Search results for: statistical inverse analysis

Authors: Linyu Wang, Mingjun Zhu, Jianhong Xiang, Hanyu Jiang

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Aiming at the problem that the spectral efficiency of hybrid precoding (HP) is too low in the current millimeter wave (mmWave) massive multiple input multiple output (MIMO) system, this paper proposes a digital joint equivalent channel hybrid precoding algorithm, which is based on the introduction of digital encoding matrix iteration. First, the objective function is expanded to obtain the relation equation, and the pseudo-inverse iterative function of the analog encoder is derived by using the pseudo-inverse method, which solves the problem of greatly increasing the amount of computation caused by the lack of rank of the digital encoding matrix and reduces the overall complexity of hybrid precoding. Secondly, the analog coding matrix and the millimeter-wave sparse channel matrix are combined into an equivalent channel, and then the equivalent channel is subjected to Singular Value Decomposition (SVD) to obtain a digital coding matrix, and then the derived pseudo-inverse iterative function is used to iteratively regenerate the simulated encoding matrix. The simulation results show that the proposed algorithm improves the system spectral efficiency by 10~20%compared with other algorithms and the stability is also improved.

Keywords: mmWave, massive MIMO, hybrid precoding, singular value decompositing, equivalent channel

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Authors: Asraful Islam

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Extended dependency graph (EDG) is a state-of-the-art isomorphic graph to represent normal logic programs (NLPs) that can characterize the consistency of NLPs by graph analysis. To construct the vertices and arcs of an EDG, additional renaming atoms and rules besides those the given program provides are used, resulting in higher space complexity compared to the corresponding traditional dependency graph (TDG). In this article, we propose an extended labeled dependency graph (ELDG) to represent an NLP that shares an equal number of nodes and arcs with TDG and prove that it is isomorphic to the domain program. The number of nodes and arcs used in the underlying dependency graphs are formulated to compare the space complexity. Results show that ELDG uses less memory to store nodes, arcs, and cycles compared to EDG. To exhibit the desirability of ELDG, firstly, the stable models of the kernel form of NLP are characterized by the admissible coloring of ELDG; secondly, a relation of the stable models of a kernel program with the handles of the minimal, odd cycles appearing in the corresponding ELDG has been established; thirdly, to our best knowledge, for the first time an inverse transformation from a dependency graph to the representing NLP w.r.t. ELDG has been defined that enables transferring analytical results from the graph to the program straightforwardly.

Keywords: normal logic program, isomorphism of graph, extended labelled dependency graph, inverse graph transforma-tion, graph colouring

Procedia PDF Downloads 181

Authors: Marisa Chrysochoou, James Mahoney, Kay Wille

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Pyrrhotite is an iron-sulfide mineral which releases sulfuric acid when exposed to water and oxygen. The presence of this mineral in concrete foundations across Connecticut and Massachusetts in the US is causing in some cases premature failure. This has resulted in a devastating crisis for all parties affected by this type of failure which can take up to 15-25 years before internal damage becomes visible on the surface. This study shares laboratory results aimed to investigate the fundamental mechanisms of pyrrhotite reaction and to further the understanding of its deterioration kinetics within concrete. This includes the following analyses: total sulfur, wavelength dispersive X-ray fluorescence, expansion, reaction rate combined with ion-chromatography, as well as damage evolution using electro-chemical acceleration. This information is coupled to a statistical analysis of over 150 analyzed concrete foundations. Those samples were obtained and process using a developed and validated sampling method that is minimally invasive to the foundation in use, provides representative samples of the concrete matrix across the entire foundation, and is time and cost-efficient. The processed samples were then analyzed using a developed modular testing method based on total sulfur and wavelength dispersive X-ray fluorescence analysis to quantify the amount of pyrrhotite. As part of the statistical analysis the results were grouped into the following three categories: no damage observed and no pyrrhotite detected, no damage observed and pyrrhotite detected and damaged observed and pyrrhotite detected. As expected, a strong correlation between amount of pyrrhotite, age of the concrete and damage is observed. Information from the laboratory investigation and from the statistical analysis of field samples will aid in forming a scientific basis to support the decision process towards sustainable financial and administrative solutions by state and local stakeholders.

