel area are considered in this study. The analysis shows that the drop in energy efficiency due to the shaded area of the roof by PV panels is negligible compared to the energy generated by these panels.

Keywords: PV panel, thermal performance, roof shading, energy efficiency

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Authors: Pierre van Tonder, Christoff Kruger

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Modular concrete elements are used for retaining walls to provide lateral support. Depending on the retaining wall layout, these precast panels may be interlocking and may be tied into the soil backfill via geosynthetic strips. This study investigates the ultimate pull-out load increase, which is possible by adding varied diameter supplementary reinforcement through embedded anchor loops within concrete retaining wall panels. Full-scale panels used in practice have four embedded anchor points. However, only one anchor loop was embedded in the center of the experimental panels. The experimental panels had the same thickness but a smaller footprint (600mm x 600mm x 140mm) area than the full-sized panels to accommodate the space limitations of the laboratory and experimental setup. The experimental panels were also cast without any bending reinforcement as would typically be obtained in the full-scale panels. The exclusion of these reinforcements was purposefully neglected to evaluate the impact of a single bar reinforcement through the center of the anchor loops. The reinforcement bars had of 8 mm, 10 mm, 12 mm, and 12 mm. 30 samples of concrete panels with embedded anchor loops were tested. The panels were supported on the edges and the anchor loops were subjected to an increasing tensile force using an Instron piston. Failures that occurred were loop failures and panel failures and a mixture thereof. There was an increase in ultimate load vs. increasing diameter as expected, but this relationship persisted until the reinforcement diameter exceeded 10 mm. For diameters larger than 10 mm, the ultimate failure load starts to decrease due to the dependency of the reinforcement bond strength to the concrete matrix. Overall, the reinforced panels showed a 14 to 23% increase in the factor of safety. Using anchor loops of 66kN ultimate load together with Y10 steel reinforcement with bent ends had shown the most promising results in reducing concrete panel pull-out failure. The Y10 reinforcement had shown, on average, a 24% increase in ultimate load achieved. Previous research has investigated supplementary reinforcement around the anchor loops. This paper extends this investigation by evaluating supplementary reinforcement placed through the panel anchor loops.

Keywords: supplementary reinforcement, anchor loops, retaining panels, reinforced concrete, pull-out failure

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Authors: Richa Soni, Vibha Bhatnagar, N. K. Jain

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This study was conducted to develop a computer mediated programme for weight management and physical fitness and examining its efficacy in reducing weight and improving physical fitness in obese adults. A user friendly, computer based programme was developed to provide a simple, quick, easy and user-friendly method of assessing energy balance at individual level. The programme had four main sections viz. personal Profile, know about your weight, fitness and food exchange list. The computer programme was developed to provide facilities of creating individual profile, tracking meal and physical activities, suggesting nutritional and exercise requirements, planning calorie specific menus, keeping food diaries and revising the diet and exercise plans if needed. The programme was also providing information on obesity, underweight, physical fitness. An exhaustive food exchange list was also given in the programme to assist user to make right food choice decisions. The developed programme was evaluated by a panel of 15 experts comprising endocrinologists, nutritionists and diet counselors. Suggestions given by the experts were paned down and the entire programme was modified in light of suggestions given by the panel members and was reevaluated by the same panel of experts. For assessing the impact of the programme 22 obese subjects were selected purposively and randomly assigned to intervention group (n=12) and no information control group. (n=10). The programme group was asked to strictly follow the programme for one month. Significant reduction in the intake of energy, fat and carbohydrates was observed while intake of fruits, green leafy vegetables was increased. The programme was also found to be effective in reducing body weight, body fat percent and body fat mass whereas total body water and physical fitness scores improved significantly. There was no significant alteration observed in any parameters in the control group.

Keywords: body composition, body weight, computer programme, physical fitness

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Authors: Carlos Arias-Alcaide, Cristina Soguero-Ruiz, Paloma Santos-Álvarez, Adrián García-Romero, Inmaculada Mora-Jiménez

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Analysing clinical data with computers in such a way that have an impact on the practitioners’ workflow is a challenge nowadays. This paper provides a first approach for monitoring the health status of COVID-19 patients through the use of some biomarkers (blood tests) and the simplest Naïve Bayes classifier. Data of two Spanish hospitals were considered, showing the potential of our approach to estimate reasonable posterior probabilities even some days before the event.

Keywords: Bayesian model, blood biomarkers, classification, health tracing, machine learning, posterior probability

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Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

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Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: ring recognition, edge detection, X-ray computed tomography, dendrochronology

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Authors: Masaki Yamaguchi, Daimei Sasayama, Shinsuke Washizuka

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The goal of this study was to examine the possibility of salivary cytokines for the screening of attention deficit hyperactivity disorder (ADHD) in children. We carried out a case-control study, including 19 children with ADHD and 17 healthy children (controls). A multiplex bead array immunoassay was used to conduct a multi-analysis of 27 different salivary cytokines. Six salivary cytokines (interleukin (IL)-1β, IL-8, IL12p70, granulocyte colony-stimulating factor (G-CSF), interferon gamma (IFN-γ), and vascular endothelial growth factor (VEGF)) were significantly associated with the presence of ADHD (p < 0.05). An informative salivary cytokine panel was developed using VEGF by logistic regression analysis (odds ratio: 0.251). Receiver operating characteristic analysis revealed that assessment of a panel using VEGF showed “good” capability for discriminating between ADHD patients and controls (area under the curve: 0.778). ADHD has been hypothesized to be associated with reduced cerebral blood flow in the frontal cortex, due to reduced VEGF levels. Our study highlights the possibility of utilizing differential salivary cytokine levels for point-of-care testing (POCT) of biomarkers in children with ADHD.

