Mixtures of Monotone Networks for Prediction

In many data mining applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. In this paper we consider partially monotone prediction problems, where the target variable depends monotonically on some of the input variables but not on all. We propose a novel method to construct prediction models, where monotone dependences with respect to some of the input variables are preserved by virtue of construction. Our method belongs to the class of mixture models. The basic idea is to convolute monotone neural networks with weight (kernel) functions to make predictions. By using simulation and real case studies, we demonstrate the application of our method. To obtain sound assessment for the performance of our approach, we use standard neural networks with weight decay and partially monotone linear models as benchmark methods for comparison. The results show that our approach outperforms partially monotone linear models in terms of accuracy. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.

The Analysis of Radial/Axial Error Motion on a Precision Rotation Stage

Rotating stages in semiconductor, display industry and many other fields require challenging accuracy to perform their functions properly. Especially, Axis of rotation error on rotary system is significant; such as the spindle error motion of the aligner, wire bonder and inspector machine which result in the poor state of manufactured goods. To evaluate and improve the performance of such precision rotary stage, unessential movements on the other 5 degrees of freedom of the rotary stage must be measured and analyzed. In this paper, we have measured the three translations and two tilt motions of a rotating stage with high precision capacitive sensors. To obtain the radial error motion from T.I.R (Total Indicated Reading) of radial direction, we have used Donaldson's reversal technique. And the axial components of the spindle tilt error motion can be obtained accurately from the axial direction outputs of sensors by Estler face motion reversal technique. Further more we have defined and measured the sensitivity of positioning error to the five error motions.

A New Fuzzy Decision Support Method for Analysis of Economic Factors of Turkey's Construction Industry

Imperfect knowledge cannot be avoided all the time. Imperfections may have several forms; uncertainties, imprecision and incompleteness. When we look to classification of methods for the management of imperfect knowledge we see fuzzy set-based techniques. The choice of a method to process data is linked to the choice of knowledge representation, which can be numerical, symbolic, logical or semantic and it depends on the nature of the problem to be solved for example decision support, which will be mentioned in our study. Fuzzy Logic is used for its ability to manage imprecise knowledge, but it can take advantage of the ability of neural networks to learn coefficients or functions. Such an association of methods is typical of so-called soft computing. In this study a new method was used for the management of imprecision for collected knowledge which related to economic analysis of construction industry in Turkey. Because of sudden changes occurring in economic factors decrease competition strength of construction companies. The better evaluation of these changes in economical factors in view of construction industry will made positive influence on company-s decisions which are dealing construction.

Application of Computational Intelligence Techniques for Economic Load Dispatch

This paper presents the applications of computational intelligence techniques to economic load dispatch problems. The fuel cost equation of a thermal plant is generally expressed as continuous quadratic equation. In real situations the fuel cost equations can be discontinuous. In view of the above, both continuous and discontinuous fuel cost equations are considered in the present paper. First, genetic algorithm optimization technique is applied to a 6- generator 26-bus test system having continuous fuel cost equations. Results are compared to conventional quadratic programming method to show the superiority of the proposed computational intelligence technique. Further, a 10-generator system each with three fuel options distributed in three areas is considered and particle swarm optimization algorithm is employed to minimize the cost of generation. To show the superiority of the proposed approach, the results are compared with other published methods.

On One Application of Hybrid Methods For Solving Volterra Integral Equations

As is known, one of the priority directions of research works of natural sciences is introduction of applied section of contemporary mathematics as approximate and numerical methods to solving integral equation into practice. We fare with the solving of integral equation while studying many phenomena of nature to whose numerically solving by the methods of quadrature are mainly applied. Taking into account some deficiency of methods of quadrature for finding the solution of integral equation some sciences suggested of the multistep methods with constant coefficients. Unlike these papers, here we consider application of hybrid methods to the numerical solution of Volterra integral equation. The efficiency of the suggested method is proved and a concrete method with accuracy order p = 4 is constructed. This method in more precise than the corresponding known methods.

