Search results for: VSS (Vector Space Similarity)

Authors: Teng Zhang, Shenshi Huang, Gang Xu, Xuelin Zhang, Shouxiang Lu

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With the acceleration of urbanization and the increasing of the population in the city, the evacuation of pedestrians suffering from disaster environments such as fire in a room or other limited space becomes a vital issue in modern society. Mice have been used in experimental crowd evacuation in recent years for its good similarities to human in physical structure and stress reaction. In this study, the effect of experience or memory on the collective behavior of mice was explored. To help mice familiarize themselves with the design of the space and the stimulus caused by smoke, we trained them repeatedly for 2 days so that they can escape from the emergency conditions as soon as possible. The escape pattern, trajectories, walking speed, turning angle and mean individual escape time of mice in each training trail were analyzed. We found that mice can build memory quickly after the first trial on the first day. On the second day, the evacuation of mice was maintained in a stable and efficient state. Meanwhile, the group with size of 30 (G30) had a shorter mean individual escape time compared with G12. Furthermore, we tested the experience of evacuation skill of mice after several days. The results showed that the mice can hold the experience or memory over 3 weeks. We proposed the importance of experience of evacuation skill and the research of training methods in experimental evacuation of mice. The results can deepen our understanding of collective behavior of mice and conduce to the establishment of animal models in the study of pedestrian crowd dynamics in emergency conditions.

Keywords: experience, evacuation, mice, group size, behavior

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Authors: Desiree Di Marco

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The aim of this work is to show through the lens of art first which kind of reality was the one represented through fascist maps, and second to study the impact of the fascist regime’s cartography (FRC) on observers eye’s. In this study, it is assumed that the FRC’s representation of reality was simplified, timeless, and even a-spatial because it underrates the concept of territoriality. Cubism and Picasso’s paintings will be used as counter-examples to mystify fascist cartography’s ideological assumptions. The difference between the gaze of an observer looking at the surface of a fascist map and the gaze of someone observing a Picasso painting is impressive. Because there is always something dark, hidden, behind and inside a map, the world of fascist maps was a world built starting from the observation of a “window” that distorted reality and trapped the eyes of the observers. Moving across the map, they seem as if they were hypnotized. Cartohypnosis is the state in which the observer finds himself enslaved by the attractive force of the map, which uses a sort of “magic” geography, a geography that, by means of symbolic language, never has as its primary objective the attempt to show us reality in its complexity, but that of performing for its audience. Magical geography and hypnotic cartography in fascism blended together, creating an almost mystical, magical relationship that demystified reality to reduce the world to a conquerable space. This reduction offered the observer the possibility of conceiving new dimensions: of the limit, of the boundary, elements with which the subject felt fully involved and in which the aesthetic force of the images demonstrated all its strength. But in the early 20th century, the combination of art and cartography gave rise to new possibilities. Cubism which, more than all the other artistic currents showed us how much the observation of reality from a single point of view falls within dangerous logic, is an example. Cubism was an artistic movement that brought about a profound transformation in pictorial culture. It was not only a revolution of pictorial space, but it was a revolution of our conception of pictorial space. Up until that time, men and women were more inclined to believe in the power of images and their representations. Cubist painters rebelled against this blindness by claiming that art must always offer an alternative. Indeed the contribution of this work is precisely to show how art can be able to provide alternatives to even the most horrible regimes and the most atrocious human misfortunes. It also enriches the field of cartography because it "reassures" it by showing how much good it can be for cartography if also for other disciplines come close. Only in this way researcher can increase the chances for the cartography of a greater diffusion at the academic level.

Keywords: cartography, Picasso, fascism, culture

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Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath

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Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.

Keywords: convolutional autoencoder, anomaly detection, web application, FLASK

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Authors: Ibrahim Ilker Ozyigit, Ertugrul Filiz, Seda Birbilener, Semsettin Kulac, Zeki Severoglu

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In this study, we have performed genetic diversity analysis of Tilia tomentosa genotypes by using randomly amplified polymorphic DNA (RAPD) primers. A total of 28 genotypes, including 25 members from the urban ecosystem and 3 genotypes from forest ecosystem as outgroup were used. 8 RAPD primers produced a total of 53 bands, of which 48 (90.6 %) were polymorphic. Percentage of polymorphic loci (P), observed number of alleles (Na), effective number of alleles (Ne), Nei's (1973) gene diversity (h), and Shannon's information index (I) were found as 94.29 %, 1.94, 1.60, 0.34, and 0.50, respectively. The unweighted pair-group method with arithmetic average (UPGMA) cluster analysis revealed that two major groups were observed. The genotypes of urban and forest ecosystems showed a high genetic similarity between 28% and 92% and these genotypes did not separate from each other in UPGMA tree. Also, urban and forest genotypes clustered together in principal component analysis (PCA).