Keywords: concrete, pyrrhotite, risk of failure, statistical analysis

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Authors: N. R. N. Idris, S. Baharom

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A meta-analysis may be performed using aggregate data (AD) or an individual patient data (IPD). In practice, studies may be available at both IPD and AD level. In this situation, both the IPD and AD should be utilised in order to maximize the available information. Statistical advantages of combining the studies from different level have not been fully explored. This study aims to quantify the statistical benefits of including available IPD when conducting a conventional summary-level meta-analysis. Simulated meta-analysis were used to assess the influence of the levels of data on overall meta-analysis estimates based on IPD-only, AD-only and the combination of IPD and AD (mixed data, MD), under different study scenario. The percentage relative bias (PRB), root mean-square-error (RMSE) and coverage probability were used to assess the efficiency of the overall estimates. The results demonstrate that available IPD should always be included in a conventional meta-analysis using summary level data as they would significantly increased the accuracy of the estimates. On the other hand, if more than 80% of the available data are at IPD level, including the AD does not provide significant differences in terms of accuracy of the estimates. Additionally, combining the IPD and AD has moderating effects on the biasness of the estimates of the treatment effects as the IPD tends to overestimate the treatment effects, while the AD has the tendency to produce underestimated effect estimates. These results may provide some guide in deciding if significant benefit is gained by pooling the two levels of data when conducting meta-analysis.

Keywords: aggregate data, combined-level data, individual patient data, meta-analysis

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Authors: Shinji Kawakura, Ryosuke Shibasaki

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We have been grouping and developing various kinds of practical, promising sensing applied systems concerning agricultural advancement and technical tradition (guidance). These include advanced devices to secure real-time data related to worker motion, and we analyze by methods of various advanced statistics and human dynamics (e.g. primary component analysis, Ward system based cluster analysis, and mapping). What is more, we have been considering worker daily health and safety issues. Targeted fields are mainly common farms, meadows, and gardens. After then, we observed and discussed time-line style, changing data. And, we made some suggestions. The entire plan makes it possible to improve both the aforementioned applied systems and farms.

Keywords: advanced statistical analysis, wearable sensing system, tradition of skill, supporting for workers, detecting crisis

Procedia PDF Downloads 371

Authors: Mohammad Abedi Sh. Khodamoradi

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The main aim of this research is to assess effective factors on citizens’ participations in plants clinics. Statistical society includes 153 citizens of region 15 of Tehran municipality, which in first six months of 2015 participated in educational classes held by Plant education center of Pardis and Pamchal Park located in region no.15. Sample size was calculated by Cochran formula and 10% was added to sample size in order to prevent probable problems and the final sample was n=124. Validity of questionnaire was calculated by professors of extension and education group in Oloom Tahghighat university of Tehran and reliability was 0.82 which was reported by editors. Data then was analyzed by SPSS software, and frequency table, comparing mean and correlation and regression also were assessed. Correlation was proved between age, type of activity and participation extent in plant clinics. Also participation would be increased in plant clinics due to positive and significant relation between educational factors and participation extent with improving educational factors. Moreover, there is inverse relation between literacy level and participation in level of 5%. Finally, regression analysis was used in order to predict each change which independent variable determines for dependent one.

Keywords: plants clinics, participations, Tehran, Iran

Procedia PDF Downloads 192

Authors: Zahid Ullah, Atlas Khan

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The rapid growth of data in diverse domains has created an urgent need for effective utilization of mathematical and statistical sciences in data analytics. This abstract explores the journey from theory to practice, emphasizing the importance of harnessing mathematical and statistical innovations to unlock the full potential of data analytics. Drawing on a comprehensive review of existing literature and research, this study investigates the fundamental theories and principles underpinning mathematical and statistical sciences in the context of data analytics. It delves into key mathematical concepts such as optimization, probability theory, statistical modeling, and machine learning algorithms, highlighting their significance in analyzing and extracting insights from complex datasets. Moreover, this abstract sheds light on the practical applications of mathematical and statistical sciences in real-world data analytics scenarios. Through case studies and examples, it showcases how mathematical and statistical innovations are being applied to tackle challenges in various fields such as finance, healthcare, marketing, and social sciences. These applications demonstrate the transformative power of mathematical and statistical sciences in data-driven decision-making. The abstract also emphasizes the importance of interdisciplinary collaboration, as it recognizes the synergy between mathematical and statistical sciences and other domains such as computer science, information technology, and domain-specific knowledge. Collaborative efforts enable the development of innovative methodologies and tools that bridge the gap between theory and practice, ultimately enhancing the effectiveness of data analytics. Furthermore, ethical considerations surrounding data analytics, including privacy, bias, and fairness, are addressed within the abstract. It underscores the need for responsible and transparent practices in data analytics, and highlights the role of mathematical and statistical sciences in ensuring ethical data handling and analysis. In conclusion, this abstract highlights the journey from theory to practice in harnessing mathematical and statistical sciences in data analytics. It showcases the practical applications of these sciences, the importance of interdisciplinary collaboration, and the need for ethical considerations. By bridging the gap between theory and practice, mathematical and statistical sciences contribute to unlocking the full potential of data analytics, empowering organizations and decision-makers with valuable insights for informed decision-making.