Selective Wet-Etching of Amorphous/Crystallized Sb20se80 Thin Films

The selective wet-etching of amorphous and crystalline region of Sb20Se80 thin films was carried out using organic based solution e.g. amines. We report the development of an in situ real-time method to study the wet chemical etching process of thin films. Characterization of the structure and surface of films studied by X-ray diffraction, SEM and EBSD methods has been done and potential application suggested.

Visual-Graphical Methods for Exploring Longitudinal Data

Longitudinal data typically have the characteristics of changes over time, nonlinear growth patterns, between-subjects variability, and the within errors exhibiting heteroscedasticity and dependence. The data exploration is more complicated than that of cross-sectional data. The purpose of this paper is to organize/integrate of various visual-graphical techniques to explore longitudinal data. From the application of the proposed methods, investigators can answer the research questions include characterizing or describing the growth patterns at both group and individual level, identifying the time points where important changes occur and unusual subjects, selecting suitable statistical models, and suggesting possible within-error variance.

Using Environmental Sensitivity Index (ESI) to Assess and Manage Environmental Risks of Pipelines in GIS Environment: A Case Study ofa Near Coastline and Fragile Ecosystem Located Pipeline

Having a very many number of pipelines all over the country, Iran is one of the countries consists of various ecosystems with variable degrees of fragility and robusticity as well as geographical conditions. This study presents a state-of-the-art method to estimate environmental risks of pipelines by recommending rational equations including FES, URAS, SRS, RRS, DRS, LURS and IRS as well as FRS to calculate the risks. This study was carried out by a relative semi-quantitative approach based on land uses and HVAs (High-Value Areas). GIS as a tool was used to create proper maps regarding the environmental risks, land uses and distances. The main logic for using the formulas was the distance-based approaches and ESI as well as intersections. Summarizing the results of the study, a risk geographical map based on the ESIs and final risk score (FRS) was created. The study results showed that the most sensitive and so of high risk area would be an area comprising of mangrove forests located in the pipeline neighborhood. Also, salty lands were the most robust land use units in the case of pipeline failure circumstances. Besides, using a state-of-the-art method, it showed that mapping the risks of pipelines out with the applied method is of more reliability and convenience as well as relative comprehensiveness in comparison to present non-holistic methods for assessing the environmental risks of pipelines. The focus of the present study is “assessment" than that of “management". It is suggested that new policies are to be implemented to reduce the negative effects of the pipeline that has not yet been constructed completely

Observation and Study of Landslides Affecting the Tangier – Oued R’mel Motorway Segment

The motorway segment between Tangier and Oued R’mel has experienced, since the beginning of building works, significant instability and landslides linked to a number of geological, hydrogeological and geothermic factors affecting the different formations. The landslides observed are not fully understood, despite many studies conducted on this segment. This study aims at producing new methods to better explain the phenomena behind the landslides, taking into account the geotechnical and geothermic contexts. This analysis builds up on previous studies and geotechnical data collected in the field. The final body of data collected shall be processed through the Plaxis software for a better and customizable view of the landslide problems in the area, which will help tofind solutions and stabilize land in the area.

Rehabilitation of Reinforced Concrete Columns

In recent years, rehabilitation has been the subject of extensive research due to increased spending on building work and repair of built works. In all cases, it is absolutely essential to carry out methods of strengthening or repair of structural elements, and that following an inspection analysis and methodology of a correct diagnosis. The reinforced concrete columns are important elements in building structures. They support the vertical loads and provide bracing against the horizontal loads. This research about the behavior of reinforced concrete rectangular columns, rehabilitated by concrete liner, confinement FRP fabric, steel liner or cage formed by metal corners. It allows comparing the contributions of different processes used perspective section resistance elements rehabilitated compared to that is not reinforced or repaired. The different results obtained revealed a considerable gain in bearing capacity failure of reinforced sections cladding concrete, metal bracket, steel plates and a slight improvement to the section reinforced with fabric FRP. The use of FRP does not affect the weight of the structures, but the use of different techniques cladding increases the weight of elements rehabilitated and therefore the weight of the building which requires resizing foundations.