Keywords: Tilia tomentosa, genetic diversity, urban ecosystem, RAPD, UPGMA

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Authors: Jimena Alarcon, Andrea Llorens, Gabriel Hernandez, Maritza Palma, Lucia Navarrete

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The research has funding from the Government of Chile and is focused on defining the design of rural primary classroom that stimulates creativity. The relevance of the study consists of its capacity to define adequate educational spaces for the implementation of the design-based learning (DBL) methodology. This methodology promotes creativity and teamwork, generating a meaningful learning experience for students, based on the appreciation of their environment and the generation of projects that contribute positively to their communities; also, is an inquiry-based form of learning that is based on the integration of design thinking and the design process into the classroom. The main goal of the study is to define the design characteristics of rural primary school classrooms, associated with the implementation of the DBL methodology. Along with the change in learning strategies, it is necessary to change the educational spaces in which they develop. The hypothesis indicates that a change in the space and equipment of the classrooms based on the emotions of the students will motivate better learning results based on the implementation of a new methodology. In this case, the pedagogical dynamics require an important interaction between the participants, as well as an environment favorable to creativity. Methodologies from Kansei engineering are used to know the emotional variables associated with their definition. The study is done to 50 students between 6 and 10 years old (average age of seven years), 48% of men and 52% women. Virtual three-dimensional scale models and semantic differential tables are used. To define the semantic differential, self-applied surveys were carried out. Each survey consists of eight separate questions in two groups: question A to find desirable emotions; question B related to emotions. Both questions have a maximum of three alternatives to answer. Data were tabulated with IBM SPSS Statistics version 19. Terms referred to emotions are grouped into twenty concepts with a higher presence in surveys. To select the values obtained as part of the implementation of Semantic Differential, a number expected of 'chi-square test (x2)' frequency calculated for classroom space is considered lower limit. All terms over the N expected a cut point, are included to prepare tables for surveys to find a relation between emotion and space. Statistic contrast (Chi-Square) represents significance level ≥ 0, indicator that frequencies appeared are not random. Then, the most representative terms depend on the variable under study: a) definition of textures and color of vertical surfaces is associated with emotions such as tranquility, attention, concentration, creativity; and, b) distribution of the equipment of the rooms, with emotions associated with happiness, distraction, creativity, freedom. The main findings are linked to the generation of classrooms according to diverse DBL team dynamics. Kansei engineering is the appropriate methodology to know the emotions that students want to feel in the classroom space.

Keywords: creativity, design-based learning, education spaces, emotions

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Authors: Roslinda Nazar, Ezad Hafidz Hafidzuddin, Norihan M. Arifin, Ioan Pop

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In this paper, the problem of steady laminar boundary layer flow and heat transfer over a permeable exponentially stretching/shrinking sheet with generalized slip velocity is considered. The similarity transformations are used to transform the governing nonlinear partial differential equations to a system of nonlinear ordinary differential equations. The transformed equations are then solved numerically using the bvp4c function in MATLAB. Dual solutions are found for a certain range of the suction and stretching/shrinking parameters. The effects of the suction parameter, stretching/shrinking parameter, velocity slip parameter, critical shear rate, and Prandtl number on the skin friction and heat transfer coefficients as well as the velocity and temperature profiles are presented and discussed.

Keywords: boundary layer, exponentially stretching/shrinking sheet, generalized slip, heat transfer, numerical solutions

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Authors: Peter K. Galenko, Stefanie Koch, Markus Rettenmayr, Robert Wonneberger, Evgeny V. Kharanzhevskiy, Maria Zamoryanskaya, Vladimir Ankudinov

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We analyze the structure of undercooled melts, crystal growth kinetics and amorphous/crystalline microstructure of rapidly solidifying glass-forming Pd-based and CuZr-based alloys. A dendrite growth model is developed using a combination of the kinetic phase-field model and mesoscopic sharp interface model. The model predicts features of crystallization kinetics in alloys from thermodynamically controlled growth (governed by the Gibbs free energy change on solidification) to the kinetically limited regime (governed by atomic attachment-detachment processes at the solid/liquid interface). Comparing critical undercoolings observed in the crystallization kinetics with experimental data on melt viscosity, atomistic simulation's data on liquid microstructure and theoretically predicted dendrite growth velocity allows us to conclude that the dendrite growth kinetics strongly depends on the cluster structure changes of the melt. The obtained data of theoretical and experimental investigations are used for interpretation of microstructure of samples processed in electro-magnetic levitator on board International Space Station in the frame of the project "MULTIPHAS" (European Space Agency and German Aerospace Center, 50WM1941) and "KINETIKA" (ROSKOSMOS).