Keywords: cytokine, saliva, attention deficit hyperactivity disorder, child

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Authors: Meriche Hacene

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Introduction: Allergy to animal hair is hypersensitivity to animal appendages to look for in front of any rhinoconjunctivitis or asthma. An anamnesis associated with the prick-tests makes it possible to guide the diagnosis, which will be supplemented in case of doubt by specific immunoglobulin E (IgE) assays. The objective of our study is to study the characteristics of patients sensitized to animal hair. Patients and methods: Retrospective study conducted on 105 adult patients and 69 children over a period of 3 years, including patients who received a specific IgE assay (respiratory panel and pediatric panel) by immunodot method. Result: 105 adult patients, including 74 women and 31 men, with an average age of 41 years, of which 8.5% had sensitization to animal hair (5 men and 4 women), namely: cat (5%), horse (4.7%) and dog (3.8%). For the 69 children, a slight female predominance was noted (56%), with an average age of 7.5 years, of which (13%) are sensitized to animal hair (5 girls and 4 boys): cat (10%), while awareness of dog and horse hair was less frequent with an identical prevalence of (4.34%). The dominant symptoms are rhinorrhea and sneezing for both categories, respectively (40% and 26.6% in adults and 23% for both symptoms in children). Cross-sensitization was observed in the 2 series: 1 single cat-dog and cat-horse case and 2 dog-horse cases in adults. In children, 100% of patients with sensitization to dog hair had cross-sensitization to cat hair, only 1 case was observed for cat-horse cross-reactivity. Conclusion This work shows that allergy to animal hair is common. Studies on more representative samples are recommended.

Keywords: specific IgE, allergy, cat, fed1

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Authors: Kanae Suzuki

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Handheld video games are popular communication tools among Japanese elementary school students today. This study aims to examine the effects of the use of handheld video games on interpersonal relationships of the students in real and virtual worlds. A two-wave panel survey was conducted for students of ten elementary schools at an interval of approximately six months. The survey questionnaire included questions about the average amount of time spent playing a handheld video game during the past one month, the frequency of communication with players during game play, and the interpersonal relationships, such as the number of real and virtual friends the students have. A multiple regression model was constructed for 324 students to examine causal relationships. The results indicated that the more frequently the students communicated with other players while playing games, the number of the real friends tended to increase. In contrast, no significant effect of the total time spent playing games was found on interpersonal relationships. The findings suggested that communication during game play is an important factor for improving interpersonal relationships of this age group.

Keywords: communication, real friend, social adjustment, virtual friend

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Authors: Jasmine Latiolais

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Much of the disaster-related literature finds a positive relationship between the impact of a natural disaster and the growth of wages. Panel datasets are often used to explore these effects. However, natural disasters do not impact a single variable in the economy. Rather, natural disasters affect all facets of the economy, simultaneously, upon impact. It is difficult to control for all factors that would be influenced by the impact of a natural disaster, which can lead to lead to omitted variable bias in those studies employing panel datasets. To address this issue of omitted variable bias, an interrupted time series analysis is used to test the short-run relationship between the impact of Hurricanes Katrina and Rita on parish wage levels in Southern Louisiana, inherently controlling for economic conditions. This study provides evidence that natural disasters do increase wages in the very short term (one quarter following the impact of the hurricane) but that these results are not seen in the longer term and are not robust. In addition, the significance of the coefficients changes depending on the parish. Overall, this study finds that previous literature on this topic may not be robust when considered through a time-series lens.

Keywords: economic recovery, local economies, local wage growth, natural disasters

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Authors: Touila Ahmed, Elie Louis, Hamza Gharbi

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State of the art question answering models have recently shown impressive performance especially in a zero-shot setting. This approach is particularly useful when confronted with a highly diverse domain such as the legal field, in which it is increasingly difficult to have a dataset covering every notion and concept. In this work, we propose a flexible generative question answering approach to contract analysis as well as a weakly supervised procedure to leverage unannotated data and boost our models’ performance in general, and their zero-shot performance in particular.