Keywords: data analytics, mathematical sciences, optimization, machine learning, interdisciplinary collaboration, practical applications

Procedia PDF Downloads 63

Authors: Ji Xi, Cheng Song Chin, Ehsan Mesbahi

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Structure-borne noise is an important aspect of offshore platform sound field. It can be generated either directly by vibrating machineries induced mechanical force, indirectly by the excitation of structure or excitation by incident airborne noise. Therefore, limiting of the transmission of vibration energy throughout the offshore platform is the key to control the structure-borne noise. This is usually done by introducing damping treatment to the steel structures. Two types of damping treatment using on-board are presented. By conducting a statistical energy analysis (SEA) simulation on a jack-up rig, the noise level in the source room, the neighboring rooms, and remote living quarter cabins are compared before and after the damping treatments been applied. The results demonstrated that, in the source neighboring room and living quarter area, there is a significant noise reduction with the damping treatment applied, whereas in the source room where air-borne sound predominates that of structure-borne sound, the impact is not obvious. The subsequent optimization design of damping treatment in the offshore platform can be made which enable acoustic professionals to implement noise control during the design stage for offshore crews’ hearing protection and habitant comfortability.

Keywords: statistical energy analysis, damping treatment, noise control, offshore platform

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Authors: Hammadi Larbi, Bergane Cheikh

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Drilling for oil is done through many mechanisms. The goal is first to dig deep and then, after arriving at the oil source, to simply suck it up. And for this, it is important to know the role of oil-based drilling muds, which had many benefits for the drilling tool and for drilling generally, and also and essentially to know the rheological behavior of the emulsion system in particular water-in-oil inverse emulsions (Water/crude oil). This work contributes to the improvement of the stability and rheological properties of crude oil-based drilling mud by organophilic clay. Experimental data from steady-state flow measurements of crude oil-based drilling mud are classically analyzed by the Herschel-Bulkley model. The effects of organophilic clay type VG69 are studied. Microscopic observation showed that the addition of quantities of organophilic clay type VG69 less than or equal to 3 g leads to the stability of inverse Water/Oil emulsions; on the other hand, for quantities greater than 3g, the emulsions are destabilized.

Keywords: drilling, organophilic clay, crude oil, stability

Procedia PDF Downloads 78

Authors: Igor V. Kuzminov

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According to its content, the proposed article is a collection of articles with comments and additions. All articles, in one way or another, have a connection with the Second Law of Thermodynamics. The content of the articles is given in a concise form. The articles were published in different journals at different times. Main topics are presented: gravity, biography of the Earth, physics of global warming-cooling cycles, multiverse. The articles are based on the laws of classical physics. Along the way, it should be noted that the Second Law of thermodynamics can be formulated as the Law of Matter Cooling. As it cools down, the processes of condensation, separation, and changes in the aggregate states of matter occur. In accordance with these changes, a picture of the world is being formed. Also, the main driving force of these processes is the inverse temperature dependence of the forces of gravity. As matter cools, the forces of gravity increase. The actions of these phenomena in the compartment form a picture of the world.

Keywords: gravitational forces, cooling of matter, inverse temperature dependence of gravitational forces, planetary model of the atom

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Authors: Nafiseh Ebrahimi, Amir Jafari

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The study of humanoid character is of great interest to researchers in the field of robotics and biomechanics. One might want to know the forces and torques required to move a limb from an initial position to the desired destination position. Inverse dynamics is a helpful method to compute the force and torques for an articulated body limb. It enables us to know the joint torques required to rotate a link between two positions. Our goal in this study was to control a human-like articulated manipulator for a specific task of path tracking. For this purpose, the human arm was modeled with a three-link planar manipulator activated by Hill muscle model. Applying a proportional controller, values of force and torques applied to the joints were calculated by inverse dynamics, and then joints and muscle forces trajectories were computed and presented. To be more accurate to say, the kinematics of the muscle-joint space was formulated by which we defined the relationship between the muscle lengths and the geometry of the links and joints. Secondary, the kinematic of the links was introduced to calculate the position of the end-effector in terms of geometry. Then, we considered the modeling of Hill muscle dynamics, and after calculation of joint torques, finally, we applied them to the dynamics of the three-link manipulator obtained from the inverse dynamics to calculate the joint states, find and control the location of manipulator’s end-effector. The results show that the human arm model was successfully controlled to take the designated path of an ellipse precisely.