Keywords: dendrite, kinetics, model, solidification

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Authors: Varong Pongsai

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The objective of this paper is introducing a new method of accounting posting which is called Matrix Method Posting. This method is based on the Matrix operation of pure Mathematics. Although, accounting field is classified as one of the social-science knowledge, many of accounting operations are placed by Mathematics sign and operation. Through the operation applying, it seems to be that the operations of Mathematics should be applied to accounting possibly. So, this paper tries to over-lap Mathematics logic to accounting logic smoothly. According to the context of discovery, deductive approach is employed to prove a simultaneously logical concept of both Mathematics and Accounting. The result proves that the Matrix can be placed to operate accounting perfectly, because Matrix and accounting logic also have a similarity concept which is balancing 2 sides during operations. Moreover, the Matrix posting also has a lot of benefit. It can help financial analyst calculating financial ratios comfortably. Furthermore, the matrix determinant which is a signature operation itself also helps auditors checking out the correction of clients’ recording. If the determinant is not equaled to 0, it will point out that the recording process of clients getting into the problem. Finally, the Matrix should be easily determining a concept of merger and consolidation far beyond the present day concept.

Keywords: matrix method posting, deductive approach, determinant, accounting application

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Authors: Anna V. Zaporozhchenko, Dmytro Kutnyakhov, Katherina Medjanik, Christian Tusche, Hans-Joachim Elmers, Olena Fedchenko, Sergey Chernov, Martin Ellguth, Sergej A. Nepijko, Gerd Schoenhense

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Graphene reveals a unique electronic structure that predetermines many intriguing properties such as massless charge carriers, optical transparency and high velocity of fermions at the Fermi level, opening a wide horizon of future applications. Hence, a detailed investigation of the electronic structure of graphene is crucial. The method of choice is angular resolved photoelectron spectroscopy ARPES. Here we present experiments using time-of-flight (ToF) momentum microscopy, being an alternative way of ARPES using full-field imaging of the whole Brillouin zone (BZ) and simultaneous acquisition of up to several 100 energy slices. Unlike conventional ARPES, k-microscopy is not limited in simultaneous k-space access. We have recorded the whole first BZ of graphene on Ir(111) including all six Dirac cones. As excitation source we used synchrotron radiation from BESSY II (Berlin) at the U125-2 NIM, providing linearly polarized (both polarizations p- and s-) VUV radiation. The instrument uses a delay-line detector for single-particle detection up the 5 Mcps range and parallel energy detection via ToF recording. In this way, we gather a 3D data stack I(E,kx,ky) of the full valence electronic structure in approx. 20 mins. Band dispersion stacks were measured in the energy range of 14 eV up to 23 eV with steps of 1 eV. The linearly-dispersing graphene bands for all six K and K’ points were simultaneously recorded. We find clear features of hybridization with the substrate, in particular in the linear dichroism in the angular distribution (LDAD). Recording of the whole Brillouin zone of graphene/Ir(111) revealed new features. First, the intensity differences (i.e. the LDAD) are very sensitive to the interaction of graphene bands with substrate bands. Second, the dark corridors are investigated in detail for both, p- and s- polarized radiation. They appear as local distortions of photoelectron current distribution and are induced by quantum mechanical interference of graphene sublattices. The dark corridors are located in different areas of the 6 Dirac cones and show chirality behaviour with a mirror plane along vertical axis. Moreover, two out of six show an oval shape while the rest are more circular. It clearly indicates orientation dependence with respect to E vector of incident light. Third, a pattern of faint but very sharp lines is visible at energies around 22eV that strongly remind on Kikuchi lines in diffraction. In conclusion, the simultaneous study of all six Dirac cones is crucial for a complete understanding of dichroism phenomena and the dark corridor.

Keywords: band structure, graphene, momentum microscopy, LDAD

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Authors: Maria Hadjisoteriou, Yiorgos Hadjichristou