Extended Study on Removing Gaussian Noise in Mechanical Engineering Drawing Images using Median Filters

In this paper, an extended study is performed on the effect of different factors on the quality of vector data based on a previous study. In the noise factor, one kind of noise that appears in document images namely Gaussian noise is studied while the previous study involved only salt-and-pepper noise. High and low levels of noise are studied. For the noise cleaning methods, algorithms that were not covered in the previous study are used namely Median filters and its variants. For the vectorization factor, one of the best available commercial raster to vector software namely VPstudio is used to convert raster images into vector format. The performance of line detection will be judged based on objective performance evaluation method. The output of the performance evaluation is then analyzed statistically to highlight the factors that affect vector quality.

King Bhumibol Adulyadej’s “Learn Wisely” Concept: An Application to Instructional Design

This study is about an application of King Bhumibol Adulyadej’s “Learn Wisely” (LW) concept in instructional design and management process at the Faculty of Education, Suan Sunahdha Rajabhat University. The concept suggests four strategies for true learning. Related literature and significant LW methods in teaching and learning are also reviewed and then applied in designing a pedagogy learning module. The design has been implemented in three classrooms with a total of 115 sophomore student teachers. After one consecutive semester of managing and adjusting the process by instructors and experts using collected data from minutes, assessment of learning management, satisfaction and learning achievement of the students, it is found that the effective SSRU model of LW instructional method comprises of five steps.

Comparison of Pore Space Features by Thin Sections and X-Ray Microtomography

Microtomographic images and thin section (TS) images were analyzed and compared against some parameters of geological interest such as porosity and its distribution along the samples. The results show that microtomography (CT) analysis, although limited by its resolution, have some interesting information about the distribution of porosity (homogeneous or not) and can also quantify the connected and non-connected pores, i.e., total porosity. TS have no limitations concerning resolution, but are limited by the experimental data available in regards to a few glass sheets for analysis and also can give only information about the connected pores, i.e., effective porosity. Those two methods have their own virtues and flaws but when paired together they are able to complement one another, making for a more reliable and complete analysis.

Climate Change Finger Prints in Mountainous Upper Euphrates Basin

Climate change leading to global warming affects the earth through many different ways such as weather (temperature, precipitation, humidity and the other parameters of weather), snow coverage and ice melting, sea level rise, hydrological cycles, quality of water, agriculture, forests, ecosystems and health. One of the most affected areas by climate change is hydrology and water resources. Regions where majority of runoff consists of snow melt are more sensitive to climate change. The first step of climate change studies is to establish trends of significant climate variables including precipitation, temperature and flow data to detect any potential climate change impacts already happened. Two popular non-parametric trend analysis methods, Mann-Kendal and Spearman-s Rho were applied to Upper Euphrates Basin (Turkey) to detect trends of precipitation, temperatures (maximum, minimum and average) and streamflow.

Osteogenesis by Dextran Coating on and among Fibers of a Polyvinyl Formal Sponge

A scaffold is necessary for tooth regeneration because of its three-dimensional geometry. For restoration of defect, it is necessary for the scaffold to be prepared in the shape of the defect. Sponges made from polyvinyl alcohol with formalin cross-linking (PVF sponge) have been used for scaffolds for bone formation in vivo. To induce osteogenesis within the sponge, methods of growing rat bone marrow cells (rBMCs) among the fiber structures in the sponge might be considered. Storage of rBMCs among the fibers in the sponge coated with dextran (10 kDa) was tried. After seeding of rBMCs to PVF sponge immersed in dextran solution at 2 g/dl concentration, osteogenesis was recognized in subcutaneously implanted PVF sponge as a scaffold in vivo. The level of osteocalcin was 25.28±5.71 ng/scaffold and that of Ca was 129.20±19.69 µg/scaffold. These values were significantly higher than those in sponges without dextran coating (p