Keywords: question answering, contract analysis, zero-shot, natural language processing, generative models, self-supervision

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Authors: Yi-Lin Chen, Sheng-Jou Hung, Tsunglin Liu

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Adaptive immune system recognizes a wide range of antigens via expressing a large number of structurally distinct T cell and B cell receptor genes. The distinct receptor genes arise from complex rearrangements called V(D)J recombination, and constitute the immune repertoire. A common method of profiling immune repertoire is via amplifying recombined receptor genes using multiple primers and high-throughput sequencing. This multiplex-PCR approach is efficient; however, the resulting repertoire can be distorted because of primer bias. To eliminate primer bias, 5’ RACE is an alternative amplification approach. However, the application of RACE approach is limited by its low efficiency (i.e., the majority of data are non-regular receptor sequences, e.g., containing intronic segments) and lack of the convenient tool for analysis. We propose a computational tool that can correctly identify non-regular receptor sequences in RACE data via aligning receptor sequences against the whole gene instead of only the exon regions as done in all other tools. Using our tool, the remaining regular data allow for an accurate profiling of immune repertoire. In addition, a RACE approach is improved to yield a higher fraction of regular T-cell receptor sequences. Finally, we quantify the degree of primer bias of a multiplex-PCR approach via comparing it to the RACE approach. The results reveal significant differences in frequency of VJ combination by the two approaches. Together, we provide a new experimental and computation pipeline for an unbiased profiling of immune repertoire. As immune repertoire profiling has many applications, e.g., tracing bacterial and viral infection, detection of T cell lymphoma and minimal residual disease, monitoring cancer immunotherapy, etc., our work should benefit scientists who are interested in the applications.

Keywords: immune repertoire, T-cell receptor, 5' RACE, high-throughput sequencing, sequence alignment

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Authors: Ghaemi Reza, Abdollahi Hamid, Dashti Elham

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Cloud computing poses a diversity of challenges in data mining operation arising out of the dynamic structure of data distribution as against the use of typical database scenarios in conventional architecture. Due to immense number of users seeking data on daily basis, there is a serious security concerns to cloud providers as well as data providers who put their data on the cloud computing environment. Big data analytics use compute intensive data mining algorithms (Hidden markov, MapReduce parallel programming, Mahot Project, Hadoop distributed file system, K-Means and KMediod, Apriori) that require efficient high performance processors to produce timely results. Data mining algorithms to solve or optimize the model parameters. The challenges that operation has to encounter is the successful transactions to be established with the existing virtual machine environment and the databases to be kept under the control. Several factors have led to the distributed data mining from normal or centralized mining. The approach is as a SaaS which uses multi-agent systems for implementing the different tasks of system. There are still some problems of data mining based on cloud computing, including design and selection of data mining algorithms.

Keywords: cloud computing, data mining, computing models, cloud services

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Authors: Jaehyug Lee, Tae-Ho Song

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Vacuum insulation panel (VIP) can achieve very low thermal conductivity by evacuating its inner space. Heat transfer in the core materials of highly-evacuated VIP occurs by conduction through the solid structure and radiation through the pore. The effect of various scattering modes in combined conduction-radiation in VIP is investigated through numerical analysis. The discrete ordinates interpolation method (DOIM) incorporated with the commercial code FLUENT® is employed. It is found that backward scattering is more effective in reducing the total heat transfer while isotropic scattering is almost identical with pure absorbing/emitting case of the same optical thickness. For a purely scattering medium, the results agree well with additive solution with diffusion approximation, while a modified term is added in the effect of optical thickness to backward scattering is employed. For other scattering phase functions, it is also confirmed that backwardly scattering phase function gives a lower effective thermal conductivity. Thus, the materials with backward scattering properties, with radiation shields are desirable to lower the thermal conductivity of VIPs.

Keywords: combined conduction and radiation, discrete ordinates interpolation method, scattering phase function, vacuum insulation panel

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Authors: Tyler Gill, Sophia Daniels

Abstract:

The paper examines how accessing the spatial-temporal constrains of data will help inform policymakers and law enforcement officials. The authors utilize Chicago crime data from 2006-2016 to demonstrate how the Emerging Hot Spot Tool is an ideal hot spot clustering approach to analyze crime data. Traditional approaches include density maps or creating a spatial weights matrix to include the spatial-temporal constrains. This new approach utilizes a space-time implementation of the Getis-Ord Gi* statistic to visualize the data more quickly to make better decisions. The research will help complement socio-cultural research to find key patterns to help frame future policies and evaluate the implementation of prior strategies. Through this analysis, homicide trends and patterns are found more effectively and recommendations for use by non-traditional users of GIS are offered for real life implementation.

Keywords: crime mapping, emerging hot spot analysis, Getis-Ord Gi*, spatial-temporal analysis

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Authors: Sanaa Rashed Abdallah, Yasser F. Hassan

Abstract:

The paper will introduce an approach where a rough sets, gene expression programming and rough neural networks are used cooperatively for learning and classification support. The Objective of gene expression programming rough neural networks (GEP-RNN) approach is to obtain new classified data with minimum error in training and testing process. Starting point of gene expression programming rough neural networks (GEP-RNN) approach is an information system and the output from this approach is a structure of rough neural networks which is including the weights and thresholds with minimum classification error.

Keywords: rough sets, gene expression programming, rough neural networks, classification

Procedia PDF Downloads 385