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This paper aims to explore and provoke a debate, through the work of the design studio, “living where the immaterial matters” of the architecture department of the University of Nicosia, on the role that the “immaterial matter” can play in enhancing innovative sustainable architecture and viewing the cities as sustainable organisms that always grow and alter. The blurring, juxtaposing binary of immaterial and matter, as the theoretical backbone of the Unit is counterbalanced by the practicalities of the contested sites of the last divided capital Nicosia with its ambiguous green line and the ghost city of Famagusta in the island of Cyprus. Jonathan Hill argues that the ‘immaterial is as important to architecture as the material concluding that ‘Immaterial–Material’ weaves the two together, so that they are in conjunction not opposition’. This understanding of the relationship of the immaterial vs material set the premises and the departing point of our argument, and talks about new recipes for creating hybrid public space that can lead to the unpredictability of a complex and interactive, sustainable city. We hierarchized the human experience as a priority. We distinguish the notion of space and place referring to Heidegger’s ‘building dwelling thinking’: ‘a distinction between space and place, where spaces gain authority not from ‘space’ appreciated mathematically but ‘place’ appreciated through human experience’. Following the above, architecture and the city are seen as one organism. The notions of boundaries, porous borders, fluidity, mobility, and spaces of flows are the lenses of the investigation of the unit’s methodology, leading to the notion of a new hybrid urban environment, where the main constituent elements are in a flux relationship. The material and the immaterial flows of the town are seen interrelated and interwoven with the material buildings and their immaterial contents, yielding to new sustainable human built environments. The above premises consequently led to choices of controversial sites. Indisputably a provoking site was the ghost town of Famagusta where the time froze back in 1974. Inspired by the fact that the nature took over the a literally dormant, decaying city, a sustainable rebirthing was seen as an opportunity where both nature and built environment, material and immaterial are interwoven in a new emergent urban environment. Similarly, we saw the dividing ‘green line’ of Nicosia completely failing to prevent the trespassing of images, sounds and whispers, smells and symbols that define the two prevailing cultures and becoming a porous creative entity which tends to start reuniting instead of separating , generating sustainable cultures and built environments. The authors would like to contribute to the debate by introducing a question about a new recipe of cooking the built environment. Can we talk about a new ‘urban recipe’: ‘cooking architecture and city’ to deliver an ever changing urban sustainable organism, whose identity will mainly depend on the interrelationship of the immaterial and material constituents?

Keywords: blurring zones, porous borders, spaces of flow, urban recipe

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Authors: Yountaik Leem, Sang Ho Lee

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In this paper, different goals and the ways to reach smart cities shown in many countries during planning and implementation processes will be discussed. Each country dealt with technologies which have been embedded into space as development of ICTs (information and communication technologies) for their own purposes and by their own ways. For example, European countries tried to adapt technologies to reduce greenhouse gas emission to overcome global warming while US-based global companies focused on the way of life using ICTs such as EasyLiving of Microsoft™ and CoolTown of Hewlett-Packard™ during last decade of 20th century. In the North-East Asian countries, urban space with ICTs were developed in large scale on the viewpoint of capitalism. Ubiquitous city, first introduced in Korea which named after Marc Weiser’s concept of ubiquitous computing pursued new urban development with advanced technologies and high-tech infrastructure including wired and wireless network. Japan has developed smart cities as comprehensive and technology intensive cities which will lead other industries of the nation in the future. Not only the goals and strategies but also new directions to which smart cities are oriented also suggested at the end of the paper. Like a Finnish smart community whose slogan is ‘one more hour a day for citizens,’ recent trend is forwarding everyday lives and cultures of human beings, not capital gains nor physical urban spaces.

Keywords: smart cities, urban strategy, future direction, comparative study

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Authors: Rongbo Shen, Jianhua Yao, Kezhou Yan, Kuan Tian, Cheng Jiang, Ke Zhou

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This study proposes a generative adversarial networks (GAN) framework to perform synthetic sampling in feature space, i.e., feature augmentation, to address the class imbalance problem in medical image analysis. A feature extraction network is first trained to convert images into feature space. Then the GAN framework incorporates adversarial learning to train a feature generator for the minority class through playing a minimax game with a discriminator. The feature generator then generates features for minority class from arbitrary latent distributions to balance the data between the majority class and the minority class. Additionally, a data cleaning technique, i.e., Tomek link, is employed to clean up undesirable conflicting features introduced from the feature augmentation and thus establish well-defined class clusters for the training. The experiment section evaluates the proposed method on two medical image analysis tasks, i.e., mass classification on mammogram and cancer metastasis classification on histopathological images. Experimental results suggest that the proposed method obtains superior or comparable performance over the state-of-the-art counterparts. Compared to all counterparts, our proposed method improves more than 1.5 percentage of accuracy.

Keywords: class imbalance, synthetic sampling, feature augmentation, generative adversarial networks, data cleaning

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Authors: Nabilah Filzah Mohd Radzuan, Andi Putra, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

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Precipitation forecast is important to avoid natural disaster incident which can cause losses in the involved area. This paper reviews three techniques logistic regression, decision tree, and random forest which are used in making precipitation forecast. These combination techniques through the vector auto-regression (VAR) model help in finding the advantages and strengths of each technique in the forecast process. The data-set contains variables of the rain’s domain. Adaptation of artificial intelligence techniques involved in rain domain enables the forecast process to be easier and systematic for precipitation forecast.

Keywords: logistic regression, decisions tree, random forest, VAR model

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Authors: Daleesha M. Viswanathan, Sumam Mary Idicula

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Dynamic hand gestures are an intrinsic component in sign language communication. Extracting spatial temporal features of the hand gesture trajectory plays an important role in a dynamic gesture recognition system. Finding a discrete feature descriptor for the motion trajectory based on the orientation feature is the main concern of this paper. Kalman filter algorithm and Hidden Markov Models (HMM) models are incorporated with this recognition system for hand trajectory tracking and for spatial temporal classification, respectively.