Keywords: arm manipulator, hill muscle model, six-muscle model, three-link lodel

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Authors: Jefferson Hernandez, Juan Padilla

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Estimation of price elasticity of demand is a valuable tool for the task of price settling. Given its relevance, it is an active field for microeconomic and statistical research. Price elasticity in the industry of oil and gas, in particular for fuels sold in gas stations, has shown to be a challenging topic given the market and state restrictions, and underlying correlations structures between the types of fuels sold by the same gas station. This paper explores the Lotka-Volterra model for the problem for price elasticity estimation in the context of fuels; in addition, it is introduced multivariate random effects with the purpose of dealing with errors, e.g., measurement or missing data errors. In order to model the underlying correlation structures, the Inverse-Wishart, Hierarchical Half-t and LKJ distributions are studied. Here, the Bayesian paradigm through Markov Chain Monte Carlo (MCMC) algorithms for model estimation is considered. Simulation studies covering a wide range of situations were performed in order to evaluate parameter recovery for the proposed models and algorithms. Results revealed that the proposed algorithms recovered quite well all model parameters. Also, a real data set analysis was performed in order to illustrate the proposed approach.

Keywords: price elasticity, volume, correlation structures, Bayesian models

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Authors: S. J. Matlan, M. Mukhlisin, M. R. Taha

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Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and time-consuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study.

Keywords: soil-water characteristic curve (SWCC), statistical analysis, unsaturated soil, geotechnical engineering

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Authors: Vinay Mishra, Meena Malkani

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Objectives: To study the effect of physical maternal nutritional markers (viz. weight, height, gestational weight gain, BMI) and third-trimester haemoglobin concentration on anthropometry and cord blood haemoglobin of their newborn. Methods: Study area: Post-natal ward of a tertiary care hospital in an urban area. Study population: All post-partum women and their newborns. Sample size: 100. Maternal and neonatal data and anthropometric measurements were recorded in semi-structured case proforma. Data analysis: The data obtained was analysed using SPSS 20 software.The comparison between the groups was done using One-Way Analysis of Variance for two groups. For more than two groups comparisons further posthoc analysis was done using Tukey test. Pearson correlation coefficient was used for correlating the variables. A P value less than 0.05 was considered significant. Results: 1. Out of the 100 studied mothers, 52% were anaemic. 2. Cord blood haemoglobin values decreased significantly with the order of birth. 3. Cord blood haemoglobin of normal-weight newborns is significantly higher as compared to that of LBW newborns. 4. Cord blood haemoglobin has strong statistical significance with maternal anaemia. 5. Pre-pregnancy weight and gestational weight gain significantly influence the neonates anthropometry. Conclusions: 1. Birth order has a prominent inverse effect on the cord blood haemoglobin. 2. Majority of the expectant mothers are anaemic and give birth to LBW babies with reduced anthropometric markers. 3. Pre-pregnancy weight, height and gestational weight gain has a very significant impact on the neonatal anthropometry. 4. Thus, maternal nutrition during gestation and during the crucial periods of growth in the pre-child bearing age group has a very significant impact on foetal development.

Keywords: maternal nutrition, anthropometry, cord blood hemoglobin, newborn

Procedia PDF Downloads 367

Authors: Si Chen, Caroline Wiltshire, Bin Li

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This study statistically models the surface f0 contour and the underlying pitch target of a well-studied third sandhi tone of Mandarin Chinese. Although the growth curve analysis on the surface f0 contours indicates non-neutralization of this sandhi tone (T3) and the base T2, their underlying pitch targets do show neutralization. These results in Mandarin are also consistent with the perception of native speakers, where they cannot distinguish the third T3 from the base T2, compensating contextual variation. It is possible to use the proposed statistical procedure of testing underlying pitch targets to verify tone sandhi processes in other tonal languages.

Keywords: growth curve analysis, Mandarin Chinese, tone sandhi, underlying pitch target

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Authors: Zahra Amirhosseini, Mahtab Nameni

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The aim of this study was to investigate the relationship between growth, beta, and Company's cash. We calculate cash as dependent variable and growth opportunity and beta as independent variables. This study was based on an analysis of panel data. Population of the study is the companies which listed in Tehran Stock exchange and a financial data of 215 companies during the period 2010 to 2015 have been selected as the sample through systematic sampling. The results of the first hypothesis showed there is a significant relationship between growth opportunities cash holdings. Also according to the analysis done in the second hypothesis, we determined that there is an inverse relation between company risk and cash holdings.