Framework of Malaysian Knowledge Society: Results from Dual Data Approach

This paper outlines the research conducted to propose na framework of 'Knowledge Society' (KS) in the Malaysian context. It is important to highlight that the emergence of KS is a result of the rapid growth in knowledge and information. However, the discussion of KS should not only be limited to the importance of knowledge, but a holistic KS is also determined by other imperative dimensions. This article discusses the results of a study conducted previously in Malaysia in order to identify the essential dimensions of KS, and consequently propose a KS framework in the Malaysian context. Two methods were employed, namely the Delphi technique and semi-structured interviews. The modified Delphi involved five rounds with ten experts, while the interviews were conducted with two prominent figures in Malaysia. The results support the proposed framework which contains seven major dimensions in order for Malaysia to become a KS in the future. The dimensions which are crucial for a holistic Malaysian KS are human capital, spirituality, economy, social, institutional, sustainability, and driven by the ICT.

Research of Dynamics Picking Mechanism of Sulzer Projectile Loom

One of the main and responsible units of Sulzer projectile loom is picking mechanism. It is specifically designed to accelerate projectile to speed of 25 m / s. Initial speed projectile of Sulzer projectile loom is independent of speed loom and determined the potential energy torsion rod. This paper investigates the dynamics picking mechanism of Sulzer projectile loom during its discharge. A result of calculation model, we obtain the law of motion lever of picking mechanism during its discharge. Construction of dynamic model the picking mechanism of Sulzer projectile loom on software complex SimulationX can make calculations for different thickness of torsion rods taking into account the backlashes in the connections, the dissipative forces and resistance forces

Investigation and Comparison of Energy Intensity in Iranian Transportation Industry (Case Study Road Transportation Sector)

Energy intensity(energy consumption intensity) is a global index which computes the required energy for producing a specific value of goods and services in each country. It is computed in terms of initial energy supply or final energy consumption. In this study (research) Divisia method is used to decompose energy consumption and energy intensity. This method decomposes consumption and energy intensity to production effects, structural and net intensity and could be done as time series or two-periodical. This study analytically investigates consumption changes and energy intensity on economical sectors of Iran and more specific on road transportation(rail road and road).Our results show that the contribution of structural effect (change in economical activities combination) is very low and the effect of net energy consumption has the higher contribution in consumption changes and energy intensity. In other words, the high consumption of energy is due to Intensity of energy consumption and is not to structural effect of transportation sector.

Analysis of Temperature Change under Global Warming Impact using Empirical Mode Decomposition

The empirical mode decomposition (EMD) represents any time series into a finite set of basis functions. The bases are termed as intrinsic mode functions (IMFs) which are mutually orthogonal containing minimum amount of cross-information. The EMD successively extracts the IMFs with the highest local frequencies in a recursive way, which yields effectively a set low-pass filters based entirely on the properties exhibited by the data. In this paper, EMD is applied to explore the properties of the multi-year air temperature and to observe its effects on climate change under global warming. This method decomposes the original time-series into intrinsic time scale. It is capable of analyzing nonlinear, non-stationary climatic time series that cause problems to many linear statistical methods and their users. The analysis results show that the mode of EMD presents seasonal variability. The most of the IMFs have normal distribution and the energy density distribution of the IMFs satisfies Chi-square distribution. The IMFs are more effective in isolating physical processes of various time-scales and also statistically significant. The analysis results also show that the EMD method provides a good job to find many characteristics on inter annual climate. The results suggest that climate fluctuations of every single element such as temperature are the results of variations in the global atmospheric circulation.

Analysing and Classifying VLF Transients

Monitoring lightning electromagnetic pulses (sferics) and other terrestrial as well as extraterrestrial transient radiation signals is of considerable interest for practical and theoretical purposes in astro- and geophysics as well as meteorology. Managing a continuous flow of data, automation of the analysis and classification process is important. Features based on a combination of wavelet and statistical methods proved efficient for this task and serve as input into a radial basis function network that is trained to discriminate transient shapes from pulse like to wave like. We concentrate on signals in the Very Low Frequency (VLF, 3 -30 kHz) range in this paper, but the developed methods are independent of this specific choice.