Keywords: orientation features, discrete feature vector, HMM., Indian sign language

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Authors: Ahmad FAROOQ, Xinfeng Zhang, Fahad Sabah, Raheem Sarwar

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In Traditional Chinese Medicine, tongue diagnosis is a vital inspection tool (TCM). In this study, we explore the potential of machine learning in tongue diagnosis. It begins with the cataloguing of the various classifications and characteristics of the human tongue. We infer 24 kinds of tongues from the material and coating of the tongue, and we identify 21 attributes of the tongue. The next step is to apply machine learning methods to the tongue dataset. We use the Weka machine learning platform to conduct the experiment for performance analysis. The 457 instances of the tongue dataset are used to test the performance of five different machine learning methods, including SVM, Random Forests, Decision Trees, and Naive Bayes. Based on accuracy and Area under the ROC Curve, the Support Vector Machine algorithm was shown to be the most effective for tongue diagnosis (AUC).

Keywords: medical imaging, image retrieval, machine learning, tongue

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Authors: Yuan Huang, Xiangping Chen, Xiaonan Luo

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Current software are continuously updating. The change between two versions usually involves multiple program entities (e.g., packages, classes, methods, attributes) with multiple purposes (e.g., changed requirements, bug fixing). It is hard for developers to understand which changes are made for the same purpose. Whether two changes are related is not decided by the relationship between this two entities in the program. In this paper, we summarized 4 coupling rules(16 instances) and 4 state-combination types at the class, method and attribute levels for software change. Related Change Vector (RCV) are defined based on coupling rules and state-combination types, and applied to classify related software changes by using Probabilistic Neural Network during a software updating.

Keywords: PNN, related change, state-combination, logical coupling, software entity

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this study is to evaluate the advantages and disadvantages of various machine learning techniques in forecasting ground-motion intensity measures given source characteristics, source-to-site distance, and local site condition. Intensity measures such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Estimating these variables for future earthquake events is a key step in seismic hazard assessment and potentially subsequent risk assessment of different types of structures. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as a statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The algorithms are adjusted to quantify event-to-event and site-to-site variability of the ground motions by implementing them as random effects in the proposed models to reduce the aleatory uncertainty. All the algorithms are trained using a selected database of 4,528 ground-motions, including 376 seismic events with magnitude 3 to 5.8, recorded over the hypocentral distance range of 4 to 500 km in Oklahoma, Kansas, and Texas since 2005. The main reason of the considered database stems from the recent increase in the seismicity rate of these states attributed to petroleum production and wastewater disposal activities, which necessities further investigation in the ground motion models developed for these states. Accuracy of the models in predicting intensity measures, generalization capability of the models for future data, as well as usability of the models are discussed in the evaluation process. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available.

Keywords: artificial neural network, ground-motion models, machine learning, random forest, support vector machine

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Authors: Sinisa Prvanov

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This research is an attempt to analyze the existing urban form of outdoor public space of Duhok city and to give proposals for their improvements in terms of urban seating. The aim of this research is to identify the main urban furniture elements and behaviour of users of three central parks of Duhok city, recognizing their functionality and the most common errors. Citizens needs, directly related to the physical characteristics of the environment, are categorized in terms of contact with nature. Parks as significant urban environments express their aesthetic preferences, as well as the need for recreation and play. Citizens around the world desire to contact with nature and places where they can socialize, play and practice different activities, but also participate in building their community and feeling the identity of their cities. The aim of this research is also to reintegrate these spaces in the wider urban context of the city of Duhok, to develop new functions by designing new seating patterns, more improved urban furniture, and necessary supporting facilities and equipment. Urban furniture is a product that uses an enormous number of people in public space. It has a high level of wear and damage due to intense use, exposure to sunlight and weather conditions. Iraq has a hot and dry climate characterized by long, warm, dry summers and short, cold winters. The climate is determined by the Iraq location at the crossroads of Arab desert areas and the subtropical humid climate of the Persian Gulf. The second part of this analysis will describe the possibilities of traditional and contemporary materials as well as their advantages in urban furniture production, providing users protection from extreme local climate conditions, but also taking into account solidities and unwelcome consequences, such as vandalism. In addition, this research represents a preliminary stage in the development of IND307 furniture design course for needs of the Department of Interior design, at the American University in Duhok. Based on results obtained in this research, the course would present a symbiosis between people and technology, promotion of new street furniture design that perceives pedestrian activities in an urban setting, and practical use of anthropometric measurements as a tool for technical innovations.