Keywords: growth, beta, liquidity, company

Procedia PDF Downloads 363

Authors: J. G. Batista, L. J. de Bessa Neto, M. A. F. B. Lima, J. R. Leite, J. I. de Andrade Nunes

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The robot manipulator is an equipment that stands out for two reasons: Firstly because of its characteristics of movement and reprogramming, resembling the arm; secondly, by adding several areas of knowledge of science and engineering. The present work shows the development of the prototype of a robotic manipulator driven by a Programmable Logic Controller (PLC), having two degrees of freedom, which allows the movement and displacement of mechanical parts, tools, and objects in general of small size, through an electronic system. The aim is to study direct and inverse kinematics of the robotic manipulator to describe the translation and rotation between two adjacent links of the robot through the Denavit-Hartenberg parameters. Currently, due to the many resources that microcomputer systems offer us, robotics is going through a period of continuous growth that will allow, in a short time, the development of intelligent robots with the capacity to perform operations that require flexibility, speed and precision.

Keywords: Denavit-Hartenberg, direct and inverse kinematics, microcontrollers, robotic manipulator

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Authors: Dimitra Alexiou

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During the last 10 years, in spite of the economic crisis, the number of tourists arriving in Greece has increased, particularly during the tourist season from April to October. In this paper, the number of annual tourist arrivals is studied to explore their preferences with regard to the month of travel, the selected destinations, as well the amount of money spent. The collected data are processed with statistical methods, yielding numerical and graphical results. From the computation of statistical parameters and the forecasting with exponential smoothing, useful conclusions are arrived at that can be used by the Greek tourism authorities, as well as by tourist organizations, for planning purposes for the coming years. The results of this paper and the computed forecast can also be used for decision making by private tourist enterprises that are investing in Greece. With regard to the statistical methods, the method of Simple Exponential Smoothing of time series of data is employed. The search for a best forecast for 2017 and 2018 provides the value of the smoothing coefficient. For all statistical computations and graphics Microsoft Excel is used.

Keywords: tourism, statistical methods, exponential smoothing, land spatial planning, economy

Procedia PDF Downloads 232

Authors: Ramin Rostamkhani, Thurasamy Ramayah

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One of the most important topics of today’s industrial organizations is the challenging issue of supply chain management. In this field, scientists and researchers have published numerous practical articles and models, especially in the last decade. In this research, to our best knowledge, the discussion of data modeling of supply chain management components using well-known statistical distribution functions has been considered. The world of science owns mathematics, and showing the behavior of supply chain data based on the characteristics of statistical distribution functions is innovative research that has not been published anywhere until the moment of doing this research. In an analytical process, describing different aspects of functions including probability density, cumulative distribution, reliability, and failure function can reach the suitable statistical distribution function for each of the components of the supply chain management. It can be applied to predict the behavior data of the relevant component in the future. Providing a model to adapt the best statistical distribution function in the supply chain management components will be a big revolution in the field of the behavior of the supply chain management elements in today's industrial organizations. Demonstrating the final results of the proposed model by introducing the process capability indices before and after implementing it alongside verifying the approach through the relevant assessment as an acceptable verification is a final step. The introduced approach can save the required time and cost to achieve the organizational goals. Moreover, it can increase added value in the organization.

Keywords: analyzing, process capability indices, statistical distribution functions, supply chain management components

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Authors: Raef Cherif, Houssine Bakkali, Wafaa El Khatiri, Yacine Yaddaden

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The analysis of how vibrations are transmitted between components is required in many engineering applications. Transfer path analysis (TPA) has been a valuable engineering tool for solving Noise, Vibration, and Harshness (NVH problems using sub-structuring applications. The most challenging part of a TPA analysis is estimating the equivalent forces at the contact points between the active and the passive side. Component TPA in situ Method calculates these forces by inverting the frequency response functions (FRFs) measured at the passive subsystem, relating the motion at indicator points to forces at the interface. However, matrix inversion could pose problems due to the ill-conditioning of the matrices leading to inaccurate results. This paper establishes a TPA model for an academic system consisting of two plates linked by four springs. A numerical study has been performed to improve the interface forces identification. Several parameters are studied and discussed, such as the singular value rejection and the number and position of indicator points chosen and used in the inversion matrix.