Keywords: Furniture design, Street furniture, Social interaction, Public space

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Authors: Dipti Patra, Guguloth Uma, Smita Pradhan

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Registration is a fundamental task in image processing. It is used to transform different sets of data into one coordinate system, where data are acquired from different times, different viewing angles, and/or different sensors. The registration geometrically aligns two images (the reference and target images). Registration techniques are used in satellite images and it is important in order to be able to compare or integrate the data obtained from these different measurements. In this work, mutual information is considered as a similarity metric for registration of satellite images. The transformation is assumed to be a rigid transformation. An attempt has been made here to optimize the transformation function. The proposed image registration technique hybrid PSO-GA incorporates the notion of Particle Swarm Optimization and Genetic Algorithm and is used for finding the best optimum values of transformation parameters. The performance comparision obtained with the experiments on satellite images found that the proposed hybrid PSO-GA algorithm outperforms the other algorithms in terms of mutual information and registration accuracy.

Keywords: image registration, genetic algorithm, particle swarm optimization, hybrid PSO-GA algorithm and mutual information

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Authors: Heerak Banerjee, Sourov Roy

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Supersymmetry, one of the most celebrated fields of study for explaining experimental observations where the standard model (SM) falls short, is reeling from the lack of experimental vindication. At the same time, the idea of additional gauge symmetry, in particular, the gauged Lμ-Lτ symmetric models have also generated significant interest. They have been extensively proposed in order to explain the tantalizing discrepancy in the predicted and measured value of the muon anomalous magnetic moment alongside several other issues plaguing the SM. While very little parameter space within these models remain unconstrained, this work finds that the γ + Missing Energy (ME) signal at the Belle-II detector will be a smoking gun for supersymmetry (SUSY) in the presence of a gauged U(1)Lμ-Lτ symmetry. A remarkable consequence of breaking the enhanced symmetry appearing in the limit of degenerate (s)leptons is the nondecoupling of the radiative contribution of heavy charged sleptons to the γ-Z΄ kinetic mixing. The signal process, e⁺e⁻ →γZ΄→γ+ME, is an outcome of this ubiquitous feature. Taking the severe constraints on gauged Lμ-Lτ models by several low energy observables into account, it is shown that any significant excess in all but the highest photon energy bin would be an undeniable signature of such heavy scalar fields in SUSY coupling to the additional gauge boson Z΄. The number of signal events depends crucially on the logarithm of the ratio of stau to smuon mass in the presence of SUSY. In addition, the number is also inversely proportional to the e⁺e⁻ collision energy, making a low-energy, high-luminosity collider like Belle-II an ideal testing ground for this channel. This process can probe large swathes of the hitherto free slepton mass ratio vs. additional gauge coupling (gₓ) parameter space. More importantly, it can explore the narrow slice of Z΄ mass (MZ΄) vs. gₓ parameter space still allowed in gauged U(1)Lμ-Lτ models for superheavy sparticles. The spectacular finding that the signal significance is independent of individual slepton masses is an exciting prospect indeed. Further, the prospect that signatures of even superheavy SUSY particles that may have escaped detection at the LHC may show up at the Belle-II detector is an invigorating revelation.

Keywords: additional gauge symmetry, electron-positron collider, kinetic mixing, nondecoupling radiative effect, supersymmetry

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Authors: Amal Khalifa, Nicolas Vana Santos

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Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.

Keywords: deep learning, steganography, image, discrete wavelet transform, fusion

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Authors: Jaewoo Choi, Ki-Tae Hwang, Eunyoung Ko

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Backgrounds/Aims: Patients with breast cancer are currently classified according to TNM stage. Nevertheless, the actual volume would be mis-estimated, and it would bring on inappropriate diagnosis. Tridimensional volume-stage derived from the ellipsoid formula was presented as useful measure. Methods: The medical records of 480 consecutive breast cancer between January 2001 and March 2013 were retrospectively reviewed. All patients were divided into three groups according to tumor volume by receiver operating characteristic analysis, and the ranges of each volume-stage were that V1 was below 2.5 cc, V2 was exceeded 2.5 and below 10.9 cc, and V3 was exceeded 10.9 cc. We analyzed outcomes of volume-stage and compared disease-free survival (DFS) and overall survival (OS) between size-stage and volume-stage with variant intrinsic factor. Results: In the T2 stage, there were patients who had a smaller volume than 4.2 cc known as maximum value of T1. These findings presented that patients in T1c had poorer DFS than T2-lesser (mean of DFS 48.7 vs. 51.8, p = 0.011). Such is also the case in OS (mean of OS 51.1 vs. 55.3, p = 0.006). The cumulative survival curves for V1, V2 compared T1, T2 showed similarity in DFS (HR 1.9 vs. 1.9), and so did it for V3 compared T3 (HR 3.5 vs. 2.6) significantly. Conclusion: This study demonstrated that tumor volume had good feasibility on the prognosis of patients with breast cancer. We proposed that volume-stage should be considered for an additional stage indicator, particularly in early breast cancer.

Keywords: breast cancer, tridimensional volume of tumor, TNM stage, volume stage

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Authors: Abdelsabour G. A. Khaled, Galal A.R. El-Sherbeny, Ahmed M. Hassanein, Gameel M. G. Aly

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Classical methods of identification, based on agronomical characterization, are not always the most accurate way due to the instability of these characteristics under the influence of the different environments. In order to estimate the genetic diversity, molecular markers provided excellent tools. In this study, Genetic variation of nine Egyptian jojoba shrubs was tested using ISSR (inter simple sequences repeats), RAPD (random amplified polymorphic DNA) markers and based on the morphological characterization. The average of the percentage of polymorphism (%P) ranged between 58.17% and 74.07% for ISSR and RAPD markers, respectively. The range of genetic similarity percents among shrubs based on ISSR and RAPD markers were from 82.9 to 97.9% and from 85.5 to 97.8%, respectively. The average of PIC (polymorphism information content) values were 0.19 (ISSR) and 0.24 (RAPD). In the present study, RAPD markers were more efficient than the ISSR markers. Where the RAPD technique exhibited higher marker index (MI) average (1.26) compared to ISSR one (1.11). There was an insignificant correlation between the ISSR and RAPD data (0.076, P > 0.05). The dendrogram constructed by the combined RAPD and ISSR data gave a relatively different clustering pattern.

Keywords: correlation, molecular markers, polymorphism, marker index

Procedia PDF Downloads 462

Authors: L. Edirisinghe, Zhihong Jin, A. W. Wijeratne, R. Mudunkotuwa

Abstract:

The virtual container yard is an effective solution to the container inventory imbalance problem which is a global issue. It causes substantial cost to carriers, which inadvertently adds to the prices of consumer goods. The virtual container yard is rooted in the fundamentals of container interchange between carriers. If carriers opt to interchange their excess containers with those who are deficit, a substantial part of the empty reposition cost could be eliminated. Unlike in other types of ships, cargo cannot be directly loaded to a container ship. Slots and containers are supplementary components; thus, without containers, a carrier cannot ship cargo if the containers are not available and vice versa. Few decades ago, carriers recognized slot (the unit of space in a container ship) interchange as a viable solution for the imbalance of shipping space. Carriers interchange slots among them and it also increases the advantage of scale of economies in container shipping. Some of these service agreements between mega carriers have provisions to interchange containers too. However, the interchange mechanism is still not popular among carriers for containers. This is the paradox that prevails in the liner shipping industry. At present, carriers reposition their excess empty containers to areas where they are in demand. This research applied factor analysis statistical method. The paper reveals that five major components may influence the virtual container yard namely organisation, practice and culture, legal and environment, international nature, and marketing. There are 12 variables that may impact the virtual container yard, and these are explained in the paper.

Keywords: virtual container yard, shipping, imbalance, management, inventory

Procedia PDF Downloads 172

Authors: Tudor Barbu

Abstract:

An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Second, an automatic pixel classification approach is proposed. The feature vectors are clustered using some unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.

Keywords: image segmentation, moment-based, texture analysis, automatic classification, validation indexes

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Authors: Volkan Kaya, Ersin Elbasi

Abstract:

Watermarking and stenography are getting importance recently because of copyright protection and authentication. In watermarking we embed stamp, logo, noise or image to multimedia elements such as image, video, audio, animation and text. There are several works have been done in watermarking for different purposes. In this research work, we used watermarking techniques to embed patient information into the medical magnetic resonance (MR) images. There are two methods have been used; frequency domain (Digital Wavelet Transform-DWT, Digital Cosine Transform-DCT, and Digital Fourier Transform-DFT) and spatial domain (Least Significant Bits-LSB) domain. Experimental results show that embedding in frequency domains resist against one type of attacks, and embedding in spatial domain is resist against another group of attacks. Peak Signal Noise Ratio (PSNR) and Similarity Ratio (SR) values are two measurement values for testing. These two values give very promising result for information hiding in medical MR images.

Keywords: watermarking, medical image, frequency domain, least significant bits, security

Procedia PDF Downloads 273

Authors: Nilubon Kurubanjerdjit, Nattakarn Iam-On, Ka-Lok Ng

Abstract:

MicroRNAs are small non-coding RNA found in many different species. They play crucial roles in cancer such as biological processes of apoptosis and proliferation. The identification of microRNA-target genes can be an essential first step towards to reveal the role of microRNA in various cancer types. In this paper, we predict miRNA-target genes for lung cancer by integrating prediction scores from miRanda and PITA algorithms used as a feature vector of miRNA-target interaction. Then, machine-learning algorithms were implemented for making a final prediction. The approach developed in this study should be of value for future studies into understanding the role of miRNAs in molecular mechanisms enabling lung cancer formation.