Keywords: transfer path analysis, matrix inverse method, indicator points, SVD decomposition

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Authors: Nida Rizvi, Deeksha Katyal, Varun Joshi

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River Hindon is an important river catering the demand of highly populated rural and industrial cluster of western Uttar Pradesh, India. Water quality of river Hindon is deteriorating at an alarming rate due to various industrial, municipal and agricultural activities. The present study aimed at identifying the pollution sources and quantifying the degree to which these sources are responsible for the deteriorating water quality of the river. Various water quality parameters, like pH, temperature, electrical conductivity, total dissolved solids, total hardness, calcium, chloride, nitrate, sulphate, biological oxygen demand, chemical oxygen demand and total alkalinity were assessed. Water quality data obtained from eight study sites for one year has been subjected to the two multivariate techniques, namely, principal component analysis and cluster analysis. Principal component analysis was applied with the aim to find out spatial variability and to identify the sources responsible for the water quality of the river. Three Varifactors were obtained after varimax rotation of initial principal components using principal component analysis. Cluster analysis was carried out to classify sampling stations of certain similarity, which grouped eight different sites into two clusters. The study reveals that the anthropogenic influence (municipal, industrial, waste water and agricultural runoff) was the major source of river water pollution. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and elucidation of multifaceted data sets, recognition of pollution sources/factors and understanding temporal/spatial variations in water quality for effective river water quality management.

Keywords: cluster analysis, multivariate statistical techniques, river Hindon, water quality

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Authors: C. Temaneh-Nyah, F. A. Phiri, D. Karegeya

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This paper presents an algorithm for obtaining the map of subscriber’s density distribution for a mobile wireless communication network based on the actual subscriber's traffic data obtained from the base station. This is useful in statistical characterization of the mobile wireless network.

Keywords: electromagnetic compatibility, statistical analysis, simulation of communication network, subscriber density

Procedia PDF Downloads 286

Authors: Ramkumar Gunasekaran, John Cater, Vinod Suresh, Haribalan Kumar

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The main objective of this project is to develop a statistical shape model using principal component analysis that could be used for analyzing the shape of the human airway. The ultimate goal of this project is to identify geometric risk factors for diagnosis and management of Obstructive Sleep Apnoea (OSA). Anonymous CBCT scans of 25 individuals were obtained from the Otago Radiology Group. The airways were segmented between the hard-palate and the aryepiglottic fold using snake active contour segmentation. The point data cloud of the segmented images was then fitted with a bi-cubic mesh, and pseudo landmarks were placed to perform PCA on the segmented airway to analyze the shape of the airway and to find the relationship between the shape and OSA risk factors. From the PCA results, the first four modes of variation were found to be significant. Mode 1 was interpreted to be the overall length of the airway, Mode 2 was related to the anterior-posterior width of the retroglossal region, Mode 3 was related to the lateral dimension of the oropharyngeal region and Mode 4 was related to the anterior-posterior width of the oropharyngeal region. All these regions are subjected to the risk factors of OSA.

Keywords: medical imaging, image processing, FEM/BEM, statistical modelling

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Authors: Jung-Hong Hong, Jing-Cen Yang, Cai-Yu Ou

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The analysis of geographic inequality heavily relies on the use of location-enabled statistical data and quantitative measures to present the spatial patterns of the selected phenomena and analyze their differences. To protect the privacy of individual instance and link to administrative units, point-based datasets are spatially aggregated to area-based statistical datasets, where only the overall status for the selected levels of spatial units is used for decision making. The partition of the spatial units thus has dominant influence on the outcomes of the analyzed results, well known as the Modifiable Areal Unit Problem (MAUP). A new spatial reference framework, the Taiwan Geographical Statistical Classification (TGSC), was recently introduced in Taiwan based on the spatial partition principles of homogeneous consideration of the number of population and households. Comparing to the outcomes of the traditional township units, TGSC provides additional levels of spatial units with finer granularity for presenting spatial phenomena and enables domain experts to select appropriate dissemination level for publishing statistical data. This paper compares the results of respectively using TGSC and township unit on the mortality data and examines the spatial characteristics of their outcomes. For the mortality data between the period of January 1^st, 2008 and December 31^st, 2010 of the Taitung County, the all-cause age-standardized death rate (ASDR) ranges from 571 to 1757 per 100,000 persons, whereas the 2^nd dissemination area (TGSC) shows greater variation, ranged from 0 to 2222 per 100,000. The finer granularity of spatial units of TGSC clearly provides better outcomes for identifying and evaluating the geographic inequality and can be further analyzed with the statistical measures from other perspectives (e.g., population, area, environment.). The management and analysis of the statistical data referring to the TGSC in this research is strongly supported by the use of Geographic Information System (GIS) technology. An integrated workflow that consists of the tasks of the processing of death certificates, the geocoding of street address, the quality assurance of geocoded results, the automatic calculation of statistic measures, the standardized encoding of measures and the geo-visualization of statistical outcomes is developed. This paper also introduces a set of auxiliary measures from a geographic distribution perspective to further examine the hidden spatial characteristics of mortality data and justify the analyzed results. With the common statistical area framework like TGSC, the preliminary results demonstrate promising potential for developing a web-based statistical service that can effectively access domain statistical data and present the analyzed outcomes in meaningful ways to avoid wrong decision making.