Keywords: microRNA, miRNAs, lung cancer, machine learning, Naïve Bayes, SVM

Procedia PDF Downloads 380

Authors: T. Thein, S. Kalyar Myo

Abstract:

Human uses visual information for understanding the speech contents in noisy conditions or in situations where the audio signal is not available. The primary advantage of visual information is that it is not affected by the acoustic noise and cross talk among speakers. Using visual information from the lip movements can improve the accuracy and robustness of automatic speech recognition. However, a major challenge with most automatic lip reading system is to find a robust and efficient method for extracting the linguistically relevant speech information from a lip image sequence. This is a difficult task due to variation caused by different speakers, illumination, camera setting and the inherent low luminance and chrominance contrast between lip and non-lip region. Several researchers have been developing methods to overcome these problems; the one is lip reading. Moreover, it is well known that visual information about speech through lip reading is very useful for human speech recognition system. Lip reading is the technique of a comprehensive understanding of underlying speech by processing on the movement of lips. Therefore, lip reading system is one of the different supportive technologies for hearing impaired or elderly people, and it is an active research area. The need for lip reading system is ever increasing for every language. This research aims to develop a visual teaching method system for the hearing impaired persons in Myanmar, how to pronounce words precisely by identifying the features of lip movement. The proposed research will work a lip reading system for Myanmar Consonants, one syllable consonants (င (Nga)၊ ည (Nya)၊ မ (Ma)၊ လ (La)၊ ၀ (Wa)၊ သ (Tha)၊ ဟ (Ha)၊ အ (Ah) ) and two syllable consonants ( က(Ka Gyi)၊ ခ (Kha Gway)၊ ဂ (Ga Nge)၊ ဃ (Ga Gyi)၊ စ (Sa Lone)၊ ဆ (Sa Lain)၊ ဇ (Za Gwe) ၊ ဒ (Da Dway)၊ ဏ (Na Gyi)၊ န (Na Nge)၊ ပ (Pa Saug)၊ ဘ (Ba Gone)၊ ရ (Ya Gaug)၊ ဠ (La Gyi) ). In the proposed system, there are three subsystems, the first one is the lip localization system, which localizes the lips in the digital inputs. The next one is the feature extraction system, which extracts features of lip movement suitable for visual speech recognition. And the final one is the classification system. In the proposed research, Two Dimensional Discrete Cosine Transform (2D-DCT) and Linear Discriminant Analysis (LDA) with Active Contour Model (ACM) will be used for lip movement features extraction. Support Vector Machine (SVM) classifier is used for finding class parameter and class number in training set and testing set. Then, experiments will be carried out for the recognition accuracy of Myanmar consonants using the only visual information on lip movements which are useful for visual speech of Myanmar languages. The result will show the effectiveness of the lip movement recognition for Myanmar Consonants. This system will help the hearing impaired persons to use as the language learning application. This system can also be useful for normal hearing persons in noisy environments or conditions where they can find out what was said by other people without hearing voice.

Keywords: feature extraction, lip reading, lip localization, Active Contour Model (ACM), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Two Dimensional Discrete Cosine Transform (2D-DCT)

Procedia PDF Downloads 269

Authors: Muhammad Umair Shahid, Abdul Rehman, Mudassir Mukhtar, Muhammad Nauman

Abstract:

The smart antenna is the prominent technology that has become known in recent years to meet the growing demands of wireless communications. In an overcrowded atmosphere, its application is growing gradually. A methodical evaluation of the performance of Fixed Beamforming algorithms for smart antennas such as Multiple Sidelobe Canceller (MSC), Maximum Signal-to-interference ratio (MSIR) and minimum variance (MVDR) has been comprehensively presented in this paper. Simulation results show that beamforming is helpful in providing optimized response towards desired directions. MVDR beamformer provides the most optimal solution.

Keywords: fixed weight beamforming, array pattern, signal to interference ratio, power efficiency, element spacing, array elements, optimum weight vector

Procedia PDF Downloads 162

Authors: S. M. Hamidi, M. Zamani

Abstract:

Magneto-plasmonic (MP) structures have turned into essential tools for the amplification of magneto-optical (MO) responses via the combination of MO activity and surface Plasmon resonance (SPR). Both the plasmonic and the MO properties of the resulting MP structure become interrelated because the SPR of the metallic medium. This interconnection can be modified the wave vector of surface plasmon polariton (SPP) in MP multilayer [1] or enhanced the MO activity [2- 3] and also modified the sensor responses [4]. There are several types of MP structures which are studied to enhance MO response in miniaturized configuration. In this paper, we propose a new MP structure based on the nano-metal grating and we investigate the MO and optical properties of this new structure. Our new MP structure fabricate by DC magnetron sputtering method and our home made MO experimental setup use for characterization of the structure.

Keywords: Magneto-plasmonic structures, magneto-optical effect, nano-garting

Procedia PDF Downloads 539