Keywords: mortality map, spatial patterns, statistical area, variation

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Authors: Khald Anisse, Amina Radgui, Mohammed Rziza

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Tracking objects on video sequences is a very challenging task in many works in computer vision applications. However, there is no article that treats this topic in catadioptric vision. This paper is an attempt that tries to describe a new approach of omnidirectional images processing based on inverse stereographic projection in the half-sphere. We used the spherical model proposed by Gayer and al. For object tracking, our work is based on snake method, with optimization using the Greedy algorithm, by adapting its different operators. The algorithm will respect the deformed geometries of omnidirectional images such as spherical neighborhood, spherical gradient and reformulation of optimization algorithm on the spherical domain. This tracking method that we call "spherical snake" permitted to know the change of the shape and the size of object in different replacements in the spherical image.

Keywords: computer vision, spherical snake, omnidirectional image, object tracking, inverse stereographic projection

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Authors: Sherelle Lou Sumera Icutan, Sheila P. Cayabyab, Mary Jane Laruan, Paulo V. Cenas, Agustina R. Tactay

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This study critically analyzed the recent theses and dissertations of the Basic Education Curriculum (BEC) teachers who finished their graduate programs in selected higher educational institutions in Region I and CAR to be able to come up with a unified result from the varied results of the analyzed research works. All theses and dissertations completed by the educators/teachers/school personnel in the secondary and elementary public and private schools in Region 1 and CAR from AY 2003–2004 to AY 2007–2008 were classified first–as to work or non-work related; second–as to the different aspects of the curriculum: implementation, content, instructional materials, assessment instruments, learning, teaching, and others; third–as to being eligible for meta-analysis or not. Only studies found eligible for meta-analysis were subjected to the procedure. Aside from documentary analysis, the statistical treatments used in meta-analysis include the standardized effect size, Pearson’s correlation (r), the chi-square test of homogeneity and the inverse of the Fisher transformation. This study found out that the BEC-teachers usually probe on work-related researchers with topics that are focused on the learning performances of the students and on factors related to teaching. The development of instructional materials and assessment of implemented programs are also equally explored. However, there are only few researches on content and assessment instrument. Research findings on the areas of learning and teaching are the only aspects that are meta-analyzable. The research findings across studies in Region I and CAR of BEC teachers that focused on similar variables correlated to teaching do not vary significantly. On the contrary, research findings across studies in Region I and CAR that focused on variables correlated to learning performance significantly vary. Within each region, variations on the findings of research works related to learning performance that considered similar variables still exist. The combined finding on the effect size or relationship of the variables that are correlated to learning performance are low which means that effect is small but definite while the combined findings on the relationship of the variables correlated to teaching are slight or almost negligible.

Keywords: meta-analysis, BEC teachers, work-related research,

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Authors: C. Bejrananda, Y. Lee, T. Khamkaew

Abstract:

With the rise of the importance of air transportation in the 21st century, the role of economics in airport planning and decision-making has become more important to the urban structure and land value around it. Therefore, this research aims to examine the relationship between an airport and its impacts on the distribution of urban land uses and land values by applying the Alonso’s bid rent model. The New Bangkok International Airport (Suvarnabhumi International Airport) was taken as a case study. The analysis was made over three different time periods of airport development (after the airport site was proposed, during airport construction, and after the opening of the airport). The statistical results confirm that Alonso’s model can be used to explain the impacts of the new airport only for the northeast quadrant of the airport, while proximity to the airport showed the inverse relationship with the land value of all six types of land use activities through three periods of time. It indicates that the land value for commercial land use is the most sensitive to the location of the airport or has the strongest requirement for accessibility to the airport compared to the residential and manufacturing land use. Also, the bid-rent gradients of the six types of land use activities have declined dramatically through the three time periods because of the Asian Financial Crisis in 1997. Therefore, the lesson learned from this research concerns about the reliability of the data used. The major concern involves the use of different areal units for assessing land value for different time periods between zone block (1995) and grid block (2002, 2009). As a result, this affect the investigation of the overall trends of land value assessment, which are not readily apparent. In addition, the next concern is the availability of the historical data. With the lack of collecting historical data for land value assessment by the government, some of data of land values and aerial photos are not available to cover the entire study area. Finally, the different formats of using aerial photos between hard-copy (1995) and digital photo (2002, 2009) made difficult for measuring distances. Therefore, these problems also affect the accuracy of the results of the statistical analyses.

Keywords: airport development area, economic rents, spatial pattern, suvarnabhumi international airport

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Authors: Hasan Vural

Abstract:

Turkey is a favorable country to produce a great variety of agricultural products because of her different geographic and climatic conditions which have been used to divide the country into four main and seven sub regions. This classification into seven regions traditionally has been used in order to data collection and publication especially related with agricultural production. Afterwards, nine agricultural regions were considered. Recently, the governmental body which is responsible of data collection and dissemination (Turkish Institute of Statistics-TIS) has used 12 classes which include 11 sub regions and Istanbul province. This study aims to evaluate these classification efforts based on the acreage of ten main crops in a ten years time period (1996-2005). The panel data grouped in 11 subregions has been evaluated by cluster and multivariate statistical methods. It was concluded that from the agricultural production point of view, it will be rather meaningful to consider three main and eight sub-agricultural regions throughout the country.

Keywords: agricultural region, factorial analysis, cluster analysis,

Procedia PDF Downloads 378

Authors: Yeongyu Choi, Ju H. Park, Ho-Youl Jung

Abstract:

In this paper, we propose labeling based RANSAC algorithm for lane detection. Advanced driver assistance systems (ADAS) have been widely researched to avoid unexpected accidents. Lane detection is a necessary system to assist keeping lane and lane departure prevention. The proposed vision based lane detection method applies Canny edge detection, inverse perspective mapping (IPM), K-means algorithm, mathematical morphology operations and 8 connected-component labeling. Next, random samples are selected from each labeling region for RANSAC. The sampling method selects the points of lane with a high probability. Finally, lane parameters of straight line or curve equations are estimated. Through the simulations tested on video recorded at daytime and nighttime, we show that the proposed method has better performance than the existing RANSAC algorithm in various environments.

Keywords: Canny edge detection, k-means algorithm, RANSAC, inverse perspective mapping

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Authors: Lukas Vierus, Thomas Schuster

Abstract:

A general framework is examined for dynamic tensor field tomography within an inhomogeneous medium characterized by refraction and absorption, treated as an inverse source problem concerning the associated transport equation. Guided by Fermat’s principle, the Riemannian metric within the specified domain is determined by the medium's refractive index. While considerable literature exists on the inverse problem of reconstructing a tensor field from its longitudinal ray transform within a static Euclidean environment, limited inversion formulas and algorithms are available for general Riemannian metrics and time-varying tensor fields. It is established that tensor field tomography, akin to an inverse source problem for a transport equation, persists in dynamic scenarios. Framing dynamic tensor tomography as an inverse source problem embodies a comprehensive perspective within this domain. Ensuring well-defined forward mappings necessitates establishing existence and uniqueness for the underlying transport equations. However, the bilinear forms of the associated weak formulations fail to meet the coercivity condition. Consequently, recourse to viscosity solutions is taken, demonstrating their unique existence within suitable Sobolev spaces (in the static case) and Sobolev-Bochner spaces (in the dynamic case), under a specific assumption restricting variations in the refractive index. Notably, the adjoint problem can also be reformulated as a transport equation, with analogous results regarding uniqueness. Analytical solutions are expressed as integrals over geodesics, facilitating more efficient evaluation of forward and adjoint operators compared to solving partial differential equations. Certainly, here's the revised sentence in English: Numerical experiments are conducted using a Nesterov-accelerated Landweber method, encompassing various fields, absorption coefficients, and refractive indices, thereby illustrating the enhanced reconstruction achieved through this holistic modeling approach.

Keywords: attenuated refractive dynamic ray transform of tensor fields, geodesics, transport equation, viscosity solutions

Procedia PDF Downloads 13